A Central Air Conditioning Fault Prediction and Diagnosis Method Based on Dual Intelligent Algorithms

A central air-conditioning and fault prediction technology, applied in neural learning methods, calculations, heating methods, etc., to achieve high computing efficiency, good generalization ability, and easy engineering application

Active Publication Date: 2021-12-31
SHENYANG ANXIN AUTOMATION CONTROL CO LTD
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Problems solved by technology

The hill-climbing algorithm only receives the optimal solution during each iteration, and it is easy to fall into a local optimal solution

Method used

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  • A Central Air Conditioning Fault Prediction and Diagnosis Method Based on Dual Intelligent Algorithms
  • A Central Air Conditioning Fault Prediction and Diagnosis Method Based on Dual Intelligent Algorithms
  • A Central Air Conditioning Fault Prediction and Diagnosis Method Based on Dual Intelligent Algorithms

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Embodiment Construction

[0112] A method for predicting and diagnosing central air-conditioning faults with dual intelligence algorithms, the method comprising the following steps:

[0113] 1. Collect on-site central air-conditioning operation real-time data set S on-line ;

[0114] 2. The real-time data set S in the "one" step on-line Input to the pre-established central air-conditioning fault prediction and diagnosis classification neural network model based on simulated annealing algorithm and extreme learning machine algorithm to judge the real-time data set S in the "one" step on-line Whether it satisfies the minimum misclassification rate of central air-conditioning failure prediction and diagnosis;

[0115] 3. The real-time data set S in the "two" step on-line If the misclassification rate of central air-conditioning fault prediction and diagnosis is satisfied, then output the classification results of central air-conditioning fault prediction and diagnosis.

[0116] In the "two" step: if t...

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Abstract

A method for predicting and diagnosing central air-conditioning faults based on dual-intelligence algorithms, comprising the following steps: collecting real-time data sets of on-site central air-conditioning operations; The central air-conditioning fault prediction and diagnosis classification neural network model of the algorithm is used to judge whether the real-time data set in the "one" step meets the requirements of the central air-conditioning fault prediction and diagnosis with the minimum misclassification rate; If the misclassification rate of fault prediction and diagnosis is the smallest, the central air-conditioning fault is output. Prediction and diagnosis of classification results. It has field implementability and is convenient for engineering application. At the same time, the extreme learning machine has good generalization ability and high computing efficiency. Therefore, using the simulated annealing algorithm to find the minimum misclassification rate of the central air conditioner is easier to obtain the global optimal solution, and improve the accuracy and precision of the online deployment of the central air conditioner fault detection and diagnosis model classification.

Description

Technical field: [0001] The invention relates to the technical field of fault prediction and diagnosis of central air-conditioning, and specifically refers to a method for predicting and diagnosing faults of central air-conditioning with dual intelligent algorithms based on a simulated annealing algorithm and an extreme learning machine algorithm. Background technique: [0002] The central air-conditioning system is not only an indispensable energy-consuming operation system in modern buildings, but also an important part of the building automation control system. With the improvement of people's quality of life requirements, the design of central air-conditioning system is becoming more and more complex. Central air-conditioning can not only provide cooling or heating, but also provide domestic hot water, bath water, constant temperature hot water for swimming pools, etc. If the central air conditioner breaks down, it will not only bring inconvenience to the operation of th...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): F24F11/38F24F11/64G06K9/62G06N3/04G06N3/08
CPCF24F11/38F24F11/64G06N3/08G06N3/045G06F18/241
Inventor 何新张博譞张秋实
Owner SHENYANG ANXIN AUTOMATION CONTROL CO LTD
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