Condition Monitoring And Fault Diagnosis Of High-Speed Wire Reducing And Sizing Unit

Reducing and sizing mill is the key equipment of modern high-speed wire rod production line. It plays an important role in the production. Once the production is stopped due to failure, it will directly affect the economic benefits of the enterprise. In order to ensure the stable operation of production, reduce the equipment maintenance cost, improve the fault diagnosis level of reducing and sizing unit, and realize the real-time condition monitoring of reducing and sizing unit, we have carried out experimental research on the condition monitoring and fault diagnosis system of high-speed reducing and sizing unit.

Development and application of equipment condition monitoring and fault diagnosis in the world

Machine operation condition monitoring and fault diagnosis technology is an effective means to ensure the safe operation of large units and prevent accidents. It can timely find the operating fault precursors of units, diagnose the causes of faults, provide decision-making basis for production maintenance, and reduce the shutdown losses caused by the traditional regular maintenance system. As a new technology, equipment condition monitoring and fault diagnosis has been developed in recent decades, and has gradually become a new subject. The modern mechanical industry is developing towards mechatronics. The automation, intelligence, large-scale and complexity of mechanical equipment all need to ensure the safe operation and reliability of the working process. Therefore, the monitoring and fault diagnosis of its working state are becoming increasingly important; On the other hand, with the development of modern testing technology, especially the progress of sensing technology, computer technology, information theory, cybernetics and reliability theory, the theory and method of condition monitoring and fault diagnosis of mechanical equipment are becoming more and more perfect.

"Online monitoring and fault diagnosis" refers to using the external information of the machine to understand the internal working status of the machine, and using the information obtained by the monitoring sensor to judge the internal faults and damages of the machine. The task of fault diagnosis is to timely report the fault and predict the occurrence and development of the fault, and eliminate false and missing reports, so as to ensure the normal operation of the system. As long as it is a non sudden fault, it can be predicted before the equipment fault occurs. This can completely change the original maintenance mode, neither waste human, material and financial resources due to excessive maintenance, nor cause major accidents due to insufficient maintenance. The purpose of equipment condition monitoring and fault diagnosis is to "ensure the design and manufacture of equipment that meets user requirements and the reliable and effective performance of equipment functions". There are four important aspects: one is to provide data and information for optimal design and correct manufacturing through performance evaluation; The second is to ensure the safe and reliable operation of the equipment without failure; The third is to ensure that the equipment can give full play to its maximum design capacity and make full use of everything; Fourth, it can timely and correctly diagnose various abnormalities or faults and guide necessary intervention.

The equipment condition monitoring and fault diagnosis system is divided into three stages

Condition monitoring. Various monitoring instruments (real-time, non real-time, on-line or off-line, regular or continuous) are used to monitor the working status of the equipment to obtain a large amount of operation status information. At the same time, necessary processing is carried out to determine whether its working status is normal.
Fault diagnosis (analysis and diagnosis stage). In order to correctly or accurately diagnose the existence of equipment faults, it is necessary to deeply analyze and study the objective relationship between various symptoms (or symptoms) and faults. Many diagnosis theories and methods have emerged in this field, including statistical identification, fuzzy logic, grey theory, neural network, etc. By comparing the collected and extracted symptoms with the known typical fault state modes, the existing faults of the equipment can be identified and diagnosed, and the relevant decisions and judgments such as their nature and degree can be explained. This is a very important key step in the system.
Governance prevention. After diagnosing the existence and nature of the fault, the problems to be considered immediately are the governance of equipment fault and the prevention of equipment fault. It also includes the estimation of the remaining life of some key components or assemblies, so as to provide the basis for the economic management department of the enterprise.

From the perspective of development history, modern equipment monitoring technology has roughly experienced three stages: the first stage is the development stage of conventional technology based on sensor technology and dynamic testing technology and by means of signal processing technology. The technology in this stage has been applied in engineering. It has absorbed a large number of modern scientific and technological achievements. The rapid development of sensor technology makes it possible to use vibration, noise, force, temperature, electricity, magnetism, light Ray and other information. Thus, monitoring and fault analysis technologies such as vibration, noise, spectrum, ferrography, nondestructive testing, thermal imaging, etc. of the equipment are produced. The second stage is the development of signal analysis and numerical processing technology combined with microcomputer technology, which provides greater convenience for the traditional monitoring technology. At the same time, many theories and methods have been produced, such as state space analysis, comparative analysis, function analysis, logical analysis, statistical and fuzzy analysis. In recent years, the emergence of various data processing software and hardware makes real-time online monitoring and fault analysis technology possible. Artificial intelligence technology provides the possibility for the intelligent development of equipment monitoring and fault analysis, which makes the development of modern monitoring technology step into the third stage. The research contents and implementation methods at this stage have begun and are continuing to undergo major changes. The process with data processing as the core will be replaced by the process with knowledge processing as the core. The research on theories, methods and application technologies such as expert system, neural network and fuzzy analysis has been carried out. At this stage, the knowledge of human experts will play a leading role, including the domain knowledge and problem-solving methods of human experts. Due to the unification of signal detection, data processing and knowledge processing, advanced technology is no longer a technology that only a few professionals can master, but a tool that general operators can use.