A fault prediction method of refrigeration equipment based on neural network

Abstract

The invention provides a fault prediction method of refrigeration equipment based on a neural network, comprising the following steps: acquiring a time series data set collected by N sensors sensitiveto the fault in the refrigeration equipment; The long-term and short-term neural network model is constructed according to the time series data set, and the actual forecasting results of the time series data set are obtained according to the long-term and short-term neural network model. Determining a fault discrimination model f (x) according to the time series data set; Acquiring a real data set of a part of the known fault conditions of the refrigeration equipment, and determining a fault threshold value according to the fault discrimination model f (x) and the real data set; The probability density of the actual predicted results is determined according to the fault discrimination model, and the health status of the refrigeration equipment is judged by comparing the probability density of the actual predicted results with the fault threshold. The invention adopts the mode of combining the long-term and short-term neural network model and the fault discrimination model f (x) to predict the fault of the refrigeration equipment, and can effectively predict the health status of the refrigeration equipment.

Description

technical field [0001] The invention relates to the technical field of refrigeration equipment, in particular to a method for predicting failures of refrigeration equipment based on a neural network. Background technique [0002] With the improvement of people's living standards, people rely more and more on frozen and refrigerated food. The frozen and refrigerated food industry has shown a momentum of rapid development, and cold storage has also been constructed on a large scale. However, at present, the management level of cold storage equipment is generally low, the skill level of technicians is not high, the refrigeration system has not been reasonably maintained, and often small workers do heavy work, and the operation is sick, which leads to the failure of annual inspection of equipment, accelerated aging, and the occurrence of ammonia in the refrigeration system. Refrigerant leaking, dew and other phenomena seriously affect the refrigeration quality of the cold storag...

AI Technical Summary

Problems solved by technology

However, at present, the management level of cold storage equipment is generally low, the skill level of technicians is not high, the refrigeration system has not been reasonably maintained, and often small workers do heavy work and operate with illnesses, resulting in annual inspections of equipment and accelerated aging, resulting in the occurrence of ammonia in the refrigeration system. Refrigerant leaking, dew and other phenomena seriously affect the refrigeration quality of the cold storage

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