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Fault diagnosis method based on multi-sensor signal analysis

A signal analysis and fault diagnosis technology, applied in the field of fault diagnosis with low misdiagnosis rate and high accuracy, it can solve the problems of incomplete diagnosis information, limitation, difficulty in acquiring knowledge of expert system, etc., so as to reduce the rate of misdiagnosis and missed diagnosis, and improve the Effects of sensitivity and precision

Active Publication Date: 2016-03-02
南通大学技术转移中心有限公司
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AI Technical Summary

Problems solved by technology

[0013] From the perspective of diagnostic methods, with the deepening of research and application, the single fault diagnosis method has inevitable defects
Facing problems such as incomplete diagnostic information, artificial determination of fuzzy membership functions, difficulty in acquiring knowledge in expert systems, and lack of fault sample training in neural networks limit the application of these single intelligent technologies.

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Embodiment Construction

[0040] First, the operating parameters of the unit at a certain time, including temperature, pressure and other data, are fused into a feature vector at this time, and multiple sensor data at multiple times or multiple mechanical states are obtained to obtain the relationship between faults and symptoms. The pattern mapping process is done according to different failure symptoms. Use this as the training set of BP neural network to determine the number of input layer nodes and output layer nodes of BP neural network, and according to the empirical formula Determine the number of hidden layer nodes. Common soft faults of air source heat pump units are: refrigerant leakage, compressor discharge valve leakage, liquid pipeline obstruction, condenser fouling and evaporator fouling. First determine the input sample data and target output of the network. For the heat pump unit, there are 8 characteristic quantities: high pressure P1, low pressure P2, condensation temperature P3, e...

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Abstract

The invention discloses a fault diagnosis method based on multi-sensor signal analysis. Pressure, temperature, flow and other parameters of a heat pump unit in the operation process are acquired by utilizing multiple sensors, and vibration signals of the unit are acquired by utilizing a vibration sensor so that the equipment state of the air source heat pump unit can be comprehensively mastered. Multiple intelligent technical methods are combined on the basis, and respective advantages of the intelligent technologies are comprehensively applied to perform state monitoring, fault diagnosis and intelligent indication on the air source heat pump unit through enhancing advantages and avoiding disadvantages so that sensitivity and accuracy of a monitoring and diagnosis system can be effectively enhanced and misdiagnosis rate and missed diagnosis rate can be reduced. Meanwhile, a use-facilitating signal processing platform is designed by adopting a GUI design method based on the MATLAB language. An accurate diagnosis decision is provided for general operation personnel without understanding system mechanism or analyzing data.

Description

technical field [0001] The invention relates to a diagnosis method using multi-sensors to obtain mechanical equipment information and adopting multi-mixing algorithm analysis, and thus constitutes a fault diagnosis method with high accuracy and low misdiagnosis rate. Background technique [0002] After the heat pump technology was proposed in 1854, it has experienced a tortuous development process and has entered a stage of comprehensive and rapid development. Especially under the environmental pressure of energy crisis and global warming, heat pump technology has become the focus of attention of various countries. The research, application and promotion of technology have also risen to a level of continuous attention. As an energy-saving and emission-reducing technology, heat pump technology has broad prospects. More and more countries, governments, and enterprises will realize the energy-saving and environmental protection benefits that heat pumps can bring. Market data al...

Claims

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Application Information

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IPC IPC(8): G01M99/00
Inventor 杨奕陈轶顾海勤李俊红陆艳娟张烨王建山张桂红
Owner 南通大学技术转移中心有限公司
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