The purpose of modern papermaking machinery monitoring is to utilize the latest advancements in modern science and technology to identify potential equipment hazards and prevent future accidents. Specifically, it involves acquiring status information of papermaking machinery while it is stationary or in operation, and referencing past operating experience to obtain the equipment's real-time status. This information allows for the prediction of the equipment's future condition and the determination of necessary maintenance strategies.
China's development has gone through four stages.
The digestion phase began (mid and late 1980s).
The installation phase of self-developed and applied online monitoring and fault diagnosis technologies (early to mid-1990s).
Develop condition monitoring and fault diagnosis systems for large equipment in accordance with international standards (mid-to-late 1990s).
Intelligent Remote Communication and Network Monitoring and Diagnostic System (Current Status)
Currently, research on testing technology in China mainly focuses on the following aspects:
1) Sensor Technology Research: Sensing technology is an instrument technology that reflects the state parameters of equipment. Various sensors, such as eddy current sensors, velocity sensors, acceleration sensors, and temperature sensors, have been developed domestically. The latest sensing technologies include fiber optics, lasers, and acoustic emission.
2) Research on signal analysis and processing techniques: Starting with traditional spectral analysis, time series analysis, and signal processing analysis, this paper introduces some advanced signal analysis methods, such as Fast Fourier Transform, Winger spectral analysis, and wavelet transform. The introduction of these methods compensates for the shortcomings of traditional analysis methods.
3) Research on Artificial Intelligence and Expert Systems: This research has become mainstream in diagnostic technology. Currently, there are "expert systems for diagnosing mechanical faults," but the application of this technology in engineering has not yet reached the expected level.
4) Research on neural networks: A neural network classification system for rotating machinery was studied, and satisfactory results were achieved.
5) Development and research of diagnostic systems: From single-machine detection and diagnosis to lower-level master-slave structure, and then to network-based distributed systems, the structure is becoming more and more complex and the real-time performance is becoming more and more demanding.
6) Research and development of dedicated portable diagnostic instruments and equipment.
