A multi-source sensing oriented operation behavior tracking system for coal mines

Abstract

The present application is suitable for the technical field of coal mine operation behavior monitoring, and provides an operation behavior tracking system for coal mine multi-source sensing, which comprises a data screening module for screening a plurality of first samples consistent with the current coal mine operation area background and different from the miner's working time length from the operation behavior database; and a data analysis module for analyzing each first sample to analyze whether there is a predetermined mode. The present application does not need to change the operation skill of the miner, nor to expand the roadway space or increase additional equipment, but only by reasonably determining the operation area layout, the stability of the equipment operation and the safety of the operation can be improved, effectively solving the problems of uncontrollable operation area difference, lack of standards and deterioration of equipment feedback in the prior art. The present application has the characteristics of low deployment cost and strong adaptability, and can be widely applied to coal mine underground support operation scene.

Description

Technical Field

[0001] This invention belongs to the field of coal mine operation behavior monitoring technology, and in particular relates to an operation behavior tracking system for multi-source sensing in coal mines. Background Technology

[0002] In the complex working environment of coal mines, to improve the safety and efficiency of underground operations, existing technologies generally employ multi-source sensing to track and monitor miners' actions. Wearable devices, positioning systems, and cameras are used to collect miners' motion data, which, combined with equipment operating parameters, achieves management goals such as early warning of hazardous behaviors, identification of fatigue states, and standardization of personnel behavior. Simultaneously, for monitoring the operational status of underground mobile support equipment, pressure sensors, tilt sensors, and other methods are used to detect equipment performance in real time to ensure equipment stability and coal mine support capabilities. However, most of these technologies focus on personnel behavior or equipment status itself, without fully considering the coupling relationship between equipment operating area configuration and personnel operating behavior.

[0003] In actual underground operating environments, mobile support equipment is typically installed by different personnel in different mining areas. Due to factors such as tunnel structure, terrain elevation differences, and limited space, there are unavoidable differences in the working space width and effective operating height of the equipment's operating area. Existing technologies generally consider these differences not to affect operation and therefore do not quantify or standardize them. However, those skilled in the art have found that when miners adjust support pressure or control support tilt, their posture adjustment is closely related to the layout of the operating area. When the operating area is unreasonable, miners will deviate from the standard operating posture to adapt to the space, leading to a deterioration in equipment response, such as increased support pressure deviation and slow tilt recovery, resulting in decreased work quality and increased safety hazards.

[0004] Therefore, existing technologies suffer from core technical defects such as uncontrollable configuration of operating areas, lack of evaluation basis, and lack of quantitative standards, which makes it impossible to effectively prevent miners' operational posture deviations and ensure the stable operation quality of underground mobile support equipment from the source. Summary of the Invention

[0005] The purpose of this invention is to provide a work behavior tracking system for multi-source sensing in coal mines, aiming to solve the problems mentioned in the background art.

[0006] This invention is implemented as follows: a multi-source sensing operation behavior tracking system for coal mines, the system comprising:

[0007] The data filtering module is used to filter out several first samples from the work behavior database that are consistent with the background of the current coal mine operation area but have different miner working hours;

[0008] The data analysis module is used to analyze each first sample and analyze whether there is a predetermined pattern: as the working time increases, the change in the posture of the miner in the operating area of ​​the underground mobile support equipment gradually increases and tends to be stable. At the same time, the comprehensive index of the deterioration feedback of the underground mobile support equipment gradually optimizes and tends to be stable.

[0009] The pattern recognition module is used to select the miner with the best change in the comprehensive index of deterioration feedback as the reference miner if the predetermined pattern is determined to exist, and find several second samples from the database that have worked with the reference miner, have the same background as the current coal mine operation area, and have worked for more than a specified time. The module analyzes whether there is a coupling relationship between the trend of equipment operation area configuration change and the trend of attitude change in the second samples.

[0010] The configuration adjustment module is used to select a second sample from several second samples whose attitude change amplitude is lower than a preset amplitude and whose comprehensive degradation feedback index is lower than a preset requirement as a standard sample if a coupling relationship is determined. The current underground movable support equipment operation area is configured and adjusted according to the equipment operation area of ​​the standard sample.

[0011] Furthermore, the range of posture changes includes a comprehensive measure of the deviation between the miner's actual body posture and the standard operating posture when the miner performs operations such as adjusting the support pressure or controlling the support tilt within the operating area of ​​the underground movable support equipment.

[0012] Furthermore, the expression for calculating the amplitude of the attitude change is as follows:

[0013]

[0014] In the formula: A represents the attitude change amplitude; n is the number of attitude parameters; d i σ is the actual offset value of the i-th attitude parameter; i Let w be the standard deviation of the i-th attitude parameter. i is the weight coefficient of the i-th attitude parameter.

[0015] Furthermore, the calculation of the comprehensive degradation feedback index of the underground mobile support equipment includes:

[0016] Analyze the first sample to determine the corresponding deviation values ​​of support pressure and support tilt within a preset time period after each operation by the miner to adjust the support pressure or control the support tilt.

[0017] Choose either the stent pressure deviation change value or the stent tilt deviation change value, or a weighted combination of the two, as the comprehensive deterioration feedback index for the first sample.

[0018] Furthermore, the calculation formula for the comprehensive degradation feedback index is as follows:

[0019]

[0020] In the formula: D represents the comprehensive index of deterioration feedback; t is the end time of the miner's operation; t0 is the start time of the miner's operation; T is the preset time period; ΔP(t) is the deviation of the support pressure; Δθ(t) is the deviation of the support inclination; τ P and τ θ α and β are the tolerance thresholds for pressure and tilt, respectively; α and β are weighting coefficients; λ is the attenuation coefficient.

[0021] Furthermore, the step of selecting the miner with the best change in the comprehensive degradation feedback index as the reference miner includes: in the predetermined mode, for the first sample whose comprehensive degradation feedback index of the underground movable support equipment has reached a stable stage, selecting the miner corresponding to the first sample with the lowest comprehensive degradation feedback index as the reference miner.

[0022] Furthermore, the specified time length includes the miner's working time for the first sample when the attitude change amplitude first reaches a stable stage in the predetermined mode.

[0023] Furthermore, the configuration of the device operating area includes a weighted combination of the working space width and the effective operating height of the device operating area.

[0024] Furthermore, the coupling relationship includes that, in several second samples, as the configuration of the device operating area gradually increases, the amplitude of the attitude change gradually decreases, but when the configuration of the device operating area reaches a certain node, the amplitude of the attitude change drops below the preset amplitude and remains stable.

[0025] Furthermore, the phrase "consistent with the current coal mine operation area background" means that the coal mine operation areas corresponding to the first and second samples are consistent with the current coal mine operation area in terms of underground roadway structure, equipment layout, support form, and operating environment conditions.

[0026] Compared with the prior art, the present invention has the following beneficial effects:

[0027] I. This invention, by introducing multi-source sensor data analysis and a historical sample-driven mechanism, establishes for the first time a correlation between the configuration of the operating area of ​​underground movable support equipment and comprehensive indicators of miner posture changes and equipment degradation feedback, thereby achieving quantitative evaluation and intelligent optimization of the equipment operating area configuration. Through predetermined pattern recognition and coupling relationship determination, the optimal operating area configuration can be automatically extracted from actual operation data, enabling miners to complete support pressure adjustment or support tilt control operations while maintaining a preset standard operating posture, significantly reducing the risk of equipment performance degradation caused by posture deviation;

[0028] Second, this invention does not require changes to miners' operating skills, nor does it require expanding tunnel space or adding extra equipment. Simply by rationally determining the layout of the operating area, it can improve equipment operational stability and safety, effectively solving the problems of uncontrollable differences in operating areas, lack of standards, and deteriorating equipment feedback in existing technologies. This invention features low deployment costs and strong adaptability, and can be widely applied to underground support operations in coal mines, promoting the optimization of human-machine collaboration and improving safe production. Attached Figure Description

[0029] Figure 1 This is a schematic diagram of a work behavior tracking system for multi-source sensing in coal mines, provided as an embodiment of the present invention. Detailed Implementation

[0030] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0031] Please see Figure 1 This embodiment provides a work behavior tracking system for multi-source sensing in coal mines, including:

[0032] The data filtering module 100 is used to filter out several first samples from the work behavior database that are consistent with the background of the current coal mine operation area but have different miner working hours.

[0033] It should be noted that "consistent with the background of the current coal mine operation area" means that the coal mine operation area corresponding to the first sample is consistent with the current coal mine operation area in terms of underground roadway structure, equipment layout, support form and operation environment conditions.

[0034] In this embodiment of the invention, the current coal mine operating area refers to the construction area within the mine where the underground movable support equipment has not yet arrived or is still in the assembly stage, and the operating area has not yet been finalized. This invention is specifically designed to optimize the pre-configuration of such operating areas, ensuring a reasonable operating space layout and height matching before the equipment is officially put into operation.

[0035] Because the assembly of underground mobile support equipment is typically completed by different assembly and installation personnel, and because the underground coal mine environment exhibits subtle topographical variations—such as changes in roadway slope, floor flatness, and the position of support components—the actual operating area for the equipment will differ. These variations are generally considered insufficient to cause significant impact in existing technologies, thus lacking any unified assessment or standardized control. However, those skilled in the art have discovered that underground mobile support equipment requires continuous human intervention and precise hand gestures, especially in operations such as adjusting support pressure or controlling support tilt. The miner's posture directly affects operational accuracy and the overall indicators of equipment degradation feedback.

[0036] If the equipment operating area is not configured properly, miners will not be able to maintain a posture close to the standard operating posture, which will not only affect current operating efficiency but also cause a decline in equipment operating quality. Therefore, determining an equipment operating area configuration that can encourage miners to naturally maintain a standard operating posture is necessary and has significant technical value.

[0037] However, while the impact of varying operating area configurations on operational behavior and equipment status is recognized, accurately obtaining a reasonable operating area configuration during equipment assembly or before commissioning remains a challenge for existing technologies. On the one hand, the operating area cannot be infinitely enlarged due to the inherently narrow space of the tunnels and the need to accommodate other secondary equipment. On the other hand, an excessively small operating area forces miners into non-standard postures, negatively impacting operational performance. Therefore, a system implementation method is urgently needed that can abstract the most advantageous configuration from historical data.

[0038] In the data filtering module 100, a strict background consistency screening condition is proposed to ensure that the first sample used for pattern analysis has strong comparability, thereby improving the reliability of the analysis results. Where data volume allows, further screening factors such as environmental humidity, gas concentration, and miner skill level can be added, or a similarity threshold can be used to determine the degree of background consistency, ensuring that the samples used for analysis do not need to be completely identical, but at least have a high degree of similarity within the same problem-solving scope. This expands the available data scale without affecting the accuracy of the trend judgments and coupling analysis obtained by the algorithm.

[0039] The operational behavior database stores personnel behavior data and equipment operation data collected during coal mine operations. This database can originate from a multi-source sensor acquisition system, including, but not limited to, miner posture data collected by wearable devices or smart cameras positioned within the operating area, operational feedback data from underground mobile support equipment, mining operation duration, work procedure information, and mine operating environment data. Through unified archiving and cleaning of the multi-source data, structured or semi-structured data samples are formed for use and analysis during the implementation of this invention.

[0040] The data analysis module 200 is used to analyze each first sample to determine if a predetermined pattern exists: as working time increases, the amplitude of the miner's posture changes within the operating area of ​​the underground mobile support equipment gradually increases and tends to stabilize. At the same time, the comprehensive index of the deterioration feedback of the underground mobile support equipment gradually optimizes and tends to stabilize.

[0041] Posture change amplitude refers to a comprehensive measure of the deviation between a miner's actual body posture and the standard operating posture when adjusting support pressure or controlling support tilt within the operating area of ​​underground movable support equipment. The formula for calculating posture change amplitude is:

[0042]

[0043] In the formula: A represents the attitude change amplitude; n is the number of attitude parameters; d i σ is the actual offset value of the i-th attitude parameter; i Let w be the standard deviation of the i-th attitude parameter. i is the weight coefficient of the i-th attitude parameter.

[0044] The calculation of the comprehensive index for the deterioration feedback of underground mobile support equipment specifically includes:

[0045] Analyze the first sample to determine the corresponding deviation values ​​of support pressure and support tilt within a preset time period after each operation by the miner to adjust the support pressure or control the support tilt.

[0046] Choose either the stent pressure deviation change value or the stent tilt deviation change value, or a weighted combination of the two, as the comprehensive deterioration feedback index for the first sample.

[0047] In this scheme, the formula for calculating the comprehensive degradation feedback index is as follows:

[0048]

[0049] In the formula: D represents the comprehensive index of deterioration feedback; t is the end time of the miner's operation; t0 is the start time of the miner's operation; T is the preset time period; ΔP(t) is the deviation of the support pressure; Δθ(t) is the deviation of the support inclination; τ P and τ θ α and β are the tolerance thresholds for pressure and tilt, respectively; α and β are weighting coefficients; λ is the attenuation coefficient.

[0050] In this embodiment of the invention, the amplitude of posture changes can be acquired through multi-source sensing technology. For example, inertial measurement unit sensors worn on key parts of the miner's body (such as the head, arms, waist, and legs) or intelligent cameras deployed in the equipment operating area can be used for posture recognition and motion tracking. These sensing methods can record the miner's posture parameters in real time when adjusting support pressure or controlling support tilt, and compare them with a pre-stored standard operating posture model to calculate quantitative characteristics of deviations such as posture offset angle and limb position offset distance, thereby forming a comprehensive measure of the amplitude of posture changes. The aforementioned posture recognition and deviation quantification technologies belong to mature existing technical fields and can be implemented using conventional sensor fusion algorithms and posture estimation algorithms.

[0051] The comprehensive degradation feedback index can be obtained based on the operational status monitoring data of underground mobile support equipment. The equipment can be equipped with pressure sensors and tilt sensors to collect changes in support pressure deviation and tilt deviation, respectively. By setting a preset time period, the degradation and recovery characteristics of the equipment's status after operation are statistically analyzed. For example, the time required for pressure to recover to a stable tolerance range and the rate at which tilt deviation returns to a stable posture are measured, reflecting the changing trend of the equipment's performance status. The preset time period can be determined based on equipment characteristics and operational experience to cover the complete response process of the impact of operational actions on the equipment's operating status. The aforementioned equipment status monitoring and deviation calculation are also mature existing technologies that can be directly applied.

[0052] The predetermined pattern was used to reveal the correlation between miners' posture adjustments and equipment operating status. When miners' working hours are short, their operating postures are mostly based on standard training movements. However, as working hours increase, miners naturally adjust their postures to adapt to the spatial differences in the current equipment operating area and to better observe the equipment status, causing the amplitude of posture changes to gradually increase, and then stabilizing as the miners gradually adapt to the environment and operating area conditions. Simultaneously, the comprehensive degradation feedback index of the underground movable support equipment also shows a gradual optimization and stabilization trend, indicating that although there is a posture shift during the adaptation process, this shift is more conducive to the stability and performance recovery of the equipment, enabling the equipment to reach a better stable operating level. This pattern shows that there is a close correlation between the miner's posture adaptive ability in the working environment and the configuration of the equipment operating area.

[0053] The pattern recognition module 300 is used to select the miner with the best change in the comprehensive index of deterioration feedback as the reference miner if the predetermined pattern is determined to exist, and find several second samples from the database that have worked with the reference miner, have the same background as the current coal mine operation area, and have worked for more than a specified time. The module analyzes whether there is a coupling relationship between the trend of equipment operation area configuration change and the trend of attitude change in the second samples.

[0054] The phrase "consistent with the background of the current coal mine operation area" in the pattern recognition module 300 means that the coal mine operation area corresponding to the second sample is consistent with the current coal mine operation area in terms of underground roadway structure, equipment layout, support form, and operating environment conditions.

[0055] "Selecting the miner with the best change in the comprehensive deterioration feedback index as the reference miner" means that, in the predetermined mode, for the first sample of the underground mobile support equipment whose comprehensive deterioration feedback index has reached a stable stage, the miner corresponding to the first sample with the lowest comprehensive deterioration feedback index is selected as the reference miner.

[0056] The specified time length refers to the miner's working time for the first sample when the attitude change amplitude first reaches a stable stage in the predetermined mode.

[0057] The device operating area configuration refers to the weighted combination of the working space width and effective operating height of the device operating area. The coupling relationship means that, in several second samples, as the device operating area configuration gradually increases, the amplitude of posture change gradually decreases, but when the device operating area configuration reaches a certain node, the amplitude of posture change drops below a preset amplitude and remains stable.

[0058] In this scheme, the coupling relationship is determined by the coupling relationship coefficient, and the formula for calculating the coupling relationship coefficient is as follows:

[0059]

[0060] Where R represents the coupling coefficient, R>0 indicates the existence of a coupling relationship; C is the configuration index of the equipment operating area; A is the attitude change amplitude; cov(C,A) is the sample covariance of C and A; σ C and σ A These are the standard deviations of C and A, respectively; γ is the sensitivity coefficient; C ∗ Configure nodes; To configure node C ∗ The partial derivative of A with respect to C.

[0061] In this embodiment of the invention, the pattern recognition module 300 is the core step of the technical solution. Its purpose is to analyze whether there is a coupling relationship between the trend of equipment operating area configuration change and the trend of posture change amplitude change, based on the data sample of the reference miner with the best comprehensive index change in degradation feedback. Through this analysis, not only can the core research point proposed in the data filtering module 100 be explained, namely, that differences in operating area configuration lead to differences in work behavior and equipment feedback, but it can also further find the most reasonable equipment operating area configuration, so that while the miner maintains a near-standard operating posture, the operating state of the underground mobile support equipment is better than the existing conditions.

[0062] The reference miner is used to establish a benchmark for comparison. This reference miner is the best performer in the predetermined mode, and its overall degradation feedback index has reached a stable stage and is lower than that of other samples. By obtaining a second sample of the reference miner's work, we can infer the pattern of its attitude change under different equipment operating area configurations, thereby extracting the true relationship between the trend of equipment operating area configuration changes and the trend of attitude change amplitude changes.

[0063] The specified time length is determined based on the point in time when the amplitude of attitude change first reaches a stable phase. This indicates that the miner has completed attitude adaptation to the working environment and equipment operating area configuration. Therefore, the second sample formed after this time length has higher stability and analytical value, helping to accurately determine the existence of coupling relationships.

[0064] The working space width and effective operating height of the equipment operating area are key indicators that can quantify differences in the operating area. Changes in these dimensions directly affect the miner's reach and hand angle during operation, representing naturally occurring sources of variation. A weighted combination of these two factors can reflect changes in the equipment operating area configuration as a single indicator. Weighting coefficients can be assigned based on empirical data or equipment importance; for example, when operating height has a more significant impact on posture, it can be given a higher weight to ensure the accuracy of the coupled analysis.

[0065] The significance of the coupling relationship lies in verifying whether the trend of changes in the operating area configuration is synchronized with the trend of changes in the attitude change amplitude. That is, as the equipment operating area configuration gradually increases, the attitude change amplitude gradually decreases. When the equipment operating area configuration reaches a certain node (this node indicates that the equipment operating area has sufficient conditions for the miner to maintain the preset standard operating attitude), the attitude change amplitude drops below the preset amplitude and remains stable. If this condition is met, it indicates that the operating area configuration has a positive effect on maintaining the standard operating attitude; if it is not met, it indicates that the configuration is insufficient to improve attitude deviation or has a negative impact, and therefore is not suitable as a standard configuration.

[0066] The pattern recognition module 300 not only avoids errors from human experience-based judgments but also autonomously extracts optimal configuration patterns from historical samples, enabling the ingenious design of the operating area configuration by reverse engineering from posture-adaptive behavior. This method reveals implicit patterns behind operational behavior that are difficult to observe directly, providing a scientific basis for the selection of standard samples and significantly improving the reliability of operating area configuration optimization.

[0067] The configuration adjustment module 400 is used to select, if it is determined that there is a coupling relationship, a second sample with a posture change amplitude lower than a preset amplitude and a comprehensive degradation feedback index lower than a preset requirement as a standard sample from several second samples, and to adjust the current underground movable support equipment operation area configuration according to the equipment operation area configuration of the standard sample.

[0068] In this embodiment of the invention, the second sample, where the attitude change amplitude is lower than a preset amplitude and the comprehensive degradation feedback index is lower than a preset requirement, represents a miner who can complete support pressure adjustment or support tilt control operations while maintaining a preset standard operating posture, and the operating status of the underground movable support equipment is also maintained at a relatively stable level. Such samples typically appear after the node determined by the pattern recognition module 300, indicating that the equipment operating area is well-configured and suitable for the reference miner. The significance of this condition is to ensure that the selected samples neither cause excessive attitude deviation of the mining tools due to an overly compact operating area, nor cause a deterioration in equipment status response due to excessive space expansion; therefore, they represent the most reasonable set of actual reflections of the equipment operating area configuration.

[0069] Standard samples, as objective representations of optimal equipment operating area configurations, reflect the operating area setup under specific mine environments and equipment assembly conditions, enabling miners to achieve good operational results without excessive adjustments to their posture. Therefore, by screening standard samples, an optimal operating area configuration can be determined before equipment installation or operation, ensuring that miners naturally assume a near-standard operating posture upon entering the operating area, thereby guaranteeing stable equipment operation feedback.

[0070] Adjusting the current equipment operating area configuration based on standard samples can be achieved by directly modifying the working space width and effective operating height of the equipment operating area to ensure that the current configuration is as consistent as possible with the configuration corresponding to the standard sample. For example, based on the weighted combination of the operating area width and height in the standard sample, the relative position of the equipment, the height of the operating interface, or the bracket assembly spacing can be fine-tuned to ensure that the miner's posture changes within a preset range when actually operating in the current equipment operating area, while also ensuring that the comprehensive degradation feedback index does not exceed the preset requirements.

[0071] This invention effectively addresses the core research point raised in the data filtering module 100: existing technologies neglect the impact of differences in the operating area of ​​underground mobile support equipment on miners' posture and equipment operating quality, and lack standardized and quantitative basis for operating area configuration. This invention, for the first time, proposes to deduce the optimal operating area configuration by learning from historical samples, based on the coupling relationship between changes in miners' posture and comprehensive indicators of equipment degradation feedback. This achieves quantitative determination of a reasonable operating environment, transforming miners' adaptive behavior into parameters for improving equipment performance and safety, demonstrating significant innovation.

[0072] This invention has promising engineering applications and can be directly applied to the assembly or maintenance and adjustment stages of underground mobile support equipment. It allows for an optimized operating area layout before deployment, reducing safety hazards and equipment performance fluctuations caused by miners' shifted operating postures. From a broader application perspective, this invention can also be extended to other coal mine equipment operation scenarios requiring close interaction between personnel and equipment in confined spaces, such as hydraulic support maintenance and coal mining machine operating platform optimization, thus promoting coal mine operations towards greater human-machine collaboration, safety, and efficiency.

[0073] This invention eliminates the need for complex ergonomic simulation modeling, subjective questionnaire surveys of miners, or tedious on-site testing and parameter tuning. Instead, it directly analyzes historical operational behavior data that has naturally occurred in real production environments. Because this data originates from the actual posture adaptation processes formed by miners working long-term in confined mine spaces, and possesses multi-source, continuous, and large-scale sample characteristics, it is more accurate, scientific, and engineering-practical compared to model extrapolations that rely on assumptions. This invention significantly leverages this data-driven advantage, automatically learning the empirical correlation between long-term adaptive posture patterns of miners and changes in equipment degradation status to derive the optimal equipment operating area configuration. This is particularly suitable for applications such as underground mobile support equipment where human-machine interaction space is extremely limited, making the optimization results more realistic, reliable, and universally applicable.

[0074] It should be understood that although the steps in the flowcharts of the various embodiments of the present invention are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the various embodiments may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least a portion of the sub-steps or stages of other steps.

[0075] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0076] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0077] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention. Therefore, the scope of protection of this patent should be determined by the appended claims.

[0078] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A work behavior tracking system based on multi-source sensing in coal mines, characterized in that, The system includes: The data filtering module is used to filter out several first samples from the work behavior database that are consistent with the background of the current coal mine operation area but have different miner working hours. The data analysis module is used to analyze each first sample and analyze whether there is a predetermined pattern: as the working time increases, the change in the posture of the miner in the operating area of ​​the underground mobile support equipment gradually increases and tends to be stable. At the same time, the comprehensive index of the deterioration feedback of the underground mobile support equipment gradually optimizes and tends to be stable. The miner's posture is obtained by analyzing the miner's posture data collected by smart cameras set up in the operating area; The expression for calculating the amplitude of the attitude change is: ； In the formula: A represents the attitude change amplitude; n is the number of attitude parameters; d i σ is the actual offset value of the i-th attitude parameter; i Let w be the standard deviation of the i-th attitude parameter. i The weight coefficient for the i-th attitude parameter; The calculation of the comprehensive degradation feedback index of the underground mobile support equipment includes: Analyze the first sample to determine the corresponding deviation values ​​of support pressure and support tilt within a preset time period after each operation by the miner to adjust the support pressure or control the support tilt. Choose either the stent pressure deviation change value or the stent tilt deviation change value, or a weighted combination of the two, as the comprehensive deterioration feedback index for the first sample. The pattern recognition module is used to select the miner with the best change in the comprehensive index of deterioration feedback as the reference miner if the predetermined pattern is determined to exist, and find several second samples from the database that have worked with the reference miner, have the same background as the current coal mine operation area, and have worked for more than a specified time. The module analyzes whether there is a coupling relationship between the trend of equipment operation area configuration change and the trend of attitude change in the second samples. The configuration adjustment module is used to select a second sample from several second samples whose attitude change amplitude is lower than a preset amplitude and whose comprehensive degradation feedback index is lower than a preset requirement as a standard sample if a coupling relationship is determined. The current underground movable support equipment operation area is configured and adjusted according to the equipment operation area of ​​the standard sample.

2. The work behavior tracking system for multi-source sensing in coal mines according to claim 1, characterized in that, The range of posture changes includes a comprehensive measure of the degree of deviation between the miner's actual body posture and the standard operating posture when the miner is adjusting the support pressure or controlling the support tilt in the operating area of ​​the underground movable support equipment.

3. The work behavior tracking system for multi-source sensing in coal mines according to claim 1, characterized in that, The formula for calculating the comprehensive degradation feedback index is as follows: ； In the formula: D represents the comprehensive index of deterioration feedback; t is the end time of the miner's operation; t0 is the start time of the miner's operation. T is the preset time period; ΔP(t) is the deviation of the support pressure; Δθ(t) is the deviation of the support tilt; τ P and τ θ α and β are the tolerance thresholds for pressure and tilt, respectively; α and β are weighting coefficients; λ is the attenuation coefficient.

4. The work behavior tracking system for multi-source sensing in coal mines according to claim 1, characterized in that, The step of selecting the miner with the best change in the comprehensive degradation feedback index as the reference miner includes: in the predetermined mode, for the first sample whose comprehensive degradation feedback index of the underground movable support equipment has reached a stable stage, selecting the miner corresponding to the first sample with the lowest comprehensive degradation feedback index as the reference miner.

5. The work behavior tracking system for multi-source sensing in coal mines according to claim 1, characterized in that, The specified time length includes the miner's working time for the first sample when the attitude change amplitude first reaches a stable stage in the predetermined mode.

6. The work behavior tracking system for multi-source sensing in coal mines according to claim 1, characterized in that, The configuration of the equipment operating area includes a weighted combination of the working space width and the effective operating height of the equipment operating area.

7. The work behavior tracking system for multi-source sensing in coal mines according to claim 1, characterized in that, The coupling relationship is included in several second samples. As the configuration of the device operating area gradually increases, the attitude change amplitude gradually decreases. However, when the configuration of the device operating area reaches a certain node, the attitude change amplitude drops below the preset amplitude and remains stable.

8. The work behavior tracking system for multi-source sensing in coal mines according to claim 1, characterized in that, The phrase "consistent with the background of the current coal mine operation area" means that the coal mine operation areas corresponding to the first and second samples are consistent with the current coal mine operation area in terms of underground roadway structure, equipment layout, support form, and operating environment conditions.

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