## 1 Introduction
However, in addition to the external operating environment, the parameter decay of the equipment itself will also affect its reliability. When electromechanical equipment is subjected to external stress or affected by the environment, its own performance parameters may be degraded, such as the reduction in coil detection accuracy, the decline in waterproof and dustproof grade, and so on. These changes may lead to weakening of the equipment's function, shortening of its life, and even failure, thus increasing the risk of equipment failure and reducing the reliability and safety of electromechanical equipment. By studying the changes in parameters in the internal decay process of the equipment, the reliability of the equipment can be effectively analyzed. Then, the corresponding prevention and parameter optimization measures can be put forward to effectively reduce the equipment's failure rate and improve the equipment's reliability, prolong the service life of the equipment, reduce the maintenance cost, and improve the use efficiency and economic benefit. [PERSON] [19] and other scholars use equipment performance parameters such as equipment utilization, manufacturing capacity, and productivity to evaluate the reliability of flexible manufacturing cells. [PERSON] [20] uses a non-dominant sorting genetic algorithm (NSGA) and entropy weight-based optimal selection method (TOPSIS) to optimize the parameters, which provides a solution for soil temperature reduction and low-cost operation in cold and arid areas in the application of ground-source heat pumps. [PERSON] [21], combining the data characteristics of the equipment accelerated decay experiment and considering the cognitive uncertainty, proposed a stochastic fuzzy accelerated decay model and its corresponding statistical analysis method. [PERSON] [22] proposed a method to describe the equipment performance decay process by using the general expression based on the life and state correlation model, and the general expression of the stochastic process solved the probability density function. This study creatively combines the external operation and maintenance strategy of highway mechanical and electrical equipment with the internal technical parameters of the equipment, formulates its operation and maintenance strategy from the point of view of equipment maintenance, and starts with the shortcomings of the operation and maintenance strategy to improve the parameter level of the equipment itself. Firstly, a multistate Markov model considering maintenance is constructed based on the basic theory of the Markov chain. Based on the fault performance in the historical operation and maintenance data of electromechanical equipment, the fault state of the equipment is classified, and the maintenance factors of the equipment's operation and maintenance are taken into consideration. By predicting the future fault state of electromechanical equipment, the purpose of this model is to realize the differential operation and maintenance strategy based on the external information of the equipment. In addition, aiming at the typical equipment with high failure rates, this study customizes the technical parameters to adapt to the environment of the equipment from the inside in order to improve the reliability of the equipment. The equipment operation and maintenance and parameter research involved in the study comprehensively considers the external operation and maintenance environment and internal quality factors of the equipment, which can essentially enhance the use value of highway mechanical and electrical equipment. The specific research ideas are shown in Figure 1.  
Figure 1: Research technology roadmap.