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A mine hoist tension fault diagnosis method, system and control system

A fault diagnosis system and mine hoist technology, applied in elevators, computer parts, instruments, etc., can solve problems such as tension fault detection methods or poor system practicability, and achieve long-term stable and reliable operation, improve service life, and maintenance costs. low effect

Active Publication Date: 2020-12-22
CENT SOUTH UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] The present invention proposes a mine hoist tension fault diagnosis method, system and control system to solve the problem of poor practicability of the tension fault detection method or system in the related art

Method used

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  • A mine hoist tension fault diagnosis method, system and control system
  • A mine hoist tension fault diagnosis method, system and control system
  • A mine hoist tension fault diagnosis method, system and control system

Examples

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Embodiment 1

[0051] The invention provides a mine hoist tension fault diagnosis method, such as figure 1 shown, including the following steps,

[0052] Model building phase:

[0053] Acquire the axial vibration signal data of several sky wheel shafts under different tension states. In this embodiment, two axial vibration signals of the sky wheel shaft are collected. To achieve a balance between, in this embodiment, the signal segment with a duration of 1s is selected to be intercepted, image 3 The axial vibration waveforms of a single rope under three working conditions of overload (S1-A), normal (S2-A), and underload (S3-A) are shown.

[0054] Feature extraction, EEMD decomposition is performed on each acquired vibration signal, and each vibration signal is decomposed into a series of IMFs. EEMD is an adaptive signal decomposition method for non-stationary nonlinear signals. For a vibration signal x(t), EEMD decomposes it into a series of IMF c k (t) and the residual term r m (t), ...

Embodiment 2

[0068] The invention provides a mine hoist tension fault diagnosis system, comprising:

[0069] Several vibration sensors 2 are used to obtain axial vibration signals of several sky wheel shafts 1;

[0070] The data collector 3 is used to transmit the vibration signals obtained by the plurality of vibration sensors 2 to the feature extraction module 4;

[0071] The feature extraction module 4 is used to extract the features of the vibration signal transmitted by the data collector 3, decompose each vibration signal into EEMD, decompose each vibration signal into a series of IMFs, and select the one with the highest ratio of energy to the total energy of the vibration signal For the first several IMFs, the energy and permutation entropy of the selected several IMFs are obtained, and the feature vectors are formed, and the feature vectors of a group of simultaneously obtained axial vibration signals of the wheel shaft are combined into the final feature vector;

[0072] Model b...

Embodiment 3

[0085] The present invention provides a mine hoist control system, which includes the above-mentioned mine hoist tension fault diagnosis system and a control unit connected with the mine hoist tension fault diagnosis system. During specific implementation, the mine hoist tension fault diagnosis system provided in Embodiment 2 can be connected with the main control PLC of the mine hoist, and a wired connection or a wireless connection can be used to realize the mine hoist tension fault diagnosis system and the mine hoist. The main control PLC communication, the mine hoist tension fault diagnosis system transmits the tension state information to the main control PLC, which can deal with the identified tension faults in real time and provide mine production safety.

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Abstract

The invention discloses a mine hoist tension fault diagnosis method, system and control system, including the following process: acquiring axial vibration signal data of a number of sky wheel shafts under different tension states, decomposing the vibration signal into a series of IMF through EEMD, selecting energy The first few IMFs with the highest proportions are obtained and their energy and permutation entropy are obtained to form eigenvectors, and a group of eigenvectors of axial vibration signals of several wheel shafts are combined into the final eigenvector; the final eigenvector and its corresponding different tension states As a sample training mine hoist tension state PSO-SVM classification model; obtain several real-time axial vibration signals of the wheel shaft; extract the final feature vector from the real-time vibration signals, and use the PSO-SVM classification model to identify the tension state in real time. It can conveniently and quickly realize the long-term, stable and reliable real-time monitoring of the tension failure of the mine hoist, and control the working state of the mine hoist, improve the safety of mine production, and improve the economic and social benefits of the mine.

Description

technical field [0001] The invention relates to the field of mine hoisting, in particular to a tension fault diagnosis method, system and control system of a mine hoist. Background technique [0002] The mine hoist is the "throat" equipment connecting the ground and the underground, and it undertakes the transportation of ore, materials and personnel. In shafts with a depth of several hundred to several thousand meters, the hoisting container is connected to the main shaft drum of the hoist through a wire rope. Therefore, the tension state of the wire rope is crucial to the safety of hoisting. For a single steel wire rope, overload failure may cause wear or breakage, resulting in a tank falling accident. For the lifting of multiple wire ropes, unbalanced tension may cause the lifting container to tilt, increase the wear of the tank, reduce the life of the wire rope, or cause instability in operation. In addition, there are many interference factors during the movement of t...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): B66B7/12B66B5/00G06K9/00G06K9/62G06N3/00
CPCB66B7/1215B66B5/0031G06N3/006G06F2218/08G06F2218/12G06F18/2411
Inventor 谭建平薛少华石理想邓积微陈昭君黄天然
Owner CENT SOUTH UNIV
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