Abstract
An in-line measurement system of bore well mud viscosity based on multi-sensor data fusion with wavelet neural network is proposed in this paper. The computer is used as the center of this system and mud viscosity is measured in-line accurately in this system. The mud viscosity is converted by double rotation viscosity sensor, rotary speed viscosity sensor, current sensor, voltage sensor, temperature sensor and flow rate sensor, there are six electric circuits of signal conditioning which is used to adjust the signals of the output of the six sensors, and then the signals are transformed by A/D convertor or pulse count. Multi-sensor data fusion technology is adopted and the wavelet neural network is used to establish the mapping relation between multi-sensor data and output. The mud viscosity is calculated and identified by the certain model. The experimental results show that this method is feasible and effective.
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More From: International Journal of Advancements in Computing Technology
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