工矿自动化

Research and application of intelligent early warning system for coal mine fires

LIU Dongyang, ZHANG Lang, YAO Haifei, XU Changfu, ZHAO Youxin, ZHANG Yibin, DUAN Sigong

2024, 50(1): 1-8, 16. doi: 10.13272/j.issn.1671-251x.2023070092

<Abstract>(859) <HTML> (377) <PDF>(137)

Abstract:
Currently, the coal mine fire monitoring system has achieved separate monitoring of some indicators such as the iconic gases, temperature, smoke, and flame of coal spontaneous combustion in mines.But the system has not effectively, comprehensively, and uniformly monitored the factors related to coal mine fires. In order to solve this problem, potential risk factors of coal mine fires are analyzed from two aspects: internal and external factors. A method of monitoring fire situation in different sources and areas is proposed. In terms of internal fires, monitoring is mainly carried out on goaf areas, enclosed goaf areas, and artificial natural fire observation points that are prone to fires. In terms of external fires, monitoring is mainly carried out on the mechanical and electrical chambers and their distribution points, belt conveyor systems, cables, and other aspects. A monitoring index system for coal mine fire sources and areas has been established. The system regularly collects or updates fire feature parameter data through manual or online monitoring. According to the data collection method and impact degree, fire monitoring indicators are divided into dynamic indicators, static indicators, and related indicators. The overall architecture and business process of a fire intelligent warning system is designed. The system uses a warning method based on multi index joint logical reasoning to achieve internal fire warning, and uses a multi parameter fusion warning method based on D-S evidence theory to achieve external fire warning. The on-site test results show that the fire intelligent warning system has achieved effective monitoring and warning of mine fires, with a visual display function of a coal mine fire risk warning "one picture". The system has a fire intelligent simulation demonstration function and a dynamic planning function for disaster avoidance routes.

Automatic height adjustment technology of shearer based on cutting roof and floor height prediction model

LI Zhongzhong, LIU Qing

2024, 50(1): 9-16. doi: 10.13272/j.issn.1671-251x.2023060044

<Abstract>(477) <HTML> (50) <PDF>(30)

Abstract:
The traditional coal seam cutting path planning predicts the height of the drum through geometric control, planning calculation, and other methods. But there are problems with large data errors in planning and prediction and inability to adapt to changes in geological conditions. In order to solve the above problems, a shearer automatic height adjustment technology based on a cutting roof and floor height prediction model is proposed. Firstly, the factors affecting the height of the cutting roof and floor are analyzed. It is pointed out that the main factors affecting the height of the cutting roof and floor include the fluctuation data of the coal seam, historical cutting data, elevation data of the scraper conveyor, and manual operation records. The above four types of data are fused and processed to establish a cutting roof and floor height prediction algorithm model based on long short term memory (LSTM) model and gray Markov model. The height of the cutting roof and floor is predicted through an algorithmic model. Secondly, based on the height data of the cutting roof and floor, combined with the position and posture and spatial coordinates of the shearer, a geometric model for calculating the height of the drum is established. At the same time, correction is made according to factors such as the sliding amount of the scraper conveyor and whether the addition and subtraction process is carried out. Finally, the height sequence of the roof and floor is converted into a drum height sequence. The cutting roof and floor height is converted into the target height of the shearer drum, which is executed by the shearer to the target height, achieving automatic adjustment of the drum height. The industrial test results show the following points. ① Under the control of automatic height adjustment technology, 90% of the predicted height deviation values of the roof and floor drums are within 10 cm of the actual height. The predicted height of the drums is significantly consistent with the actual height. ② Compared with traditional manual control methods, the number of manual intervention height adjustment times for cutting coal in the middle has decreased from 49 to 21. It indicates that the height prediction model for cutting the roof and floor and the geometric model for calculating the height of the drum are accurate and reasonable, and the automatic height adjustment technology for the shearer drum is feasible.

A coal mine data acquisition, fusion and sharing system based on object model

SHANG Weidong, WANG Haili, ZHANG Xiaoxia, WANG Hao, XU Hualong

2024, 50(1): 17-24, 34. doi: 10.13272/j.issn.1671-251x.2023070047

<Abstract>(192) <HTML> (48) <PDF>(63)

Abstract:
In current coal mine data acquisition, fusion, and sharing, there are problems of lack of standardization and semantic inconsistency in device attributes, inability to cross operating systems in data acquisition protocols, poor real-time data access, and low data sharing efficiency. In order to solve the above problems, a coal mine data acquisition, fusion, and sharing system based on object model is designed. On the basis of the coding standard for coal mine data based on tag numbers, a device object model is designed to overcome the problems of lack of standardization of device attributes and semantic inconsistency in device attributes. By using industrial protocol acquisition, Restful API Q&A acquisition, and file data acquisition methods for data access, it can support domestic operating systems and provide convenient message monitoring tools to accurately determine the cause of communication abnormalities. The model implements data fusion through device object model mapping, introduces data governance mechanisms to ensure data accuracy and consistency, and stores data in the form of object models to save storage space and improve storage efficiency. The model stores all device object data in one table. The object-oriented data sharing interface can be simplified into real-time data sharing interface and historical data sharing interface, reducing redundant interfaces and thus reducing data access times. The application results show that the system reduces the difficulty of semantic parsing during data usage after standardizing device data. The system improves the performance of data computation, storage, and access, providing guarantees for big data analysis.

Underground personnel positioning system based on 5G+UWB and inertial navigation technology

LI Mingfeng, LI Yan, LIU Yong, WU Xuesong, XU Jisheng, CHANG Jianming, WANG Tao, PAN Hongguang

2024, 50(1): 25-34. doi: 10.13272/j.issn.1671-251x.2023100066

<Abstract>(709) <HTML> (191) <PDF>(89)

Abstract:
In practical applications of coal mine personnel positioning systems, there are problems of insufficient equipment computing power and storage resources. The problems result in preventing the use of complex ranging and positioning algorithms, inadequate real-time transmission and response performance of positioning data, and significant human and material resource losses in system deployment. In order to solve the above problems, a new underground personnel positioning system based on 5G+UWB and inertial navigation technology is proposed. The system deploys UWB positioning base stations with low energy consumption and strong anti-interference capability at the end. The positioning base station is connected to the 5G base station in a cascaded manner. The positioning base station collects UWB and inertial navigation data, and uses the 5G network to transmit it back to the computing platform. The positioning information is solved and stored on the computing platform. The inertial navigation based personnel position estimation is used as the predicted value. The UWB based trilateral positioning algorithm is used to obtain personnel position estimation as the observed value. The Kalman filter is used to fuse the predicted and observed values to reduce positioning errors. The testing system is built at the main experimental base of the coal mine, simulating the real underground environment of the coal mine, and conducting comparative experiments. The results show the following points. ①In the x-axis direction and the y-axis direction, the coincidence degree between the position information obtained by the Kalman filter algorithm of the fusion inertial navigation and the real position information is the highest, indicating that the position information obtained by the Kalman filter algorithm of the fusion inertial navigation is closest to the real position, and the average error is 22.192 cm. ② The position information of the underground personnel positioning system combined with 5G + UWB and inertial navigation technology has the highest coincidence degree with the real position information, and the error is [15 cm, 20 cm], with a maximum average error of 26 cm on the x-axis and 24 cm on the y-axis, exceeding the precision of most current underground personnel positioning systems.

Hydraulic fracturing and punching integration enhanced permeability gas extraction technology

WANG Baogui

2024, 50(1): 35-41. doi: 10.13272/j.issn.1671-251x.2023050014

<Abstract>(166) <HTML> (41) <PDF>(20)

Abstract:
The existing hydraulic fracturing, hydraulic punching, hydraulic slotting, hydraulic cutting and other underground hydraulic permeability enhancement technologies in coal mines have complex processes, single adaptability conditions, and high labor intensity. However, drilling and punching integration, drilling and expansion integration, hydraulic punching/fracturing integration and other technologies are not ideal for enhancing the permeability of hard coal. There are problems such as cumbersome processes and inability to operate continuously. In order to solve the above problems, a hydraulic fracturing and punching integration enhanced permeability gas extraction technology is proposed. During the drilling process, high-pressure water jet is used to perform hydraulic enhanced permeability operations on coal seams at fixed points (directional, segmented). It can achieve integrated drilling, hydraulic punching of soft coal, and hydraulic injection fracturing of hard coal. The study reveals the principle of hydraulic fracturing and punching integration permeability enhancement. The hydraulic punching is used to flush out part of the coal body in soft coal seams, achieving pressure relief and permeability enhancement of soft coal seams. The fixed-point hydraulic jet fracturing is performed on hard coal seams, achieving fracture formation and permeability enhancement in hard coal seams. The drilling tool of hydraulic fracturing and punching integration is developed to meet the requirements of high pump pressure and large displacement. The drilling tool has strong rock breaking and chip removal capabilities. The process is simple and controllable. The drilling tool control methods for high-pressure water jet punching and hydraulic jet fracturing are provided. The stamping process during drilling and stamping process during drill withdrawal are discussed. The on site engineering tests are conducted using fracturing and punching integration drilling tools in the 16101 bottom drainage roadway of a coal mine. The results show that hydraulic punching operation in the soft coal section shortens the time by 60% to 80% compared to traditional hydraulic punching. The coal output from a single hole increases by about 2 times, and the average gas extraction purity per 100 meters per hole increases by 1 time. The hydraulic jet fracturing operation is carried out in the hard coal section. The average gas extraction purity per 100 meters per hole increases by 2 times compared to traditional hydraulic punching.

Research progress on coal rock recognition technology based on electromagnetic waves

LIU Yuan, SI Lei, WANG Zhongbin, WEI Dong, GU Jinheng

2024, 50(1): 42-48, 65. doi: 10.13272/j.issn.1671-251x.2023070095

<Abstract>(255) <HTML> (42) <PDF>(40)

Abstract:
Applying electromagnetic waves to coal rock recognition can effectively improve the resolution capability of coal rock interfaces. Based on the coal rock interface model, the principle of using electromagnetic wave technology for coal rock recognition is explained. The paper introduces six methods for coal rock recognition, including γ–ray method, radar detection method, Terahertz signal method, electron resonance method, X-ray method, and infrared thermal imaging method. The principles of each method are analyzed, and the advantages and disadvantages of each method are compared as well as their applicability in coal mines underground. The research status of each method is analyzed in combination with practical industrial applications. The γ–ray method has significant advantages in detection distance, but it has radiation problems. It is basically eliminated. The radar detection method has the advantage of accurate recognition, but due to its severe signal attenuation and short detection distance, it is currently generally used for thickness measurement in thin coal seams. The Terahertz signal method has a short detection distance and can only be applied when the composition of the underground environment is stable. The electronic resonance method has severe signal attenuation, short detection distance, and high difficulty. It is currently basically abandoned in mines. The X-ray method has strong penetration and clear imaging, but it poses great harm. In the infrared thermal imaging method, the active infrared excitation method requires a lot of time to excite coal and rock, and there are significant safety hazards in high gas mine environments. Although the cutting flash temperature method takes a short time, it is difficult to achieve effective coal rock recognition for situations with multiple cutting teeth and complex layout. It is pointed out that the accuracy of electromagnetic wave coal rock recognition is determined by the echo information of electromagnetic waves, and further in-depth exploration should be carried out.

A multi-target road detection model in a low-light environment in an open-pit mining area based on hyperbolic embedding

GU Qinghua, SU Cunling, WANG Qian, CHEN Lu, XIONG Naixue

2024, 50(1): 49-56, 114. doi: 10.13272/j.issn.1671-251x.2023060021

<Abstract>(166) <HTML> (77) <PDF>(54)

Abstract:
The environment of open-pit mines is distinctive, and the conditions of the roads in them are complex and constantly changing. Insufficient lighting in the area being mined can make it challenging to identify and position multiple targets on the roads. This, in turn, affects the results of detection and poses serious risks to the safe operation of uncrewed mining trucks.Currently available models to identify obstacles on roads cannot accommodate the impact of poor lighting, and thus, yield inaccurate results. They also have significant shortcomings in identifying small obstacles in the mining area. In this study, we develop a multi-target model of detection for the dark/light environment of an open-pit mine using hyperbolic embedding to address the above-mentioned issues. We introduce the Retinex-Net convolutional neural network to the image preprocessing stage of the detection model to enhance dark images and improve their clarity. To address the issue of an excessively large number of features in the dataset without a clear preference for focus, we incorporate the global attention mechanism into the improved process of feature extraction. This enabled the collection of critical feature-related information in three dimensions. Finally, we incorporate a fully connected hyperbolic layer into the prediction stage of the model to minimize feature loss and prevent overfitting. The results of experiments to verify the proposed model showed that ① it could reliably classify and accurately identify large-scale targets in the low-light environment of the open-pit mining area, and was able to highly accurately identify mining trucks and small vehicles over long distances. It could also accurately identify and locate scaled targets, including pedestrians, such that this satisfies meeting the safety-related requirements of uncrewed mining trucks operating in diverse environments.② The model achieved an accuracy of detection of 98.6% while maintaining a speed of 51.52 frames/s, where this was 20.31%, 18.51%, 10.53%, 8.39%, and 13.24% higher than the accuracies of the SSD, YOLOv4, YOLOv5, YOLOx, and YOLOv7, respectively. Its accuracy of detection of pedestrians, mining trucks, and excavators on mining roads exceeded 97%.

A coal foreign object detection method based on cross modal attention fusion

CAO Xiangang, LI Hu, WANG Peng, WU Xudong, XIANG Jingfang, DING Wentao

2024, 50(1): 57-65. doi: 10.13272/j.issn.1671-251x.2023110035

<Abstract>(658) <HTML> (49) <PDF>(61)

Abstract:
The RGB image of coal foreign objects lacks target space and edge information, the color and texture between the object to be detected and the background are similar, the contrast is low, and there are overlapping and occlusion phenomena among the objects to be detected, resulting in insufficient feature extraction of coal foreign objects, and the existing foreign object detection methods are difficult to achieve ideal results. In order to solve the above problems, a coal foreign object detection method based on cross modal attention fusion is proposed. By introducing Depth images to construct a dual feature pyramid network (DFPN) for RGB images and Depth images, a shallow feature extraction strategy is adopted to extract low-level features of Depth images. Basic features such as deep edges and deep textures are used to assist deep features of RGB images, effectively obtaining complementary information between the two features. It thereby enriches the spatial and edge information of foreign object features and improves detection precision. A cross modal attention fusion module (CAFM) based on coordinate attention and improved spatial attention is constructed to synergistically optimize and fuse RGB features and Depth features. It enhances the network's attention to the visible parts of occluded foreign objects in the feature map, and improves the precision of occluded foreign object detection. Finally, regional convolutional neural network (R-CNN) is used to output the classification, regression, and segmentation results of coal foreign objects. The experimental results show that in terms of detection precision, the average segmentation precision AP of the proposed method is 3.9% higher than the better Mask transformer in the two-stage model. In terms of detection efficiency, the proposed method has a single frame detection time of 110.5 ms, which can meet the real-time requirements of foreign object detection. The coal foreign object detection method based on cross modal attention fusion can assist color, shape, and texture features with spatial features. It accurately recognizes the differences between coal foreign objects and between coal foreign objects and conveyor belts, effectively improves the detection precision of complex feature foreign objects. It reduces false alarms and missed detections, and achieves precise detection and pixel level segmentation of coal foreign objects under complex features.

Coal gangue recognition method based on water heat transfer and infrared thermal imaging

CHENG Gang, CHEN Jie, PAN Zeye, WEI Yifan, CHEN Sensen

2024, 50(1): 66-71, 137. doi: 10.13272/j.issn.1671-251x.2023050056

<Abstract>(296) <HTML> (70) <PDF>(61)

Abstract:
The coal gangue recognition method based on visible light images has low accuracy and slow recognition speed. The coal gangue recognition method based on high-energy ray transmission has significant radiation, resulting in limited application. The infrared thermal imaging has advantages such as strong penetration and no influence from light. But the surface temperature of coal and gangue is relatively close at room temperature, resulting in no significant difference between coal and gangue in infrared thermal images, making it difficult to achieve good recognition results. In order to solve the above problems, a coal gangue recognition method based on water heat transfer and infrared thermal imaging is proposed. The method conducts infrared thermal imaging experiments on coal and gangue under different water temperatures (18, 21, 24, 27, 30 ℃). The method distinguishes between coal and gangue based on the differences in infrared thermal images and temperature changes. The experimental results show that the infrared thermal images of coal and gangue are different at different water temperatures. When the water temperature is lower than the ambient temperature, there is a significant difference between the infrared thermal images of coal and gangue. Under the same water temperature conditions, the difference between the infrared thermal images of coal and gangue gradually increases with time. The surface temperature changes of coal and gangue both show an increasing trend with the increase of water temperature and time. But the surface temperature changes of gangue are greater than those of coal. When the water temperature is 18℃ and the time is 180 s, the difference and temperature difference between the infrared thermal images of coal and gangue reach their maximum. This indicates that low-temperature water can serve as a heat transfer medium, which is more conducive to creating a large temperature difference between coal and gangue. The accurate and rapid recognition of coal and gangue infrared thermal images can be achieved.

Factors influencing the dust-blocking effect of air curtains during the fully mechanized excavation of working faces

XIA Dingchao, LYU Pin, DU Peng, WANG Jinyue

2024, 50(1): 72-79. doi: 10.13272/j.issn.1671-251x.2023060007

<Abstract>(248) <HTML> (74) <PDF>(44)

Abstract:
Prevalent research on dust pollution during fully mechanized excavation has mainly focused on the impact of individual factors on the effectiveness of air curtains in fully mechanized excavation sites. However, scant research has been devoted to the interaction between factors, because of which pressure-induced air diversion technology has not been adequately applied to this context.To investigate the impact of the radial distance of the outlet of air, the ratio of this outlet, and the distance between the outlet and the wall-coated air duct on the effectiveness of dust blocking by air curtains, the authors of this study consider the excavation of the working face of the 810 west wing machine tunnel at the Pansan Mine . We used Fluent software to numerically simulate the distribution of wind flow and the diffusion of dust under a distance of the radial outlet of air of 10-25 m, a ratio of the outlet of 0.6-0.9, and an axial distance of the outlet of 6-12 m.The results showed that: ① As the distance of the radial outlet of air increased, the radial vortex air curtain transforms more fully in the tunnel . The wind flow at the front end of the excavation operator was more evenly distributed, and the wind speed was directed toward the working face such that this was more conducive to the formation of an axial dust-blocking air curtain.When the radial distance of the outlet of air was 10 m, vortical characteristics became apparent within a distance of 7 m from the working surface, and the direction of wind became disordered. When the radial distance of the air outlet was 25 m, the wind flow tended to be uniform within 7 m of the working surface, and its direction was evenly distributed toward the working surface. This led to the formation of an axial dust-blocking wind curtain that could cover the entire section.② As the ratio of the radial outlet of air increased, the volume of axial airflow of the rectifier air cylinder decreased to reduce the velocity of axial airflow and the intensity of the jet. This in turn reduced the disturbance caused by the axial airflow to that at the top of the mechanized working face that was being excavated. A higher ratio of the radial outlet of air was more conducive to the formation of an axial dust-blocking flow field, with the wind directed toward the working surface and covering the entire section. This led to an axial dust-blocking air curtain. ③ The dust-blocking ability of the radial vortical air curtain initially increased and then decreased as the ratio of the radial outlet of air increased. Its ability then continued to improve as the ratio was further increased. ④ We implemented the dust-control technology based on the air curtain with forced ventilation-induced diversion. When the pressure-induced volume of air was 300 m³/min and the volume of air suction was 400 m³/min, the distance between the radial outlet of air and the attached wall of the air duct was 20 m. The ratio of the radial outlet of air, and the distance between this outlet and the air duct of the rectifier was 8-10 m. The air curtain was able to collect dust near the port of the dust suction for efficient dust control and removal.We conducted an on-site test of the fully mechanized excavation working face of the 810 west wing machine tunnel. The empirically measured data of wind speed and dust mass concentration at measuring points and the results of numerical simulations were consistent with each other. Highly concentrated dust was blocked at the front end of the working face, and its isolation was noticeable. This confirms the effectiveness of the numerical simulations.

Research on dust reduction technology of air chamber in fully mechanized mining face

ZHANG Jingzhao, SU Huidong, YAN Zhenguo, MA Wenjie, XIONG Shuai, ZHANG Chenyu

2024, 50(1): 80-87. doi: 10.13272/j.issn.1671-251x.2023060062

<Abstract>(152) <HTML> (69) <PDF>(10)

Abstract:
In response to the dust control problem in excavation roadways, the traditional long pressure short suction ventilation dust reduction technology has problems such as large dust diffusion areas and easy blockage of jet holes in the air curtain dust reduction technology. Taking the Balasu Coal Mine fully mechanized mining face as the engineering research background, a mathematical model of dust movement during the excavation process is established. It is found that the key factors to reduce the dust concentration in the fully mechanized mining face are to control the disturbance range of the wind flow field in the excavation roadway and reduce the movement time of dust particles. Based on the above key factors, an air chamber dust reduction technology has been developed on the basis of air curtain dust reduction. By installing air sleeves at the end of the positive pressure air duct and working together with the air curtain, the dust is enclosed in the air chamber area. The dust is extracted by a negative pressure fan to improve dust reduction efficiency. Fluent software is used to simulate and compare the dust reduction of long pressure short suction ventilation, air curtain, and air chamber. The technical parameters of air chamber dust reduction are optimized. The simulation results show that when using the air chamber dust reduction technology, the dust concentration at the breathing zone of the human body in the fully mechanized mining face is 350 mg/m³. It is significantly lower than the 600 mg/m³ when using long pressure and short suction ventilation for dust reduction and the 480 mg/m³ when using air curtain dust reduction. The optimal technical parameters for air chamber dust reduction are a positive pressure air duct 14 meters away from the excavation face and a negative pressure air duct end diameter of 0.6 meters. On site experiments are conducted on the fully mechanized mining face of the second coal seam and second return air roadway in Balasu Coal Mine. The results showed that when using air chamber dust reduction, the minimum dust concentration in the excavation roadway is 118 mg/m³. It is better than the 184 mg/m³ when using long pressure short suction ventilation and 156 mg/m³ when using air curtain dust reduction. The dust reduction efficiency is also improved by an average of 54.8% compared to long pressure short suction ventilation for dust reduction.

A method for constructing a knowledge graph of unsafe behaviors in coal mines

FU Yan, LIU Zhihao, YE Ou

2024, 50(1): 88-95. doi: 10.13272/j.issn.1671-251x.2023060014

<Abstract>(779) <HTML> (99) <PDF>(102)

Abstract:
Although knowledge graphs have been widely applied in various fields, there is relatively little research on coal mine safety, especially in the area of unsafe behavior underground. A bottom-up knowledge graph of unsafe behaviors in coal mines has been constructed. Firstly, a combination of traditional machine learning and deep learning algorithms is used for named entity recognition. RoBERTa is used for word vectorization. The bidirectional long short term memory network (BiLSTM) is used to annotate the vectors, improving the network model's capability to capture contextual features. To solve the problem of insufficient data volume in the dataset of unsafe behaviors in coal mines, a multi-layer perceptron (MLP) is used. The conditional random field (CRF) model is adopted to solve the problem of unrecognized word relationships and capture full-text information and prediction results. Secondly, based on the structural characteristics of the statements, a dependency syntax tree structure based on the knowledge "entity - relationship - entity" triplet is designed to extract and represent knowledge resources in the field of unsafe behavior underground. Finally, a knowledge graph of unsafe behaviors underground is constructed. The experimental results show that the RoBERTa-BiLSTM-MLP-CRF model has good recognition performance for four types of entity categories: results, violating behavior, erroneous behavior, and careless behavior, with accuracy rates of 86.7%, 80.3%, 80.7%, and 77.4%, respectively. ② Under the same dataset, the accuracy, recall, and F₁ value of the RoBERTa-BiLSTM-MLP-CRF model training are improved by 1.6%, 1.5%, and 1.6%, respectively, compared to the RoBERTa-BiLSTM-CRF model.

A fault diagnosis method for mine rolling bearings based on deep learning

DOU Guidong, BAI Yishuo, WANG Junli, HUANG Bohao, YANG Kang

2024, 50(1): 96-103, 154. doi: 10.13272/j.issn.1671-251x.2023070085

<Abstract>(731) <HTML> (73) <PDF>(100)

Abstract:
A fault diagnosis method for mine rolling bearings based on Markov transition field(MTF) and dual-channel multi-scale convolutional capsule network (DMCCN) is proposed to address the problem of traditional convolutional neural networks being unable to fully explore data features in complex environments such as coal mines. The MTF-DMCCN fault diagnosis model is constructed. After encoding the original vibration signal based on MTF and grayscale image, a dual channel input mode is used to connect the convolutional network to obtain shallow features. The method inputs the feature maps fusion into the capsule network to improve the sensitivity of the model to spatial information. The method introduces Inception modules into the network to focus on multi-scale features and enhance the network's feature extraction capabilities. Finally, vectorization processing is carried out through the capsule layer to achieve fault diagnosis and classification of rolling bearings. The results of ablation, noise resistance, and generalization experiments show that the Inception module, grayscale image input, and MTF image input all have a positive promoting effect on bearing fault diagnosis. MTF coding has the highest improvement in diagnostic precision of the model. The MTF-DMCCN model has good robustness and noise resistance. The MTF-DMCCN model has excellent adaptability to variable speed and still exhibits good generalization performance under different operating conditions. To further validate the performance of the model, image encoding methods such as Gram angle difference field (GADF), Gram angle sum field (GASF), grayscale image, and MTF are selected and combined with different networks. Comparative experiments are conducted using the University of Cincinnati intelligent maintenance system (IMS). The results show that the MTF-DMCCN model can effectively recognize the type of rolling bearing faults, with an average fault diagnosis accuracy of 99.37%.

Analysis of attitude adjustment for airborne drilling rig of anchor excavator

WU Di, FU Baoding, SUN Bo, KANG Le, LIU Zhixiang, ZOU Kang

2024, 50(1): 104-114. doi: 10.13272/j.issn.1671-251x.2023060016

<Abstract>(128) <HTML> (53) <PDF>(6)

Abstract:
The deployment of the front drilling rig requires a significant amount of time before and after water exploration and drainage operations. Loading advanced drilling equipment on the anchor excavator can reduce equipment deployment time and improve drilling efficiency. At present, research on anchor excavator units that integrate excavation, anchoring, and exploration mostly focuses on the structural design of equipment and the design of hydraulic control systems. There is relatively little research on the interference features between different structures. The paper analyzes the interference situation during the attitude adjustment process of the airborne drilling rig. A mathematical model for the interference between the anchor excavator and the airborne drilling rig is established based on the geometric position relationship during the attitude adjustment. The formula for calculating the maximum rotation angle is derived when the anchor excavator interferes with the airborne drilling rig. The maximum angle of interference between the anchor excavator and the airborne drilling rig is taken as the indicator. The influence of various size parameters of the anchor excavator and airborne drilling rig on the maximum angle of the airborne drilling rig in various directions is studied. The results show the following points. ① The larger the inclination angle of the anchor excavator keel, the greater the pitch adjustment angle of the airborne drilling rig. By adjusting the inclination angle of anchor excavator keel, the adjustment range of the elevation angle during the operation of the water exploration drilling rig can be effectively changed. ② The variation of the keel height has little effect on the pitch angle. The variation of the keel height does not affect the variation of the pitch angle, but has a greater impact on the pitch angle, which is proportional. The increase in the length of the keel connecting the twisted ear to the tail of the keel increases the pitch angle, but the effect on the pitch angle is not significant. To change the elevation angle, the value of the keel height can be changed firstly. To change the depression angle, the value of the length of the keel connecting the hinge to the tail of the keel can be changed firstly. ③ When the spacing between the anchor excavator keel protection plates is larger, the maximum horizontal rotation angle of the airborne drilling rig is larger. When it increases to a certain extent, the maximum horizontal rotation angle is no longer affected by the increase in spacing between the anchor excavator keel protection plates. When the distance between the keel protection plates of the anchor excavator is greater than a certain value, the larger the center distance of the support oil cylinder of the anchor excavator, the greater the maximum horizontal rotation angle of the airborne drilling rig. The influence of the spacing between the keel protection plates of the anchor excavator on the maximum horizontal rotation angle of the airborne drilling rig is greater than the center distance of the support oil cylinder of the anchor excavator. ④ When the width of the rear end of the airborne drilling bit is small, it does not affect the maximum horizontal angle. When the width of the rear end of the airborne drilling bit increases to a certain value, the larger the width of the rear end of the airborne drilling bit, the smaller the maximum horizontal angle. When the width of the rear end of the airborne drilling bit is less than a certain value, the larger the width of the front end of the airborne drilling bit, the smaller the maximum horizontal angle. The example verification results show that increasing the inclination angle of the keel, the height of the keel connecting bolts, the height of the keel, and the length of the keel connecting ear to the tail of the keel, while reducing the height difference between the upper edge of the drill bit and the connecting ear of the drill frame, and the length of the keel upper protective plate, effectively increases the maximum pitch angle of the airborne drilling rig.

Trajectory planning and tracking control of a seven degree of freedom shotcrete robot in coal mine roadway

CHENG Huan, DENG Liying

2024, 50(1): 115-121. doi: 10.13272/j.issn.1671-251x.2023050057

<Abstract>(154) <HTML> (79) <PDF>(25)

Abstract:
During the construction process, the coal mine roadway shotcrete robot has the problems of discontinuous motions, large position errors, and low stability. In order to solve the above problems, a trajectory planning and tracking control method of a seven degree of freedom shotcrete robot in coal mine roadways is proposed. Based on the range of motion of the working arm when the shotcrete robot is stationary and the shotcrete length of the airbrush along the roadway direction, the roadway is divided into several sections to be sprayed. The robot's motion trajectory between each section and the motion trajectory of the working arm on each section are planned to ensure continuous action of the robot during the spraying process. A kinematic model of the shotcrete robot is established. Firstly, the robot's motion trajectory is planned using the cubic polynomial interpolation method. Secondly, the reference trajectory generated by the cubic polynomial interpolation is tracked and controlled using the model predictive control algorithm. It achieves precise and smooth motion of the robot in the roadway. A kinematic model of the working arm is established based on the standard D-H parameter method. The 3-5-3 section polynomial interpolation method is used to plan the motion trajectory of the robot's working arm on the section to be sprayed, so that the working arm has continuous acceleration during the spraying process. The simulation results show that the maximum position error of the shotcrete robot during its motion is 0.07 m, and the maximum directional angle error is only 0.99 rad. The overall motion speed is stable, and it can quickly return to a stable state after speed fluctuations, meeting the requirements of accurate and stable robot motion. During the motion of the working arm, the spraying trajectory, joint variable changes, joint velocity and acceleration curves are overall continuous and smooth, meeting the requirements of continuous and stable spraying actions.

Mine pipeline inspection robot design and traction performance analysis

ZHAO Pengyang, YAN Hongwei, ZHANG Dengxiao, XIAO Canjun, HE Bolong

2024, 50(1): 122-130, 162. doi: 10.13272/j.issn.1671-251x.2023040063

<Abstract>(462) <HTML> (56) <PDF>(24)

Abstract:
In response to the problem of gas extraction pipeline damage and leakage inspection, a spiral mine pipeline inspection robot with pipeline inspection and motion control functions is designed. The structure and inspection and control system scheme of the robot are introduced. A mechanical analysis model is established for the operation of robots in pipelines, and the factors affecting the robot's traction performance are studied through dynamic simulation. The results show that the traction force of the robot during operation in the pipeline is related to the pipeline material, spiral angle, and the normal force between the pipeline wall and the driving wheel. The optimal spiral angle for robots operating in pipelines of different materials is different. When operating in pipelines of the same material, the traction force is higher in the absence of medium transportation than in the presence of medium transportation. The traction force of the robot increases with the increase of normal force. But there is no significant change in the optimal spiral angle. As the spiral angle increases, the traction force first increases and then decreases, reaching its maximum at a spiral angle of 40°. To improve the performance of robots passing through curved pipes, a variable spiral angle bending strategy is proposed. The robot actively controls the spiral angle to change in a sinusoidal pattern with the rotation of the spiral motion unit, so that the spiral angle on the inner side of the pipeline is smaller than that on the outer side. A robot testing platform to test the mine pipeline inspection robot is established. The results show that the optimal spiral angle for the robot to operate in the straight pipe is 40°. The traction performance of the robot can be improved by increasing the normal force. When using the variable spiral angle bending strategy, the robot has better performance and stability in passing through curved pipes compared to fixed spiral angle bending.

A bottom air temperature prediction model based on PSO-Elman neural network

CHENG Lei, LI Zhengjian, SHI Haorong, WANG Xin

2024, 50(1): 131-137. doi: 10.13272/j.issn.1671-251x.2023090062

<Abstract>(118) <HTML> (30) <PDF>(18)

Abstract:
Currently, most underground wind temperature predictions use BP neural networks. But their prediction precision is affected by the number of learning samples and they are prone to falling into local optima. Elman neural networks have local memory capability, which improves the stability and dynamic adaptability of the network. However, there are still problems such as slow convergence speed and easy falling into local optima. In order to solve the above problems, the particle swarm optimization (PSO) algorithm is used to optimize the weights and thresholds of the Elman neural network. A bottom air temperature prediction model based on the PSO Elman neural network is established. The analysis shows that the relative humidity of the inlet and outlet wind, the surface inlet wind temperature, the surface atmospheric pressure, and the depth of the shaft are the main influencing factors of the bottom air temperature. Therefore, they are used as input data for the model, and the output data of the model is the bottom air temperature. The experimental results on the same sample dataset show that the Elman model converges at 90 iterations and the PSO Elman model converges at 41 iterations. It indicates that the PSO-Elman model converges faster. Compared with the BP neural network model, support vector regression (SVR) model, and Elman model, the prediction error of the PSO-Elman model is significantly reduced. The mean absolute error, mean square error (MSE), and mean absolute percentage error are 0.376 0 ℃, 0.278 3, and 1.95%, respectively. The determination coefficient R² is 0.992 4, which is very close to 1, indicating that the prediction model has good predictive performance. The verification results of the example show that the relative error range of the PSO-Elman model is −4.69%-1.27%, the absolute error range is −1.06-0.29 ℃, and the MSE is 0.26. The overall prediction precision can meet the actual needs of the underground.

Prediction of mine strata behaviors law and main control factors in the fully mechanized caving face of Hujiahe Coal Mine

XI Guojun, YU Zhimi, LI Liang, LI Xiaofei, DING Ziwei, LIU Jiang, ZHANG Chaofan

2024, 50(1): 138-146. doi: 10.13272/j.issn.1671-251x.2023070066

<Abstract>(112) <HTML> (68) <PDF>(11)

Abstract:
Among the existing prediction methods for strata behaviors law in working faces, the methods based on numerical simulation and statistical regression cannot achieve real-time and precise prediction of strata behaviors law in working faces. Deep learning methods have problems such as a large number of hyperparameters that are difficult to set and slow model training speed. In order to solve the above problems, based on the time-series data of internal stress changes in the coal body monitored during the mining process of the 402102 working face in Hujiahe Coal Mine, the particle swarm optimization based gate recurrent unit (PSO-GRU) is applied to predict the strata behaviors law in the working face. The PSO algorithm is used to optimize GRU. The PSO-GRU model is constructed to achieve automatic optimization of hyperparameters, thereby improving the training speed and prediction precision of GRU. Based on the prediction results, the analytic hierarchy process (AHP) is used to establish the evaluation index system of the main control factors of the strata behaviors of the 402102 mining face. The roof conditions, mining technology, coal seam occurrence, and geological structure are identified as the first level indicators affecting the strata behaviors of the working face. The 14 representative second level indicators are further subdivided. The test results show the following points. ① Compared with the unoptimized GRU model, the mean square error (MSE) of the PSO-GRU model is reduced by 83.9%, the root mean square error (RMSE) is reduced by 59.8%, the mean absolute error (MAE) is reduced by 59.0%, and the coefficient of determination R² is increased by 28.9%. ② The PSO-GRU model has a fitting degree of over 0.980 for predicting strata behaviors data, demonstrating good nonlinear fitting and generalization capabilities. ③ The occurrence factors of coal seams in geological conditions have the greatest impact on the strata behaviors of the mining face, with a weight of 0.47. Among the factors that can be intervened by humans, the impact of advancing speed on the strata behaviors of the working face is the greatest, with a weight of 0.13.

The influence of hard roof cutting and pressure relief technology on the deformation law of surrounding rock in roadways

ZHAO Changxin, LI Xiaoxu, SHI Meng, JI Ruifeng, ZHANG Yan

2024, 50(1): 147-154. doi: 10.13272/j.issn.1671-251x.2023030029

<Abstract>(115) <HTML> (43) <PDF>(18)

Abstract:
The goaf roadways have problems of high surrounding rock stress and large deformation under the conditions of hard roof and wide coal pillars in thick coal seams. In order to solve the above problems, this paper takes the 16403 fully mechanized mining face of Laoshidan Coal Mine as the engineering research background. The paper theoretically analyzes the influencing factors of large deformation of goaf roadways from the perspective of lateral fracture structure of wide coal pillar roof. The numerical simulation method is used to study the implementation of different roof cutting and pressure relief schemes for 16402 transportation roadway. The stress transmission law of the lateral roof of the 16403 return airway near the goaf during mining is studied. The hydraulic fracturing drilling is carried out on site for roof cutting and pressure relief to achieve deformation control of the surrounding rock of the goaf roadway. The research results indicate that the fracture structure of "cantilever beam in low hard rock layer+masonry beam in high hard rock layer" is the main reason for the large deformation of the wide coal pillar in the goaf roadway of the extra thick coal seam. The roof cutting and pressure relief technology can be used to destroy the lateral fracture structure of the wide coal pillar roof to control the large deformation of the surrounding rock in the goaf roadway. The change in roof cutting angle can cause a change in the length of key block B. The larger the roof cutting angle, the smaller the length of key block B. The degree of load transfer from the lateral roof of the goaf side to the coal pillar is weaker, and the mining stress borne by the surrounding rock of the goaf roadway is smaller. When the roof cutting angle is 100°, the vertical stress and deformation of the surrounding rock of the goaf roadway are the smallest. After hydraulic fracturing drilling is carried out at a roof cutting angle of 100° in the 16402 transportation roadway, the deformation of the roof and floor of the 16403 return air roadway is reduced by 86.5% compared to the 16402 return air roadway without roof cutting pressure relief. The deformation of the two sides is reduced by 87.1%. The stability of the surrounding rock of the goaf roadway is greatly improved.

Experimental study on the permeability features of long flame gas water phase

CHEN Gonghui, TANG Mingyun, NING Jiangqi, ZHANG Hailu

2024, 50(1): 155-162. doi: 10.13272/j.issn.1671-251x.2023070022

<Abstract>(91) <HTML> (21) <PDF>(8)

Abstract:
There is a large amount of CBM in the long flame coal. With the continuous increase of mining depth, it is necessary to explore the complex permeability features between CBM and groundwater in the coal reservoir to reduce the difficulty of CBM mining and improve the efficiency of CBM mining. Taking the long flame coal in the Weijiamao mining area of Zhungeer Banner, Ordos, Inner Mongolia as the experimental object, the TCXS-II coal rock gas water relative permeability tester is used to conduct the long flame gas water phase permeability experiment. The non steady state method is used to obtain the gas water phase permeability features of long flame coal under different effective stresses, pore pressures, and temperatures during the gas water drive process. The results show the following points. ① When the effective stress increases from 3.7 MPa to 7.7 MPa, the increase in gas phase relative permeability decreases, while the decrease in water phase relative permeability slightly increases. The increase of effective stress will have an inhibitory effect on the permeability of the fluid, and the inhibitory effect on water phase seepage is greater than that on gas phase seepage. The residual water saturation increases with the increase of effective stress. ② When the pore pressure increases from 2 MPa to 6 MPa, the decrease in the relative permeability curve of the water phase slows down, and the increase in the relative permeability curve of the gas phase becomes more obvious. The range of gas water co-permeation becomes wider, the saturation of the isotonic point increases, and the residual water saturation decreases. ③ When the temperature rises from 20 ℃ to 80 ℃, the increase in gas phase relative permeability and the decrease in water phase relative permeability gradually increase. The range of gas water co-permeation becomes wider, the residual water saturation shows a decreasing trend, and the gas phase permeability flow rate shows an increasing trend. The research results can provide theoretical basis and experimental reference for the research of CBM extraction technologies such as hydraulic fracturing and thermal injection in long flame coal reservoirs.

2024 Vol. 50, No. 1

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