A coal mining face advancing degree detection system and method

Abstract

The application discloses a kind of coal face advancing degree detection system and method, the method obtains push stroke detection device data;Firstly, the self-moving tail car is moved forward by the transfer machine;Processor corrects the actual advancing degree of working face according to the inclination sensor data, the self-moving tail car is moved forward secondly by the transfer machine, and the push stroke detection device data and inclination sensor data are sent to processor to calculate the second knife advancing degree of working face;The self-moving tail car is moved forward secondly by the transfer machine, and the push stroke detection device data and inclination sensor data are sent to processor to calculate the third knife advancing degree of working face;Self-moving tail rack is moved forward as a whole;After self-moving tail rack is moved forward as a whole, open new working face advancing cycle, and working face advancing degree data is continuously accumulated.The method can effectively correct the advancing degree measurement error caused by working face fluctuation, realize high-precision, automatic detection without cumulative error.

Description

Technical Field

[0001] This invention relates to the field of equipment status monitoring technology for underground coal mining faces, and particularly to a coal mining face advance detection system and method. Background Technology

[0002] Coal mining is the core process of coal mine production. The advance rate of a fully mechanized mining face is a key parameter for calculating coal mine output and determining the mining position, reflecting the speed of face advancement. Simultaneously, the advance rate is also fundamental data for mine pressure analysis of the fully mechanized mining face. By calculating the pressure step distance through the advance rate and the working face pressure analysis cycle, pressure can be predicted, and the face advancement control strategy can be adjusted in a timely manner, which is of great significance for the safe and efficient operation of the working face. Therefore, accurately obtaining the advance rate data of the fully mechanized mining face is crucial.

[0003] Currently, the progress of the working face is mainly obtained through manual measurement by the coal mine surveying department, a cumbersome and dangerous process. With the increasing prevalence of intelligent control systems for working faces, various manufacturers have designed different progress detection systems. For example, patent CN112593990A uses laser ranging between the hydraulic support and the scraper conveyor for detection; patent CN 114991843A uses a stroke sensor in the hydraulic support's pushing cylinder for detection; and patent CN 107905846B uses positioning base stations in the two roadways of the working face and positioning tags on the hydraulic support for detection. Existing detection methods mainly rely on indirect detection by measuring the distance of each advance of the working face, and lack consideration for the undulations of the working face, resulting in significant errors in progress detection. Summary of the Invention

[0004] The main objective of this invention is to provide a coal mining face advance detection system to solve the problems of low accuracy and large cumulative error in current face advance detection.

[0005] Another objective of this invention is to provide a method for detecting the advance rate of a coal mining face.

[0006] To achieve the above objectives, a first aspect of the present invention provides a coal mining face advance detection system, comprising an advance stroke detection device, an inclination sensor, and a processor, wherein, The pushing stroke detection device is installed at the tail of the self-moving machine on the working face; The tilt sensor is mounted on the tail frame of the self-propelled machine; The processor calculates the path segment of the working face for each advance based on the data collected by the push stroke detection device and the tilt angle sensor data, and then fits the working face advance curve to calculate the advance degree of the coal mining working face.

[0007] In one embodiment of the present invention, the pushing stroke detection device adopts a laser ranging system. A laser ranging sensor is installed on the working face side end of the self-moving machine tail self-moving trolley. The self-moving machine tail frame emits a laser and returns the ranging value after each working face advancement is completed.

[0008] In one embodiment of the present invention, a tilt sensor is installed on the tail frame of the self-propelled machine to detect the pitch angle of the tail frame in the working face advancing direction, and the detection is performed before each end support is pulled up.

[0009] To achieve the above objectives, a second aspect of the present invention provides a method for detecting the advance of a coal mining face, comprising: Step S1: Before the end support is advanced on the working face, acquire the data L0 from the pushing stroke detection device and the data α0 from the tilt sensor, and record them by the processor; Step S2: After the working face is advanced, the transfer machine drives the self-moving tail trolley to move forward for the first time, and sends the data L1 from the pushing stroke detection device and the data α1 from the tilt angle sensor to the processor; Step S3: The processor corrects the actual advance of the working face based on the tilt sensor data α1 using the following formula:

[0010] Step S4: After the working face is advanced for the second time, the transfer machine drives the self-moving tail carriage to move forward for the second time, and the data L2 of the pushing stroke detection device and the data α2 of the tilt angle sensor are obtained and sent to the processor to calculate the second cutting depth of the working face;

[0011] Step S5: After the third advancement of the working face, the transfer machine drives the self-moving tail carriage to move forward for the second time, and the data L3 of the pushing stroke detection device and the data α3 of the tilt angle sensor are obtained and sent to the processor to calculate the third cutting depth of the working face;

[0012] Step S6: After the third cutter advances on the working face, the self-moving machine tail frame moves forward as a whole. After completion, the data L0 of the pushing stroke detection device and the data α0 of the tilt angle sensor are acquired and recorded by the processor. Step S7: After the self-moving machine tail frame moves forward as a whole, start a new working face advance cycle and repeat steps S2 to S6. The working face advance data is continuously accumulated.

[0013] The coal mining face advance detection system and method of this invention can effectively correct the advance measurement error caused by the undulation of the working face, realize high-precision coal mining face advance detection without cumulative error, and improve the data reliability and security of intelligent coal mining. Attached Figure Description

[0014] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein: Figure 1 This is a structural diagram of a coal mining face advance detection system provided in an embodiment of the present invention; Figure 2 This is a schematic diagram of the sensor and processor arrangement of the automated control system for self-moving tail section provided in an embodiment of the present invention; Figure 3 A flowchart of a method for detecting the advance of a coal mining face provided in an embodiment of the present invention; Figure 4 A diagram showing the first cutter advance on the working face provided in an embodiment of the present invention; Figure 5 This is a diagram showing the advancement of the second cutter on the working face, provided in an embodiment of the present invention. Figure 6 This is a diagram showing the third cutter advancing on the working face, provided in an embodiment of the present invention. Figure 7 The computer device provided in the embodiments of the present invention.

[0015] Among them, 1-self-moving machine tail frame; 2-self-moving machine tail trolley; 3-transfer machine; 4-end bracket; 11-laser rangefinder sensor; 12-laser rangefinder reflector; 13-tilt sensor; 14-processor. Detailed Implementation

[0016] It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0017] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0018] A coal mining face advance detection system and method according to an embodiment of the present invention are described below with reference to the accompanying drawings.

[0019] This embodiment provides a coal mining face advance detection system. For example... Figure 1 and Figure 2 As shown, the system comprises a push stroke detection device, a tilt sensor, and a processor; wherein, The pushing stroke detection device is installed at the tail of the self-moving machine on the working face; The tilt sensor is mounted on the tail frame of the self-propelled machine; The processor calculates the path segment of the working face for each advance based on the data collected by the push stroke detection device and the tilt angle sensor data, and then fits the working face advance curve to calculate the advance degree of the coal mining working face.

[0020] Among them, such as Figure 1 As shown, 1 is the tail frame of the self-propelled machine; 2 is the tail trolley of the self-propelled machine; 3 is the transfer machine; and 4 is the end support.

[0021] Specifically, the displacement detection device is deployed between the moving parts and the fixed structure at the tail of the self-propelled machine on the working face, typically employing laser ranging technology for non-contact displacement monitoring. In practice, an industrial-grade laser ranging sensor is installed at the rigid end of the self-propelled tail trolley near the working face, and a high-reflectivity target is correspondingly placed at the tail of the frame. Each time the working face advances, the transfer conveyor pulls the trolley forward. The sensor measures the continuous change in the distance between the trolley and the tail of the frame to obtain raw displacement data, which is then transmitted to the processor in real time via a fieldbus. This device features automatic dust removal and vibration damping design, enabling stable operation in high-dust, high-vibration underground environments, with measurement accuracy down to the millimeter level.

[0022] Specifically, the tilt sensor is rigidly fixed to the center of the main beam of the self-propelled tail frame via a flange mounting base. Its sensitive axis is arranged along the working surface advancement direction to sense the pitch angle change of the frame relative to the horizontal reference plane in real time. During the static gap before each end support is pulled up, the sensor triggers sampling to acquire the frame's attitude angle data. This sensor has built-in temperature compensation and low-pass filtering functions, effectively suppressing mechanical vibration and electromagnetic interference. With an angular resolution of one-thousandth of a degree, it can accurately capture the frame tilt state caused by undulations in the working surface, providing key parameters for subsequent path correction.

[0023] Specifically, the processor is deployed within the explosion-proof electrical control box at the self-propelled tail section, responsible for receiving and fusing time-series data from two types of sensors. Its core logic involves correcting the original travel data based on the distance and angle changes before and after two adjacent advances using geometric projection relationships. This eliminates measurement errors caused by the slope of the base plate, allowing the processor to calculate the actual spatial displacement for each advance. The processor converts the single-step displacement into path segments with direction vectors, accumulating them sequentially to form a discrete trajectory point set. Then, cubic spline interpolation or Kalman filtering algorithms are used to smooth the point set, ultimately fitting a continuous working face advance curve. The system incorporates a circular queue storage structure, automatically recognizing the "three-cut, one-cycle" operation mode. It resets the baseline data after each overall frame advance, preventing error accumulation and achieving long-term accurate measurement and real-time uploading of the advance progress.

[0024] It is known that this system acquires real-time data on the propulsion stroke and spatial attitude of the self-propelled machine tail through coupled sensing of laser ranging and tilt monitoring. The processor automatically calculates and eliminates measurement errors caused by the pitch and tilt of the machine body, accurately fits the actual advance curve of the working face and dynamically calculates the advance rate, realizing the automation, continuity and high precision of advance rate monitoring. It eliminates the need for manual entry into dangerous areas for measurement, and provides reliable real-time data support for optimizing working face support parameters, analyzing the manifestation law of mine pressure and dynamically adjusting mining plans. It significantly improves the intelligent management level and safety production guarantee capability of fully mechanized mining faces.

[0025] In one embodiment of the present invention, the pushing stroke detection device adopts a laser ranging system. A laser ranging sensor is installed on the working surface side end of the self-moving machine tail self-moving trolley. The self-moving machine tail frame emits a laser and returns the ranging value after each working surface advancement is completed.

[0026] Specifically, the pushing stroke detection device adopts a laser ranging system, configured as follows: a laser ranging sensor is rigidly installed on the working face side end of the self-propelled tail carriage, with the sensor's emitting end facing the end support; the corresponding laser ranging reflector is fixedly installed on a relatively stationary component such as the top beam or base of the end support, forming a non-contact measurement reference. After each working face advancement operation is completed and the transfer machine drives the self-propelled tail carriage to complete its forward movement, the laser ranging sensor emits a laser beam towards the reflector and receives the echo signal, returning the current ranging value L in real time. n This distance measurement value represents the absolute displacement of the self-propelled tail trolley relative to the end support reference, serving as the raw data input for subsequent advance calculation. A line-of-sight optical path is maintained between the laser rangefinder and the reflecting device. Its measurement range covers the maximum single advance step distance (0.8~1.2m) and the cumulative adjustment range, with measurement accuracy controlled within ±5mm to ensure that the accuracy requirements for advance calculation are met.

[0027] In one embodiment of the present invention, a tilt sensor is installed on the tail frame of the self-propelled machine to detect the pitch angle of the tail frame in the working face advancing direction, and the detection is performed before each end support is pulled up.

[0028] Specifically, the tilt sensor is rigidly mounted on the longitudinal centerline of the self-propelled machine's tail section frame, specifically positioned on a structural beam near the unloading point of the transfer machine, ensuring synchronized attitude changes with the frame body. Its detection axis is precisely aligned along the working face's advancing direction (i.e., the frame's longitudinal axis), used to acquire the pitch angle of the self-propelled machine's tail section frame in real time during the moving process. This sensor employs a high-precision MEMS dual-axis or single-axis tilt measurement element, with a measurement range covering ±15°, an accuracy better than 0.05°, and a response time of less than 10ms, ensuring sensitive detection of even minute tilts of the frame.

[0029] Key detection timing: Before each end bracket pull-out (i.e., the instant the self-moving tail trolley is about to start moving forward), the processor triggers the tilt sensor to perform a static sampling, acquiring the current spatial attitude reference value of the frame. The selection of this sampling point has a clear engineering logic—before the end bracket pull-out, the system is in a relatively static state, and the frame attitude is stable. The tilt data collected at this time purely reflects the frame tilt caused by the undulation of the top and bottom plates, eliminating dynamic vibration interference during the movement and providing an accurate attitude correction reference for subsequent advance calculation. The measured pitch and tilt angle data, together with the synchronously acquired laser ranging value, constitute a spatiotemporal registration data pair. Through the processor's built-in trigonometric function correction algorithm, the deviation of the laser ranging value in the horizontal projection direction caused by the frame pitch is effectively eliminated, thereby controlling the cumulative advance error within ±1%, significantly improving long-term detection accuracy and data reliability.

[0030] In summary, the coal face advance detection system of this invention solves the problems of low accuracy and large cumulative error in current face advance detection. It can effectively correct the advance measurement error caused by face undulations, achieve high-precision automatic detection without cumulative error, and improve the data reliability and security of intelligent coal mining.

[0031] To achieve the above embodiments, this invention also provides a method for detecting the advance of a coal mining face, such as... Figure 3 As shown, it includes: Step S1: Before the end support is advanced on the working face, acquire the data L0 from the pushing stroke detection device and the data α0 from the tilt sensor, and record them by the processor; Step S2: After the working face is advanced, the transfer machine drives the self-moving tail trolley to move forward for the first time, and sends the data L1 from the pushing stroke detection device and the data α1 from the tilt angle sensor to the processor; Step S3: The processor corrects the actual advance of the working face based on the tilt sensor data α1 using the following formula:

[0032] Step S4: After the working face is advanced for the second time, the transfer machine drives the self-moving tail carriage to move forward for the second time, and the data L2 of the pushing stroke detection device and the data α2 of the tilt angle sensor are obtained and sent to the processor to calculate the second cutting depth of the working face;

[0033] Step S5: After the third advancement of the working face, the transfer machine drives the self-moving tail carriage to move forward for the second time, and the data L3 of the pushing stroke detection device and the data α3 of the tilt angle sensor are obtained and sent to the processor to calculate the third cutting depth of the working face;

[0034] Step S6: After the third cutter advances on the working face, the self-moving machine tail frame moves forward as a whole. After completion, the data L0 of the pushing stroke detection device and the data α0 of the tilt angle sensor are acquired and recorded by the processor. Step S7: After the self-moving machine tail frame moves forward as a whole, start a new working face advance cycle and repeat steps S2 to S6. The working face advance data is continuously accumulated.

[0035] Specifically, the schematic diagram of the first cutter advancing on the working face is as follows: Figure 4 As shown in the diagram, the second cutter advances on the working face. Figure 5 As shown in the diagram, the third cutter advances on the working face. Figure 6 As shown in the diagram, after the third cut is completed, the entire self-moving tail frame moves forward, completing the same schematic diagram. Figure 2 Among them, number 11 is the laser rangefinder sensor; 12 is the laser rangefinder reflector; 13 is the tilt sensor; and 14 is the processor.

[0036] The coal face advance detection method of this invention can effectively correct the advance measurement error caused by the undulation of the working face, realize high-precision automatic detection without cumulative error, and improve the data reliability and security of intelligent coal mining.

[0037] To implement the methods of the above embodiments, the present invention also provides a computer device, such as... Figure 7 As shown, the computer device 600 includes a memory 601 and a processor 602; wherein, the processor 602 reads executable program code stored in the memory 601 to run a program corresponding to the executable program code, so as to implement the various steps of the method described above.

[0038] To implement the above embodiments, this application also proposes a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the method described in the foregoing embodiments.

[0039] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

[0040] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0041] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.

Claims

1. A coal mining face advance detection system, characterized in that, The system includes a displacement detection device, a tilt sensor, and a processor, wherein... The pushing stroke detection device is installed at the tail of the self-moving machine on the working face; The tilt sensor is mounted on the tail frame of the self-propelled machine; The processor calculates the path segment of the working face for each advance based on the data collected by the push stroke detection device and the tilt angle sensor data, and then fits the working face advance curve to calculate the advance degree of the coal mining working face.

2. The system according to claim 1, characterized in that, The pushing stroke detection device adopts a laser ranging system. A laser ranging sensor is installed on the working face side end of the self-moving machine tail trolley. The self-moving machine tail frame emits a laser and returns the ranging value after each working face advancement is completed.

3. The system according to claim 1, characterized in that, The tilt sensor is installed on the tail frame of the self-propelled machine to detect the pitch angle of the tail frame in the working face advancement direction. The detection is performed before each end support is pulled up.

4. A method for detecting the advance rate of a coal mining face, characterized in that, include: Step S1: Before the end support is advanced on the working face, acquire the data L0 from the pushing stroke detection device and the data α0 from the tilt sensor, and record them by the processor; Step S2: After the working face is advanced, the transfer machine drives the self-moving tail trolley to move forward for the first time, and sends the data L1 from the pushing stroke detection device and the data α1 from the tilt angle sensor to the processor; Step S3: The processor corrects the actual advance of the working face based on the tilt sensor data α1 using the following formula: Step S4: After the working face is advanced for the second time, the transfer machine drives the self-moving tail carriage to move forward for the second time, and the data L2 of the pushing stroke detection device and the data α2 of the tilt angle sensor are obtained and sent to the processor to calculate the second cutting depth of the working face; Step S5: After the third advancement of the working face, the transfer machine drives the self-moving tail carriage to move forward for the second time, and the data L3 of the pushing stroke detection device and the data α3 of the tilt angle sensor are obtained and sent to the processor to calculate the third cutting depth of the working face; Step S6: After the third cutter advances on the working face, the self-moving machine tail frame moves forward as a whole. After completion, the data L0 of the pushing stroke detection device and the data α0 of the tilt angle sensor are acquired and recorded by the processor. Step S7: After the self-moving machine tail frame moves forward as a whole, start a new working face advance cycle and repeat steps S2 to S6. The working face advance data is continuously accumulated.

5. A computer device, characterized in that, Including processor and memory; The processor reads executable program code stored in the memory to run a program corresponding to the executable program code, so as to implement the coal mining face advance detection method as described in claim 4.

6. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements a method for detecting the advance of a coal mining face as described in claim 4.

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