Multi-sensor fusion heat pump full life cycle AI maintenance early warning system

By using a multi-sensor fusion heat pump AI maintenance and early warning system, and employing dynamic sliding window, KPCA and LLE dimensionality reduction technologies, combined with a dual attention mechanism for lifecycle and operating conditions, the system solves the problem of multi-source data fusion in heat pump maintenance, achieves accurate fault identification and efficient early warning, and improves the stability and economy of equipment operation.

CN121383528APending Publication Date: 2026-01-23SAINT OAK LTD
0 Cites 9 Cited by

Patent Information

Application Number
CN202511883341.2
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-12-15
Publication Date
2026-01-23

AI Technical Summary

Technical Problem

Existing heat pump maintenance early warning technologies mostly rely on single sensor data or fixed threshold judgments, lacking an effective cross-space adaptation and mapping mechanism. This results in insufficient data support, an inability to achieve collaborative complementarity of multi-source data, an inability to identify equipment faults, information redundancy and feature conflicts, and an inability to provide effective early warning support.

Method used

The AI ​​maintenance and early warning system, which adopts multi-sensor fusion, acquires the operating parameters of the heat pump throughout its entire life cycle through a sensor array. Combined with the dynamic sliding window, KPCA dimensionality reduction, and LLE dimensionality reduction in the data fusion module, these parameters are mapped to the same feature space. The system uses a dual attention mechanism of life cycle and operating condition to dynamically adjust feature weights, establishes a fault type and core feature mapping library, and performs dual judgment and graded output early warning.

Benefits of technology

It enables accurate fault identification and phase division, improves early warning accuracy and operation and maintenance efficiency, reduces energy consumption and operation and maintenance costs, and promotes operation and maintenance from passive emergency repair to proactive prevention.

✦ Generated by Eureka AI based on patent content.
Patent Text Reader

Abstract

The invention discloses a multi-sensor fusion heat pump full life cycle AI maintenance early warning system, and relates to the technical field of new energy utilization, and the early warning system comprises a data collection module which obtains operation parameters in a heat pump full life cycle based on a sensor array, and constructs a data set after preprocessing the parameters; the operation parameters comprise temperature, pressure, flow and micro vibration; the data fusion module is used for extracting trend correlation characteristics and parameter coupling characteristics from temperature, pressure and flow parameters by adopting a dynamic sliding window adaptive to a working condition, and preserving core nonlinear information through KPCA dimension reduction; the micro-vibration signal extraction comprises frequency domain and time domain features. According to the method, features are extracted through a working condition adaptive dynamic sliding window, then through cross-space mapping and a life cycle-working condition double-attention mechanism, the analysis and early warning module depends on a core feature mapping library and a two-dimensional dynamic baseline, through instantaneous and accumulated deviation double judgment, abnormal accurate recognition and stage division are achieved, and early warning perspectiveness is high.
Need to check novelty before this filing date? Find Prior Art