The effect of bearings faults to coefficients obtaned by using wavelet transform

Bayram, Samet; Kaplan, Kaplan; Kuncan, Melih; Ertunç, H. Metin

doi:10.1109/siu.2014.6830398

Cited by 26 publications

(19 citation statements)

References 4 publications

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“…In this stage, the motor is in the torque control mode. 21 There are resistance and inductance inside the DC torque motor. The simplified circuit diagram is shown in Figure 4:…”

Section: Establishment Of the Mathematical Modelmentioning

confidence: 99%

Design and test of electromechanical disc brake controller for mine hoist

Jin

Wang

2022

Measurement and Control

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Electromechanical braking technology is an effective way to improve the braking response of mine hoist. Through the analysis of the mine hoist electromechanical mechanical disc brake, a mathematical model including the motor, reducer and thread pair is established. The control process is analyzed in detail, and then the control strategy is obtained. An automatic control system based on linear quadratic regulator and PI controller is proposed. The braking goal of self-adaptive adjustment of braking clearance and on-line adjustment of braking force is realized. Compare the simulation and test results, discuss the performance of the controller. The results of the experiment indicate that the brake gap adjustment time is less than 10 s, stable within 1±0.2 mm, and the steady-state error is less than 2%. The positive pressure of the brake has a linear relationship with the motor voltage, with a slope of 920.4 and an intercept of −1298.88. It can replace the existing hydraulic brakes without the problem of low degree of automation and high pollution, which provides a new way for the control system of electromechanical brake.

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“…In this stage, the motor is in the torque control mode. 21 There are resistance and inductance inside the DC torque motor. The simplified circuit diagram is shown in Figure 4:…”

Section: Establishment Of the Mathematical Modelmentioning

confidence: 99%

Design and test of electromechanical disc brake controller for mine hoist

Jin

Wang

2022

Measurement and Control

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“…As the current prototype is able to collect different parameters from the ventilation system, once a certain amount of units are manufactured and deployed in real working environments, these data in combination with the information from the faults that might appear after a certain amount of service hours will allow us to develop the aforementioned prediction model. For some specific characteristics, such as the diagnosis of faults in bearings, an effective method can be chosen from among all the possible ones [25][26][27], based on the data provided by the designed system. Another improvement that could be considered is the use of a commercial cloud platform such as AWS or Azure.…”

Section: Future Workmentioning

confidence: 99%

Real-time monitoring solution with vibration analysis for industry 4.0 ventilation systems

et al. 2022

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Predictive maintenance has revealed as one of the paradigms of Industry 4.0. This paper addresses a complete system for the acquisition, computing, monitoring and communication of ventilation equipment in underground tunnels based on TCP/IP protocol and accessible via WEB services. Not only does the proposed system collect different sensor data (temperatures, vibrations, pressures, tilt angles or rotational speed), it performs local data processing as well. This feature is the newest and most important of all those provided by the system design, and there is no equipment that offers a similar performance in current ventilation systems. This paper shows the design and implementation of the equipment (system architecture and processing), as well as the experimental results obtained.

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“…Classification has good results. Bayram et al [17] proposed a method based on wavelet transform coefficients to realize the classification of different bearing fault types. Kaplan et al [18] proposed an improved method for bearing fault feature extraction based on texture analysis and LBP, and achieved 100% success rate in the classification of these signals.…”

Section: Introductionmentioning

confidence: 99%

Bearing fault diagnosis using transfer learning and optimized deep belief network

Zhao

Yang

Chan³

et al. 2022

Meas. Sci. Technol.

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Bearing is an important component in mechanical equipment. Its main function is to support the rotating mechanical body and reduce the friction coefficient and axial load. In the actual operating environment, the bearings are affected by complex working conditions and other factors. Therefore, it is very difficult to effectively obtain data that meets the conditions of independent and identical distribution of training data and test data, which result in unsatisfactory fault diagnosis results. As a transfer learning method, joint distribution adaptive (JDA) can effectively solve the learning problem of inconsistent distribution of training data and test data. In this paper, a new bearing fault diagnosis method based on JDA and deep belief network (DBN) with improved sparrow search algorithm (CWTSSA), namely JACADN is proposed. In the JACADN, the JDA is employed to carry out feature transfer between the source domain samples and target domain samples, that is, the source domain samples and target domain samples are mapped into the same feature space by the kernel function. Then the maximum mean difference is used as the metric to reduce the joint distribution difference between the samples in the two domains. Aiming at the parameter selection of the DBN, an improved sparrow search algorithm (CWTSSA) with global optimization ability is used to optimize the parameters of the DBN in order to construct an optimized DBN model. The obtained source domain samples and target domain samples are divided into training set and test set, which are input the optimized DBN to construct a bearing fault diagnosis model for improving the diagnosis accuracy. The effectiveness of the proposed method is verified by vibration data of QPZZ-II rotating machinery. The experimental results show that the proposed JACADN method can effectively improve the fault diagnosis accuracy of rolling bearings under variable operating conditions.

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The effect of bearings faults to coefficients obtaned by using wavelet transform

Cited by 26 publications

References 4 publications

Design and test of electromechanical disc brake controller for mine hoist

Design and test of electromechanical disc brake controller for mine hoist

Real-time monitoring solution with vibration analysis for industry 4.0 ventilation systems

Bearing fault diagnosis using transfer learning and optimized deep belief network

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