Abstract
During down-hole perforation and fracturing, there are always strong mechanical vibration and impact that affect dynamic pressure measurement. In order to overcome the influence, a specialized buffer device was designed for the dynamic pressure sensor. Based on the double-diaphragm shock tube, we researched the influence of the specialized buffer device on the dynamic characteristics of the pressure sensor. Based on BP neural network, a mathematical model was built to characterize the pressure sensor with the buffer device, and the method was studied to implement dynamic compensation of the pressure sensor. According to the results of dynamic calibration and compensation for the typical piezoelectric pressure sensor with the buffer device, the specialized buffer device can greatly reduce the working bandwidth of the pressure sensor. The method of dynamic compensation based on BP neural network can not only effectively widen the working bandwidth of the piezoelectric dynamic pressure sensor, but also improve the accuracy of dynamic measurement.
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Yang, F., Zhao, C., Zhu, H., Kong, D. (2023). Study on Mathematical Model and Dynamic Compensation of Oil Down-Hole Pressure Sensor Based on BP Neural Network. In: Hu, C., Cao, W. (eds) Conference Proceedings of 2022 2nd International Joint Conference on Energy, Electrical and Power Engineering. CoEEPE 2022. Lecture Notes in Electrical Engineering, vol 1060. Springer, Singapore. https://doi.org/10.1007/978-981-99-4334-0_46
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DOI: https://doi.org/10.1007/978-981-99-4334-0_46
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