Study On The Methods For Detecting The Conditions Of Key Devices And Predicting Their Remaining Lives

Key devices are the core tools and resources for enterprise production. From manufacturing, electricity to nuclear engineering and military aerospace, every industry has its own major devices, such as aircraft carriers, large power transformers, aircraft engines and generators. The status of these devices is very important, and once the devices fail to work properly, the consequences are often disastrous. Thus, capturing, tracking, testing, and evaluating the device's condition and their remaining lives can ensure that the devices are in a correct or stable status. This is a hot research problem, and it is also the focus of the current industry. This paper focuses on the major devices status testing and the remaining life prediction by using numerical methods, process modeling, and statistical analysis. It develops the methods for the condition detection, condition assessment, remaining life prediction, and flexible process management. Through real cases study, the effectiveness of the proposed methods is verified. Specifically, the main contributions are as follows:First, in view of the features associated with products and devices in the industrial process, changes based on the product status will inevitably lead to some changes in the physical quantity and geometric theory. We utilize the product physical quantity and geometric changes to detect devices status and the hidden fault, and construct an device-oriented and process-oriented integration product state evaluation model. And then we use the statistical process control theory and the dual membership matrix to propose a process-oriented product and device condition detection method. By establishing examples with the lens production device manufacturing process, the effectiveness and feasibility of the method is validated.Second, to assess the healthy status of the devices, we abstract the mainstream assessment methods and propose an open, task-driven, cut-index system for the major device condition assessment. By building an index system and evaluation model, we further design an open major device condition assessment model. By using the web-based techniques to design and implement an assessment system, we have successfully applied the system to assess the power transformer device.Third, for the problem of large devices remaining life prediction, this paper compares the remaining life prediction models under different mechanisms, and proposes a method to use Hough transform so as to predict the remaining life by using the parameters of a linear method. The method is convenient, rapid, and it is able to replace the traditional paper-based mapping methods.Fourth, together with the condition detection and remaining life prediction in the process management, this paper also proposes a flexible process management method for state inspection and remaining life prediction. Through the process of building a condition inspection of the devices and the remaining life prediction model, we define the basic process activities, flexible activity, and flexible connection, and realize the flexible combination and dynamic management for condition detection and remaining life prediction. After that, we design and implement the flexible process self-definition and management system prototype.Finally, we outline the future research objectives and the key working directions for the next step.