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Air conditioning unit fault diagnosis method based on DHMM and CPDSPC

An air-conditioning unit and fault diagnosis technology, applied in the field of fault diagnosis, can solve problems such as sensor measurement error, affecting state estimation accuracy, model error, etc., and achieve the effect of ensuring stability and high-precision fault diagnosis

Active Publication Date: 2021-07-30
NANJING UNIV OF INFORMATION SCI & TECH
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In the past few decades, there have been many researches on the fault diagnosis of air conditioning units, but the measurement error of the sensor and the model error will affect the accuracy of the state estimation, resulting in the inability to accurately diagnose the fault

Method used

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  • Air conditioning unit fault diagnosis method based on DHMM and CPDSPC
  • Air conditioning unit fault diagnosis method based on DHMM and CPDSPC
  • Air conditioning unit fault diagnosis method based on DHMM and CPDSPC

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Embodiment Construction

[0080] DETAILED DESCRIPTION OF THE PREFERRED DESCRIPTION OF THE DRAWINGS FIG.

[0081] The present invention designs a fault diagnosis method based on Dynamic Hidden Markov Model, DHMIC Hidden Markov Model, DHMM and Discrete Process Control (DSPC), in actual application, such as figure 1 As shown, the following steps A to D will be implemented.

[0082] Step A. Based on the change in the timing of the designated work attributes on the air conditioner, the cooling coils and the fan respectively correspond to each of the fault feature timing changes, and then obtain the calendar tube and the fan respective fault feature matrix X. cc , X sf And further for the fault feature matrix X cc , X sf , Perform fault feature reduction operation, obtain the main fault feature matrix O corresponding to the cooling coil and the fan separately. cc , O sf , Then go to step B.

[0083] In practice, the above step A is specifically performed steps A1 to A5.

[0084] Step A1. Collecting the freezing ...

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Abstract

The invention relates to an air conditioning unit fault diagnosis method based on DHMM and CPDSPC. Aiming at the fault diagnosis problem of air conditioning unit equipment, fault features are effectively extracted by using a reverse transmission neural network, Kalman filtering or particle filtering method, main components of the fault features are extracted by using a principal component analysis method and used as observed values of a dynamic hidden Markov model, and the dynamic hidden Markov model is used for describing the dynamic change of the health condition of the air conditioning unit equipment so as to realize state estimation; and finally, a discrete statistical process control method based on Conway-Maxwell-Poisson distribution is applied, wrong state estimation is filtered out, high-precision fault diagnosis is achieved, and the stability of actual work is guaranteed.

Description

Technical field [0001] The present invention relates to a method of fault diagnosis based on DHMM and CPDSPC, which is a fault diagnosis technology. Background technique [0002] The HVAC has a maximum of 50% -60% in the total energy consumption of the HVAC. About 42% of refrigeration energy in HVAC, and 26% of maintenance costs are caused by equipment failures. It is estimated that HVAC fault diagnosis can reduce energy consumption of 10% -40%. As an important subsystem of a HVAC system, the air conditioner set is used to adjust indoor air to a suitable temperature. The system consists of a cooling coil, a fan, and other devices, and the equipment in the air conditioner is coupled to each other, and the control of indoor temperature, humidity, and the like are realized by closed loop control to meet people's comfort requirements. In this case, once a device in the air conditioner is failed, the load of its connected device will become large, which can cause these devices to be m...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01M99/00G06F17/15
CPCG01M99/005G06F17/15Y02B30/70
Inventor 严颖蔡骏张菀李涛
Owner NANJING UNIV OF INFORMATION SCI & TECH
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