A Novel Approach for Shearer Memory Cutting Based on Fuzzy Optimization Method

Computational Intelligence and Neuroscience

et al. 2016

Self Cite

In order to reduce the enlargement of coal floor deformation and the manual adjustment frequency of rocker arms, an improved approach through integration of improved genetic algorithm and fuzzy logic control (GFLC) method is proposed. The enlargement of coal floor deformation is analyzed and a model is built. Then, the framework of proposed approach is built. Moreover, the constituents of GA such as tangent function roulette wheel selection (Tan-RWS) selection, uniform crossover, and nonuniform mutation are employed to enhance the performance of GFLC. Finally, two simulation examples and an industrial application example are carried out and the results indicate that the proposed method is feasible and efficient.

Section: The Enlargement Problem Of Coal Floor Deformationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An Improved Genetic Fuzzy Logic Control Method to Reduce the Enlargement of Coal Floor Deformation in Shearer Memory Cutting Process

Tan

Computational Intelligence and Neuroscience

et al. 2016

Self Cite

“…In [ 9 ], Zhong-Bin et al developed a remote monitoring platform of the shearer by using Virtual-Prototype technology to realize the remote monitoring for the shearer in the fully mechanized long-wall coal mining face. In [ 10 ], Zhou et al proposed a novel approach based on the coal floor height variation which is taken as a significant factor and fuzzy optimization theory to improve the implement precision of shearer memory cutting. In [ 11 ], P. W. Tse and Y. L. Tse designed an innovative system that is installed in a passenger car or a truck that is running on road and provides instantaneous engine health evaluation and diagnosis.…”

Section: Literature Reviewmentioning

confidence: 99%

A Dynamic Health Assessment Approach for Shearer Based on Artificial Immune Algorithm

Computational Intelligence and Neuroscience

et al. 2016

Self Cite

In order to accurately identify the dynamic health of shearer, reducing operating trouble and production accident of shearer and improving coal production efficiency further, a dynamic health assessment approach for shearer based on artificial immune algorithm was proposed. The key technologies such as system framework, selecting the indicators for shearer dynamic health assessment, and health assessment model were provided, and the flowchart of the proposed approach was designed. A simulation example, with an accuracy of 96%, based on the collected data from industrial production scene was provided. Furthermore, the comparison demonstrated that the proposed method exhibited higher classification accuracy than the classifiers based on back propagation-neural network (BP-NN) and support vector machine (SVM) methods. Finally, the proposed approach was applied in an engineering problem of shearer dynamic health assessment. The industrial application results showed that the paper research achievements could be used combining with shearer automation control system in fully mechanized coal face. The simulation and the application results indicated that the proposed method was feasible and outperforming others.

“…Based on the workflow of fully mechanized mining equipment, Zhou (Zhou et al 2015;Wang et al 2009Wang et al , 2013 established collaborative control models of the posture control and comprehensive mining equipment. Chen et al (2011) used aPM32 electric hydraulic control system to realize automatic drop, move, and upper support systems, to monitor and display the roof pressure, and to calculate the shearer position, the control of cutting height, and the running speed.…”

Section: Introductionmentioning

confidence: 99%

An operation optimization method of a fully mechanized coal mining face based on semi-physical virtual simulation

Shi

Xie

et al. 2019

Int J Coal Sci Technol

A mathematical hydraulic support self-tracking model for three-machine cooperative mining is proposed to address low efficiency and difficulties in strategy evaluation of a fully mechanized coal face. The proposed model uses the coordinates and traction speed of the shearer to calculate the frequency of the circular hydraulic support and realize the coordinated operation of the three-machine mining technology. A unity3d hardware-in-the-loop simulation experimental hearer and hydraulic support platform was used to validate the model of autonomous follow-up. The results indicate that collaborative control of coal mining allowed for an efficiency 3.76% higher than under automatic operation mode and 46.03% higher than under manual control; thus, The mathematical model provided an improved production efficiency of the fully mechanized mining face. The mathematical model also provides a more intelligent and reliable security support, and improves the intelligent level of hydraulic support follow-up control.