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Deep seabed mining machine fault diagnosis and fault-tolerant systems Sensor Research

Author: LiWenJun
Tutor: YangChunHua
School: Central South University
Course: Control Theory and Control Engineering
Keywords: Mining machine Troubleshooting Integrated neural networks Sensor fault
CLC: TD424
Type: Master's thesis
Year: 2005
Downloads: 106
Quote: 4
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Abstract


Deep seabed mining machine is a complex mechanical system of hydraulic power , the traditional fault diagnosis method because of the need to establish a precise mathematical model of the object , resulting in mining machine fault diagnosis is difficult to achieve . This paper, the theory of intelligent diagnosis and methods will be integrated neural networks and sensor fault-tolerant technology by combining mining machine condition monitoring and fault diagnosis, which is a stable process of deep-sea mining , mining machine to improve operational reliability , with a very significance. Ore mining machine including collection systems , running gear , hydraulic system of three parts. Parts of possible faults in the analysis , based on the sum of the vehicle skidding , steering failure , pitch angle gauge track motor failure , pump failure , motor failure and ten major fault , and for the characteristics of these faults , for a set of mineral machine fault diagnosis system research and design. This paper presents the structure of the system framework , and summarizes its features ; Then the mining machine sensor fault tolerance methods were studied by the sensor hardware redundancy, as well as the weighted fusion algorithm combines gray prediction model was constructed with fault detection, isolation and fault-tolerant redundancy sensor unit to ensure that the mining machine is not the same dual sensors in case of failure of the output is always active ; then create three diagnostic sub-networks , from mining collector system , running gear , hydraulic system three different sides on the mining machine fault diagnosis , and use the diagnostic decision fusion network diagnostic results of sub-networks integration consultation, the final diagnoses get the system to improve the fault diagnosis. Simulation results show that the system can effectively achieve the mining machine fault diagnosis and fault-tolerant sensors for the upcoming \Finally, the paper system software design. System software development platform used Windows2000, use VISUAL C 6.0 and SQL Server7.0 preparation , providing information input , data query , fault diagnosis and fault simulation capabilities for deep-sea mining process mining machine fault diagnosis .

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CLC: > Industrial Technology > Mining Engineering > Mining machinery > Mining machinery > Seabed deposits and mining machinery
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