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Electrostatic sensors are applied to measure velocity of solid particles in many industries because controlling the velocity particles improves product quality and process efficiency. The purpose of current paper is optimization of these sensors which is required to achieve maximum spatial sensitivity and minimum statistical error.

Different electrode of electrostatic sensors with different length, thickness and sensor separations were experimentally applied in laboratory. Then, correlation velocity, signal bandwidth and statistical error were calculated.

High sensor separation is a crucial factor because it would lead to increase signal similarity and decrease statistical error. This paper focuses on the effect of sensor separation on optimization of electrostatic sensors.

From observations, the optimal value for length, thickness and sensor separations was 0.6, 0.5 and 15 cm, respectively. Consequently, statistical error has improved by about 17 per cent. These results provided a significant basis of optimization of electrostatic sensors.

Circular pipelines are mostly used for pneumatic conveyance in industrial processes. For optimum and efficient production in industries that use a pipeline for conveyance, tomographic image of the transport particles is paramount. Sensing mechanism plays a vital role in process tomography. The purpose of this paper is to present a two‐dimensional (2‐D) model for sensing the characteristics of electrostatic sensors for electrical charge tomography system. The proposed model uses the finite‐element method.

The domain is discretized into discrete shapes, called finite elements, by using a MATLAB. Each of these elements is taken as image pixels, on which the electric charges carried by conveyed particles are transformed into equations. The charges' interaction and the sensors installed around the circumference, at the sensing zone of the conveying pipeline are related by the proposed model equations. A matrix compression technique was also introduced to solve the problem of unevenly sensing characteristics of the sensors due to elements' number's concentration. The model equations were used to simulate the modeled electrostatic charge distribution carried by the particles moving in the pipeline.

The simulated results show that the proposed sensors are highly sensitive to electrostatic charge at any position in the sensing zone, thereby making it a good candidate for tomographic image reconstruction.

Tomographic imaging using finite element method is found to be more accurate and reliable compared to linear and filtered back projection method.

Electrostatic monitoring technology is a useful tool for monitoring and detecting component faults and degradation, which is necessary for engine health management. This paper aims to carry out online monitoring experiments of turbo-shaft engine to contribute to the practical application of electrostatic sensor in aero-engine.

Combined with the time and frequency domain methods of signal processing, the authors analyze the electrostatic signal from the short timescale and the long timescale.

The short timescale analysis verifies that electrostatic sensor is sensitive to the additional increased charged particles caused by abnormal conditions, which makes this technology to monitor typical failures in aero-engine gas path. The long scale analysis verifies the electrostatic sensor has the ability to monitor the degradation of the engine gas path performance, and water washing has a great impact on the electrostatic signal. The spectrum of the electrostatic signal contains not only the motion information of the charged particles but also the rotating speed information of the free turbine.

The findings in this article prove the effectiveness of electrostatic monitoring and contribute to the application of this technology to aero-engine.

The research in this paper would be the foundation to achieve the application of the technology in aero-engine.

The aero-engine array electrostatic monitoring technology (AEMT) can provide more and more accurate information about the direct product of the fault, and it is a novel condition monitoring technology that is expected to solve the problem of high false alarm rate of traditional electrostatic monitoring technology. However, aliasing of the array electrostatic signals often occurs, which will greatly affect the accuracy of the information identified by using the electrostatic sensor array. The purpose of this paper is to propose special solutions to the above problems.

In this paper, a method for de-aliasing of array electrostatic signals based on compressive sensing principle is proposed by taking advantage of the sparsity of the distribution of multiple pulse signals that originally constitute aliased signals in the time domain.

The proposed method is verified by finite element simulation experiments. The simulation experiments show that the proposed method can recover the original pulse signal with an accuracy of 96.0%; when the number of pulse signals does not exceed 5, the proposed method can recover the pulse peak with an average absolute error of less than 5.5%; and the recovered aliased signal time-domain waveform is very similar to the original aliased signal time-domain waveform, indicating that the proposed method is accurate.

The proposed method is one of the key technologies of AEMT.

Since carbon nanotubes (CNTs) were discovered by Iijima in 1991, they have gained more and more attention by people because of their unique physical and chemical properties. The CNTs have one-dimensional nanostructure, high surface adsorption capacity, good conductivity and electronic ballistic transmission characteristics and therefore have excellent mechanical, electrical, physical and chemical properties. CNTs are ideal basic materials to make nanometer gas sensors. Nanometallic materials function as to enhance electrode activity and promote the electron transfer, so if composite nanometallic materials M (such as Au, Pt, Cu and Pd) and CNTs are used, all kinds of their characters of components would have coeffect. Electrochemical sensors by use of such composite as electrode would have a higher detection sensitivity.

CNTs were synthesized via chemical vapor deposition technique and were purified afterward. CNTs-M(Pt,Au) suspension was prepared by chemical deposition using spinning disc processor (SDP) and was coated on gold electrode. The modified electrodes were constructed, based on immobilization of glucose oxidase on an Au electrode by electrostatic effect. CNTs-Pt/ glassy carbon electrodes (GCE) electrodes were made by electrochemically deposition of platinum particles on GCE modified by CNTs. The microstructures of the harvested CNTs, CNTs-M (M = Au, Pt) were analyzed under scanning electron microscopy and transmission electron microscopy. The application of the sensor in medical detection has been evaluated.

The results shown that CNTs-Au biosensors exhibit good reproducibility, stability and fast response to glucose detection, it can be used in the clinic detection of glucose concentration in human serum. Using CNTs-Pt/GCE for formaldehyde detection exhibited high sensitivity and good reproducibility.

This study modified CNTs by using self-assembled techniques through SDP with nano Pt and Au by electrodeposition for the first time. CNTs-Pt/GCE electrode was prepared by depositing platinum particles electrochemically on GCE modified by CNTs. CNTs-Au-modified electrode was prepared by immobilization of glucose oxidase on an Au electrode first by electrostatic effect. Electrochemical behaviors of glucose at CNTs-Au and formaldehyde at CNTs-Pt/GCE were investigated by cyclic voltammetry.

The purpose of this paper is to introduce a rapid method for calculating capacitive sensor signal variations for any small permittivity or electrode modifications at any position in space.

When a capacitive sensor is probing its surrounding, the modification of the permittivity, the displacement or the deformation of one or more electrodes induce a signal variation which depends on the position of the modification. Seeing that modification as a small perturbation and using Gauss identity, it is possible to find integral expressions of the sensor sensitivity map.

Capacitive sensor sensitivity map expressions depend only on the perturbation to measure, on the electric field before the perturbation, and on a sensitivity field which is the electric field produced by the sensor when the measuring electrode is held to 1 V while the others, except the floating ones, are grounded. The sensitivity field is a kind of Green's function for the capacitive sensor. The knowledge of the electric and sensitivity fields makes it possible to obtain the whole sensor sensitivity map at once without requiring time consuming parametric calculations.

The sensitivity field calculation provides a simple and direct view of the capacitive sensor capabilities. That should improve capacitive sensor design.

The purpose of this paper is to conduct a review of types of tomographic systems that have been widely researched within the past 10 years. Decades of research on non-invasively and non-intrusively visualizing and monitoring gas-liquid multi-phase flow in process plants in making sure that the industrial system has high quality control. Process tomography is a developing measurement technology for industrial flow visualization.

A review of types of tomographic systems that have been widely researched especially in the application of gas-liquid flow within the past 10 years was conducted. The sensor system operating fundamentals and assessment of each tomography technology are discussed and explained in detail.

Potential future research on gas-liquid flow in a conducting vessel using ultrasonic tomography sensor system is addressed.

The authors would like to undertake that the above-mentioned manuscript is original, has not been published elsewhere, accepted for publication elsewhere or under editorial review for publication elsewhere and that my Institute’s Universiti Teknologi Malaysia representative is fully aware of this submission.

The pressure sensors can convert external pressure or mechanical deformation into electrical power and signal, which cannot only detect pressure or strain changes but also harvest energy as a self-powered sensor. This study aims to develop a self-powered flexible pressure sensor based on regular nanopatterned polymer films.

In this paper, the self-powered flexible pressure sensor is mainly composed of two nanopatterned polymer films and one conductive electrode layer between them, which is a sandwich structure. The regular nanostructures increase the film roughness and contact area to enhance the friction effect. To enhance the performance of the pressure sensor, different nanostructures on soft polymer sensitive layers are fabricated using UV nanoimprint lithography to generate more triboelectric charges.

Finally, the self-powered flexible pressure sensor is prepared, which consists of sub-200 nm resolution regular nanostructures on the surface of the elastic layer and an indium tin oxide electrode thin film. By converting the friction mechanical energy into electrical power, a maximum power of 423.8 mW/m2 and the sensitivity of 0.8 V/kPa at a frequency of 5 Hz are obtained, which proves the excellent sensing performance of the sensor.

The acquired electrical power and pressure signal by the sensor would be processed in the signal process circuit, which is capable of immediately and sustainably driving the highly integrated self-powered sensor system. Results of the experiments show that this new pressure sensor is a potential method for personal pressure monitoring, featured as being wearable, cost-effective, non-invasive and user-friendly.

Advanced devices and fabrication methods dominated the second Eurosensors conference held in The Netherlands in November 1988. Rory Chase reports.

The purpose of this paper is to show the evolution of microsystems together with modeling methods in the space of dozen years as a result of finished research in the frame of several projects.

In this paper several approaches are presented. First, microsystems were built in multi project wafer technology. They were demonstrators like micromotor, micromirrors or micropumps modeled using dedicated design tool. A multi purpose chip was also designed using HDL description and FEM simulations. The next project concerned chemical sensors, where specialized models were developed and implemented in VHDL‐AMS in order to perform multidomain behavioral simulations. Dedicated tools were also developed for medical applications.

The evolution of MEMS technology is strictly connected with simulation and modeling methods. The success and short time to market need fast and accurate simulation methods. This paper shows that the approach depends on application. Moreover, it is connected with the access to the technology.

This paper presents a brief overview on projects performed in DMCS‐TUL department. It shows the evolution of modeling methods and technology used in developing and fabrication of microsystems for various applications.