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Vibration monitoring and paper machine fault diagnosis and maintenance

Views: 2     Author: Site Editor     Publish Time: 2022-01-13      Origin: Site

paper machine

At present, the technologies for fault diagnosis and maintenance of paper machine mainly include oil analysis technology and vibration monitoring technology. Vibration monitoring technology mainly uses vibration signals to perform condition monitoring and fault diagnosis of paper machines. The oil analysis branch mainly analyzes the performance of the lubricating oil itself and the condition of the wear particles carried by the lubricating oil.

(1) Introduction to vibration monitoring technology:

According to relevant data statistics, more than 60% of mechanical equipment failures are caused by mechanical vibration, and vibration is closely related to the operation of mechanical systems. With the rapid development of my country's paper industry in recent years, large, complex and refined paper machines have also developed rapidly, so the vibration problem of paper machine engineering has become more and more prominent. Maintenance increasingly relies on online vibration monitoring technology.

The paper machine vibration monitoring and fault diagnosis technology analyzes and studies the collected vibration data using signal processing technology, and then performs pattern recognition to determine whether the mechanical equipment is abnormal, find out the location and cause of the fault, or predict the fault. . Because the vibration monitoring and its fault diagnosis method not only guarantee the normal operation of the paper machine, but also have good real-time performance, and it is easy to be used with the paper machine equipment, and also reduces the equipment maintenance cost, thereby increasing the economic benefits of the enterprise. It is of great practical significance to carry out analytical research.

(2) The main distribution of the vibration monitoring parts of the paper machine:

The state vibration monitoring and fault diagnosis of the paper machine are mainly divided into the detection and diagnosis of the operation performance of the paper machine and the operation status of the paper machine.

①Running performance monitoring is carried out by measuring vibration, pressure pulse, rotational speed and paper quality. The main aspect of monitoring is the influence of different rotating equipment components of machinery on the running process of the paper machine. The measurement point is connected to the computer monitoring station, and the measurement signal is calculated by the synchronous time-average method. The trend data in question, the measurement data and the results of the applied calculation are stored. Trend data can carry out detailed calculation and analysis of frequency spectrum and signal in time domain, and it is mainly used to analyze the variation range of different parameters. Nip vibration, paper quality and headbox pressure fluctuations are the targets to be monitored. The changes of these monitored parameters are reflected and displayed to the monitoring personnel in the form of the proportion of each monitoring equipment. The main monitoring points are located at the rear screen pressure measurement, drying pulse generator, pump pulse generator, tube bundle pressure measurement, sizing pump pressure measurement, nip roll vibration, nip roll pulse generator, blade loading pressure vibration, roll vibration, roll pulse generator, etc.

②Running status monitoring is based on vibration measurement to monitor the running status of paper machine equipment. Through condition monitoring, it is possible to detect and timely arrange maintenance and repair work in the early stage of mechanical failure of the paper machine, thus ensuring the normal operation of the paper machine and reducing the occurrence of unplanned downtime. Sensors and analysis stations are the main equipment for monitoring the running status of the paper machine. By systematically measuring vibration signals, and using the measurement results to calculate time-domain signals, envelopes and spectra.


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