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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.

The purpose of this study is to determine the contamination level in natural water resources because the tremendous development in the agriculture sector has increased the amount of contamination in natural water sources. Hence, the water is polluted and unsafe to drink.

Three types of sensor arrays were suggested: parallel, star and delta. The simulation of all types of sensor array was carried out to calculate the sensors’ impedance value, capacitance and inductance during their operation to determine the best sensor array. The contamination state was simulated by altering the electrical properties values of the environmental domain of the model to represent water contamination.

The simulation results show that all types of sensor array are sensitive to conductivity, σ, and permittivity, ɛ (i.e. contaminated water). Furthermore, a set of experiments was conducted to determine the relationship between the sensor’s impedance and the water’s nitrate and sulphate contamination. The performance of the system was observed where the sensors were tested, with the addition of distilled water with different concentrations of potassium nitrate and potassium sulphate. The sensitivity of the developed sensors was evaluated and the best sensor was selected.

Based on the outcomes of the experiments, the star sensor array has the highest sensitivity and can be used to measure nitrate and sulphate contaminations in water.

The star sensor array presented in this paper has the potential to be used as a useful low-cost tool for water source monitoring.

Intelligent pneumatic actuator (IPA) is a new generation of actuator developed for Research and Development (R&D) purposes in the academic and industrial fields. The purpose of this paper is to show the application of optical encoder and pressure sensor in IPA, to develop a real-time model similar to the existing devices, and to assess the position control performance using a proportional-integrative (PI) controller and a bang-bang controller in real-time.

A micro optical encoder chip is used to detect cylinder rod position by reading constructed laser stripes on a guide rod, whereas a pressure sensor is used to detect the chamber pressure reading. To control the cylinder movements by manipulating pulse-width modulation (PWM) cycles, two unit valves of two ports and two positions were used. A PI controller and a bang-bang controller are used with suitable gain value to drive the valve using PWM to achieve the target actuator position.

The results show the experimental results of the closed-loop position tracking performance of the system using a data acquisition (DAQ) card over MATLAB software.

This paper presents a real-time model used to replace the microcontroller-based system from previous IPA design. The paper proposes two control strategies, PI and bang-bang, to control position using encoder and pressure reading.