A bolt and nut service state analysis and replacement cycle prediction method and system

By acquiring the service status characteristics and cost data of bolts and nuts, generating anomaly scores, establishing predictive models, and optimizing replacement time, the dynamic adaptability and resource waste problems of bolt and nut maintenance strategies in existing technologies are solved, and the synergistic optimization of safety and economy is achieved.

CN122453373APending Publication Date: 2026-07-24SHANDONG YONGRUI FASTENER CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
SHANDONG YONGRUI FASTENER CO LTD
Filing Date
2026-03-31
Publication Date
2026-07-24

AI Technical Summary

Technical Problem

In the existing technology, the maintenance strategy for bolts and nuts fails to dynamically adapt to different working conditions, ignores the differences in equipment operating environment and load intensity, resulting in resource waste or safety risks, and lacks the ability to quantitatively characterize the degree of deterioration, making it impossible to achieve a synergistic balance between risk control and resource optimization.

Method used

By acquiring service status characteristic data and replacement cost data of bolts and nuts, anomaly scores are generated, a predictive model is established, replacement time is optimized, the optimal replacement cycle is generated, and decisions are made by combining multi-dimensional data and cost factors.

Benefits of technology

It enables dynamic adaptation of bolt and nut maintenance to different working conditions, quantifies the degree of deterioration, integrates multi-dimensional data, and achieves a synergistic balance between risk control and resource optimization, avoiding resource waste and safety risks.

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Abstract

The application belongs to the technical field of mechanical equipment maintenance, and provides a bolt and nut service state analysis and replacement cycle prediction method and system, which comprises obtaining service state characteristic data and replacement cost data of the bolt and nut; then, a current service state anomaly score is generated based on weighted fusion of the state characteristic data, and a service state prediction model is constructed by using an autoregressive model combined with historical prediction bias to generate a final prediction score of state anomaly at a future time; finally, different replacement times are preset, the corresponding comprehensive replacement cost evaluation value and state anomaly degree estimation value are comprehensively considered, a replacement time optimization model is established, the optimal replacement time is solved, and a replacement cycle prediction value is generated accordingly; the application realizes bolt and nut replacement cycle prediction based on real-time state and cost constraints, effectively controls maintenance cost while ensuring equipment safety.
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