Table of contents

The 2022 2^nd International Conference on Measurement Control and Instrumentation (MCAI 2022) was held in Guangzhou, China from July 22 to 24, 2022. In view of the current COVID-19 pandemic, it was chosen to be held online. MCAI 2022 promoted research and developmental activities in the fields of "Measurement Control" and "Instrumentation" as well as scientific information interchange between researchers, engineers, and practitioners working all around the world.

In the conference, we had the honor of having invited both Prof. Guixiong Liu from South China University of Technology, China and Prof. Zhen Zhou, Guangzhou Hexin Instrument Co., Ltd., China to serve as our Conference General Chairs. The conference consisted of keynote speeches, oral presentations and online Q&A discussion, attracting 100 individuals and institutions worldwide. Primarily, keynote speakers were each allocated 30-45 minutes to hold their speeches. Then in the oral presentations, the excellent papers we had selected were presented by their authors by turns.

We were delighted and honored to invite three prominent professors as keynote speakers to deliver their speeches. For a start, Prof. Zongmin Ma from North University of China showed us his research: Non-contact Atomic Force Microscopy Instruments and Atomic Scale Precision Measurements. By developing the ultra-high vacuum non-contact atomic force microscope (NC-AFM), he solved the key technologies of probe vibration control and precise detection, force spectrum measurement, and realized atomic scale imaging characterization in terms of non-destructive imaging of magnetic information and uncoupled measurement of surface charge. Besides, Assoc. Prof. Zhiwei Shi from Guangdong University of Technology, China made a report on Multi-sensor Information Fusion Technology for Intelligent Networked Vehicles. Aiming at the development of intelligent networked vehicles, he proposed a vehicle headlight far-light system based on multi-sensor information fusion, which mainly includes three major parts: information fusion, drive control and optical design, ensuring in a maximum degree the intelligent lighting functions and simple structure, low cost. The wonderful speeches of each keynote speaker had triggered heated discussion. Besides, every participant praised this conference for disseminating useful and insightful knowledge.

List of Committee member is available in this pdf.

All papers published in this volume have been reviewed through processes administered by the Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing Publishing.

• Type of peer review: Single Anonymous

• Conference submission management system: Morressier

• Number of submissions received: 97

• Number of submissions sent for review: 89

• Number of submissions accepted: 55

• Acceptance Rate (Submissions Accepted / Submissions Received × 100): 56.7

• Average number of reviews per paper: 2

• Total number of reviewers involved: 20

• Contact person for queries:

Name: Xuexia Ye

Email: xx.ye@keoaeic.org

Affiliation: AEIC Academic Exchange Information Centre

The synthesis electric field is an important indicator to assess electromagnetic environment of DC transmission line, and field mill is often used in practical engineering. In order to solve the problem that the shielding plate in the field mill have unreliable grounding due to rotation and the electric field is distorted by accumulated charge, the structure of static shielding plate and moving induction plate are designed in this paper. On this basis, a complete synthetic electric field measuring device is developed. The instrument is calibrated under laboratory conditions, and the results show that calibration curve has good linear characteristic.

The temperature control blanket in medical use is a device that can help regulate the temperature of the human body by controlling the temperature of the circulating liquid in the blanket and physically warming or cooling the human body. This article presents a novel design of precision assessment method of temperature control blanket by studying the essential metrological parameters of the device and designing a testing device for load simulation. The experimental results show that the measurement method and the design of the simulated load presented in this article can establish the metrological traceability system of temperature control blanket in medical use in China in order to ensure the accuracy and reliability of the device, which is of great importance for the quality control of the device.

In order to ensure the safety of the long-term service shipbuilding portal crane, this paper analyzes the stress distribution of the crane metal structure by using the finite element analysis method, which plays an auxiliary role in the crane safety assessment. The working condition at the most dangerous working position of the crane is selected as the stress test condition for analysis, and compared with the simulation calculation. The finite element calculation results show that the stress distribution of the whole machine is relatively reasonable. The overall stress is basically less than 100 MPa, and the maximum stress value is 131 MPa, which is less than the allowable stress value of the material. And through the comparison with the actual stress testing data, they are also basically consistent, and the structure of the crane can be used safely.

Vibration comfort is an important indicator for evaluating escalator riding experience. The measuring principle of vibration comfort of escalator step and armbands was analyzed. The calculation methods of vibration acceleration extraction, frequency meter weight, root mean square (RMS) and vector sum were summarized. A wireless triaxial acceleration data acquisition module was developed based on micro-electromechanical system (MEMS) acceleration sensor, MCU and high-speed WIFI module, and a vibration comfort detection application (APP) based on the Android operating system was developed. The calibrated detection device was applied to escalator field test. The results showed that the maximum vibration RMS and average RMS of the step and the armband on both sides can be quickly calculated, and the vibration comfort level can be divided, which provided important data reference for equipment maintenance.

The iron terminals are mostly used in the small ultrasonic transducers which are connected to the circuit board by the direct or indirect welding method. Although the method is considered to be firm and reliable, the ultrasonic transducer or the whole system is easy to be damaged when the ultrasonic transducer is replaced or maintained. Moreover, the terminals of the ultrasonic transducer are easy to be oxidized. The miniaturized ultrasonic transducer with the electroplated copper terminals is innovatively designed to enhance the oxidation resistance of its terminals. Then the ultrasonic transducers are installed on the circuit board by the copper claw spring instead of welding. In addition, the waterproof miniaturized ultrasonic transducer is replaced by the fully covered waterproof sound permeable membrane and the non waterproof miniaturized ultrasonic transducer. The experimental results demonstrate that the quality of the signal transmission of the ultrasonic transducer is not affected, and the convenience of replacement and maintenance of the ultrasonic transducer is improved. With this design process, the overall waterproof performance of the system is also significantly enhanced while the system cost is reduced, market future is wide prospect.

Pipes with insulation are widely used in the industrial field. The traditional nondestructive testing technology for on-line pipes with insulation often requires the removal of a large number of insulation layers and the forcing of the owner to stop for testing. The traditional testing mode not only has low detection efficiency, but also forces the owner to spend a lot of manpower, material resources and financial resources. In recent years, a series of new nondestructive testing (NDT) technologies have different advantages for in-service pipeline testing with coated layers. However, Digital radiographic (DR) testing can satisfy the integrity inspection of on-line pipeline with insulation well. In this paper, the basic principle of DR testing and the configuration of instrument parameters are introduced. Based on the analysis and discussion of the actual testing cases, it is proved that digital ray testing can effectively solve the quality testing of on-line insulation pipeline, and it is a new nondestructive testing technology worthy of further study and popularization.

Base impedance has a direct effect on mechanical equipment's properties, and thus its accurate measurement constitutes an important foundation for the evaluation of these properties. Through theoretical deduction and base impedance measurement, we investigated the influences of impact hammer parameters on mechanical impedance measurement using an impact excitation method. By comparing the effects of hammer head softness and hammer size on base's mechanical impedance measurements, we know that soft and hard hammer heads were suitable for the impedance measurement in low and high frequency regions, respectively, and that hammer size had a little influence on impedance measurements.

Aiming at the problem that some of the spare power cable pipelines without cable are damaged, and there is no effective detection equipment to detect the blocked state of the pipeline. This paper proposed a dynamic laser scanning method for obstacles in the pipeline, and designed a power pipeline fault positioning device. The infrared laser ranging technology based on time-of-flight is used to dynamically detect the distance between obstacles in the pipeline and the laser sensor, so as to detect the status and location of pipeline blockage. Taking ARM microcontroller as the core, equipped with VL53L0X laser module, the hardware design of the device was completed, and the software program was completed based on the Keil μVision5 IDE environment. The measurement and error analysis of obstacles of two different materials are carried out. The results show that the longer the measurement distance, the larger the error, and the highest measurement error is 1.47%, which fully meets the needs of engineering measurement.

In recent years, because climate change is a major issue related to human survival and sustainable development, the global climate is warming and glaciers are melting, so the country has been advocating "green environmental protection, low-carbon life". To achieve this goal, China is constantly looking for green and sustainable energy. However, in thunderstorm weather, wind turbines are more likely to be attacked by lightning. Even if we have a set of strict technology for lightning protection of wind turbines, we cannot resist direct lightning strikes. The blade of a wind turbine is the first target of lightning strikes. Therefore, this paper designs a lightning current monitoring system for wind turbines based on Rogowski coils, and designs a current measurement system that can be stably used to monitor the whole process of discharge when wind turbines are struck by lightning, so as to improve the safety of wind turbines. To improve the wind power generation technology due to the economic losses caused by lightning strikes to wind power generation enterprises.

This paper mainly studies the influence of high temperature conditions on Li-MnO₂ primary battery, and analyzes the influence of high temperature conditions on the performance of Li-MnO₂ primary battery by testing the capacity, voltage and internal resistance of the product. Through impedance test, the different polarization differences between products stored at high temperature and normal temperature were analyzed. The effects of high temperature environment on the internal macro structure and micro material components of the battery were analyzed by means of electronic computed tomography (CT), scanning electron microscope and X-ray energy spectrometer (SEM-EDS) and X-ray photoelectron spectroscopy (XPS). Finally, through various test data, the internal reaction mechanism of the battery at high temperature was analyzed to deepen the research on the performance of Li-MnO₂ primary battery.

With the deepening of people's understanding of the harm of air pollution, indoor air quality is getting more and more attention. This paper designs an indoor air quality monitoring system based on sensor technology and Internet of things technology, the system function includes air quality detection, real-time data display, server transfer, remote display throught Wechat mini programe and others, the system can detect six important environmental parameters and allows users to view the data on mobile phone. Based on the data collected, this paper also designs an air quality evaluation algorithm.

Taking the temperature-pressure controllable acoustic measurement system for the seabed sediment as the object, according to the HostLink communication protocol of the Omron CP1H type PLC, FINS and C-mode commands are used to design and realize the control and monitoring of PLC by temperature-pressure monitoring software for seabed sediment. Moreover, SerialPort, Timer, and Chart controls in Visual Studio 2010 platform are used to realize the communication, data acquisition, and real-time curve drawing of the industrial field, developing, and realizing the automatic measurement of seabed sediment based on automatic detection and control of temperature and pressure. In addition, the actual measurement and application verify the reliability and stability of the system design.

In this paper, a design sample of rubber support base of battery pack is analyzed and verified. The status and response of the sample under the actual working scene are simulated and analyzed by using structural finite element simulation. The weak point position and local stress-strain index of the rubber support base are obtained, and the stress variation and fatigue life under two different types of mounting base are compared and analyzed. At the same time, the main failure modes of the rubber support base are verified by the durability test of the real samples and the microscopic characterization analysis of the fracture morphology, which are consistent with the simulation results. On this basis, the design and optimization suggestions of the rubber support base are put forward.

As one of the main indoor gas pollutants, formaldehyde gas (HCHO) seriously threatens human health and ranks second among toxic chemicals in China. In order to monitor the concentration of formaldehyde in the environment in real time, an online Quartz Crystal Microbalance (QCM) analyzing device based on FPGA is developed in this paper. This device is composed of QCM sensor module and FPGA signal processor. Firstly, graphene oxide film is prepared on QCM chip to adsorb formaldehyde, which causes the change of resonance frequency. Secondly, to monitor the quality of adsorbed formaldehyde through frequency change, FPGA signal processor is mainly integrated with Direct Digital Synthesis module, Analogue-to-Digital Conversion module, Low-Pass Filter module and Frequency Domain Analysis module. These modules have the characteristics of high speed, low power consumption and parallel processing, which provide the best solution for the online implementation of the analyzing device. Finally, the standard gas experiment shows that the device is feasible and reliable for the analysis of formaldehyde gas mass concentration, with a resolution of about 10 counts per 1% concentration.

It is important to monitor the iced condition for operating wind turbine blades. However, most sensors are difficult to be used in this quite cold and lightweight environment. Although the fiber bragg grating (FBG) is a good candidate for the case. With the change of the temperature, the thermal expansion coefficient and thermo-optical coeffecient of FBG material will affect the accuracy of characteristics of FBG sensor. Aiming at the application of fiber optic sensor in low temperature environment and ultrathin requirement, the low temperature characteristics of FBG sensor with free arc shape package has been studied. The low temperature calibration experiments of two packaged FBG samples are tested from -35°C ~20°C in a constant temperature freezer with alcohol tank. The effects of low temperature characteristics of two FBGs packaged with free straight and arc shape tubes are compared. The results show that arc shape can effectively reduce the repeatability error and improve its accuracy due to providing possible low temperature contracting of the optical fibers. Flat arc shape makes it possible to package ultrathin FBG temperature sensor.

The progress of material technology makes the structural deformation of composites more complex and more difficult to monitor. The distributed optical fiber sensor has a wide monitoring range and can continuously obtain the strain data of the structure in space for structural deformation reconstruction. In this paper, the optical frequency domain reflectometer (OFDR) and distributed optical fiber sensor are used as measurement tools to design the deformation reconstruction experiment of a cantilever beam with constant cross section. Based on the Ko theory, the strain signals collected by the distributed optical fiber sensors are converted into displacement signals, and the deformation reconstruction of the cantilever beam is carried out, and then compared and analyzed with the actual measured values. The experiment verifies the effectiveness of using distributed fiber optic sensors for cantilever beam bending deformation based on Ko theory, which provides a favorable reference for structural health monitoring.

By building three finite element analysis models for its four-bar metal structure under different amplitudes (the boom span is 13.5m, 22.5m and 34.5m), the relationship between stress, amplitude and load at key parts is established by linear interpolation method; At the same time, the relationship between the measured strain data of key parts and the load and amplitude is linearly fitted. The analysis and comparison between the finite element calculation data and the measured data are well verified. In order to provide a feasible analysis method for solving the working performance of four-bar linkage structure of portal crane. At the same time, it provides a more convenient method for the compilation of typical load, which is the important basic data for the calculation and analysis of residual fatigue life of later structures.

Impact monitoring of plate structures has always been a hot spot in structural health monitoring research. In order to improve the accuracy of impact monitoring, this paper proposes a beam-focusing impact localization algorithm based on passive tomography using a sensor arrangement method in a ring array. The impact damage monitoring of large-sized structures in different directions is performed by each linear array of the ring array and the impact damage localization distribution maps of the corresponding linear arrays are generated. The localization accuracy of the linear arrays in different directions is obtained experimentally to assign the weights of each linear array to achieve image reconstruction of the impact damage. The experimental results show that the method can achieve a more accurate visualization of the impact location, and the reconstructed impact laminar image can well reflect the impact location distribution information. It can be used for the localization of impact damage and extended monitoring.

The access of distributed photovoltaic power sources will change the power flow distribution in the distribution network. When the line load is light and the photovoltaic access capacity is large, the distribution network will become a multi-source network, which will cause the reverse flow of the line, increase the line voltage, and affect the power quality of the distribution network. Aiming at this problem, this paper studies the voltage control strategy after photovoltaic grid-connected, and proposes a four-level reactive voltage control strategy to solve the voltage problem when photovoltaic large-scale grid-connected. Finally, the method is verified by an example.

Aiming at the low efficiency of manual detection in the detection of water channel defects of engine cylinder block and the poor generalization ability of traditional machine vision in manual design features, an improved water channel defect detection model of cylinder block based on fast RCNN network is proposed. Restnet50 is selected as the feature extraction network of waterway defects, and feature pyramid network (FPN) is introduced to improve the detection ability of small defects; The anchor box is optimized by k-means++ clustering algorithm to improve the positioning of the target box. Experiments show that the map of the improved network in the engine cylinder block waterway defect data set reaches 88.74%, the accuracy is increased by 4% compared with the original fast RCNN, and the recall rate is increased by 1.67%. The recognition and detection effect in real samples is good, and it can be effectively used for the engine cylinder block waterway defect detection.

A reliability evaluation method of pseudo-failure life distribution for Industrial Robot Servo System (IRSS) based on The Generalized Lambda Distribution (GLD) was proposed in the paper. The IRSS pseudo-failure life GLD distribution was established. Quantile estimation method was applied to estimate the GLD parameters. The proposed method had no need of presetting specific distribution morphology, and thus improve the accuracy of IRSS pseudo-failure reliability modeling. In the application experiment, the IRSS pseudo-failure life distribution reliability evaluation method based on GLD was used to obtain the IRSS failure life, the reliability evaluation result was consistent with the design failure life, which indicated the validity of the proposed method.

As a measuring instrument, the signal analyzer is widely used in communication, microwave, aviation and other fields. It can not only measure the quality of the input signal, but also quickly demodulate the measured signal to obtain the information contained in the signal. In this paper, a method of pulse compression time sidelobe analysis applied to the signal analyzer is proposed to analyze and test the pulse measurement signal. First, the correlation between the pulse measurement signal and the pulse reference signal is processed by pulse compression. Secondly, the sidelobe suppression analysis is carried out by using the window function method for the reference signal. Finally, according to the pulse compression correlation amplitude results, the main side lobes are separated, and the time side lobes are further analyzed and the corresponding parameters are calculated. The simulation results show that the root mean square error of parameter calculation is less than 5%, which meets the standard of signal analyzer for pulse compression time sidelobe analysis.

Centrifugal fan is widely used in industry, vehicle and ship application to provide air cycle power. To detect the fan fault at early stage, this paper explores the fault feature in the vibration signal and fault diagnosis method through the fault injection test, where impeller unbalance, rotor unbalance, and bearing fault are involved. Firstly, the fault mechanism is introduced; then, the fault injection methods of the three faults are introduced to obtain the faulty fans; finally, health and fault tests are performed, where the vibration sensors are employed and distributed on the fan in the axial and radial direction. Moreover, the acquired vibration data is analyzed by using time-domain and frequency-domain methods, and further the fault features between health and fault are compared and discussed. The analysis results indicate that the three faults can be detected through the vibration intensity and magnitude comparison at their individual characteristic frequencies in the spectrum.

To address the problem of asynchronous delay caused by combining at least two array platforms in 2D/3D location, in this paper, we analyze the impact of time difference between asynchronous devices on time-delay estimation from the experimental phenomenon. Then, we propose a USB asynchronous correction algorithm which takes the known propagation delay as the benchmark, the time difference of asynchronous equipment is calculated by offseting the time delays on the left and right sides. The experimental results show it can correct the time difference for USB asynchronous microphone arrays, which achieve a great location accuracy.

Aiming at the key technical requirements of ultrasonic measurement of internal temperature of high temperature solid structure, firstly, the mechanical structure of ultrasonic transducer is miniaturized and high-temperature resistant design is carried out, so that it can withstand the high temperature of 800°C. Meanwhile, the multi-waveform, multi-channel and multi-frequency excitation detection is achieved, and the integration of structure and function is realized. In addition, the high-speed data acquisition module adopts a 1GSPS sampling rate acquisition card combined with the phase-based acoustic time integral zero sub-measurement method to achieve the nanosecond acoustic time measurement accuracy required by ultrasonic temperature measurement. Finally, the reconstructed internal temperature field of steel structure is carried out by using the developed electromagnetic ultrasonic temperature measuring instrument and compared with the temperature measuring result of thermocouple, which verifies the reliability of high temperature resistant electromagnetic ultrasonic probe and high-speed acquisition module. The research shows that the integration of ultrasonic temperature measurement technology and the design and development of instruments will provide effective analysis methods, research means and testing tools for exploring the internal temperature parameters of structures.

The characteristics and action mechanisms of intentional interference sources were analyzed. Then, a fast detection method of intentional co-channel interference was proposed based on such technologies as real-time spectrum analysis, digital phosphor display, and co-channel signal direction-finding. Next, two classical intentional interference scenarios were reproduced, and interference sources were detected fast through the proposed method.

In view of the problems such as difficulty in and high cost of vibration signal collection of rotating mechanical rotating shaft, this paper proposes a low-cost, fast, stable and reliable hydraulic turbine rotating wheel vibration signal online monitoring scheme specially designed to the imbalance and dynamic balance counterweight of hydraulic turbine rotating shaft. Three high-frequency wireless acceleration sensors are installed on the rotating shaft to monitor the vibration signals of the three directions in real time. Vibration signals are sent to the cloud platform to facilitate data storage. The acceleration signal is decomposed by WOA-VMD. The time domain signal shows the running track of the shaft to guide the dynamic balance counterweight of the rotor. The frequency domain signal is used to analyze the machine vibration in the shaft frequency domain and predict the health status of the shaft according to the frequency change. According to this system, completed the experiment of a hydraulic turbine experiment, proved the feasibility and rationality of the system, and has good application prospect and practical value.

In Fretting is an important research direction in the detection of urban underground space structure. Traditional geophones have three issues with achieving fretting detection in the field, high cost, large size and low accuracy. A fretting signal acquisition system based on AD7177 is proposed to solve the above problems, which takes STM32 as the design core. A decision-making scheme that combines the signal acquisition system with the vibration sensor is introduced, which is used to settle the large size and high cost of the instrument. To improve the system accuracy, the AD7177 high-precision A/D conversion module and GPS are used for signal processing and positioning timing respectively. Finally, tests and field experiments were conducted in a state equipped with large storage space and WIFI transmission, which shows the system is convenient and successful. The experimental results show that the scheme is effective, the AD7177-based fretting signal acquisition system has high accuracy and small volume, which has a good ability to complete fretting detection.

As radar is a kind of measuring device, the altitude measuring accuracy is a quite important core tactical indicator. In engineering practice, the altitude measuring accuracy deteriorates significantly in low elevation range, especially for low frequency radar such as VHF radar. This urgent problem to be solved is what we focus on in this article. After building a multipath reflection model, a method of altitude super-resolution measurement based on synthetic steering vector and model matching is proposed. Then some simulation analysis is finished, and some validation experiments are carried out on a practical VHF radar prototype. The results of theoretical simulation and prototype experiments show obviously improved altitude measuring performance compared with traditional measuring methods, verifying the correctness and engineering feasibility of the super-resolution altitude measurement technology proposed in this article. This study should have certain practical guiding significance for the theoretical and application research of related fields.

The estimation method based on the electrochemical impedance spectrum can comprehensively describe the reaction process of Li-ion battery without causing damage to the battery, and is suitable for estimating the state of health of the battery. In this paper, the equivalent circuit model of Li-ion battery is established by analyzing the ac impedance spectrum of Li-ion battery and the internal reaction process of the battery, and corresponding each component of the model and the composite link with the curve segments in the impedance spectrum, and the model parameters are identified offline with the help of The Nyquist diagram of impedance spectrum. It is found that the charge transfer internal resistance and low-frequency impedance amplitude in the equivalent circuit increase monotonically with the aging of the battery. Then, the temperature compensation coefficient was introduced to solve the influence of temperature factors on the SOH estimation of lithium batteries, And the root mean squared error of SOH estimation before and after temperature compensation was reduced from 31.7 to 3.0, and the sum of squares for Error was reduced from 13054.7 to 19.8, which significantly improved the SOH estimation of batteries with different temperatures; and a model based on BP neural network was constructed, And the correlation coefficient of model prediction was 0.994. Solving the influence of production process differences on SOH estimation of lithium batteries, and the advantages and disadvantages of the two estimation methods are summarized.

In this paper, unsupervised method is studied to solve the problem that it is difficult for spacecraft to obtain tagged hitch data. Firstly, the incremental cross-correlation filtered attribute selection algorithm (ICF) is used to complete the selection of feature subsets of spacecraft multivariate time series (MTS);Then the unsupervised learning model of LSTM-SAE is trained on a large number of normal data; Finally, a complete hitch monitoring and health evaluation system is established and verified on the data of three fault degrees. The feature space of normal data is constructed, and the health state of spacecraft is measured by the reconstruction error of faulted data and the distance of feature space. It solves the problem of predicting and avoiding catastrophic failures of spacecraft under the conditions of lack of prior knowledge, unbalanced data distribution and incomplete failure modes.

A battery module was taken as the research object, and the BSR test of the module was carried out based on the silent vibration table, and the BSR evaluation of the module was realized through the combination of subjective and objective mode. In order to achieve the accurate positioning of the abnormal noise of the module, the frequency point of the abnormal sound is locked based on the relative approach technology, and the playback and confirmation of the abnormal noise of the module is carried out based on the filter playback technology. Finally, acoustic imaging is used to locate the abnormal noise of the module. The research results show that the evaluation of BSR needs to be combined objectively and subjectively, and the rapid identification and location of abnormal noise of battery modules is realized by combining relative approach technology, filter playback technology and acoustic imaging technology.

according to the measurement principle and performance requirements of acoustic Doppler velocity profile, a circuit for weak frequency signal processing is designed. The measurement principle, circuit structure, data comparison before and after signal processing and frequency measurement accuracy data analysis are introduced. The performance comparison and application of the instrument are carried out according to the relevant standards. The experimental results show that the signal processing circuit realizes the constant amplitude amplification of the wide dynamic range frequency signal, and the processed signal is converted by A / D and then measured by digital frequency to obtain a high frequency accuracy. In the application of channel flow measurement, the velocity profile can reflect the change trend of cross-section velocity and complete the accurate measurement of flow rate. It shows that the flow profile instrument based on the signal processing circuit can meet the requirements of on-line monitoring of flow velocity and flow of river and channel.

Gas steam boilers are special equipment subjected to high temperature and pressure, it is particularly important to detect and deal with operation faults in time. Against the 4 types of common fault of gas steam boilers, the fault diagnosis model was established based on deep neural networks (DNN), and the model parameters were optimized and verified by experiments. The results show that the fault diagnosis model performs the best as Tanh of the activation function, 100 of Batch_Size, Adam of Optimizer, 10^-5 of learning rate and 0.2 of Dropout since the output accuracy is above 92% and the model begins to converge with iterative times of 12. The accuracy of fault identification of reaches 100% in verification experiments and the model can still effectively recognize the dataset from the early stage which suggests that the fault diagnosis based on deep neural networks has high accuracy and provides a reliable solution for the safety supervision of special equipments.

As a kind of nondestructive testing technology, stress wave technology has the advantages of long propagation distance, strong anti-interference ability and convenient use, and has become one of the important means to detect wood properties and defects at home and abroad. This paper introduces several stress wave wood testing equipment commonly used in the field of wood non-destructive testing at this stage, and analyzes its characteristics. The research status of stress wave wood nondestructive testing technology is analyzed from three aspects: mechanical property testing, internal defect testing and factors affecting stress wave propagation velocity. Finally, the existing problems and development trends of stress wave technology in wood nondestructive testing are discussed to provide reference for further research in this field.

Technologies such as external sensors, data acquisition, trend analysis, and cloud services make remote operation and maintenance of equipment status monitoring more convenient and lower maintenance costs. In this paper, an industrial robot operation and maintenance system is designed. First, the online monitoring of the robot is realized by collecting the control parameters, state parameters, fault information and external sensor monitoring information of the industrial robot. Then, the health baseline of the industrial robot is established based on the historical operation data. The online data is compared with the baseline data to realize the online assessment of the robot's health status. Finally, a visualization platform for remote operation and maintenance of the robot is built to realize the online display of parameters, health trend tracking and fault status early warning, which is convenient for maintenance personnel to take timely countermeasures.

According to the characteristics of unmanned aircraft systems (UASs) with multi-rotors, this paper realizes the reliability evaluation. Referring to the relevant standards and specifications for reliability evaluation of electronic products and communication products, the methods of sampling, test plan, test conditions and index evaluation related to reliability evaluation of Referring to are proposed. Based on the exponential distribution, the reliability index and its calculation method are put forward, and the evaluation method for non-failure data is also studied. The method is applied and the reliability level of UASs with multi-rotors is obtained. This method meets the actual market demand and provides a practical method for UASs reliability evaluation.

To develop the digital twin system of unmanned aircraft vehicle (UAV), a multi-information fusion and time-varying simulation technology based on the testing data is proposed. And a UAV digital twin system is developed. First, the system composition and the working principle of the UAV digital twin system are introduced, respectively. Second, the Ko displacement theory is applied to realize the integration of the acquired data and the finite element simulation model. Then, the model reduced method is introduced, which can reduce the scale of the finite element model and improve the calculation efficiency. Finally, the experimental verification is carried out. The test results and simulation calculation data show that the relative errors between the proposed calculation method and the test results are within 30%, which meets the requirements of engineering application. The test results show that the proposed UAV digital twin technology is feasible, providing a reference case for the development of UAV digital twin technology, which has practical engineering significance and military value.

In this paper, the insulator string images captured by Using unmanned aerial vehicles (UAVs) in the power inspection are taken as the research object. The image processing and deep learning methods are used to label the images, and the self-explosion fault of the identified and segmented insulator strings is identified and located.

In the process of semantic segmentation of insulator string images, the given image data set is enhanced, and images are exchanged with image processing algorithms. Based on SegNet, each pixel in the picture is classified, and then the self-encoding is used for reference, and the image is first encoded and then decoded. The coding layer before the model uses the VGG-16 network to extract smaller pictures, so as to meet the requirements of semantic segmentation, and the decoding layer after the model obtains the classification probability value of each point and classifies each point. The experimental results show that the SegNet algorithm can realize the recognition and segmentation of insulator string images under complex conditions with high accuracy.

In order to realize the identification and location of the self-exploding fault position of the insulator string, the training model can be used to detect the position of the self-exploding insulator in the image. First, the data of target detection is preprocessed, and then the data set transformation method of rotation transformation and image mirroring is used; then the SSD model is selected to identify and locate the self-explosion position of the insulator. The SSD model combines the advantages of the Faster R-CNN model and the YOLO model. It runs faster and has higher detection accuracy, which meets practical applications. The experimental results show that the SSD algorithm is more targeted to the insulator data set, and can improve the speed and accuracy of insulator identification and positioning.

The concept and technical principle of the digital prototype are introduced, and the test content and method of the digital prototype for reactance equipment are proposed. For typical communication countermeasure equipment, the content and essence of the digital prototype are discussed in detail. How to carry out the acceptance test and how to apply it in the simulation platform in the future are also discussed. A simple digital prototype, prototype test platform, and simulation platform are constructed to verify the concepts and methods proposed in this paper.

Due to the rapid growth of the number of sensors in modern industrial society, detecting outliers in time series has become very important. And unsupervised detection of outliers in time series is a very challenging task. For most detection tasks of time series outliers, the autoencoder is one of the main choices. And the recursive network is usually used in the self-coding network structure. However, recent studies have shown that the network structure using dilated causal convolution performs better than the recursive network in all kinds of sequence modeling. In this paper, the encoder and decoder are network structures based on extended causal convolution The time series are reconstructed and then compared with the original data to calculate the distance between them, so as to identify the outliers. We use the Temporal convolution autoencoders to evaluate anomaly data sets in multiple time series. Our results show that the Temporal convolution autoencoders has better anomaly detection ability. In addition, we learned that the combination of Feature Engineering and super parameters will also have a great impact on the results, so ablation experiments need to be carried out carefully.

Metrology support includes the management of measurement equipment and measurement process, which is an indispensable part of engineering construction. Aiming at the health status of instrumentation in use in enterprises metrological verification, BP and SOFM neural networks are introduced, the characteristics of the two neural networks are introduced, the sample data system and network algorithm are designed, and a set of scientific and complete evaluation methods are produced through algorithm practice and data analysis, which provides direction for the research on the health status of instrumentation in use.

At present, Imaging Photoplethysmography (IPPG) has attracted extensive attention on heart rate measurement, because of its non-contact, non-invasive and safe characteristics. However, in reality, the IPPG signal is extremely feeble and susceptible to be submerged by ambient interference such as illumination. To this end, we propose a new IPPG signal processing approach to enhance the anti-interference capability of measuring heart rate through a modified EEMD algorithm with updated white-noise iterating. In the modified EEMD algorithm, based on the standard deviation of the input IPPG signal, zero-mean white noises are generated randomly for iterative ensemble averaging. Through this new method, the fault caused by the residual white noise of traditional EEMD is solved. Lastly, through the comparative experiments of our own acquisition statistics, the approach proposed by this paper has significantly improved the performance in terms of accuracy, timeliness and anti-interference under various scenarios. The mean absolute error reaches 1.4 beats per minute and the correlation coefficient r reaches 0.8089. In addition, the modified EEMD algorithm reduces the running time by more than 10 times compared to the original method, approximately 0.16s per time.

In engineering practice, a constant voltage output control system of synchronous rectifier primary side regulator (PSR) flyback converter is proposed to overcome the sampling defect of the existing digital approximation double line sampling scheme for primary side control synchronous rectifier structure. Regardless of the slope of the sampling waveform and the knee point, the single-output DAC midpoint sampling can achieve high sampling accuracy and good knee point following effect. At the same time, the neutral-point sampling error of the single-output DAC is analyzed, and a sampling compensation scheme which can simultaneously act in continuous current mode (CCM) and discontinuous current mode (DCM) is designed to further correct the sampling voltage obtained by neutral-point sampling, so as to compensate the voltage error of neutral-point sampling. Thus, the output voltage can be accurately constant in DCM and CCM.

In a high-speed sampling system, the clock jitter of analog-to-digital converters (ADCs) will greatly affect its sampling accuracy, leading to the reduction of the signal-to-noise ratio (SNR) of the system output. Therefore, it is necessary to compensate the sampling results to reduce the sampling error caused by clock jitter by measuring the distribution sequence of jitter. In this paper, the influence of clock jitter on the ADC sampling process is analyzed, and an ADC clock jitter measurement scheme based on a simple coherent sampling algorithm is investigated. This scheme can accurately measure the distribution sequence of clock jitter, and has the characteristics of low computational complexity and high precision. The simulation results show that this algorithm can accurately measure the clock jitter sequence with root-mean-square (RMS) greater than 5ps when the amplitude noise of the input signal is greater than 35dB, and the relative error is less than 5%.

Using robots to replace human beings to achieve large-scale automatic operations has become an inevitable trend. Wall-climbing robots have important application value in the field of aerial work. For the existing wall-climbing robots have limitation on movement flexibility and overcome own gravity by adsorption friction, this paper innovatively proposes a wall-climbing robot with suspension traction, back push adsorption and McNum wheel driving. Meanwhile, an electronic control system and control algorithm are designed. Experiments results show that the wall-climbing robot has advantages of high relative load, omnidirectional movement, strong continuity of movement and smooth operation.

Room temperature ionic conductivity of the solid-state electrolyte is the essencial element of the commercialization of solid-state lithium-ion batteries. First-principles method is a good tool as it simulates the atomic level dynamics, and provides accurate insides of the ion moving velocity, path, and the microscopic environment. However, the first-principles method is time and computational resources-consuming. It is usually applied to systems with hundreds of atoms and the simulation time is less than 100 picoseconds. The classical molecular dynamics method applies to systems containing thousands of atoms and the simulation time can reach the scale of nanoseconds. However, it is based on the experimental force-field parameters and can only be applied to limited systems with experimentally-proofed good parameters. The method used in this paper is a combination of the first-principles simulation and classical dynamics. Deep-learning tool Deepmd-kit is used to train the first-principles simulation data of the targeted system into a tailor-made force-field model. The verified model for the specific system will then be used in the classical molecular dynamics simulation. With the first-principles precise and classical efficiency, the molecular dynamics simulation of ion movement at room temperature is achieved. The results of Li₁₀GeP₂S₁₂ and Li₁₀SiP₂S₁₂ showed good agreement with the experiments.

Based on improving the dynamic and static performance of the brushless DC motor control system, a speed current closed-loop brushless DC motor control scheme is designed by using SVPWM. In the light of the environment of matlab/simulink, the vector control model of BLDCM is established by using the control strategy of id=0 and the idea of modularization. The simulation results show that the system has good dynamic and static performance and stable operation, which proves the reliability and effectiveness of the simulation model.

With the continuous improvement of modern manufacturing automation and process intensification, the complexity of tools and machined parts has greatly increased, and their performance directly affects the quality of workpieces and production efficiency. Accurate prediction of tool life is conducive to improving production efficiency and reducing enterprise costs. In this paper, a tool life prediction method based on multi-source feature PSO-SVR neural network is proposed. By monitoring and collecting the current and vibration signals of the tool during the machining process of CNC machine tools, the time-frequency eigenvalues are extracted. The effective features are extracted by feature selection technology as the input of support vector regression (SVR) neural network, and the parameters of the network are optimized by particle swarm optimization (PSO), so as to improve the accuracy of the predict, and finally predict the remaining useful life(rul) of the tool.

In order to solve the problem of insufficient accuracy and reliability of ship position display in AIS(Automatic Identification System) system, a federated Kalman filter is designed, an open algorithm architecture is built, AIS and BDS positioning information sources are selected for fusion, and the information fusion part of the federated Kalman filter framework is improved by IMMF algorithm and covariance crossover algorithm to obtain more accurate and reliable target position information and ship motion state. Simulation experiments are carried out, and the experimental results show that, compared with GPS positioning or BDS(Bei Dou Navigation Satellite) positioning in AIS alone, AIS/BDS combined positioning based on federated Kalman filter structure has higher system fault tolerance, positioning accuracy and stability, and improves the safety of ship navigation.

HIL(Hardware in the loop) simulation of UAV(Unmanned Aerial Vehicle) plays an important role in flight control sysrtem development and algorithm verification. Taking the open source flight control system Pixhawk as the research object, this paper establishes a HIL system based on NI(National Instrument) hardware platform. The dynamic model and kinematic model are modeled through Simulink, the online management of simulation model is realized through Veristand, and the online display of model parameters and fault injection are realized through Labview. The simulation system can test the functional performance, reliability and safety of flight control system. The simulation results show that the simulation platform works reliably and has good real-time performance. It can effectively and reliably carry out the HIL of flight control system for UAV.