Air conditioning system sensor fault detection method and device and electronic equipment

Abstract

The invention discloses an air conditioning system sensor fault detection method and device and electronic equipment. The method comprises the following steps: determining system evaluation indexes, building a target function, and therefore a fitness function is determined; selecting a Gaussian radial basis kernel function and a polynomial kernel function to construct a vertical air conditioning system sensor fault detection hybrid kernel function matrix, and establishing a hybrid kernel function-based KPCA mathematical model for describing the operation state of the air conditioning system and sensor fault detection; and optimizing the hybrid kernel function parameters by using a multi-objective particle swarm algorithm to obtain fault detection optimization of the air conditioning systemsensor. According to the invention, the multi-target particle swarm optimization algorithm is introduced to solve the problem of fault detection optimization of the air conditioning system sensor, the hybrid algorithm is improved to solve the target problem, certain advantages are achieved, and fault detection optimization of the air conditioning system sensor can be achieved.

Description

technical field [0001] The invention belongs to the field of air-conditioning system fault detection, and relates to a fault detection optimization method, in particular to a fault detection method, device and electronic equipment of an air-conditioning system sensor. Background technique [0002] As an important part of the intelligent building system, HVAC (Heating Ventilating and Air Conditioning, HVAC) system has been widely used and achieved rapid and remarkable development with the development of intelligent buildings. Nowadays, intelligent buildings put forward higher requirements for intelligent integration of indoor environmental quality and energy consumption of buildings. Then, under the premise of stable operation of HVAC system, the requirements for comfort, intelligence and energy saving are constantly increasing. This drives HVAC systems to become more and more complex. In an increasingly complex HVAC system, due to its own defects, overload operation and lac...

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Problems solved by technology

[0003] In order to solve the problem in the prior art that the parameter selection is difficult to achieve the optimum in the implementation process of the algorithm, the object of the present invention is to provide a method, device and electronic equipment for detecting the fault of an air-conditioning system sensor. Kernel Principal Component Analysis, KPCA) is improved, and a hybrid kernel function KPCA method based on multi-objective particle swarm optimization (Multi-objective Particle Swarm Optimization, MOPSO) algorithm optimization is proposed to detect sensor faults, and to achieve the detection rate of air-conditioning system sensor faults Further improve and optimize

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