A Fault Diagnosis Method for Chillers Based on GSRA Model

Abstract

The invention discloses a GSRA model-based fault diagnosis method for a chiller. This method first uses genetic algorithm to optimize the weighted index under each degradation level, and constructs a comprehensive reference failure mode; secondly, it introduces a correlation degree threshold to make a qualitative diagnosis of the failure mode to be checked, and uses the gray similarity correlation degree (GSRD) and the threshold to determine its suspected failure mode ; Finally, use GSRD to carry out quantitative diagnosis on the qualitative results to determine the category and degradation level of the failure mode to be checked. This method can be effectively applied to chiller fault diagnosis. Compared with the traditional method of using the reference fault mode under a single degradation level to represent the comprehensive reference fault mode and relying solely on the principle of maximum correlation degree to determine the fault mode, the method proposed by the present invention significantly improves the fault diagnosis performance. Recognition has a good classification effect, and has many advantages such as small amount of calculation, simple parameter optimization, and does not require sample data to obey a specific distribution.

Description

technical field [0001] The invention belongs to the technical field of refrigeration equipment, and in particular relates to a method for diagnosing a fault of a chiller based on a GSRA (Grey Similarity Relational Analysis) model. Background technique [0002] The chiller is the main component of the HVAC system. At present, most of the chillers operating in the actual field in China only monitor and control their operating status, and can only complete "high pressure alarm" and "low pressure alarm" for fault detection and diagnosis. Alarm" and other hard fault detection functions. It is a common phenomenon that on-site chillers lack the ability to detect and diagnose soft faults. Applying effective fault detection and diagnosis technology to chillers, finding faults and eliminating them in time is of great significance for maintaining indoor environment comfort, reducing equipment loss, and saving energy. [0003] In the past ten years, many scholars have conducted extens...

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Problems solved by technology

[0006] In order to solve the above-mentioned defects existing in the prior art, the present invention aims at the characteristics of "small samples and poor information" in on-site fault diagnosis of chillers, and proposes a fault diagnosis method for chillers based on the GSRA model, which can effectively solve the problem of The shortcomings of existing methods, it not only has a good classification effect for small sample pattern recognition, but also has many advantages such as small amount of calculation, simple parameter optimization, and does not require sample data to obey a specific distribution.

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