Method for adjusting nitrogen and oxygen concentration of cold-chain air conditioner based on deep neural network

By constructing an oxygen potential disturbance field through a multi-objective variational inversion network and an oxygen content prediction network, the problem of nitrogen and oxygen concentration regulation of cold chain gas conditioners in complex environments is solved, precise regulation and adaptive control are achieved, and the stability and preservation effect of the system are improved.

CN120722972AActive Publication Date: 2025-09-30SUZHOU CHAOYUN NEW ENERGY CO LTD
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Patent Information

Application Number
CN202511198863.9
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-08-26
Publication Date
2025-09-30
Estimated Expiration
2045-08-26

AI Technical Summary

Technical Problem

Existing cold chain gas conditioners have difficulty accurately predicting changes in nitrogen and oxygen concentrations in complex environments. The adjustment strategies are slow to respond and lack adaptability, resulting in reduced control accuracy and food preservation risks.

Method used

A multi-objective variational inversion network and an oxygen content prediction network are used to construct an oxygen potential disturbance field and generate an intelligent adjustment strategy. Combined with the historical behavior response relationship, dynamic coordination of nitrogen injection, oxygen replacement and pressure difference stabilization is achieved, with adaptability and abnormal recovery capabilities.

Benefits of technology

It achieves precise adjustment of cold chain gas conditioners under various types of goods and environments, improves adjustment accuracy and system stability, and has adaptability and abnormal recovery capabilities, which is significantly better than traditional methods.

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Abstract

The invention discloses a cold-chain air conditioner nitrogen and oxygen concentration adjusting method based on a deep neural network. The cold-chain air conditioner nitrogen and oxygen concentration adjusting method comprises the following steps that 1, potential feature representation is constructed; 2, inputting the potential feature representation into a multi-target variational inversion network, and reasoning to obtain an oxygen potential disturbance field; 3, generating an oxygen content prediction curve based on the oxygen potential disturbance field in combination with a historical adjustment behavior response relationship; 4, a decision calculation module generates an adjustment strategy sequence; 5, synchronously issuing the adjustment strategy sequence to each device; step 6, after each adjustment period is finished, writing the feedback sample into an incremental training cache; step 7, when the incremental training cache reaches a set capacity threshold value, performing weight updating on the multi-target variational inversion network by using an adaptive learning rate mechanism; and 8, when the disturbance reasoning abnormity of the oxygen potential disturbance field is identified, starting a field pattern tracking recovery mechanism. According to the method, a cold chain oxygen control strategy is intelligently generated in combination with multi-target variational inversion and a graph tracking recovery mechanism.
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