5results about How to "Realize intelligent maintenance" patented technology

The invention relates to the technical field of power supply, and provides an aircraft power supply system health state evaluation method based on dynamic weight, comprising the following steps: S1, determining the grade of an aircraft power supply system; s2, initializing parameters; s3, a subjective weight determination model and an objective weight determination model are established; s4, obtaining the weight of each index in the finished product parameter level; s5, calculating the health index of the index; s6, judging whether circulation is ended or not; s7, obtaining subjective and objective weights of the layer indexes; s8, obtaining subjective and objective weight difference and a health state change rate; s9, obtaining a subjective and objective weight ratio; s10, obtaining fuzzy subjective and objective weights; s11, fuzzy weighting is adopted to obtain a weight; s12, carrying out normalization on the weight values; s13, returning to the step S5; and S14, obtaining the health level of the power supply system. According to the method, the model and the fuzzy rule table are determined through the subjective and objective weight ratio, and nonlinear self-adaptive fusion is achieved.

Embodiments of the present application provide a subway maintenance planning data processing method, device, medium and electronic equipment. The method comprises: acquiring decision reference data associated with train maintenance planning in the whole subway network; based on the decision reference data, determining train maintenance planning data for each date within a future period through a pre-constructed mixed integer programming model, the train maintenance planning data including the date for each train to perform a balanced maintenance work package, the date for performing a pantograph work package, and the date for performing a car washing work package. The technical solution of the embodiments of the present application can improve the accuracy of subway maintenance planning data processing.

The utility model discloses building monitoring equipment convenient to maintain, which relates to the technical field of building monitoring and comprises a mounting assembly and a mounting top plate, a sliding assembly is fixed at the bottom of the mounting top plate, a fixing part is fixed on the surface of the mounting top plate, a connecting part is movably connected to the inner wall of the bottom of the sliding assembly, and the connecting part is fixedly connected with the mounting top plate. An external electric part is arranged on one side of the mounting top plate, and the auxiliary assembly is arranged on the top of the connecting part. The beneficial effects of the utility model are that through the cooperation of the quick-release locking mechanism, the synchronous power supply linkage system and the self-adaptive dustproof heat dissipation device, the maintenance efficiency and the operation safety of the equipment are significantly improved, the problems of tedious disassembly, delayed power supply and insufficient dust prevention are effectively solved, the safety of electrical operation is ensured, and the maintenance cost is reduced. And meanwhile, intelligent maintenance of power-off quick release is realized, and the reliability and maintenance convenience of the monitoring system are greatly improved.

This invention discloses a machine needle lifecycle management system based on big data and artificial intelligence, specifically relating to the field of machine needle management. It includes data collection, analysis, and optimization at each stage, such as needle receiving, loading, use, maintenance, replacement, and disposal. Through intelligent data analysis and prediction, the system can monitor the health status and operation of machine needles in real time, accurately predict remaining lifespan and potential risks, greatly improving management efficiency. Unlike traditional manual management methods, this system integrates various types of data through a big data platform and automatically generates maintenance strategies using artificial intelligence algorithms, achieving data-driven precision maintenance and risk warning. Furthermore, through quality traceability and risk scoring modules, the system can effectively identify potential problems and handle them in a real-time closed-loop manner, ensuring production quality. Overall, this technology provides a more efficient, transparent, and intelligent solution for machine needle management.