With the development of modern science and technology, especially the emergence of various new technologies such as information technology, computer technology, and sensor technology, data acquisition, signal processing and analysis methods are becoming more and more perfect, and the fault diagnosis technology of industrial reciprocating compressor equipment is becoming the integration technology of computer, control, communication and artificial intelligence. In recent years, fault monitoring and diagnosis technology has shown the following development trends:
Industrial reciprocating compressor diagnostic technology absorbs a large number of modern scientific and technological achievements, so that the diagnostic technology can use vibration, noise, stress, temperature, oil, electromagnetic, light, radiation and other information to implement diagnosis, and it can also use several methods to perform a comprehensive diagnosis at the same time.
A variety of modern information processing methods, such as neural network, holographic spectrum technology, wavelet analysis, data fusion technology, data mining technology and other cutting-edge scientific achievements have also been used in the field of reciprocating compressor fault diagnosis, which improves the accuracy of diagnosis.
Real-time monitoring is a requirement of aviation, aerospace technology and modern industrial production. Modern industry requires a high degree of automation, integration and large-scale production equipment. The more complex industrial equipment, the more it should have a high degree of reliability and the ability to resist failures to ensure system safety, stability, long-term, full-load, and optimized operation. This requires fast and effective fault signal acquisition, transmission, storage, analysis and identification, and decision support.
In the industrial field, it is often necessary for technicians to have a high level of professionalism and field diagnosis experience to identify the cause of the failure from the monitored fault information. In order to promote the application of diagnostic technology, it is necessary to use the instrument or system intelligence to create an easy diagnostic system, which can reduce the restriction on the technical level of users.
It is necessary to make full use of computer and its software technology and expert knowledge and experience to make the diagnosis system intelligent, so that the results obtained by ordinary technicians using the diagnosis system can reach the level of diagnosis experts. Neural networks, expert systems, decision support systems and data mining technologies can provide technical support for the realization of artificial intelligence diagnosis.
With the popularization and application of the Internet, many large-scale enterprises have developed networked equipment management, and networked equipment monitoring and diagnosis have become inevitable.
The sensor group is used to monitor industrial equipment, and the wired or wireless communication of the data acquisition system is connected to the monitoring and diagnosis system and the enterprise management information system through the network, so that the management department can obtain the operating status information of the reciprocating compressor equipment in a timely manner, which is conducive to scientific maintenance decision-making. With the help of the Internet, a wide range of expert support, online consultation, and remote diagnosis can also be provided.
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