Optimization and prediction of engine block vibration using micro-electro-mechanical systems capacitive accelerometer, fueled with diesel-bioethanol (water-hyacinth) blends by response surface methodology and artificial neural network

The current investigation is focused on the vibration signals analysis for health status diagnosis of the single-cylinder diesel engine fueled with bioethanol diesel mixture. The water hyacinth (WH) plants (Eichhornia crassipes) are used as raw materials for bioethanol production. The bio-ethanol obtained from WH has been mixed with diesel fuel (WBED) to various extent. Systematically designed experiments were conducted with different working parameters like load, fuel injection pressure (FIP), and compression ratio (CR) in a diesel engine. The Micro-Electro-Mechanical Systems (MEMS) capacitive accelerometer was used to get vibration signals from the engine while operating with blended fuels. The obtained experimental vibrations data have been used to predict the engine vibration by using Response Surface Methodology (RSM) technique and Artificial Neural Network (ANN). The experimental results have been compared with RSM and ANN prediction results. From results, it is elicited that the acceleration declines with the increase in load and CR. At all tested blends, FIP produces a significant effect on the engine block vibration. Among all blends, WBED 5 and WBED 10 produce less vibration as compared to other diesel bioethanol blends. At optimized operating condition the engine block vibration for WBED 5; the experimental acceleration is 0.016962 m/s2 and the predicted acceleration by RSM and ANN is 0.016182 m/s2 and 0.0166 m/s2, respectively. For WBED 10, the acceleration is 0.0172604 m/s2 and the predicted acceleration by RSM and ANN 0.016207 m/s2 0.017 m/s2, respectively, has been found.

Acceleration Anomaly Detection Method for Sensor Axle Box of Unmanned Vehicle

Detecting the anomaly acceleration of the sensor’s axle box of unmanned vehicles is very important for judging the wear condition of vehicle track and evaluating the state of the track. A capacitive accelerometer is connected with acquisition equipment to collect the information of train axle box’s acceleration change when the vehicle is running; instrument amplifier AD8250 with a digitally programmable gain is selected as system signal conversion chip to realize acceleration signal conversion; sliding variance of axle box’s acceleration of the unmanned vehicle is calculated based on sliding variance statistical analysis method, which is confirmed by time window and distance window. Fixing the width of a sliding window according to the response statistics caused by the line excitation link, the acceleration sliding variance is compared with the standard one to determine whether the acceleration is in an anomaly state. The test results show that the anomaly acceleration of the sensor axle box of the unmanned vehicle detected by the proposed method is consistent with the actual results, which provides a reliable basis for vehicle track condition assessment.

Modeling and Analysis of a SiC Microstructure-Based Capacitive Micro-Accelerometer

In this study, a comb-type capacitive accelerometer based on a silicon carbide (SiC) microstructure is presented and investigated by the finite element method (FEM). It has the advantages of low weight, small volume, and low cross-coupling. Compared with silicon(111) accelerometers with the same structure, it has a higher natural frequency. When the accelerometer vibrates, its resistive force consists of two main components: a viscous damping and an elastic damping force. It was found that viscous damping dominates at low frequency, and elastic damping dominates at high frequency. The second-order linear system of the accelerometer was analyzed in the time-frequency domain, and its dynamic characteristics were best when the gap between the capacitive plates was 1.23 μm. The range of this accelerometer was 0–100 g, which is 1.64 times that of a silicon(111) accelerometer with the same structure. In addition, the accelerometer could work normally at temperatures of up to 1200 °C, which is much higher than the working temperatures of silicon devices. Therefore, the proposed accelerometer showed superior performance compared to conventional silicon-based sensors for inertial measurements.

Research on Decomposition of Offset in MEMS Capacitive Accelerometer

In a MEMS capacitive accelerometer, there is an offset due to mechanical and electrical factors, and the offset would deteriorate the performance of the accelerometer. Reducing the offset from mechanism would benefit the improvement in performance. Yet, the compositions of the offset are complex and mix together, so it is difficult to decompose the offset to provide guidance for the reduction. In this work, a decomposition method of offset in a MEMS capacitive accelerometer was proposed. The compositions of the offset were first analyzed quantitatively, and methods of measuring key parameters were developed. Based on our proposed decomposition method, the experiment of offset decomposition with a closed-loop MEMS capacitive accelerometer was carried out. The results showed that the offset successfully decomposed, and the major source was from the fabricated gap mismatch in the MEMS sensor. This work provides a new way for analyzing the offset in a MEMS capacitive accelerometer, and it is helpful for purposefully taking steps to reduce the offset and improve accelerometer performance.

Design of MEMS Capacitive Accelerometer for Automotive Airbag Application

The objective of this paper is to bring out the responsiveness of the capacitive accelerometer with changes in the input acceleration. The performance analysis of the device is done using COMSOL MULTIPHYSICS .It is analysed that when the capacitance reaches a threshold value, amplifying the electric signal the air bag could be initiated.3D capacitive accelerometers which are less prone to noise and temperature variations. They reduce the severity of the accident by sensing the sudden increase in negative acceleration and deployment of the airbags. The dependency between the acceleration and the capacitance has been analysed. The sensitivity of the device with respect to forces in real time accident conditions is observed.