The Use of a Multilabel Classification Framework for the Detection of Broken Bars and Mixed Eccentricity Faults Based on the Start-Up Transient

Georgoulas, George; Climente-Alarcón, Vicente; Antonino-Daviu, José A.; Tsoumas, Ioannis P.; Stylios, Chrysostomos; Arkkio, Antero; Nikolakopoulos, George

doi:10.1109/tii.2016.2637169

Cited by 41 publications

(10 citation statements)

References 43 publications

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“…The effect of sideband frequencies of the fundamental component amplitude of stator current was investigated. Other authors [5] used a start-up transient process and a multilabel classification framework to detect the broken rotor bar fault and mixed eccentricity faults. Furthermore, a study [6] used a nonuniform time resampling algorithm to realize fault diagnosis of the broken rotor bar under the soft start of the inverter power supply.…”

Section: Introductionmentioning

confidence: 99%

Current Characteristics Analysis and Fault Injection of an Early Weak Fault in Broken Rotor Bar of Traction Motor

Yin

Xie

Peng

et al. 2018

Mathematical Problems in Engineering

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Aiming at the destructive and irreversible problems of the broken rotor bar fault of the traction motor, the current characteristics of the early weak fault of the single bar are analyzed, and the broken rotor bar fault simulation injection is realized on the experimental platform. Firstly, a damage factor from the change rule of the metal resistance value of a rotor bar is defined. By means of such a damage factor, the relationship between the severity of the fracture of a single rotor bar and the phase resistance of the traction motor was obtained. Through the superposition principle, the traction motor in the fault of the rotor bar was regarded as a normal motor in which the reverse current source was superimposed on the fault rotor bar. The characteristic values of the stator current fault component were obtained when the single bar had broken. Finally, the relationship between the fault characteristics component of the stator current and the fracture severity of the single rotor bar was established. On this basis, on hardware-in-the-loop fault injection benchmark of the traction drive control system based on dSPACE, the gradual injection of early weak faults in the early broken rotor bar was carried out and the results were analyzed. The experimental data demonstrated the correctness of the current characteristics analysis and fault injection.

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Section: Introductionmentioning

confidence: 99%

Current Characteristics Analysis and Fault Injection of an Early Weak Fault in Broken Rotor Bar of Traction Motor

Yin

Xie

Peng

et al. 2018

Mathematical Problems in Engineering

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show abstract

“…A method of fault feature extraction based on intrinsic mode function (IMF) envelope spectrum is proposed by Yang et al [8] and the support vector machine (SVM) classifiers was used to provide the possibility of machinery faults. And Georgoulas et al [9] analyzed the motor fault characteristics and identified them with time-frequency characteristics, in this research Markov distance classifier was used to identify the motor health. A new vibration spectral imaging (VSI) feature enhancement method was proposed by Amar et al [10] under the condition of low signal-to-noise ratio, and artificial neural network (ANN) was used as the fault classifier according to these enhanced fault features.…”

Section: Related Workmentioning

confidence: 99%

“…(8) is the fuzzy synthetic operator, whose operation logic is shown in Eq. (9). The element vi in the output vector v represents the membership degree of the current symptom corresponding to defect cause i.…”

Section: A Defect Cause Classification and Fuzzy Semantic Inferencementioning

confidence: 99%

Fault Location of Strip Steel Surface Quality Defects on Hot-Rolling Production Line Based on Information Fusion of Historical Cases and Process Data

Wang

Chen

2020

IEEE Access

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Surface quality is the most important index to improve the overall quality of strip steel. In order to implement the fault location on the hot-rolling line with surface defects of strip steel, a fault tracing model based on information fusion of historical production cases and process data is proposed. For historical cases, the model determines the defect cause labels through text similarity calculation, and fuzzy semantic inference is used to obtain the probability distribution of defect causes on this basis; for the process data, the model uses L1 regularization method for feature selection, and XGBoost integration method is used to train the correlation model between process data and defects to determine the contribution of each feature in the data source. Finally, based on the D-S evidence theory, different rules are set to merge the two judgments to determine the probability of each source of failure on the hot-rolling production line. The model is applied to the real production environment of iron and steel enterprises, and it is verified that the proposed method can effectively assist experts in decision-making, which greatly improves the efficiency of tracing the source of faults on the hot-rolling production line.

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“…[6][7][8][9][10][11][12][13][14][15][16][17][18][19].53] Na A Na A Approximation (7) [19.53-0] Na Na Na Na A: Applicable; Na: Not applicable.…”

Section: Log-energy Entropymentioning

confidence: 99%

Broken Rotor Bar Detection in LS-PMSM Based on Startup Current Analysis Using Wavelet Entropy Features

et al. 2017

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High-efficiency motors are being gradually introduced in many industrial applications because of their positive impacts on the environment by reducing energy consumption and CO 2 emission. In this respect, line start permanent magnet synchronous motors (LS-PMSMs) have been introduced recently. Due to their unique configuration, LS-PMSMs allow the obtaining of super premium efficiency levels, accompanied with a high torque and power factor. However, since the use of LS-PMSMs in the industry is in its infancy, no efficient scheme has yet been reported for broken rotor bar (BRB) fault detection in this type of motor. Accordingly, the main aim of this research is to investigate the fault-related feature for BRB faults on LS-PMSMs. In this regard, a simulation model and experimental setup for the investigation of BRB in LS-PMSM are implemented. The detection strategy for BRB in LS-PMSM proposed here is based on the monitoring of the start-up current signal and discrete wavelet transform. The entropy features are used as fault-related features for BRB faults. Finally, the ability of these features is validated for the detection of BRB in LS-PMSM through statistical analysis. In this research, the importance of the starting load is also considered for BRB detection in LS-PMSMs.

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The Use of a Multilabel Classification Framework for the Detection of Broken Bars and Mixed Eccentricity Faults Based on the Start-Up Transient

Cited by 41 publications

References 43 publications

Current Characteristics Analysis and Fault Injection of an Early Weak Fault in Broken Rotor Bar of Traction Motor

Current Characteristics Analysis and Fault Injection of an Early Weak Fault in Broken Rotor Bar of Traction Motor

Fault Location of Strip Steel Surface Quality Defects on Hot-Rolling Production Line Based on Information Fusion of Historical Cases and Process Data

Broken Rotor Bar Detection in LS-PMSM Based on Startup Current Analysis Using Wavelet Entropy Features

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