Intelligent recognition of cutting load of coal mining equipment based on vibration wavelet packet feature

Yang, Jianjian; Wang, Zi-Rui; Tang, Zhiwei; Wang, Fengdong; Zhang, Zhihua; Song, Han Jung; Wu, Miao

doi:10.1109/icmic.2017.8321539

Cited by 3 publications

(4 citation statements)

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“…F P is the restoring force caused by the voltage generated by the PH, and its magnitude is related to the force-voltage factor α and the output voltage V P of the PH, which can be expressed by (1). F E is the restoring force due to the current generated in EH, and its value is related to the force-current factor β and the induced current I E of the induction coil, which can be expressed by (2).…”

Section: B Mathematical Modelling and Analysis Of The Proposed Hpehmentioning

confidence: 99%

“…Moreover, if the battery is adopted for power supply, it must be sealed in the monitoring system to eliminate the safety problems like the electric spark, and it brings another headache that how to replace it frequently. While the large equipment in the coal mine like drum rock cutting vibrator in shearer often contains large amounts of energy with a vibration frequency band of 1-200Hz and acceleration concentrated lower than 5 g [2]. Therefore, it is a desirable strategy to harvest vibration energy from the equipment and convert it to the continuous supply power for the monitoring system considering the intensive and continuous vibration of the mechanical equipment.…”

Section: Introductionmentioning

confidence: 99%

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High Performance Hybrid Piezoelectric-Electromagnetic Energy Harvester for Scavenging Energy From Low-Frequency Vibration Excitation

et al. 2020

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There are many difficulties in the power supply of the wireless monitoring system for coal mine mechanical equipment. Vibration energy scavenging is a green and effective way to solve this problem considering the intense and continuous vibration of coal mechanical equipment. In this paper, a novel hybrid vibration energy harvester was designed and manufactured, which combined electromagnetic and piezoelectric transduction units. Vibration drives the two units to move in the vertical and horizontal directions to realize the energy conversion. The mathematic model was built to calculate and predict the performance while the simulation on the distribution of magnetic field and piezoelectricity potential provided the details in the design. Besides, the output signal generated by the vibration excitation of the electromagnetic unit, piezoelectric unit and the whole energy harvester were studied simultaneously. Moreover, the resonance frequency was tested to be 14Hz, and the optimum matching impedance was measured to be 1k and 10k with the parallel and series connection of PH and EH, respectively. The maximum output power of the HPEH with the parallel connection pattern can reach 80.10mW at the acceleration of 2g. In the application experiment, the HPEH can facilely light up 120 LEDs and supply stable power for the electronics and sensors.INDEX TERMS Vibration energy acquisition, hybrid energy harvester, electromagnetic, piezoelectric, coal mine mechanical equipment.

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Section: B Mathematical Modelling and Analysis Of The Proposed Hpehmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

High Performance Hybrid Piezoelectric-Electromagnetic Energy Harvester for Scavenging Energy From Low-Frequency Vibration Excitation

et al. 2020

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“…In recent years, many studies, which aimed to increase cutting performance and reduce cutting consumption by using the roadheaders more efficiently, have been conducted by different researchers. 8–25 Ramazan comakli et al. deeply analyzed the influences of coal and rock properties on roadheader cutting load, and subjected different sandstones with uniaxial compressive strength to cutting tests under different levels of cutting parameters, and the change rule of roadheader cutting load under different coal rock properties is obtained.…”

Section: Introductionmentioning

confidence: 99%

“…put forward the method of using the shearer motor working parameters or the shearer rocker arm horizontal vibration signal to reflect the hardness of coal and rock. 25 From the above references, there are many reference studies on the performance prediction and dynamic characteristics of roadheader, aiming to improve the cutting performance of the roadheader by optimizing the cutting head parameters, and some achievements have been certainly achieved. Moreover, some literatures studies on the coal and rock hardness identification methods.…”

Section: Introductionmentioning

confidence: 99%

Rock hardness identification based on optimized PNN and multi-source data fusion

Tian

Song

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part C:

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To solve the problem that it is difficult to identify the cutting rock wall hardness of the roadheader in coal mine, a recognition method of cutting rock wall hardness is proposed based on multi-source data fusion and optimized probabilistic neural network. In this method, all kinds of cutting signals (the vibration signal of cutting arm, the pressure signal of hydraulic cylinders and current signal of cutting motor) are analyzed by wavelet packet to extract the feature vector, and the multi feature signal sample database of rock cutting with different hardness is established. To solve the problems of uncertain spread and complex network structure of probabilistic neural network (PNN), a PNN optimization method based on differential evolution algorithm (DE) and QR decomposition was proposed, and the rock hardness was identified based on multi-source data fusion by optimizing PNN. Then, based on the ground test monitoring data of a heavy longitudinal roadheader, the method is applied to recognize the cutting rock hardness, and compared with other common pattern recognition methods. The experimental results show that the cutting rock hardness recognition based on multi-source data fusion and optimized PNN has higher recognition accuracy, and the overall recognition error is reduced to 6.8%. The recognition of random cutting rock hardness is highly close to the actual. The method provides theoretical basis and technical premise for realizing automatic and intelligent cutting of heading face.

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A Complex Vibration Analysis of a Drive System Equipped with an Innovative Prototype of a Flexible Torsion Clutch as an Element of Pre-Implementation Testing

Wieczorek

Konieczny

Burdzik

et al. 2022

Sensors

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The paper presents how an important aspect of introducing new machines, especially in the mining industry, is testing a prototype under laboratory conditions. For this purpose, advanced methods of analyzing the vibrations of a drive system equipped with an innovative prototype of a flexible torsion clutch are presented. The main goal is to present a comprehensive method for analyzing vibration signals in various dimensions of the signal analysis. As a result of this approach, it can be seen how much important information about the tested clutch can be obtained by using various analysis methods in terms of time–frequency distributions or order analysis. To emphasize the differences in the functioning of the tested clutch and the possibility of monitoring these differences on the basis of the observation of residual processes, such as vibrations, the results for the flexible and locked clutch are compared.

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Intelligent recognition of cutting load of coal mining equipment based on vibration wavelet packet feature

Cited by 3 publications

References 0 publications

High Performance Hybrid Piezoelectric-Electromagnetic Energy Harvester for Scavenging Energy From Low-Frequency Vibration Excitation

High Performance Hybrid Piezoelectric-Electromagnetic Energy Harvester for Scavenging Energy From Low-Frequency Vibration Excitation

Rock hardness identification based on optimized PNN and multi-source data fusion

A Complex Vibration Analysis of a Drive System Equipped with an Innovative Prototype of a Flexible Torsion Clutch as an Element of Pre-Implementation Testing

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