Air conditioning system sensor fault diagnosis method based on wavelet neural network

A wavelet neural network, sensor failure technology, applied in heating and ventilation control systems, heating and ventilation safety systems, heating methods, etc., can solve the problems of sensor measurement deviation drift, advanced control strategy goals cannot be achieved, misleading control systems and other problems

Inactive Publication Date: 2018-09-07
上海智容睿盛智能科技有限公司
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Problems solved by technology

However, the sensors in the air-conditioning system often have measurement deviation or drift after long-term use, and measurement

Method used

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  • Air conditioning system sensor fault diagnosis method based on wavelet neural network
  • Air conditioning system sensor fault diagnosis method based on wavelet neural network
  • Air conditioning system sensor fault diagnosis method based on wavelet neural network

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Embodiment Construction

[0102] The specific implementation manners of the present invention will be described below in conjunction with the accompanying drawings.

[0103] Such as figure 1 , figure 2 with image 3 As shown, the air-conditioning system sensor fault diagnosis method based on wavelet neural network, the method includes steps: comprehensive analysis and diagnosis, used to define the air-conditioning state control, diagnosis condition set, decision-making event set; sensor fault classification and feature description in the air-conditioning system, using It is used to classify fault types; sensor fault diagnosis in air conditioning system is used to generate fault diagnosis process; determine network structure and basis function; training sample selection and preprocessing; set alarm threshold.

[0104]The air conditioning system sensor fault diagnosis method based on wavelet neural network, the comprehensive analysis and diagnosis include:

[0105] Definition 1 Conditioning state spa...

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Abstract

The invention provides an air conditioning system sensor fault diagnosis method based on a wavelet neural network. The method is characterized by comprising the steps that comprehensive analysis and diagnosis are conducted for defining an air conditioner state control, a diagnosis condition set and a decision event set; sensor fault classification and characteristic description of an air conditioner system are used for classifying fault types; sensor fault diagnosis of the air conditioning system is used for generating a fault diagnosis flow; a network structure and a primary function are determined; selection and pretreatment of training samples are conducted; and an alarming threshold is set. The method has good diagnosis effect on abrupt changing faults such as bias faults and completefaults. Drift biases can be detected as long as the drift distance exceeds the alarming threshold. The method also has good fault detection effect on precision decrease faults of sensors.

Description

technical field [0001] The invention relates to an air-conditioning fault diagnosis method, in particular to a wavelet neural network-based air-conditioning system sensor fault diagnosis method. Background technique [0002] In order to achieve the purpose of saving energy and improving indoor air quality, various optimization control strategies of air conditioning systems (Heating, Ventilation and Air Conditioning, HVAC) have become increasingly complex, but the implementation of these optimization strategies must have a prerequisite: the accuracy and reliability of sensors sex. However, the sensors in the air-conditioning system often have measurement deviation or drift after long-term use, and measurement failures will inevitably mislead the control system, resulting in the failure to achieve the goals of advanced control strategies. Therefore, how to detect it in time when the sensor has a measurement deviation is the first problem to be solved. On the other hand, a la...

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Application Information

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IPC IPC(8): F24F11/38F24F11/64F24F110/10F24F110/20F24F130/40
Inventor 江凤罗莹
Owner 上海智容睿盛智能科技有限公司
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