Table of contents

This paper presents a sensor system for capacitive ice detection, with planar electrodes located on a PCB. In order to minimize the required area, the electrodes are concurrently designed as an antenna structure for wireless data communication. With this approach a compact and thin sensor system for capacitance measurements can be realized. The capacitive sensor works on the principle of a mutual capacitance measurement method. An electrode of the sensor system works on one hand as an excitation source, emitting an electric field with a few hundred kHz and at the same time on the other hand the electrode acts as a 2.45GHz ISM patch antenna for wireless data communication. The scientific questions addressed in this paper are: Are the parasitics introduced as a result of the patch antenna and transmitter/receiver electrodes controllable under the assumption that the measured capacities are within the range of several hundred femtofarads? Do the capacitive couplings of the measuring electrodes influence the matching and the radiation pattern of the antenna, so that wireless data transmission is still possible? For both questions also the impact of the temperature is investigated.

Nowadays phased microphone arrays have become a standard technique for acoustic source localization. Until now microphone arrangement is generally based on the conventional beamforming. Compared to the conventional beamforming, deconvolution algorithms such as DAMAS can achieve significantly improved spatial resolution. Recently the computing speeds of deconvolution algorithms have become faster and faster due to the developments of acceleration algorithms and computer ability. In this paper, phased microphone arrays based on deconvolution algorithms is preliminarily investigated in this paper. Three common microphone arrangements (circle array, grid array and spiral array) with same microphone channels are designed firstly. Subsequently their dynamic ranges with deconvolution algorithms are compared. At low frequency, these three arrays have nearly the same dynamic range. However at high frequency, circle array nearly has the same dynamic range with spiral array, while grid array has smallest dynamic range. Considering the experimental costs, circle array could replace spiral array as the first choice of microphone arrangement based on deconvolution algorithms

Based on their favourable mechanical features, applications of ceramics are continuously spreading in industrial environment. Such a good feature is their resistance against heat shock, so, currently they are applied e.g. as coating material for gas turbines. The paper proposes an indirect method for supervision of the cutting tool wear in the optimisation of a micro-milling process of ceramics. It replaces the expensive and time consuming measurement of the cutting tool wear in which the experiment have to be stopped, the tool has to be taken from the machine and it has to be measured e.g. by microscope. The replaced measurement has also the disadvantage that the tool has to be positioned (again) when putting it back to the machine bringing also inaccuracies to the machining. Experiments show that the proposed novel technique allows monitoring the tool wearing process characteristics without measuring the tool directly, even if the applied indirect measurement (on the workpiece) incorporates some inaccuracies. The introduced methodology supported the ceramics milling technology optimisation according to tool live and machining process time, simultaneously.

The paper presents detailed model of noise sources in supercapacitors. Noise phenomena observed in supercapacitors may be used as a diagnostic tool for assessment of supercapacitor quality or degradation mechanisms (e.g. corrosion of the electrodes or clogging up the pores) during ageing. Therefore, it is important to consider where noise is generated. The equivalent circuit of noise sources existing in supercapacitor is proposed. Methods of noise sources identification are also considered. Limitations of the proposed model are underlined. Final conclusions show a path of further investigations of random phenomena in supercapacitors.

In the field of electrical machine diagnosis the finding of faults in the stator of the electrical machine is one of the greatest challenges. Stator faults have many possible reasons. They may be generated by shorts in the winding or circuit-breaks in one or more coils. In order to find that kind of faults, it is usually necessary to remove the electrical machine from the vehicle and to analyse the machine with external measurement devices. This approach is very expensive, time consuming and unnecessary, in the case that there is no fault. In the following paper, a method is described how the electrical resistances of the stator coils is estimated for diagnostic purposes. For the application of this method only the measurement system is used, which is usually installed in the vehicle. With using the internal sensors in the machine the cost and the time can be reduced. An removal of the electrical machine may be prevented and the using of external measuring equipment can be avoided.

Luminaires for outdoor use are subjected to mechanical vibrations, mainly due to wind, that can generate stress conditions on the devices and affect their reliability performance. The effects of such vibrations on the luminaires can impact both the fixing systems and the device's components; in the last case, such effects can be divided into electrical type failures (LED control gear failure, electronic components failure, etc.) and optical type failures (breakage or detachment of the optics placed on the LED). Starting from the study of international standards concerning vibration tests for luminaires, and from scientific literature, several laboratory tests have been performed to verify the behaviour of equipment subjected to wind induced vibrations. After that, a new test profile applicable to luminaires for outdoor use has been proposed. In order to establish properly wind induced vibration levels and optimize luminaires testing costs.

The focus on diagnostic and fault tolerant architectures is an important subject of the reliability analysis, especially in Oil&Gas application. This paper proposes a new approach for redundant configuration that guarantee the maximum productivity and minimize the possible equipment down-time due to an item failure. Sensors, transmitters and indicators used in this manufacturing field could be connected in 2DA or 3DA redundant configuration in order to obtain this scope.

The aim of the measurement and control activity is to carry out accurate and reliable measurements of a lot of physical quantities in the shortest possible time. Over the last few years, the evolution of electronics, information technology and telecommunications has made it possible to develop automatic measurement system to accomplish complex measurements in ever faster times, with a high degree of reliability and storage capacity. This work focuses on design, implementation and testing of a flow rate automatic measurement system.

A new diagnostic technique using a quasi-optical cavity resonant system to detect parameters of glow discharge plasma is presented in this paper. In this approach, electron density was calculated from resonant parameters of the quasi-optical cavity. The reliability and repeatability of this new diagnostic technique was well approved. The key feature of the proposed method is that the experimental implementation was in real time with high stability and sensitivity.

This research covers a novel approach to non-contact angle encoder disk roughness measurements while using the proposed system attached to the rotary table with an implemented reference angle encoder. Non-contact surface measurement methods are analyzed in the paper. The proposed non-contact surface roughness measurement technique involves the use of a conventional optical disc laser reading system as a cost saving solution. Assets and drawbacks as well as detailed analysis of the measurement procedure are given in the paper. The structure of the device is presented within this article together experimental results.

Following the current trend of the automotive context, also in the motorcycle applications the employment of sensors for improving vehicle performance and passenger's safety are becoming even more widespread. Among the most recent examples of this trend we can find the systems designed to electronically control and to on-line adapt the suspension subsystems. Of course, the correct operating of such systems is strictly related to the reliability of the information provided by the sensors involved in the related measurement and control chain. In this framework, the paper proposes an Instrument Fault Detection and Isolation (IFDI) Scheme for a motorcycle semi-active suspension system equipping a real prototype motorcycle. In particular, the proposed scheme is based on the analytical redundancy existing among the quantities measured by the involved sensors. As for the residuals generation, suitable soft sensors based on artificial neural networks are proposed to allow the fault detection and isolation.

The aim of the article is to analyze the applicability of infrared thermography as a diagnostic tool to support the inspections of the structure and equipment elements of bridges. Infrared thermography consists of recording the power of electromagnetic radiation emitted by the surface of a given body. Thanks to the IR camera, the energy of the infrared radiation is converted into an electrical signal whose value depends on the temperature of the object. The starting point is the assumption that the distribution of temperature anomalies, recorded by IR camera, may be associated with located under the surface hidden defects. In-situ and laboratory tests were performed to document the use of this NDT tool in bridge diagnostics.

Generally, it is difficult to estimate model parameters for time varying output system especially when the input is unknown. One way to estimate them is to repeat simulations to search for the case where the outputs match by changing model parameters and input signals. However, such method is time consuming. Our previous studies show that the backward simulation with an appropriate model can estimate the input signal. Therefore, it is efficient only to change model parameters in the backward simulation if we can properly assume an appropriate model for the system. This paper describes a method using a generic causal model for determination of a thermal model to match the measured temperature change. Such simulator is implemented by using Node-RED. The performance of the simulator is shown for the cases of ideal resolution data, limited resolution data, and real measured data.

The article presents a brief insight into the university research of efficient methods aimed at revealing counterfeit electronic components. Methods like multichannel curve tracing, component internal structure X-raying, system on chip optical inspection with higher magnification microscopy and Scanning Electron Microscopy combined with Element Energy Dispersive Spectroscopy (EDS) are powerful means for authenticity verification. Comparative analysis results serve as an illustration of cases where various features differences can warn not to let a particular component delivery penetrate the assembly process.

Many electronic systems used in industry or other special areas are put at risk by counterfeit electronic components occurrence, especially by semiconductors. These counterfeit components represent a serious threat for systems functionality and reliability. We can take as a fraudulent or as a suspicious component any component of unknown origin, which we can find any difference in contrast to the original manufacturer component of the same model. This article describes advanced microscopic techniques used in problems with counterfeit integrated circuits. Their genuineness evaluation ability is discussed and illustrated with several microscopic images.

The paper presents the rules induction algorithm designed to identify and locate faults in the analog systems. Compared to the most popular numerical methods, such as Artificial Neural Networks, this approach enables presenting knowledge behind the reasoning mechanism. This way it is possible to better understand relations between measured symptoms and particular faults. The method exploits the preliminaries of the AQ algorithm, which was proposed for the discrete data. The modification proposed in this paper covers the analysis of continuous features and adjusting the method to work in the uncertainty conditions. Evaluation of the approach, using DC motor driven servomechanism is performed.

The idea of using the changes of the characteristics of natural or forced vibrations (natural frequency, natural modes, damping) for the determination of the position and magnitude of damage to building structures originated in the 70s [1]. The achievement of ever higher accuracy of developing dynamic displacement sensors and evaluation instruments has made this idea increasingly applicable. Identification is a process defining the properties of a structure and the characteristics of its design model. The often required identification task of determining the rate of deterioration of structures by means of their dynamic response has been numerous lately. The paper sums up the experience of the Institute of Theoretical and Applied Mechanics (ITAM) of the Czech Academy of Sciences, with laboratory tests of large models and in-situ measurements.

A machine learning technique was used to monitor the state of damage of steel specimens subjected to cyclic contact fatigue tests and to make a continuous measurement without coming into contact with the specimens examined. Six different sets of specimens were considered and the torque and vibration data obtained from their respective tests were analyzed. Different statistical and spectral characteristics were obtained from each dataset, to represent their information content. The correlation existing between the characteristics was studied to select only the essential ones. The global data volume was reduced by a principal component analysis. The data thus obtained were subsequently processed, and classified, developing a K-means algorithm. The results were formulated in probabilistic terms with the aid of membership charts, confusion matrices and probability curves. The results obtained from this first analysis are highly encouraging. The algorithm is able to assess the damage status of the specimens, as well as detect the operating conditions of the machine. A substantial advantage of this method is the ability to estimate quantitatively the damage by calculating the distance of the current data from specific references. The performances of this approach were numerically estimated in terms of sensitivity, specificity and accuracy.

Providing high quality data for the test and evaluation of diagnostic algorithms is of high importance for modern complex systems. To this end a testbed capable of supporting degradation of components and instrumentation has been designed, manufactured and commissioned. It has specifically been designed to replicate five component and instrumentation faults with high accuracy and repeatability for different degrees of severity. This paper documents the design process and shows some of the capabilities of this platform.

This paper proposes a fast-estimation approach to demodulating multiple frequency signal for online electromagnetic rail detection. In order to speed up the demodulation, the approach uses the sine function's expression to build Kalman filtering model, and by only one measured point, it can demodulate each component's amplitude in multi-frequency signal induced in sensors. Instead of using all measured points in a period, the demodulating speed is faster than other demodulation methods, like FFT and fast correlation. Finally, the experimental result shows that this approach can follow the amplitude variation caused by the defect for online electromagnetic rail detection.