Central air conditioner fault diagnosis method and device based on stacking fusion algorithm

Abstract

The invention discloses a central air-conditioning fault diagnosis method based on a stacking fusion algorithm. The method comprises the following steps: establishing a central air-conditioning system digital twinborn model; state data of the central air-conditioning system during normal operation and different faults are collected, and a sample data set is obtained after data preprocessing and feature extraction are carried out; dividing the sample data set into a training data set and a test data set, and constructing a double-layer stacking model; training each base learner by adopting a k-fold cross validation method, and obtaining a prediction result of each base learner as a secondary training data set; when each base learner is trained, multiple groups of different machine learning algorithms are selected for combination, and a secondary training data set in multiple groups of combination modes is generated; inputting the plurality of groups of secondary training data sets into a secondary learning device for training to obtain a plurality of central air conditioner fault diagnosis models; the prediction performance of the multiple central air conditioner fault diagnosis models is evaluated, and the model with the optimal performance is selected as the optimal central air conditioner fault diagnosis model for fault diagnosis.

Description

technical field [0001] The invention belongs to the technical field of central air-conditioning, and in particular relates to a central air-conditioning fault diagnosis method and device based on a stacking fusion algorithm. Background technique [0002] In the process of urbanization, with the expansion of city scale, the number and scale of large public buildings have increased significantly. Among them, the two major trends of rapid development of building electrification and rising building intelligence have won the attention of all walks of life. extensive attention. Due to the cooling needs of large public buildings, the scale of the central air-conditioning system and its automatic control system is increasing, and the types and quantities of equipment are increasing, so the system complexity is increasing. During the operation of the system, various failures will inevitably occur. If these failures are not eliminated in time, it will inevitably cause the system oper...

AI Technical Summary

Problems solved by technology

However, when a single learning algorithm is used to predict the fault diagnosis model, due to too many input data variables, the complexity of the prediction model is increased, resulting in over-fitting of the prediction output and reducing the accuracy of the model prediction

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