WEBApr 1, 2014 · Roller bearing is one of the most widely used and critical elements in rotating machinery. In consequence, bearing fault diagnosis in machines, as well as to discriminate the different fault conditions have been a great interest. In this study, firstly, analytical model of a shaftball bearing system is developed. The shaft is assumed to be perfectly .
WEBDec 31, 2022 · The experimental results reveal that the method can effectively realize the fault diagnosis of rolling mill equipment under variable working conditions and can achieve average diagnostic rates of ...
WEBApr 23, 2023 · Purpose The main purpose of this paper is to change the structure of the SDP to include more fault information. Furthermore, improve the diagnostic accuracy and antinoise performance of the bearing fault diagnosis method based on SDP. Methods First, a multiinterval asymmetric dot pattern (MADP) is proposed by modifying the .
WEBSection 2 introduces the instruction and structure of the highspeed wire rod finishing mill group. A fault diagnosis method based on expert experience and datadriven for highspeed ... six highprecision gears, five angular contact ball bearings, and three cylindrical roller bearings. Among them, II axis, III axis, IV axis, V axis, VI axis ...
WEBFault diagnosis for rolling bearings has been an important engineering problem for decades. To detect the damaged bearing surface, engineers analyze the features from the extracted vibration signals of the machine. As artificial intelligence rapidly develops and provides favorable effects in data analytics, using deeplearning technology to attack .
WEBSep 8, 2023 · The reliable and safe operation of industrial systems needs to detect and diagnose bearing faults as early as possible. Intelligent fault diagnostic systems that use deep learning convolutional neural network (CNN) techniques have achieved a great deal of success in recent years. In a traditional CNN, the fully connected layer is loed in the .
WEBApr 12, 2024 · The feature information extracted by CNN is not integrated due to lack of feature learning ability, which will induce unsatisfactory diagnostic results and poor generalization ability. To deal with the above issues, a dualflow convolutional neural network (DFCNN) is proposed for intelligent diagnosis the faults of roller bearings.
WEBJul 31, 2019 · This case study is to identify and evaluate the root cause for failure of a roller press mill. Cement plant has a heavy crushing operation the roller#8217;s top surface is eroded, which is replaced by hard metal deposition by welding. In .
WEBNov 10, 2020 · Safety and reliability are absolutely important for modern sophistied systems and technologies. Therefore, malfunction monitoring capabilities are instilled in the system for detection of the incipient faults and anticipation of their impact on the future behavior of the system using fault diagnosis techniques. In particular, stateoftheart .
WEBJan 22, 2016 · Recent advances on SVM based fault diagnosis and process monitoring in complied industrial processes ... systems. These methods are also applied in some other systems,, three tank system [61] and industrial hot strip mill [62 ... Multifault diagnosis of ball bearing based on features extracted from timedomain and multiclass .
WEBA modelbased deep learning algorithm for fault diagnosis is proposed to effectively detect the operation state of coal mills and generate the warnings in advance. The coal mill is one of the important auxiliary engines in the coalfired power station. Its operation status is directly related to the safe and steady operation of the units. In this paper, a model .
WEBDec 2, 2023 · The demands for improving machinery condition monitoring and fault diagnosis have increased the need for the development of monitoring tools. Oil monitoring, acoustic emission, thermography monitoring, and vibration analysis have received considerable attention in condition monitoring of rotating machinery [1,2,3,4,5].Presently, .
WEBSep 15, 2017 · In the field of hot rolling process monitoring, the activation of nonlinear dynamic behaviour may render the procedure of fault diagnosis more difficult. Principal component analysis (PCA) is known as a popular method for diagnosis but as it is basically a linear method, it may pass over some useful nonlinear features of the system behaviour.
WEBAug 20, 2022 · The ball screw is the core component of the CNC machine tool feed system, and its health plays an important role in the feed system and even in the entire CNC machine tool. This paper studies the fault diagnosis and health assessment of ball screws. Aiming at the problem that the ball screw signal is weak and susceptible to interference, .
WEBThe bearing is the key component of rotating machinery, and its performance directly determines the reliability and safety of the system. Databased bearing fault diagnosis has become a research hotspot. Naive Bayes (NB), which is based on independent presumption, is widely used in fault diagnosis. However, the bearing data are not .
WEBApr 7, 2020 · is proposed in this paper, by which fault data samples can be generated by the fault simulation of a. coal mill system model. The core lies in constructing a model of the coal mill system t hat ...
WEBJan 1, 2011 · Key words: HAGC; fault diagnosis; neural network; wavelet transform Hydraulic Gauge Control (HAGC) system is the core technology of strip rolling mill. The work con› ditions decide the quality of steel strip directly. In fact, many approaches have been proposed in the past about the research about fault diagnosis for HAGCCiZ].
WEBVertical mill is an important equipment existing in cement industry. In the normal operation process, defect may easily occurs at some components due to the severe working environment. Taking the bearing component as an example, this paper proposed a novel fault diagnosis method based on entropy feature to discriminate the ball fault, outer .
WEBApr 17, 2023 · Xin G, Li Z, Jia L, et al. Fault diagnosis of wheelset bearings in highspeed trains using logarithmic shorttime Fourier transform and modified selfcalibrated residual network. ... Yang L, Zeng C, et al. Integrated approach for ball mill load forecasting based on improved EWT, refined composite multiscale dispersion entropy and fireworks ...
WEBJan 25, 2024 · The bearing used in this experiment is manufactured by NTN company and the model is NU204 ET2X. The fault of the bearing was caused by using wirecut machining to a depth and width of mm and mm, respectively. The types of bearing faults tested included outer ring faults, ball faults, and inner ring faults, as shown in .
WEBOct 1, 2020 · Results showed the potential of motor current signal in bearing fault diagnosis with high classifiion accuracy. ... a case study for a paper mill at Swedish showed that preventing unplanned stoppage for a year will increase the ... Harsha, : Fault diagnosis of ball bearings using machine learning methods. Expert Syst. Appl. .
WEBOct 1, 2022 · The proposed approach that diagnoses the faults of a rolling mill bearing by employing the improved sparrow search algorithm deep belief network (ISAADBN) with limited data samples improves the efficiency of the diagnosis and achieves the highest diagnosis accuracy withlimited data samples. Given the complexity of the operating .
WEBOct 5, 2023 · Learning powerful discriminative features is the key for machine fault diagnosis. Most existing methods based on convolutional neural network (CNN) have achieved promising results. However, they primarily focus on global features derived from sample signals and fail to explicitly mine relationships between signals. In contrast, .
WEBAug 15, 2021 · It is an important guide to the current problem of insufficient data and low diagnosis accuracy faced in the fault diagnosis of multirow bearings such as rolling mills. The structure of DCGAN.
WEBJan 4, 2024 · The parts where ball mills often fail are mainly in the reduction box gears and rolling bearings as well as the ball mill barrel bearings. Failure of these components during production will seriously affect the efficiency of the overall grinding process. Xinhai Mining recommends inspection and fault diagnosis of the gear transmission system and .
WEBIn this paper, a ball mill gear reducer was regarded as the research object. Based on the HMM pattern recognition theory, DHMM methods that were used in fault diagnosis had been researched. The vibration signal was required a series transformations which are feature extraction, normalization, scalarization and quantization to get the sequence .
WEBMay 28, 2003 · Condition monitoring leading to fault diagnosis and prediction of electrical machines and drives has recently become of importance. The topic has attracted researchers to work in during the past few years because of its great influence on the operational continuation of many industrial processes. Correct diagnosis and early .
WEBSep 1, 2020 · Based on the defined label, the coal mill faults are coded as shown in Table 4. Construction of SAE model. Establishing an optimal SAE model is critical to the accuracy of. Conclusion. In this paper, a fault diagnosis method of coal mill based on simulated fault data is proposed for solving the problem that massive fault samples are inaccessible.
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