scholarly journals Fault Diagnosis of Coal Mining Machinery Based on State Parameters

2020 ◽  
Author(s):  
Dong Song
Keyword(s):  
Fault Diagnosis ◽  
Coal Mining ◽  
Fault Type ◽  
Fault Parameters ◽  
Underground Coal Mines ◽  
Mining Machinery ◽  
The Status ◽  
New Perspective ◽  
Judgment Condition ◽  
Cutting Unit

The reliable operation of coal mining machinery acts as an important guarantee for safe productions in underground coal mines. The status monitoring and fault diagnosis of traditional coal mining machinery mainly rely on threshold judgments. However, a single judgment condition and a long fault propagation chain can be found in the method of threshold judgments, which make it difficult to accurately seek the fault type. By using the data analysis of state parameters for coal mining machinery, fault parameters and propagation paths can be analyzed effectively. This paper takes the cutting unit of a certain type of bolter miners as an example, a static and dynamic numerical analysis method of the cutting unit of bolter miners are established by virtue of FTA-Petri net models and BP-Firefly neural networks, which can provide a new perspective for fault diagnosis of coal mining machinery.

A Fault Diagnosis of Suck Rod Pumping System Based on SVM

2013 ◽  
Vol 307 ◽  
pp. 285-289 ◽  
Author(s):  
Wei Wu ◽  
Yu Zhou ◽  
Hang Xin Wei
Keyword(s):  
Fault Diagnosis ◽  
Support Vector ◽  
Oil Well ◽  
Pump System ◽  
Indicator Diagram ◽  
Invariant Moments ◽  
Pumping System ◽  
System A ◽  
Fault Type ◽  
Shape Characteristics

Aiming at the defects of fault diagnosis in the traditional method for sucker rod pump system, a new method based on support vector machine (SVM) pump fault diagnosis is proposed. Through studying the theory of invariant moment and the shape characteristics of pump indicator diagram, seven invariant moments is extracted from the indicator diagram as a pumping unit well condition of the characteristic parameters. Then these parameters are pretreatment, and it makes up seven eigenvector which are regarded as the input eigenvector of the SVM. The experiment indicates that the method can not only detect the fault of the pumping oil well but also can recognize the fault type of it, which is very effective for safety protection and fault diagnosis of the pumping oil.

scholarly journals Analog Circuit Fault Diagnosis Based on Support Vector Machine Classifier and Fuzzy Feature Selection

Electronics ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 1496
Author(s):  
Hao Liang ◽  
Yiman Zhu ◽  
Dongyang Zhang ◽  
Le Chang ◽  
Yuming Lu ◽  
...  
Keyword(s):  
Support Vector Machine ◽  
Fault Diagnosis ◽  
Mutual Information ◽  
Analog Circuit ◽  
Fault Classification ◽  
Support Vector ◽  
Svm Classifier ◽  
Fault Parameters ◽  
Diagnosis Method ◽  
Circuit Fault Diagnosis

In analog circuit, the component parameters have tolerances and the fault component parameters present a wide distribution, which brings obstacle to classification diagnosis. To tackle this problem, this article proposes a soft fault diagnosis method combining the improved barnacles mating optimizer(BMO) algorithm with the support vector machine (SVM) classifier, which can achieve the minimum redundancy and maximum relevance for feature dimension reduction with fuzzy mutual information. To be concrete, first, the improved barnacles mating optimizer algorithm is used to optimize the parameters for learning and classification. We adopt six test functions that are on three data sets from the University of California, Irvine (UCI) machine learning repository to test the performance of SVM classifier with five different optimization algorithms. The results show that the SVM classifier combined with the improved barnacles mating optimizer algorithm is characterized with high accuracy in classification. Second, fuzzy mutual information, enhanced minimum redundancy, and maximum relevance principle are applied to reduce the dimension of the feature vector. Finally, a circuit experiment is carried out to verify that the proposed method can achieve fault classification effectively when the fault parameters are both fixed and distributed. The accuracy of the proposed fault diagnosis method is 92.9% when the fault parameters are distributed, which is 1.8% higher than other classifiers on average. When the fault parameters are fixed, the accuracy rate is 99.07%, which is 0.7% higher than other classifiers on average.

Research and Application on Technology of Flood-Storage and Flood-Detention of Coal Mining Subsidence Area of Suzhou Coal Mine

2014 ◽  
Vol 641-642 ◽  
pp. 80-83
Author(s):  
Jia Zhong Zheng ◽  
Mei Zhu ◽  
Zheng Long Wang
Keyword(s):  
Coal Mining ◽  
Dynamic Change ◽  
Storage Conditions ◽  
Flood Routing ◽  
Mining Subsidence ◽  
Subsidence Area ◽  
The Status ◽  
Suzhou City ◽  
Change Trend ◽  
Coal Mining Subsidence

The artical is based on the investigation of the basis of the status quo of Zhuxianzhuang and Luling coal mining subsidence area in Anhui province Suzhou city(hereinafter referred to as the "Zhu Lu subsidence area"), a preliminary analysis of the dynamic change trend of detention space in Zhu Lu subsidence area, and based on the hysteresis storage conditions of subsidence area, use the flood routing model to simulate the hysteresis effect of storage at different subsidence scenarios of different frequency flood. Finally, using the experience type channel evolution model and peak delay routing model further revealed storage effect on flood process of Zhu Lu subsidence area.

scholarly journals Energy Analysis Method Based on Wavelet Transform for Sensor Fault Diagnosis

2011 ◽  
Vol 2-3 ◽  
pp. 117-122 ◽  
Author(s):  
Peng Peng Qian ◽  
Jin Guo Liu ◽  
Wei Zhang ◽  
Ying Zi Wei
Keyword(s):  
Wavelet Transform ◽  
Fault Diagnosis ◽  
Wavelet Analysis ◽  
Energy Analysis ◽  
Sensor Faults ◽  
Analysis Method ◽  
Sensor Fault ◽  
Fault Type ◽  
Ideal Tool ◽  
Non Stationary Signal

Wavelet analysis with its unique features is very suitable for analyzing non-stationary signal, and it can also be used as an ideal tool for signal processing in fault diagnosis. The characteristics of the faults and the necessary information on the diagnosis can be constructed and extracted respectively by wavelet analysis. Though wavelet analysis is specialized in characteristics extraction, it can not determine the fault type. So this paper has proposed an energy analysis method based on wavelet transform. Experiment results show the method is very effective for sensor fault diagnosis, because it can not only detect the sensor faults, but also determine the fault type.

scholarly journals Deep convolutional tree-inspired network: a decision-tree-structured neural network for hierarchical fault diagnosis of bearings

2021 ◽  
Author(s):  
Xu Wang ◽  
Hongyang Gu ◽  
Tianyang Wang ◽  
Wei Zhang ◽  
Aihua Li ◽  
...  
Keyword(s):  
Neural Network ◽  
Fault Diagnosis ◽  
Decision Tree ◽  
Structural Characteristics ◽  
Proposed Model ◽  
The Hierarchical Structure ◽  
Hierarchical Decision ◽  
Tree Methods ◽  
New Perspective ◽  
Simple Combination

AbstractThe fault diagnosis of bearings is crucial in ensuring the reliability of rotating machinery. Deep neural networks have provided unprecedented opportunities to condition monitoring from a new perspective due to the powerful ability in learning fault-related knowledge. However, the inexplicability and low generalization ability of fault diagnosis models still bar them from the application. To address this issue, this paper explores a decision-tree-structured neural network, that is, the deep convolutional tree-inspired network (DCTN), for the hierarchical fault diagnosis of bearings. The proposed model effectively integrates the advantages of convolutional neural network (CNN) and decision tree methods by rebuilding the output decision layer of CNN according to the hierarchical structural characteristics of the decision tree, which is by no means a simple combination of the two models. The proposed DCTN model has unique advantages in 1) the hierarchical structure that can support more accuracy and comprehensive fault diagnosis, 2) the better interpretability of the model output with hierarchical decision making, and 3) more powerful generalization capabilities for the samples across fault severities. The multiclass fault diagnosis case and cross-severity fault diagnosis case are executed on a multicondition aeronautical bearing test rig. Experimental results can fully demonstrate the feasibility and superiority of the proposed method.

scholarly journals Fault diagnosis mechanism of gears and bearings for coal mining equipment in a complex geological environment

2021 ◽  
Vol 25 (1) ◽  
pp. 115-122
Author(s):  
Shuilin Wang ◽  
SongYong Liu ◽  
Fanping Meng
Keyword(s):  
Fault Diagnosis ◽  
Coal Mining ◽  
Research Method ◽  
Geological Environment ◽  
Mining Equipment ◽  
Traditional Research ◽  
The Difference ◽  
New Research ◽  
Fault Mechanism ◽  
Positioning Algorithm

The traditional research method of fault diagnosis mechanism has poor stability, which leads to the difference of fault diagnosis and location results. Therefore, under the complex geological environment, a new research method of fault diagnosis mechanism of gear and bearing for coal mining equipment is proposed. This method calculates gears and bearings’ yield strength by analyzing coal mining equipment’s bearing capacity elasticity. According to the fitting degree, the equipment sample’s projection space is confirmed, the fault features of gear and bearing are extracted by segmentation algorithm, the optimal fitness is set by positioning algorithm, the location of fault center is obtained, and the fault mechanism diagnosis is studied. Experimental results show that compared with the traditional method, the proposed method is more stable, and the difference in fault diagnosis results is minimal. It can be seen that this method is more suitable for fault diagnosis of coal mining equipment.

The Dialectics of Affect

Anxiety ◽  
2020 ◽  
pp. 133-174
Author(s):  
Bettina Bergo
Keyword(s):  
The Self ◽  
Human Race ◽  
Human Actions ◽  
Knowing That ◽  
The Status ◽  
History Of ◽  
New Perspective ◽  
Spiritual History

Initially influenced by Schelling’s lectures on positive philosophy (1841–1842), Kierkegaard ultimately withdrew from his lectures, devoting his attention exclusively to the redaction of Either/Or. The Concept of Anxiety was written in the shadow of that work under a uniquely anonymous pseudonym. Of course, anxiety in his deformalization of late idealism was not a concept; it belonged and did not belong to the understanding. Indeed, it precedes human actions under the sign of inherited “sinfulness” and as sheer possibility. If Kierkegaard aligned freedom with a leap, then anxiety was the affect precursive to it. Anxiety was the prethetic knowing that we are able to do. . . X. Tracing the “spiritual” history of the human race which carries the sins of the fathers even as it freely enacts sin, Kierkegaard urged that the more spiritual the culture, the more anxious it was. No longer the adjuvant of reason as in Hegel, anxiety belonged to the irreducible condition of a living subject. Over the five years that separated the Concept of Anxiety from Sickness onto Death, Kierkegaard’s mood of “Angest” will intensify as it is approached from his new perspective of Coram Deo (“before God”). Within the new perspective, the status and the meaning of the self is altered, showing a clearer relation to infinity. For the task of Kierkegaard’s philosophy—learning to become the nothing that one is—had attained a new stage in his existential dialectic. His arguments influenced Heidegger’s recourse to anxiety as a passage toward the question of being.

scholarly journals COUNSELS OF PERFECTION AND REFORMATION POLITICAL THOUGHT

2018 ◽  
Vol 62 (2) ◽  
pp. 311-330
Author(s):  
SARAH MORTIMER
Keyword(s):  
Sixteenth Century ◽  
Political Thought ◽  
Human Beings ◽  
Ethical Thought ◽  
Good Works ◽  
Reformation Theology ◽  
The Status ◽  
New Perspective ◽  
Theological Critique ◽  
The Church

AbstractThe debate over counsels of perfection was a crucial aspect of the formation of political and ethical thought in the sixteenth century. It led both Protestants and Catholics to consider the status of law and to consider how far it obliged human beings, rather than simply permitting particular actions. From Luther onwards, Protestants came to see God's standards for human beings in absolute terms, rejecting any suggestion that there were good works which were merely counselled rather than commanded, and therefore not obligatory. This view of ethics underpinned the Protestant theological critique of Catholic doctrines of merit but it also shaped the distinctively Protestant account of natural law. It enabled Luther and his allies to defend magisterial control over the church, and it also formed a crucial element of Protestant resistance theory. By examining the Lutheran position on counsels, expressed in theological and political writings, and comparing it with contemporary Catholic accounts, this article offers a new perspective on Reformation theology and political thought.

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