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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Advancements in Computing Technology
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
