Online state monitoring and fault diagnosis device and method for rotary machine

A technology for fault diagnosis devices and rotating machinery, applied in measuring devices, testing of machine/structural components, computer components, etc., can solve problems such as difficult to achieve early diagnosis and prevention of faults, difficult to meet the needs of diagnosis, etc., to achieve a rich state Monitoring and fault diagnosis methods, clear functions, and the effect of improving online monitoring and fault diagnosis performance

Inactive Publication Date: 2011-05-11
GUANGZHOU UNIVERSITY
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  • Abstract
  • Description
  • Claims
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Problems solved by technology

[0003] The traditional monitoring method is initially to use secondary instruments for monitoring. This method can only be effective under the condition of simple

Method used

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  • Online state monitoring and fault diagnosis device and method for rotary machine
  • Online state monitoring and fault diagnosis device and method for rotary machine
  • Online state monitoring and fault diagnosis device and method for rotary machine

Examples

Experimental program
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Embodiment 1

[0043] Such as figure 1 It shows the structure of an on-line monitoring and fault diagnosis device of the present invention. The device is a portable rapid diagnostic equipment, all functions are concentrated on a portable machine, suitable for rapid diagnosis or preliminary diagnosis by professional researchers related to fault diagnosis. The device includes a data acquisition device 101, a feature extraction device 102, a data management device 103, a multi-model detector training device 104, a multi-model fault diagnosis device 105, a display device 106, and a mouse, keyboard and other users to set parameters 107 with device management means. In the embodiment of the portable rapid diagnostic device, the sensor group 110 can be configured by the user.

[0044] The data acquisition device 101 collects the signals of the sensor group 110 (including n signals of sensor 1, sensor 2, ..., sensor n on the same device) according to the sensor installation and data acquisition sc...

Embodiment 2

[0132] Figure 9 An embodiment of on-line monitoring and fault diagnosis based on a hidden Markov model-support vector machine hybrid model using two industrial computers is described. This example is used for online monitoring and fault diagnosis of a single device or a small number of devices. One of the industrial computers is a collection and diagnosis machine 901, and the other industrial computer 902 is used as a detector training machine.

[0133] The collection and diagnosis machine 901 integrates data collection and diagnosis functions. Compared with Embodiment 1, 901 does not have a multi-model detector training device 104 . At the same time, the data management device of 901 is simplified as the management device 903 for collecting and diagnosing data, which is only responsible for managing detectors and collecting and diagnosing data. The data collected by the data collection device 101 is saved on the collection and diagnosis machine 901 . Periodically or when...

Embodiment 3

[0137] Figure 10 An embodiment of using the present invention to carry out on-line monitoring and fault diagnosis by adopting multiple diagnostic subsystems is described. This example is used in the embodiment of centralized online monitoring and fault diagnosis of multiple devices or large-scale devices. The example consists of a detector training machine 902, a main control machine 1001, multiple collection and diagnosis extension machines 1003-1005 and sensor groups 1011-1013, and is composed of MAP or TCP / IP bus. The structure of the detector training machine 902 is as shown in Embodiment 2, and the structure of the collection and diagnosis extensions 1003-1005 is the same as that of 901 in Embodiment 2; only their communication devices need to support the bus. The main control machine 1001 is specially responsible for the integration of the diagnosis results and the management of the database, that is, the strengthening of the function of the data management device 103 ...

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Abstract

The invention relates to an online state monitoring and fault diagnosis device and an online state monitoring and fault diagnosis method for a rotary machine. The device comprises a data acquisition device 101, a feature extraction device 102, a data management device 103, a display device 106, a device 107 such as a mouse, a keyboard or the like for setting parameters and managing equipment by a user, a multi-model detector training device 104, and a multi-model fault diagnosis device 105. The method comprises the following steps of: acquiring signals by using the data acquisition device; storing the signals, and extracting features of the signals by using the standard feature array extraction device; training a detector by using the training device for the detector for identification; performing identification by adopting the trained hybrid model detector; and outputting and recording the identification result. The device and the method can diagnose common rotary machine faults such as shaft eccentricity, bearing eccentricity, rolling body abrasion and the like, and have the advantages of high automation degree, capability of identifying multiple fault types, capability of realizing early diagnosis, good fault database expansibility and the like.

Description

technical field [0001] The invention relates to an on-line state monitoring and fault diagnosis device and method for a rotating machine, in particular to an intelligent on-line state monitoring and diagnosis device and method for large-scale rotating machinery equipment and key equipment. Background technique [0002] With the continuous advancement of science and technology, especially the trend of system integration, many mechanical equipment such as generators and steam turbines are becoming larger, faster, and more complex, and the requirements for safety and automation of equipment are also increasing. high. Once some key components, such as high-speed rotating shafts and bearings, fail, not only the cost of replacing the equipment itself will be borne, but more importantly, the entire continuous production process will be interrupted, causing major economic losses such as production stoppages and even endangering work. personal safety of personnel. The monitoring of...

Claims

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Application Information

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IPC IPC(8): G06K9/66G01M99/00
Inventor 张春良岳夏李胜李建朱厚耀
Owner GUANGZHOU UNIVERSITY
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