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Research On Detection System Of Acoustic Emission System Of Acoustic Logging Tool Based On WIFI Interconnection

Posted on:2021-06-06Degree:MasterType:Thesis
Country:ChinaCandidate:Y LengFull Text:PDF
GTID:2480306563486414Subject:Geological Resources and Geological Engineering
Abstract/Summary:PDF Full Text Request
In daily logging,the operating voltage of the acoustic system of the sonic logging tool is high,and it is prone to failure.Therefore,the rapid detection of the acoustic system is the focus of the maintenance of the sonic instrument.And with the advent of the"Internet of Everything" era,it is particularly important to develop a wireless interconnection detection system.In this paper,a multi-node distributed detection system based on WIFI interconnection is developed.The system includes a lithium battery-based transmission sound system power supply and power supply detection node,and a sound wave synchronous acquisition node.Each node as the Client is interconnected with the Server host through WIFI,so that the modules are electrically isolated,forming a distributed transmission sound system detection system based on wireless interconnection,which prevents common mode interference that wired communication often encounters.In the lower computer,stm32 transplanted uC/OS-II operating system and LwIP,and developed FPGA high-speed sound wave acquisition module.The Server host uses IOCP technology through WIFI to cooperate with multiple sub-node Clients to perform realtime,large data volume network communication.The host computer software adopts a three-tier structure system and publish-subscribe model,simple factory model and other object-oriented ideas to develop it,which improves the code utilization and scalability.The Server host controls all nodes to work together through WIFI to collect power signals and excited sound signals.BP neural network algorithm based on wavelet transform denoising and wavelet packet transform to extract energy features is developed in the waveform analysis of the collected acoustic wave signals,which classifies the waveforms and facilitates the detection of faults in the acoustic system of acoustic emission.
Keywords/Search Tags:Acoustic Logging Emission Sound System, WIFI Interconnection, BP Neural Network, Default Detection
PDF Full Text Request
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