A Joint Positioning and Attitude Solving Method for Shearer and Scraper Conveyor under Complex Conditions

Xie, Jiacheng; Zhao-jian, Yang; Wang, Xuewen; Wang, Shuping; Zhang, Qing

doi:10.1155/2017/3793412

Cited by 24 publications

(22 citation statements)

References 10 publications

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“…In this system, the coal-mining machine, scraper conveyor, hydraulic support group, hydraulic liquid supply pump, and down hole working surface are used as agents. And the information interaction and perception with multiple agents (Xie et al 2017(Xie et al , 2019a realizes the whole collaboration and achieves efficient coal mining. To allow the three machines to interact effectively with each other and the down hole environment, aUnity3D model system framework was built between and is shown in Fig.…”

Section: Semi-physical Simulation Construction Of Fully Mechanized MImentioning

confidence: 99%

“…The application of advanced design methods such as reliability design and finite element analysis has allowed fully mechanized automatic coal mining technology, thus improving mining effectiveness (Ralston et al 2017a, b). This work presents a self-contained semi-physical collaborative planning simulation system based on Unity3D (Xie et al 2017(Xie et al , 2018a(Xie et al , b, 2019a to predict the self-following strategy of this hydraulic support.…”

Section: Introductionmentioning

confidence: 99%

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

Shi

Xie

Wang

et al. 2019

Int J Coal Sci Technol

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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.

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Section: Semi-physical Simulation Construction Of Fully Mechanized MImentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

Shi

Xie

Wang

et al. 2019

Int J Coal Sci Technol

Self Cite

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“…The scraper conveyor is the key equipment of mechanized coal mining in fully mechanized coal face [1,2]. It is a continuous conveying machine with a flexible body used in longwall mining face [3][4][5].…”

Section: Introductionmentioning

confidence: 99%

Discrete Element Method‐ (DEM‐) Based Study on the Wear Mechanism and Wear Regularity in Scraper Conveyor Chutes

Xia

Wang

et al. 2019

Mathematical Problems in Engineering

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The scraper conveyor is the key conveying equipment for fully mechanized coal mining. Wear failure of the chute is the main form of failure of the scraper conveyor. In this study, the discrete element method (DEM) was combined with the wear model. The wear mechanism and wear regularity of the chute were explored by tracking the changes in the position of coal particles during the wear process. After the validation of wear simulation, a wear test of coal for different intrinsic parameters was designed. In one wear cycle, the three-body wear was about 32.84 times that of the two-body wear. In the research range, the wear of the scraper conveyor chute increased with the increase of Poisson’s ratio, shear modulus, and density of the coal. The shear modulus showed remarkable effect on the wear of the chute, followed by Poisson’s ratio and density. There existed a linear relationship between the shear modulus and wear (R2 = 0.8232). This study is expected to be used to predict the wear of the scraper conveyor chute and provide a theoretical basis for the applicability of the chute in different mines.

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“…In view of the special environment in coal mine, radio navigation [3], satellite positioning [4], and astronomical navigation [5] are typically rely on external reference information source so that their practical applications are restricted [6]. The positioning technology of the shearer based on inertial navigation is an autonomous navigation system which neither requires external information nor radiates external energy; therefore, strap-down inertial navigation system (SINS) is more applicable to navigating and localizing the shearer in the coal mine environment [7,8]. SINS can track the position and orientation of the movement of the carrier in real time based on the accelerometer and gyroscope inherent in SINS.…”

Section: Introductionmentioning

confidence: 99%

An Improved Strong Tracking Kalman Filter Algorithm for the Initial Alignment of the Shearer

et al. 2019

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The strap-down inertial navigation system (SINS) is a commonly used sensor for autonomous underground navigation, which can be used for shearer positioning under a coal mine. During the process of initial alignment, inaccurate or time-varying noise covariance matrices will significantly degrade the accuracy of the initial alignment of the shearer. To overcome the performance degradation of the existing initial alignment algorithm under complex underground environment, a novel adaptive filtering algorithm is proposed by the integration of the strong tracking Kalman filter and the sequential filter for the initial alignment of the shearer with complex underground environment. Compared with the traditional multiple fading factor strong tracking Kalman filter (MSTKF) method, the proposed MSTSKF algorithm integrates the advantage of strong tracking Kalman filter and sequential filter, and multiple fading factor and forgetting factor for east and north velocity measurement are designed in the algorithm, respectively, which can effectively weaken the coupling relationship between the different states and increase strong robustness against process uncertainties. The simulation and experiment results show that the proposed MSTSKF method has better initial alignment accuracy and robustness than existing strong tracking Kalman filter algorithm.

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A Joint Positioning and Attitude Solving Method for Shearer and Scraper Conveyor under Complex Conditions

Cited by 24 publications

References 10 publications

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

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

Discrete Element Method‐ (DEM‐) Based Study on the Wear Mechanism and Wear Regularity in Scraper Conveyor Chutes

An Improved Strong Tracking Kalman Filter Algorithm for the Initial Alignment of the Shearer

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