A Combined Fault Diagnosis Method of Centrifugal Chiller and Fresh Air System

Abstract

The invention discloses a combined fault diagnosis method of a centrifugal chiller unit and a fresh air system, comprising: historical operation data noise reduction processing and feature screening, cluster analysis, determination of support vector machine training parameters, establishment of a fault diagnosis model, and the like. Noise reduction processing and feature screening remove the inevitable noise and outlier data in the original data, and convert them into a data structure that can be recognized by the support vector machine, select variables that are significantly related to the fault, save storage space and shorten the model in the data structure Training time; cluster analysis determines the closeness of fault features to improve diagnostic accuracy; determining the training parameters of support vector machine can improve the training accuracy of fault diagnosis model and compress the model generation time. The method can carry out joint fault diagnosis of dual systems with high precision, less time consumption and wide applicability, and discover problems existing in the dual systems in time, so as to achieve the purposes of improving operation performance, saving energy and reducing maintenance costs.

Description

technical field [0001] The invention belongs to the technical field of fault diagnosis, and in particular relates to a joint fault diagnosis method of a centrifugal chiller and a fresh air system. It is applicable to the diagnosis of a total of 9 kinds of faults in centrifugal chillers and fresh air supply systems in the field of HVAC. Background technique [0002] The energy consumption in the whole process of construction accounts for a huge proportion of my country's total energy consumption. Taking the total energy consumption of building operation as an example, it accounted for about 20% of the country's total energy consumption in 2015. In the energy consumption of building operation, the energy consumption of the HVAC system accounts for about 60% of the total energy consumption of the building, and due to the widespread problems of unreasonable design and improper maintenance, various HVAC subsystems often operate at low The energy efficiency ratio range has exace...

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Problems solved by technology

In the above methods, although the fault tree and expert system can diagnose multiple faults at the same time, they require a large amount of prior knowledge and tedious rule settings, rely too much on individual buildings, and have obvious personality characteristics, so they are not too high. Universality; artificial neural network, regression model, fuzzy algorithm, etc. all need a large amount of input operating data under normal and fault conditions to construct the model, which is often difficult to achieve in actual engineering, and it is difficult to achieve multiple faults The joint diagnosis may not guarantee the accuracy of the joint diagnosis, and it is also prone to overfitting problems resulting in poor generalization ability; the independent meta-analysis, designated meta-analysis and principal component analysis in the statistical method need the operating data of the unit under normal conditions Carry out model construction and judge whether a fault occurs by comparing some characteristic indicators, but the types of faults it is suitable for diagnosing are relatively single, and if two faults have the same fault characteristics, it is difficult to give an accurate diagnosis result

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