An intelligent speed regulation and energy feedback system based on coal mine belt conveyor

Abstract

The application relates to an intelligent speed regulation and energy feedback system based on a coal mine belt conveyor, relates to the technical field of intelligent control of mine transportation equipment, obtains the initial form of a bulk material and the vibration, belt speed and displacement characteristics of a conveyor, discretizes the material into virtual slices, and converts accumulated exciting energy. The dynamic angle of repose and the initial form are combined to deduce the profile, and a collapse index is generated. The unit deformation resistance is reconstructed and spatially integrated to obtain the equivalent total resistance, the steady-state demand torque is extracted, the frequency instruction is generated when the constraints are met, and the constraint conditions are updated according to the feedback optimization parameters; the dynamic collapse resistance reduction effect caused by the vibration fluidization of bulk coal flow in the long-distance transportation process can be identified, and the operation frequency of the conveyor can be finely and energy-efficiently regulated.

Description

Technical Field

[0001] This application relates to the field of intelligent control technology for mining transportation equipment, specifically an intelligent speed regulation and energy feedback system for coal mine belt conveyors. Background Technology

[0002] Existing speed control technologies for belt conveyors typically obtain the initial coal flow volume or mass in the loading area at the tail end of the conveyor and use it as the sole core variable for speed control decisions. This technology assumes that the coal flow maintains its initial shape throughout the entire transportation process, treating bulk coal as a rigid slider and ignoring its dynamic evolution under vibration excitation.

[0003] However, coal is a typical bulk material, and its internal friction is attenuated by the periodic low-frequency vibration of the idler rollers along the line, resulting in a vibration fluidization effect. This causes the coal pile to dynamically collapse, its profile to widen to both sides, and its dynamic angle of repose to decrease. The coal flow gradually evolves from a tall, towering shape at the tail end to a low, flat, thin layer in the middle and lower reaches, with a decreased cross-sectional height-to-width ratio and a significant reduction in internal deformation resistance.

[0004] The existing system cannot detect this dynamic drag reduction phenomenon and always drives the frequency converter according to the high resistance model corresponding to the initial thick coal pile, resulting in high energy efficiency losses in the middle and downstream sections. Therefore, there is an urgent need for a technical solution that can sense the dynamic morphological evolution of bulk coal in real time and accurately reconstruct the deformation resistance along the line to achieve refined energy-saving speed regulation. Summary of the Invention

[0005] The purpose of this application is to provide an intelligent speed regulation and energy feedback system for coal mine belt conveyors, which aims to identify the dynamic collapse and drag reduction effect caused by vibration fluidization during long-distance transportation of bulk coal flow, and to achieve precise energy-saving control of the conveyor's operating frequency.

[0006] The objective of this application can be achieved through the following technical solution: Firstly, an intelligent speed regulation and energy feedback system for coal mine belt conveyors, comprising the following modules:

[0007] The feature extraction module is used to obtain the initial morphological features of the target bulk material and the vibration features, belt speed features, and displacement features of the belt conveyor during operation.

[0008] The processing module is used to discretize the target bulk material into continuous virtual slices based on the displacement characteristics, and to convert the vibration characteristics into the cumulative excitation energy characteristics of the virtual slices on the transmission path based on the belt speed characteristics.

[0009] The morphology analysis module is used to obtain the dynamic angle of repose characterizing the lateral widening of the virtual slice, and to deduce the dynamic contour parameters of the virtual slice by combining the initial morphological features and the cumulative excitation energy features, and to generate the collapse index characterizing the material morphology change.

[0010] The resistance assessment module is used to reconstruct the preset unit deformation resistance of the virtual slice based on the collapse index, and to spatially integrate the reconstructed preset unit deformation resistance along the transmission path to obtain the equivalent total operating resistance.

[0011] The control module is used to extract the steady-state demand torque of the current operating condition based on the equivalent total operating resistance. When the steady-state demand torque meets the preset constraints, a target operating frequency command is generated. After executing the target operating frequency command, feedback optimization parameters characterizing the control effect are obtained, and the preset constraints are updated according to them.

[0012] Secondly, a method for intelligent speed regulation and energy feedback based on coal mine belt conveyors includes the following steps:

[0013] Acquire the initial morphological characteristics of the target bulk material and the vibration characteristics, belt speed characteristics, and displacement characteristics of the belt conveyor during operation;

[0014] Based on the displacement characteristics, the target bulk material is discretized into continuous virtual slices, and based on the belt speed characteristics, the vibration characteristics are converted into the cumulative excitation energy characteristics of the virtual slices on the transmission path.

[0015] The dynamic repose angle characterizing the lateral widening of the virtual slice is obtained, and the dynamic contour parameters of the virtual slice are deduced by combining the initial morphological features and the cumulative excitation energy features, and the collapse index characterizing the material morphological change is generated.

[0016] Based on the collapse index, the preset unit deformation resistance of the virtual slice is reconstructed, and the reconstructed preset unit deformation resistance is spatially integrated along the transmission path to obtain the equivalent total operating resistance.

[0017] Based on the equivalent total operating resistance, the steady-state demand torque under the current operating condition is extracted. When the steady-state demand torque meets the preset constraints, a target operating frequency command is generated. After executing the target operating frequency command, feedback optimization parameters characterizing the control effect are obtained, and the preset constraints are updated accordingly.

[0018] Thirdly, a computer storage medium stores computer-executable instructions, which, when executed, implement the intelligent speed regulation and energy feedback system based on a coal mine belt conveyor described in the first aspect.

[0019] Compared with the prior art, the beneficial effects of this application are:

[0020] This application introduces the physical phenomenon of dynamic collapse of bulk materials caused by vibration fluidization into the speed control of belt conveyors, and constructs a dynamic repose angle decay model based on accumulated excitation energy, breaking the rigid assumption of constant coal flow morphology. By discretizing to obtain virtual slices and tracking the coal flow morphology along the entire line in real time, the deformation resistance along the line is accurately reconstructed;

[0021] The coupled model based on the collapse index and correction factor eliminates the component of false resistance overestimation in the traditional system, enabling the frequency converter to break through the conservative speed reduction limit in the mid-to-lower range. The overall energy efficiency significantly exceeds that of the existing system. The introduction of a feedback optimization mechanism based on the motor phase shift angle change rate dynamically corrects the optimal operating line density constraint to form a self-consistent closed loop, which can achieve fine energy-saving control of the conveyor operating frequency. Attached Figure Description

[0022] Figure 1 This is a schematic diagram of a module of an intelligent speed regulation and energy feedback system for a coal mine belt conveyor according to this application;

[0023] Figure 2 This is a schematic diagram illustrating the steps of an intelligent speed regulation and energy feedback method for a coal mine belt conveyor according to this application. Detailed Implementation

[0024] The technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. The components described and shown in the accompanying drawings can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but only to illustrate selected embodiments of this application.

[0025] Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without inventive effort are within the scope of protection of this application. It should be noted that similar reference numerals and letters in the following figures indicate similar items. Therefore, once an item has been defined in one figure, it does not need to be further defined and explained in subsequent figures. The terms first, second, etc. are only used to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0026] Belt conveyors are core equipment in underground and surface production systems of coal mines, responsible for the horizontal transport and inclined lifting of materials. Their operating energy consumption accounts for a significant proportion of the total electricity consumption of mines. With the deepening of intelligent construction in coal mines, implementing variable frequency speed control based on real-time load for belt conveyors has become an important technical direction for reducing ineffective energy consumption and achieving precise transportation.

[0027] Current mainstream intelligent speed control technologies typically deploy lidar sensors or belt scales in the loading area at the tail of the machine. By scanning the coal drop section or weighing in real time, they obtain the initial coal flow volume or mass information entering the belt, and use this as the sole core variable for speed control decisions. Under this technical architecture, the control system assumes that the relationship between the initial volume or mass and the total running resistance is a static linear mapping, believing that as long as the loading state at the tail of the machine is accurately measured, the drive requirements of the motor throughout the entire process can be linearly calculated.

[0028] However, the above technical approach has a flawed physical assumption: it assumes that the coal flow maintains its initial shape at the loading point throughout the long process of being transported by the conveyor belt from the tail to the head of the machine. This assumption treats bulk coal as a rigid sliding block, assuming that the height, width, and shape of the coal pile cross-section remain absolutely static and constant over a transportation distance of several kilometers and a running time of several tens of minutes.

[0029] This rigid assumption deviates significantly from the fundamental laws of bulk mechanics. Coal, in its natural state, is a typical bulk material, and its macroscopic packing morphology is entirely determined by the internal friction between particles. However, internal friction is not constant and will significantly decrease with the accumulation of external vibration excitation, thereby changing its macroscopic packing morphology.

[0030] In actual coal transportation operations, the densely arranged idlers along the belt conveyor continuously apply periodic low-frequency mechanical vibrations to the material being transported during belt operation. As the coal flow slices advance along the transport path, the cumulative vibration energy absorbed gradually increases. This continuous mechanical excitation weakens the static frictional interlocking force between bulk particles, inducing a physical effect called vibration fluidization. Under the influence of vibration fluidization, the internal friction angle of the bulk material decreases, which macroscopically manifests as the dynamic collapse of the coal pile and the widening of its profile to both sides.

[0031] The coal piles, initially towering and steep in the loading area, gradually evolve into a low, flat, and laterally extended thin layer as they move along the conveyor belt to the middle and lower reaches. The core physical quantity describing this evolution is the dynamic angle of repose—the maximum angle of inclination of the slope that can maintain a stable shape in a vibrating environment. The dynamic angle of repose is necessarily smaller than the reference static angle of repose of the material in a completely static state, and it decreases as the vibration energy absorbed by the material increases. Physically, this manifests as the coal pile becoming flatter as it moves, and the aspect ratio of its cross-section continuously decreasing.

[0032] The existing speed control system completely lacks the ability to perceive the above physical phenomena. Because it always uses the initial shape of the towering coal pile at the tail end as the sole reference, the system still uses the resistance coefficient corresponding to the initial thick coal seam when calculating the internal deformation resistance of the material in the downstream position of the conveyor. The internal deformation resistance of the material refers to the additional running resistance generated when bulk materials pass through the idlers on the belt due to the internal bending deformation of the coal seam under its own weight and the reaction force of the idler supports, as well as the mutual squeezing and slippage between particles.

[0033] In real-world operating conditions, after the coal flow collapses and flattens, the aspect ratio of the cross-section decreases significantly, the normal compressive force between particles decreases substantially, and the internal shear slip resistance drops sharply. However, existing control systems cannot recognize this dynamic resistance reduction phenomenon. They consistently drive the frequency converter to output excessive electromagnetic torque based on the high resistance model corresponding to the thick coal pile at the tail end, maintaining an excessively high belt speed setting. This results in the conveyor being in a state of ineffective kinetic energy waste in the middle and downstream sections, leading to a systematic deviation in overall energy efficiency, with energy efficiency losses often exceeding 15%.

[0034] In summary, the core technical problem that urgently needs to be solved is how to construct a technical solution that can perceive the dynamic morphological evolution of bulk coal due to vibration fluidization during transportation in real time, accurately reconstruct the actual material deformation resistance along the line, and thus guide the belt conveyor to implement refined energy-saving speed regulation.

[0035] Therefore, such as Figure 1 As shown, this application provides an intelligent speed regulation and energy feedback system for coal mine belt conveyors, including the following modules:

[0036] The feature extraction module is used to obtain the initial morphological features of the target bulk material and the vibration features, belt speed features, and displacement features of the belt conveyor during operation.

[0037] The processing module is used to discretize the target bulk material into continuous virtual slices based on the displacement characteristics, and to convert the vibration characteristics into the cumulative excitation energy characteristics of the virtual slices on the transmission path based on the belt speed characteristics.

[0038] The morphology analysis module is used to obtain the dynamic angle of repose characterizing the lateral widening of the virtual slice, and to deduce the dynamic contour parameters of the virtual slice by combining the initial morphological features and the cumulative excitation energy features, and to generate the collapse index characterizing the material morphology change.

[0039] The resistance assessment module is used to reconstruct the preset unit deformation resistance of the virtual slice based on the collapse index, and to spatially integrate the reconstructed preset unit deformation resistance along the transmission path to obtain the equivalent total operating resistance.

[0040] The control module is used to extract the steady-state demand torque of the current operating condition based on the equivalent total operating resistance. When the steady-state demand torque meets the preset constraints, a target operating frequency command is generated. After executing the target operating frequency command, feedback optimization parameters characterizing the control effect are obtained, and the preset constraints are updated according to them.

[0041] In another implementation, such as Figure 2 As shown, this application also provides a method for intelligent speed regulation and energy feedback of coal mine belt conveyors, including the following steps:

[0042] Acquire the initial morphological characteristics of the target bulk material and the vibration characteristics, belt speed characteristics, and displacement characteristics of the belt conveyor during operation;

[0043] Based on the displacement characteristics, the target bulk material is discretized into continuous virtual slices, and based on the belt speed characteristics, the vibration characteristics are converted into the cumulative excitation energy characteristics of the virtual slices on the transmission path.

[0044] The dynamic repose angle characterizing the lateral widening of the virtual slice is obtained, and the dynamic contour parameters of the virtual slice are deduced by combining the initial morphological features and the cumulative excitation energy features, and the collapse index characterizing the material morphological change is generated.

[0045] Based on the collapse index, the preset unit deformation resistance of the virtual slice is reconstructed, and the reconstructed preset unit deformation resistance is spatially integrated along the transmission path to obtain the equivalent total operating resistance.

[0046] Based on the equivalent total operating resistance, the steady-state demand torque under the current operating condition is extracted. When the steady-state demand torque meets the preset constraints, a target operating frequency command is generated. After executing the target operating frequency command, feedback optimization parameters characterizing the control effect are obtained, and the preset constraints are updated accordingly.

[0047] The feature extraction module is responsible for acquiring the initial morphological features of the target bulk material, as well as the vibration features, belt speed features, and displacement features during the operation of the belt conveyor. These four types of features are the source of raw data for all subsequent calculations.

[0048] Displacement and belt speed characteristics are provided by an incremental encoder mounted on the shaft end of the main drive motor. The real-time angular displacement pulse count output by the encoder is digitized and directly stored as the displacement characteristic in the register of the control system; the corresponding instantaneous speed conversion value (derived from the pulse frequency) is updated in real time as the belt speed characteristic. These two characteristics together constitute the basic spatiotemporal dual-domain information describing the belt's operating state.

[0049] Vibration characteristics are provided by MEMS triaxial accelerometers evenly distributed on the idler supports along the conveyor line. The triaxial accelerometers simultaneously sense vibration acceleration in the belt running direction (longitudinal), belt transverse direction, and perpendicular direction to the belt surface (vertical).

[0050] For the vibration fluidization physical mechanism that this invention focuses on, the vibration acceleration perpendicular to the belt direction is the main excitation source driving the fluidization rearrangement of particles inside the bulk material. Therefore, the system extracts the acceleration parameter values ​​perpendicular to the belt surface from the signals of each sensor as vibration characteristics, that is, the vertical vibration acceleration parameter values ​​at each location. The energy power injected into the material by vibration is proportional to the square of the vertical vibration acceleration parameter value. Therefore, taking the vertical acceleration parameter value has both clear physical meaning and facilitates subsequent integration calculations.

[0051] The processing module performs spatial discretization of the target bulk material based on displacement characteristics. The system presets a fixed physical space step size, which is determined by encoder pulse counts. For example, the encoder pulse count corresponding to the actual forward movement of the conveyor belt by 0.5 meters is set as the trigger threshold. Whenever the cumulative increase in displacement characteristics reaches the preset physical space step size, an explosion-proof 3D laser profilometer deployed downstream of the coal drop point at the tail end of the conveyor performs real-time scanning of the point cloud data of the current cross-section. By performing filtering and noise reduction and cross-sectional profile fitting on the point cloud data, the initial cross-sectional area, initial peak height, and initial bottom width of the target bulk material are extracted, and these three parameters are used as the initial morphological features.

[0052] Among them, the initial cross-sectional area represents the size of the cross-section of the slice when it just falls onto the conveyor belt and before it vibrates and collapses, which is the core basis for calculating the equivalent mass of the slice; the initial peak height represents the distance from the highest point of the coal pile at this cross-section to the conveyor belt surface; and the initial bottom width represents the lateral width of the contact area between the coal flow cross-section and the conveyor belt surface.

[0053] After obtaining the initial cross-sectional area, the system immediately calls the pre-calibrated bulk density constant of the bulk material and the preset physical space step size. It then performs a multiplication operation on the initial cross-sectional area, the preset physical space step size, and the bulk density constant to calculate the equivalent mass of the virtual slice, which is then encapsulated as an inherent invariant attribute in the slice data package. This design is based on the law of conservation of mass as its core constraint: under normal operating conditions without coal spillage, although the cross-sectional shape of the slice continuously evolves during transport by the conveyor belt, the total mass of coal it contains remains constant. Therefore, calculating the equivalent mass once at the beginning of the slice's lifecycle significantly reduces computational overhead and ensures the correctness of subsequent resistance calculations from a physical axiom perspective.

[0054] After completing the feature extraction, the system encapsulates the initial morphological features, equivalent mass, along with the timestamp and spatial coordinate information corresponding to the cross-section, into a single data packet. This data packet is then written to the tail of the control system's shift register queue, thus generating the virtual slice for the current cross-section. The spatial coordinate attributes of each virtual slice data packet in the queue are updated synchronously with the actual operation of the conveyor belt to accurately reflect the real-time position of each slice on the transmission path. Through this design, the continuously flowing physical coal flow is mapped into a discrete virtual slice queue with clear coordinates, initial morphology, and mass information in the digital control space, laying a data foundation for subsequent full-line tracking and morphological deduction along the path.

[0055] Another core computational task of the processing module is to convert vibration characteristics into cumulative excitation energy characteristics of each virtual slice along the transmission path based on belt speed characteristics. Cumulative excitation energy is the core physical quantity that quantifies the mechanical vibration energy absorbed by bulk materials as they move from the tail of the machine along the path to the current spatial coordinates. It is the direct physical driving factor that leads to the dynamic collapse of the coal pile and the decrease in the internal friction angle.

[0056] The specific calculation approach is as follows: First, divide the square of the vibration characteristic (i.e., the vertical acceleration parameter value at each position) by the belt velocity characteristic at the same position to obtain the excitation force density per unit spatial length at that position. Its physical meaning is the intensity of the excitation force exerted by the belt on the material slice per unit forward distance. Then, multiply this excitation force density by a preset energy conversion parameter to obtain the spatial energy differential term, representing the infinitesimal vibration energy absorbed by the slice within a small spatial increment. This derivation is based on the following physical relationships:

[0057] Virtual slices in spatial micro-elements The time infinitesimal within the distance is equal to Divide by local speed The vibrational energy power absorbed by the material is proportional to the square of the vertical acceleration parameter value. Therefore, after converting the time-domain integral to the spatial-domain integral, the numerator of the integrand is the square of the acceleration parameter value, and the denominator is the belt velocity. The physical meaning is clear, and the derivation is rigorous and self-consistent. Performing a definite integral operation on the above spatial energy differential term from the starting point of the transmission path to the spatial coordinates of the current virtual slice yields the cumulative excitation energy characteristics of the virtual slice, which are mathematically expressed as follows:

[0058] ;

[0059] In the formula, Indicates the first A virtual slice in spatial coordinates The characteristics of the cumulative excitation energy at the location; Represents spatial coordinates Vibration characteristics at that location Represents spatial coordinates Belt speed characteristics at the location; This represents the preset energy conversion parameters, which are system preset constants and have significance for energy dimension conversion.

[0060] The accumulated excitation energy characteristic is updated in real time synchronously with the spatial coordinates of the slice in the shift register queue, serving as the core input variable for calculating the dynamic angle of repose in the morphological analysis module. The accumulated excitation energy is zero when the slice is first placed on the conveyor belt; as the slice moves towards the head of the machine with the conveyor belt, the continuous vibration of the idler rollers along the path continuously injects mechanical energy into the slice, and the accumulated excitation energy increases monotonically, eventually reaching its maximum value in the unloading zone at the head of the machine.

[0061] The angle of repose is an important physical parameter describing the internal frictional characteristics of bulk materials. Its value reflects the maximum angle of inclination of the surface when the bulk material can naturally maintain a stable packing shape under the action of gravity. In a completely static environment, the bulk particles rely on surface roughness and the mechanical interlocking force to form a static frictional balance, and the corresponding angle is called the reference angle of repose (i.e., the static angle of repose).

[0062] When bulk materials are in a continuous vibration environment, the injected mechanical energy weakens the static frictional interlocking between particles, causing the particles to enter a microscopically free vibrational fluidization state. Macroscopically, the bulk material slides and collapses to both sides until a new dynamic frictional equilibrium is reached. The angle of inclination of the inclined plane that can maintain a stable shape in a vibration environment is called the dynamic angle of repose. The dynamic angle of repose is always numerically smaller than the reference angle of repose, and it decreases monotonically with increasing applied vibration energy. This law is highly consistent with the accepted principles of powder engineering and bulk dynamics.

[0063] In this invention, the morphology analysis module first obtains the preset reference angle of repose and fluidization sensitivity parameters of the target bulk material. The reference angle of repose is an inherent physical property of coal when it is naturally stacked without vibration, and can be determined through a standard conical chute experiment; the fluidization sensitivity parameter is a calibration constant characterizing the sensitivity of a specific material to vibration energy, and can be obtained through fitting via a vibration table experiment. Both parameters are pre-calibrated and written into the control program during the system debugging phase, and are used as preset system constants.

[0064] Based on the two preset constants mentioned above, and combined with the cumulative excitation energy characteristics of the current virtual slice, the morphological analysis module constructs the attenuation factor according to the following logic: using the negative of the product of the fluidization sensitivity parameter and the cumulative excitation energy characteristics as the exponent, a natural exponential function is constructed, and the result is the attenuation factor.

[0065] The attenuation factor ranges from greater than zero to less than or equal to one. When the cumulative excitation energy is zero, the attenuation factor is exactly one, corresponding to the initial physical state where the dynamic angle of repose is equal to the reference angle of repose under vibration-free conditions. As the cumulative excitation energy increases, the attenuation factor decreases non-linearly, and the dynamic angle of repose decreases monotonically, accurately reproducing the physical evolution law of bulk materials becoming flatter as they move. Multiplying the preset reference angle of repose by the attenuation factor yields the dynamic angle of repose of the current virtual slice, mathematically expressed as follows:

[0066] ;

[0067] In the formula, Indicates the first A virtual slice in spatial coordinates The dynamic angle of repose at the location; Indicates the preset reference angle of repose; This represents the fluidization sensitivity parameter; This indicates the cumulative excitation energy characteristics of the slice. The dynamic angle of repose is the core quantity characterizing the lateral widening of the virtual slice: the smaller the dynamic angle of repose, the more flat and wide the coal pile tends to be, and the greater the lateral widening.

[0068] After obtaining the dynamic repose angle of the virtual slice, the morphology analysis module further combines the initial morphological features to deduce the dynamic contour parameters of the slice at the current position, namely the actual bottom width and the actual peak height, and uses the ratio of the two as the collapse index.

[0069] To facilitate engineering calculations, this invention equates the geometry of the coal flow cross-section on the trough conveyor belt to an isosceles triangle model constrained by a dynamic angle of repose. In this model, the base of the cross-section corresponds to the actual bottom width, the vertical height of the cross-section corresponds to the actual peak height, and the angle between the two sides and the base is equal to the current dynamic angle of repose. Based on this geometric model, the triangle area formula establishes a constraint relationship between the cross-sectional area, the bottom width, and the peak height; the geometric definition of the dynamic angle of repose establishes another constraint relationship between the peak height and the bottom width. Under the premise of cross-sectional area conservation, the following derivation is made simultaneously from the above two geometric constraints:

[0070] Calculation of actual bottom width: Divide the initial cross-sectional area by the tangent of the dynamic repose angle, perform a square root operation on the result, and then multiply the result by two to obtain the current actual bottom width of the virtual slice. Its mathematical expression is as follows:

[0071] ;

[0072] Calculation of actual peak height: Multiply the initial cross-sectional area by the tangent of the dynamic repose angle, and perform a square root operation on the result to obtain the current actual peak height of the virtual slice. Its mathematical expression is as follows:

[0073] ;

[0074] In the above two formulas, This represents the initial cross-sectional area in the initial morphological features. The dynamic repose angle of the current virtual slice. and Together, these constitute the dynamic contour parameters, describing the actual geometry of the slice at its current spatial location. The ratio of the actual peak height to the actual bottom width is defined as the collapse index, mathematically expressed as follows:

[0075] ;

[0076] In the formula, For the first A virtual slice in spatial coordinates The slump index, or aspect ratio of the cross-section, is a core characteristic describing the evolution of coal flow morphology. In the tail loading area, the coal pile is tall and steep, with the dynamic angle of repose approximately equal to the reference static angle of repose, resulting in the highest slump index. As the vibration fluidization effect accumulates, the dynamic angle of repose continuously decreases, the actual bottom width increases while the actual peak height decreases, and the slump index continues to decrease monotonically. When reaching the middle and lower reaches of the conveyor, the coal flow has significantly flattened and widened, and the slump index is at a lower level. The slump index condenses the geometric changes of the cross-section into a scalar characteristic, serving as a crucial bridge connecting the two core aspects of morphological perception and resistance reconstruction.

[0077] As can be seen from the above derivation, under the constraint of initial cross-sectional area conservation, the actual bottom width increases as the dynamic angle of repose decreases, while the actual peak height decreases as the dynamic angle of repose decreases; both follow a strict physical-geometric relationship. Specifically, when the dynamic angle of repose approaches zero, the coal flow tends to be completely flattened (the slump index approaches zero); when the dynamic angle of repose equals the reference static angle of repose, the slump index equals the initial aspect ratio, demonstrating complete physical consistency and verifying the correctness of the model.

[0078] The resistance assessment module is driven by the collapse index output by the morphology analysis module. It reconstructs the preset unit deformation resistance through a nonlinear correction factor model, and then performs spatial integration of the reconstructed deformation resistance of each slice along the transmission path to finally obtain the equivalent total running resistance that has been accurately eliminated by morphology error.

[0079] The equivalent mass of the virtual slice is calculated once during slice generation in the processing module and encapsulated into the data packet, then directly invoked in the resistance assessment module. The calculation of the equivalent mass is based on the core constraint of mass conservation, using the initial cross-sectional area... Preset physical space step size With preset bulk material density Multiplying the three together, we get the following mathematical expression:

[0080] ;

[0081] In the formula, For the first The equivalent quality of a virtual slice; This is the initial cross-sectional area; Preset physical space step size; The preset density (bulk density) of the target bulk material is used, and since the equivalent mass remains unchanged throughout the entire life cycle of the slice, the mass parameter reference in the resistance assessment module is simple and reliable.

[0082] Material deformation resistance refers to the running resistance component generated by the friction and wear between internal particles when bulk materials sag between idlers. The higher the material cross-section (larger slump index), the greater the internal normal pressure between particles, and the higher the shear slip resistance; the flatter the material cross-section (smaller slump index), the smaller the internal compressive pressure between particles, and the resistance decreases non-linearly. This invention introduces a power function correction factor based on the slump index to characterize the above non-linear relationship: applying a preset resistance parameter to the slump index... For exponentiation, the result of the exponentiation is compared with a preset scale parameter. Multiply by these to obtain the correction factor. Based on the correction factor, equivalent mass, and preset unit deformation resistance, the reconstructed first... The mathematical expression for the preset unit deformation resistance (i.e., the actual material deformation resistance) of a virtual slice is as follows:

[0083] ;

[0084] In the formula, For the first Preset unit deformation resistance after reconstruction of a virtual slice; The preset unit deformation resistance represents the baseline value of the deformation resistance when the material passes through the idler roller in a standard shape (unit mass, unit aspect ratio); For equivalent slice quality; It is the acceleration due to gravity; This represents the collapse index of the slice; The value ranges from 0.5 to 1, and its physical meaning is: when When the value is less than 1, the drag decreases sublinearly as the collapse index decreases, which is more consistent with the nonlinear law observed in granular experiments than the simple linear assumption.

[0085] Preset scale parameters The correction factor is used to characterize the dimensionality adaptation and working condition response intensity. Its function is to adjust the power function calculation result of the collapse index from a dimensionless quantity to a value similar to the preset unit deformation resistance. The matching physical magnitudes reflect the sensitivity of the deformation resistance of the target bulk material to the change of the slump index under the current belt conveyor roller arrangement and operating conditions. The larger the value, the more sensitive the deformation resistance is to changes in the slump index, and vice versa.

[0086] Preset scale parameters The calibration test predetermines the following: for the target belt conveyor and the target bulk material, the cross-sectional aspect ratio of the loading area at the tail end of the conveyor is selected to be close to the initial morphological characteristics (i.e., the collapse index is close to the preset initial benchmark value). The location of the point is used as the calibration operating point, and the actual deformation resistance at the calibration operating point is measured using a torque sensor or weighing device. Combined with the predetermined preset resistance parameters The preset unit deformation resistance and the equivalent mass corresponding to the calibration operating point ,in accordance with The mathematical relation is obtained by inverse solution:

[0087] ;

[0088] Alternatively, based on multiple sets of measured deformation resistance data at different locations along the transmission path, the least squares fitting method can be used to simultaneously determine... and The optimal combination of values ​​is used to improve the fitting accuracy of the correction factor across the entire range.

[0089] From a physical perspective, traditional speed control systems are equivalent to forcibly setting the collapse index of all virtual slices to a constant value corresponding to the initial state of the tail section, resulting in a long-term overestimation of the deformation resistance of the mid-to-downstream slices. In contrast, this invention, through real-time dynamic updates of the collapse index, accurately maps the actual shape of each slice to the corresponding resistance correction factor, fundamentally eliminating this systematic overestimation error.

[0090] The dynamic total deformation resistance is obtained by summing the preset unit deformation resistances of each virtual slice reconstructed on the current transmission path. Here, the transmission path refers to the single-sided belt currently responsible for transporting the target bulk material. Combined with the preset no-load resistance parameters and lifting resistance parameters of the belt conveyor, the three are superimposed to obtain the equivalent total operating resistance, which is mathematically expressed as follows:

[0091] ;

[0092] In the formula, This represents the equivalent total operating resistance. This is the no-load resistance parameter, which reflects the basic frictional resistance of the belt and the load-bearing idler group during no-load operation and is independent of the coal flow load. To improve the resistance parameter, reflecting the additional traction force required for the conveyor to overcome the gravitational component of the material when the conveyor is arranged at an angle; This represents the total number of virtual slices on the current transmission path, i.e., the number of valid slices in the shift register queue.

[0093] The equivalent total operating resistance accurately eliminates morphological errors and is far lower than traditional estimates, especially in the downstream section of the conveyor. The dynamic total deformation resistance component is significantly lower than the fixed coefficient estimate of the traditional system, directly reflecting the true low-resistance state after the coal flow vibrates, fluidizes, and collapses. This provides a precise and reliable load constraint basis for subsequent control modules and is the core data support for breaking through the traditional conservative speed reduction limitations.

[0094] The control module uses the equivalent total operating resistance as the core input and generates the target operating frequency command and implements closed-loop feedback updates according to the following logic. First, the equivalent total operating resistance is multiplied by the preset drive drum radius of the belt conveyor to obtain the steady-state torque required to maintain stable operation under the current working conditions. The drive drum radius is a key mechanical parameter that converts the belt traction tension into the motor shaft torque and is stored as a preset system constant. The steady-state torque requirement represents the minimum output torque required to maintain the target belt speed under the precisely reconstructed low-resistance state and is the core calculation for subsequent constraint verification.

[0095] Secondly, the steady-state required torque is compared and verified with the maximum permissible output torque in the preset constraints. The maximum permissible output torque is a core boundary constraint to ensure the safe operation of the main drive motor, and its value is determined by the motor's rated torque and safety margin coefficient. When the steady-state required torque is less than or equal to the maximum permissible output torque, it means that the proposed speed reduction command is within the safe operating range of the motor's load capacity, and the system continues to execute subsequent speed reduction logic; if the steady-state required torque exceeds this limit, the system maintains the current operating frequency and waits for the next control cycle to re-evaluate.

[0096] When the steady-state torque demand meets the constraints, the system obtains the current real-time coal feed rate, divides it by the current optimal operating linear density in the preset constraints, and obtains the target operating belt speed. Then, the target operating belt speed is multiplied by the preset conversion parameter to complete the linear mapping from belt speed to frequency, generating a target operating frequency command and sending it to the frequency converter for execution. The real-time coal feed rate is the coal feed quality per unit time output by the upstream coal feeding equipment; the optimal operating linear density is the expected load per unit length of the belt in the preset constraints, representing the optimal fullness target; the target operating belt speed is the minimum belt speed required to maintain the optimal fullness of the belt at the current coal feed rate; and the preset conversion parameter is a calibration constant for converting the belt speed into the frequency converter output frequency.

[0097] From a physical perspective, traditional systems suffer from inflated steady-state torque requirements due to overestimation of resistance, triggering overload protection mechanisms and thus refusing to execute speed reduction commands. In contrast, this invention precisely reconstructs the equivalent total operating resistance, ensuring that the calculated steady-state torque requirement falls strictly within the safe operating range of the maximum permissible output torque. This eliminates the false speed reduction limitation imposed due to misjudgment of overload, fully releasing the energy-saving speed reduction potential of the frequency converter.

[0098] During the execution of the target operating frequency command by the main drive motor, its stator excitation current signal and torque current signal are acquired in real time, and the rate of change of their phase shift angles is used as feedback optimization parameters. The stator excitation current and torque current correspond to the flux component and torque component in the vector control framework of the asynchronous motor, respectively. Their phase shift angles reflect the dynamic position of the motor's electromagnetic operating point, while the rate of change of the phase shift angles sensitively indicates the rate at which the motor approaches the stability boundary under the current load conditions. It is a sensitive electrical indicator for sensing the actual load level and overload risk.

[0099] When feedback optimization parameters Greater than or equal to the preset critical threshold This indicates that the motor load has approached its stable operating boundary, and the current optimal operating linear density setting is too low (corresponding to a low belt speed command), posing a potential risk of motor instability. At this point, the system updates the preset constraints: feeding back the optimized parameters... With preset critical threshold The difference between the preset compensation parameters Multiply them to obtain the linear density adjustment value;

[0100] The current optimal operating line density Subtract the linear density adjustment value to obtain the transient operating linear density; then take the larger value between the transient operating linear density and the minimum allowable operating linear density as the updated optimal operating linear density, the mathematical expression of which is as follows:

[0101] ;

[0102] ;

[0103] In the formula, For transient operating line density; The optimal running line density before the update; The sensitivity of the linear density adjustment to the feedback deviation is controlled by preset compensation parameters. The updated optimal running line density; To ensure that the conveying efficiency meets minimum production requirements, the minimum allowable operating line density is maintained.

[0104] The core logic of this feedback update mechanism is as follows: When the motor shows signs of approaching overload, the system actively increases the optimal operating linear density, that is, increases the expected load per unit length of the belt. This is equivalent to requiring a higher belt speed in the next control cycle, thereby alleviating the motor load and restoring stable operation. The update amount is proportional to the extent to which the feedback optimization parameter exceeds the critical threshold. Both the adjustment sensitivity and adjustment amplitude can be tuned through preset compensation parameters. The minimum operating linear density constraint ensures that the system does not sacrifice energy-saving effects due to excessive speed increase. When the feedback optimization parameter is lower than the preset critical threshold, the preset constraint remains unchanged, and the system continues to perform energy-saving speed regulation under the current optimal operating linear density.

[0105] Through the aforementioned feedback optimization mechanism, the preset constraints can be updated in each control cycle. The system can continuously approach the optimal energy-saving operating point under complex coupled disturbances such as different coal feed rates, different belt tension states, and different vibration conditions, forming a complete self-consistent closed-loop control system from physical perception, morphological deduction, resistance reconstruction, speed regulation execution to state feedback and constraint updates. From the perspective of a positive closed loop:

[0106] After the frequency converter executes the speed reduction command, the actual running time of the belt is extended, and the duration of vibration excitation absorbed by each virtual slice on the transmission path increases accordingly. This further increases the accumulated excitation energy, leads to a more thorough coal flow collapse, a further decrease in the dynamic angle of repose, and a further reduction in the equivalent total operating resistance. Consequently, the system operates more smoothly and energy-efficiently at low speeds, forming a positively self-consistent closed loop where the physical process and control logic mutually reinforce each other. This inherent physical self-consistency is the essential advantage of this invention over general empirical compensation-based speed regulation strategies.

[0107] Through the above steps, the present invention can achieve the following technical effects: 1) The present invention introduces the long-neglected physical phenomenon of dynamic collapse of bulk material caused by vibration fluidization into the speed control system of belt conveyor for the first time, and constructs a dynamic rest angle nonlinear decay model based on accumulated excitation energy, breaking the rigid assumption that the coal flow morphology of the traditional control system is constant from beginning to end, and realizing the technical leap from static load following to bulk morphology evolution driven.

[0108] 2) By discretizing the target bulk material into virtual slices with independent data packets and constructing a shift register queue for real-time tracking, this invention achieves synchronous and accurate simulation of the true coal flow morphology at all locations along the entire conveyor line, providing a solid data foundation for the refined reconstruction of resistance along the line. 3) The nonlinear coupling model of collapse index and resistance correction factor constructed in this invention accurately eliminates the false resistance overestimation component that has long existed in traditional speed control systems from the total resistance, enabling the frequency converter to break through the original conservative speed reduction limit in the mid-to-downstream section. Under normal continuous coal supply conditions, it can reduce the output frequency more than traditional algorithms, and the comprehensive energy efficiency ratio significantly surpasses all existing apparent control systems, demonstrating outstanding substantial progress.

[0109] 4) This invention further introduces a feedback optimization mechanism based on the phase shift angle change rate of the stator excitation current and torque current of the main drive motor. This mechanism can sense the speed regulation effect in real time and dynamically correct the optimal operating line density constraint, enabling the system to continuously approach the optimal energy-saving operating point under complex operating conditions, forming a self-consistent closed loop in both physics and logic. 5) The technical solution described in this invention is entirely based on the existing conveyor hardware platform. All functions can be achieved through software algorithm upgrades without the need for additional mechanical equipment or modification of the belt conveyor. This results in extremely low engineering implementation costs and broad prospects for widespread application.

[0110] In another embodiment, this application also provides a computer storage medium storing computer-executable instructions, which, when executed, implement the aforementioned intelligent speed regulation and energy feedback system based on a coal mine belt conveyor.

[0111] The computer-executable instructions are burned into or installed in the industrial computer or programmable logic controller of the belt conveyor control system in the form of firmware or software programs. They acquire sensor data by calling hardware interfaces, execute the calculation logic of the above steps through the algorithm calculation module, and send frequency control commands to the frequency converter through the communication interface. The computer storage medium can be FLASH memory, EEPROM, disk, or other types of non-volatile storage media; the specific form does not affect the implementation of the technical solution of this invention.

[0112] The above embodiments are only used to illustrate the technical methods of this application and are not intended to limit it. Although this application has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical methods of this application without departing from the spirit and scope of the technical methods of this application.

Claims

1. A smart speed regulation and energy feedback system for coal mine belt conveyors, characterized in that, Includes the following modules: The feature extraction module is used to obtain the initial morphological features of the target bulk material and the vibration features, belt speed features, and displacement features of the belt conveyor during operation. The processing module is used to discretize the target bulk material into continuous virtual slices based on the displacement characteristics, and to convert the vibration characteristics into the cumulative excitation energy characteristics of the virtual slices on the transmission path based on the belt speed characteristics. The morphology analysis module is used to obtain the dynamic angle of repose characterizing the lateral widening of the virtual slice, and to deduce the dynamic contour parameters of the virtual slice by combining the initial morphological features and the cumulative excitation energy features, and to generate the collapse index characterizing the material morphology change. The resistance assessment module is used to reconstruct the preset unit deformation resistance of the virtual slice based on the collapse index, and to spatially integrate the reconstructed preset unit deformation resistance along the transmission path to obtain the equivalent total operating resistance. The control module is used to extract the steady-state demand torque of the current operating condition based on the equivalent total operating resistance. When the steady-state demand torque meets the preset constraints, a target operating frequency command is generated. After executing the target operating frequency command, feedback optimization parameters characterizing the control effect are obtained, and the preset constraints are updated according to them.

2. The intelligent speed regulation and energy feedback system for coal mine belt conveyors according to claim 1, characterized in that, The process of obtaining a virtual slice includes: The angular displacement pulse count and instantaneous speed conversion value of the main drive motor of the belt conveyor are obtained as displacement characteristics and belt speed characteristics, respectively. The acceleration signal of the vibration sensor along the belt conveyor is obtained, and the parameter value perpendicular to the belt direction is extracted as vibration characteristics. When the cumulative increase of the displacement feature reaches the preset physical space step size, the point cloud data of the current cross section of the target bulk material is obtained, and the initial cross-sectional area, initial peak height and initial bottom width are extracted as initial morphological features based on it. The initial morphological features, timestamp information, and spatial coordinate information of the current section are encapsulated into the same data packet, and the data packet is written to the tail of the shift register queue to generate a virtual slice of the current section.

3. The intelligent speed regulation and energy feedback system for coal mine belt conveyors according to claim 2, characterized in that, The process of obtaining the characteristics of cumulative excitation energy includes: Divide the square of the vibration characteristic by the belt velocity characteristic to obtain the excitation force density per unit space length, and multiply the excitation force density by the preset energy conversion parameter to obtain the spatial energy differential term; The cumulative excitation energy characteristics of the virtual slice are obtained by performing a definite integral operation on the spatial energy differential term from the starting point of the transmission path to the current spatial coordinates. ; ； in, Indicates the first A virtual slice in spatial coordinates The characteristics of the cumulative excitation energy at the location, Represents spatial coordinates Vibration characteristics at that location Represents spatial coordinates Belt speed characteristics at the location, This indicates the preset energy conversion parameters.

4. The intelligent speed regulation and energy feedback system for coal mine belt conveyors according to claim 1, characterized in that, The process of obtaining the dynamic angle of repose includes: Obtain the preset reference angle of repose and fluidization sensitivity parameters of the target bulk material, and based on the accumulated excitation energy characteristics... Attenuation factor obtained from fluidization sensitivity parameter ; The dynamic angle of repose of the virtual slice is obtained based on the reference angle of repose and the attenuation factor. ,in, Indicates the first A virtual slice in spatial coordinates The dynamic angle of repose at that point Indicates the reference angle of repose. This represents the fluidization sensitivity parameter.

5. The intelligent speed regulation and energy feedback system for coal mine belt conveyors according to claim 3, characterized in that, The process of generating the collapse index includes: The initial cross-sectional area in the initial morphological features Divided by the dynamic angle of repose The tangent value is taken, and the square root of the division result is multiplied by two to obtain the current actual bottom width of the virtual slice. ; Multiply the initial cross-sectional area in the initial morphological features by the tangent of the dynamic rest angle, and then take the square root of the multiplication result to obtain the current actual peak height of the virtual slice. The actual bottom width and the actual peak height are used as dynamic contour parameters, and the ratio between the two is used as the collapse index. ; ， ， 。 6. The intelligent speed regulation and energy feedback system for coal mine belt conveyors according to claim 5, characterized in that, The process of obtaining the equivalent total operating resistance includes: Based on the initial cross-sectional area in the initial morphological features and the physical space step size and the preset density of the target bulk material Obtain the equivalent quality of the virtual slice ; Regarding the collapse index Execute with preset resistance parameters For exponentiation, the result of the exponentiation is compared with a preset scale parameter. Multiplication yields the correction factor ; Based on the correction factor, the equivalent mass, and the preset unit deformation resistance Obtain the preset unit deformation resistance after reconstruction ,in, It is the acceleration due to gravity; The dynamic total deformation resistance is obtained by summing the preset unit deformation resistances of each virtual slice reconstructed on the current transmission path, and then combining this with the preset no-load resistance parameters and lifting resistance parameters of the belt conveyor to obtain the equivalent total operating resistance. ; ； in, Indicates the no-load resistance parameter. Indicates the resistance parameter. This indicates the total number of virtual slices on the current transmission path.

7. The intelligent speed regulation and energy feedback system for coal mine belt conveyors according to claim 2, characterized in that, The process of generating the target operating frequency instruction includes: The steady-state required torque is obtained by multiplying the equivalent total operating resistance by the preset drive drum radius of the belt conveyor. When the steady-state required torque is less than or equal to the maximum allowable output torque in the preset constraints: The current real-time coal feed rate is obtained and divided by the current optimal operating line density in the preset constraints to obtain the target operating belt speed. The target operating belt speed is multiplied by the preset conversion parameters to obtain the target operating frequency, and the target operating frequency command is generated.

8. The intelligent speed regulation and energy feedback system for coal mine belt conveyors according to claim 7, characterized in that, The process of updating preset constraints includes: During the execution of the target operating frequency command by the main drive motor, its stator excitation current signal and torque current signal are acquired in real time, and the phase shift angle change rate of the two is obtained as a feedback optimization parameter. When the feedback optimization parameter Greater than or equal to the preset critical threshold hour: Compare the difference between the two with the preset compensation parameter. Multiplying them yields the linear density adjustment value, which is the current optimal operating linear density. Subtracting the linear density adjustment value yields the transient operating linear density. To obtain the updated optimal running line density ,in, The minimum permissible operating line density.

9. A method for intelligent speed regulation and energy feedback based on coal mine belt conveyors, characterized in that, Includes the following steps: Acquire the initial morphological characteristics of the target bulk material and the vibration characteristics, belt speed characteristics, and displacement characteristics of the belt conveyor during operation; Based on the displacement characteristics, the target bulk material is discretized into continuous virtual slices, and based on the belt speed characteristics, the vibration characteristics are converted into the cumulative excitation energy characteristics of the virtual slices on the transmission path. The dynamic repose angle characterizing the lateral widening of the virtual slice is obtained, and the dynamic contour parameters of the virtual slice are deduced by combining the initial morphological features and the cumulative excitation energy features, and the collapse index characterizing the material morphological change is generated. Based on the collapse index, the preset unit deformation resistance of the virtual slice is reconstructed, and the reconstructed preset unit deformation resistance is spatially integrated along the transmission path to obtain the equivalent total operating resistance. Based on the equivalent total operating resistance, the steady-state demand torque under the current operating condition is extracted. When the steady-state demand torque meets the preset constraints, a target operating frequency command is generated. After executing the target operating frequency command, feedback optimization parameters characterizing the control effect are obtained, and the preset constraints are updated accordingly.

10. A computer storage medium storing computer-executable instructions, characterized in that, When the computer-executable instructions are executed, they implement the intelligent speed regulation and energy feedback system based on a coal mine belt conveyor as described in any one of claims 1-8.

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