scholarly journals Modeling and Studying Acceleration-Induced Effects of Piezoelectric Pressure Sensors Using System Identification Theory

Sensors ◽  
2019 ◽  
Vol 19 (5) ◽  
pp. 1052 ◽  
Author(s):  
Fujing Xu ◽  
Tiehua Ma
Keyword(s):  
System Identification ◽  
Empirical Mode Decomposition ◽  
Pressure Sensor ◽  
Pressure Sensors ◽  
Shock Acceleration ◽  
Transient Pressure ◽  
Digital Compensation ◽  
Mode Decomposition ◽  
Inherent Frequency ◽  
Identification Theory

Transient pressure testing is often accompanied by shock acceleration. Aiming at the acceleration-induced effects of pressure sensors, a dynamic compensation method combining empirical mode decomposition (EMD) with system identification theory (SIT) is proposed in this paper. This method is more effective at reducing the error of the acceleration-induced effects without affecting the sensor’s sensitivity and inherent frequency. The principle and theoretical basis of acceleration-induced effects is analyzed, and the static and dynamic acceleration-induced effects on the quartz crystal of a piezoelectric pressure sensor are performed. An acceleration-induced effects dynamic calibration system is built using a Machete hammer, which generates acceleration signals with larger amplitude and narrower pulse width, and an autoregressive exogenous (ARX)mathematical model of acceleration-induced effects is obtained using empirical mode decomposition-system identification theory (EMD-SIT). A digital compensation filter for acceleration-induced effects is designed on the basis of this model. Experimental results explain that the acceleration-induced effects of the pressure sensor were less than 11% after using the digital compensation filter. A series of test data verify the accuracy, reliability, and generality of the model.

scholarly journals Rotating Machinery Diagnosing in Non-Stationary Conditions with Empirical Mode Decomposition-Based Wavelet Leaders Multifractal Spectra

Sensors ◽  
2021 ◽  
Vol 21 (22) ◽  
pp. 7677
Author(s):  
Iwona Komorska ◽  
Andrzej Puchalski
Keyword(s):  
Empirical Mode Decomposition ◽  
Pressure Sensors ◽  
Multifractal Spectrum ◽  
Vibration Velocity ◽  
Rotating Machines ◽  
Mode Decomposition ◽  
Acceleration Sensors ◽  
Wavelet Leaders ◽  
Real Objects ◽  
Stationary Conditions

Diagnosing the condition of rotating machines by non-invasive methods is based on the analysis of dynamic signals from sensors mounted on the machine—such as vibration, velocity, or acceleration sensors; torque meters; force sensors; pressure sensors; etc. The article presents a new method combining the empirical mode decomposition algorithm with wavelet leader multifractal formalism applied to diagnosing damages of rotating machines in non-stationary conditions. The development of damage causes an increase in the level of multifractality of the signal. The multifractal spectrum obtained as a result of the algorithm changes its shape. Diagnosis is based on the classification of the features of this spectrum. The method is effective in relation to faults causing impulse responses in the dynamic signal registered by the sensors. The method has been illustrated with examples of vibration signals of rotating machines recorded on a laboratory stand, as well as on real objects.

Empirical mode decomposition-adaptive least squares method for dynamic calibration of pressure sensors

2017 ◽  
Vol 28 (4) ◽  
pp. 045010 ◽  
Author(s):  
Zhenjian Yao ◽  
Zhongyu Wang ◽  
Jeffrey Yi-Lin Forrest ◽  
Qiyue Wang ◽  
Jing Lv
Keyword(s):  
Least Squares ◽  
Empirical Mode Decomposition ◽  
Least Squares Method ◽  
Pressure Sensors ◽  
Dynamic Calibration ◽  
Mode Decomposition

Development of circuit solution and design of capacitive pressure sensor array for applied robotics

2020 ◽  
Vol 8 (4) ◽  
pp. 296-307
Author(s):  
Konstantin Krestovnikov ◽  
Aleksei Erashov ◽  
Аleksandr Bykov
Keyword(s):  
Pressure Sensor ◽  
Output Signal ◽  
Sensor Array ◽  
Applied Pressure ◽  
Pressure Sensors ◽  
Fine Tuning ◽  
Capacitive Pressure Sensor ◽  
Cell Parameters ◽  
Linear Pattern ◽  
Sensor Structure

This paper presents development of pressure sensor array with capacitance-type unit sensors, with scalable number of cells. Different assemblies of unit pressure sensors and their arrays were considered, their characteristics and fabrication methods were investigated. The structure of primary pressure transducer (PPT) array was presented; its operating principle of array was illustrated, calculated reference ratios were derived. The interface circuit, allowing to transform the changes in the primary transducer capacitance into voltage level variations, was proposed. A prototype sensor was implemented; the dependency of output signal power from the applied force was empirically obtained. In the range under 30 N it exhibited a linear pattern. The sensitivity of the array cells to the applied pressure is in the range 134.56..160.35. The measured drift of the output signals from the array cells after 10,000 loading cycles was 1.39%. For developed prototype of the pressure sensor array, based on the experimental data, the average signal-to-noise ratio over the cells was calculated, and equaled 63.47 dB. The proposed prototype was fabricated of easily available materials. It is relatively inexpensive and requires no fine-tuning of each individual cell. Capacitance-type operation type, compared to piezoresistive one, ensures greater stability of the output signal. The scalability and adjustability of cell parameters are achieved with layered sensor structure. The pressure sensor array, presented in this paper, can be utilized in various robotic systems.

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