Transfer storage bin discharging adjusting system and method based on horizontal continuous loading

Abstract

The invention discloses a transshipment storage bin discharging adjusting system and adjusting system based on horizontal continuous loading. The transshipment storage bin discharging adjusting system comprises a transshipment machine analysis module, a storage bin collection module and an analysis regulation and control module. The reversed loader analysis module is used for collecting carrying data of a reversed loader and analyzing the carrying data to generate carrying parameters; the carrying parameters are transmitted to the reversed loader and the storage bin, and the reversed loader and the storage bin are controlled in real time; the storage bin acquisition module is used for acquiring operation data in the storage bin; the analysis regulation and control module obtains the internal operation data of the storage bin and the carrying data and carrying parameters of the reversed loader, the real-time impact force of discharging of the storage bin is obtained, and then the discharging weight of the reversed loader is calibrated in real time. The method has the beneficial effects that a nonlinear calibration model is established according to impact force, vibration acceleration and sensor response characteristics, interference of impact vibration on weighing signals is effectively eliminated, and the real blanking weight is output.

Description

Technical Field

[0001] This invention belongs to the field of material transfer and adjustment technology, specifically relating to a material transfer and storage bin unloading adjustment system based on horizontal continuous loading, and also relating to a material transfer and storage bin unloading adjustment method based on horizontal continuous loading. Background Technology

[0002] In the field of bulk material transportation and storage in coal mines, transfer machines and storage silos are key equipment in the intermediate links, and their loading and unloading processes directly affect the continuity and uniformity of the entire production line.

[0003] Existing transfer and unloading control systems have the following problems: Traditional transfer machines mostly use fixed speed or manual adjustment to control the loading capacity, failing to dynamically adjust the transfer speed and angle according to the real-time status of the storage bin, resulting in local accumulation or empty bins. Because the material is affected by impact, vibration, and air disturbance during its descent, the weighing sensor signal often experiences instantaneous fluctuations, leading to discrepancies between the actual unloaded weight and the theoretical weight, affecting measurement accuracy and bin balance.

[0004] Therefore, there is an urgent need for a system that can synchronously sense, regulate, and self-calibrate the transfer and unloading processes under horizontal continuous loading conditions, so as to improve unloading accuracy and material flow balance. Summary of the Invention

[0005] The first objective of this invention is to provide a material handling and adjustment system for a transfer and storage silo based on horizontal continuous loading, which solves the problems of real-time coordinated control of the transfer and storage silo unloading process and large weight detection errors in the prior art.

[0006] The second objective of this invention is to provide a method for adjusting the unloading of a transfer storage bin based on horizontal continuous loading.

[0007] The first technical solution adopted in this invention is a material feeding and adjustment system for a horizontally continuously loaded transfer and storage silo, which includes a transfer machine and a storage silo, and also includes a transfer machine analysis module, a storage silo acquisition module, and an analysis and control module. The transfer machine analysis module is used to collect the transport data of the transfer machine, analyze the transport data to generate transport parameters, and transmit the transport parameters to the transfer machine and the storage silo for real-time control of the transfer machine and the storage silo. The storage silo data acquisition module is used to collect operational data inside the storage silo; The analysis and control module acquires the internal operating data of the storage silo and the transport data and parameters of the transfer machine to obtain the real-time impact force of the material being discharged from the storage silo, and then calibrates the discharge weight of the transfer machine in real time.

[0008] The invention is further characterized by: The transshipment machine analysis module includes a three-dimensional laser rangefinder, an inertial attitude sensor, a vibration sensor, a first weight sensor, a second weight sensor, a strain sensor, and a tilt sensor; The three-dimensional laser rangefinder is installed above the transfer machine, the inertial attitude sensor is fixed to the transfer machine body, the vibration sensor is installed on the transfer machine body, the first weight sensor is installed at the bottom of the storage bin, and the second weight sensor is installed in the lifting mechanism, bucket support point, or conveyor belt load-bearing idler of the transfer machine; the tilt sensor is installed on the fixed bracket of the transfer machine guide chute; and the strain sensor is installed on the load-bearing beam of the transfer machine frame. The material storage bin acquisition module includes a first weight sensor and a feeding speed sensor; The feeding speed sensor is installed above the feeding position of the storage hopper.

[0009] The second technical solution adopted in this invention, based on a method for adjusting the unloading of a horizontally continuously loaded transfer storage silo, includes the following steps: S1. The transfer machine analysis module collects the transport data of the transfer machine, analyzes the transport data to generate transport parameters, and transmits the transport parameters to the transfer machine and the storage silo to control the operation of the transfer machine and the storage silo. S2, The storage bin acquisition module collects the operating data inside the storage bin; S3. The analysis and control module analyzes the operating data inside the storage silo and the transport data output by the transfer machine to obtain the actual weight of the material discharged by the transfer machine.

[0010] Another feature of the technical solution of this invention is that: The transport data mentioned in S1 is: Discrete point cloud on the surface of a material body measured by a three-dimensional laser rangefinder; Inertial sensors collect real-time data on the triaxial acceleration and triaxial angular velocity of the transfer machine; The first weight sensor collects the weight of the material in the storage bin; the second weight sensor collects the weight of the material being transported by the lifting mechanism of the transfer machine, the bucket support point, or the load-bearing idler of the conveyor belt.

[0011] The process of analyzing transport data is as follows: The discrete point cloud of the material surface on the transfer machine measured by the three-dimensional laser ranging device is... ,in For planar grid coordinates, The stacking height of the corresponding points; using point cloud. Fit the height distribution function of the stacked surface ; By analyzing the height function Calculate the theoretical volume V of the transported material by performing a double integral over the projected area A of the material accumulation.r ,Right now:

[0012] Among them, is the shape correction factor, used to correct volume deviations caused by irregular stacking, with a value range of 0.8 to 1.0; A is the projected area of ​​the material stacking; , All are spatial integral variables; The real-time three-axis attitude angle data of the transfer machine are calculated by using inertial sensors to collect the three-axis acceleration and three-axis angular velocity data in real time, forming an attitude vector group: ,in The pitch angle of the transfer machine. The roll angle of the transfer machine. This refers to the yaw angle of the transfer aircraft; Using attitude vector groups Establish the attitude transformation matrix T(α) t ,β t γ t The attitude compensation of the stacked surface model is performed so that it can return to the horizontal reference coordinate system under any tilt state. After attitude compensation, the center of gravity of the material accumulation is solved, and the coordinates of the center of gravity are calculated. , , Then, based on the vertical coordinates of the stacked centroid... Based on the distribution of geometric shapes, calculate the key morphological parameters of the accumulation; Combined with the load weight W from the transfer machine's load weight sensor signal m Mapping function with material feeding position The local volume of the material feeding area is divided into V sections. d Mapped to theoretical volume V r The material weight W at the material feeding position is obtained. d ; The weight W of the theoretical volume is obtained based on the analysis of height, length, width, and theoretical density. t The real-time weighing data of the transfer machine is obtained from the second weight sensor, and then the actual unloading weight W is obtained. a The transport parameters are calculated by the ratio of theoretical weight to actual weight; the transport parameters are compactness coefficients. and control coefficient ; Based on the compactness coefficient The calculation results control the vibration equipment below the transfer machine; based on the adjustment coefficient... The calculation results are used to adjust the reprint speed.

[0013] The calculation method for A is to extract all points from the surface point cloud obtained by scanning. Effective height points > 0 are vertically projected onto the xy horizontal plane to form a two-dimensional point set. The outermost boundary of these points is identified using a contour extraction algorithm to obtain a closed polygonal region. The area of ​​this polygonal region is the projected area A of the material accumulation. Calculate the coordinates of the centroid ( , , The formula for ) is:

[0014] in, This represents the material density at grid cell (i, j); Let x represent the x-coordinate of the i-th grid cell; This represents the y-coordinate of the i-th row of grid cells; Represents the z-coordinate of the grid cell (i,j); The formula for calculating the key morphological parameters of the deposit is:

[0015] in: The height of the center of gravity is the vertical coordinate of the stacked center of gravity minus the reference height of the transfer machine's base plate. ; The average effective width is the maximum width of the stack in the lateral direction. The average effective length is the maximum projected length of the pile along the transfer direction; The weight of theoretical volume The calculation formula is:

[0016] in The height of the center of gravity; This represents the average effective width. The average effective length; This is the theoretical density of the material; Material weight for:

[0017] in The spatial mapping weight function is determined based on the relative positional relationship between the unloading point of the transfer machine and the discharge port of each storage bin. Its value range is [0,1], and it satisfies that the sum of the weights of the discharge ports of each storage bin corresponding to the same unloading point is 1. This refers to the local volume division of the material feeding area; This represents the theoretical volume of the transported material. The first weight sensor collects the unloading weight from the storage bin; Spatial mapping weight function Determined by the following formula:

[0018] in, This is the horizontal distance from the unloading point of the transfer machine to the discharge port of the corresponding storage bin; The maximum effective mapping distance is preset, and its value is determined according to the structural dimensions of the storage silo, generally ranging from 2m to 6m. This refers to the number of feed inlets. denoted as , which is the horizontal distance between the unloading point of the transfer machine and the center position of the discharge port of the p-th storage silo.

[0019] Tightness coefficient The calculation formula is:

[0020] in Real-time weighing data collected by the second weight sensor; The weight of the material on the transfer machine is the theoretical volume of the material. Control coefficient The calculation formula is:

[0021] in Real-time material transfer volume; For material transfer volume; Real-time material transfer volume The calculation formula is:

[0022] in This represents the current transfer speed of the transfer machine; The duration of a single feeding operation; Real-time weighing data collected by the second weight sensor.

[0023] Based on the compactness coefficient The specific process of controlling the vibration device below the transfer machine is as follows: When At that time, vibration is performed by a vibrating device installed below the transfer machine, making the material pile up more compactly; when During normal operation, the vibration equipment should not be started. According to the control coefficient The specific process for adjusting the reprint speed is as follows: When If the value is greater than 1, it indicates that the current reprint rate exceeds the planned rate. Therefore, the reprint speed should be reduced to allow for faster reprinting. =1; when If the value is less than 1, it indicates that the reprint rate is insufficient. The reprint speed should be increased to... =1; when When =1, the transfer machine is in its optimal state.

[0024] The specific calculation process for the actual weight of the material discharged from the transfer machine in S3 is as follows: Multimodal sensing data was collected by multimodal sensing devices deployed under the frame and bin opening of the transfer conveyor. This data was then input into an impact weight calibration model to calculate and analyze the actual weight of the material discharged from the transfer conveyor. ; The impact weight calibration model calculates the actual weight of the material being fed by the transfer machine. The method is as follows:

[0025] in, The first weight sensor collects the unloading weight from the storage bin; The instantaneous impact force during material feeding; The instantaneous vibration acceleration of the transfer machine platform is collected by the vibration sensor; η t α1 and β1 are impact response correction factors used to characterize the impact characteristics of materials and differences in silo morphology; α1 and β1 are model self-learning parameters, adjusted based on historical sample data.

[0026] The multimodal sensing device includes a vibration sensor, a strain sensor, and a first weight sensor; Vibration sensors collect instantaneous vibration acceleration data from the transfer conveyor platform. The first weight sensor collects the unloading weight of the storage bin. The strain mass of the structure was acquired by the strain sensor. ; Instantaneous impact force during material feeding Data collected by vibration sensors Structural strain mass acquired by strain sensors The calculation is as follows:

[0027] in The strain mass of the structure is obtained by the strain sensor; The instantaneous vibration acceleration of the transfer machine platform is collected by the vibration sensor.

[0028] The beneficial effects of this invention are: 1. This invention uses the transfer machine analysis module and the storage bin acquisition module to work together to obtain the transfer volume, height, speed and feeding status in real time, so as to achieve the matching of loading capacity and feeding rate and avoid uneven stacking or material interruption.

[0029] 2. This invention establishes a nonlinear calibration model based on impact force, vibration acceleration, and sensor response characteristics, effectively eliminating the interference of impact vibration on the weighing signal and outputting the true material weight. Attached Figure Description

[0030] Figure 1 This is the overall architecture diagram of the material unloading and adjustment system of the transfer and storage silo based on horizontal continuous loading of the present invention. Detailed Implementation

[0031] The following detailed description is provided in conjunction with the accompanying drawings and specific embodiments.

[0032] Example 1 like Figure 1 As shown, the material handling and adjustment system for the transfer and storage bin based on horizontal continuous loading includes a transfer machine and a storage bin, as well as a transfer machine analysis module, a storage bin data acquisition module, and an analysis and control module. The transfer machine analysis module is used to collect the transport data of the transfer machine, analyze the transport data to generate transport parameters, and transmit the transport parameters to the transfer machine and the storage silo for real-time control of the transfer machine and the storage silo. The storage silo data acquisition module is used to collect operational data inside the storage silo; The analysis and control module acquires the internal operating data of the storage silo and the transport data and parameters of the transfer machine to obtain the real-time impact force of the material being discharged from the storage silo, and then calibrates the discharge weight of the transfer machine in real time.

[0033] The transfer machine includes equipment such as the car body, gantry frame, lifting mechanism, bucket, frame, belt, and guide chute.

[0034] Example 2 The material handling and regulation system for a horizontally continuous loading transfer and storage bin includes a transfer machine and a storage bin, as well as a transfer machine analysis module, a storage bin data acquisition module, and an analysis and control module. The transfer machine analysis module is used to collect the transport data of the transfer machine, analyze the transport data to generate transport parameters, and transmit the transport parameters to the transfer machine and the storage silo for real-time control of the transfer machine and the storage silo. The storage silo data acquisition module is used to collect operational data inside the storage silo; The analysis and control module acquires the internal operating data of the storage silo and the transport data and parameters of the transfer machine to obtain the real-time impact force of the material being discharged from the storage silo, and then calibrates the discharge weight of the transfer machine in real time.

[0035] The transshipment machine analysis module includes a three-dimensional laser rangefinder, an inertial attitude sensor, a vibration sensor, a first weight sensor, a second weight sensor, a strain sensor, and a tilt sensor; The three-dimensional laser rangefinder is installed above the transfer machine, the inertial attitude sensor is fixed to the transfer machine body, the vibration sensor is installed on the transfer machine body, the first weight sensor is installed at the bottom of the storage bin, and the second weight sensor is installed in the lifting mechanism, bucket support point, or conveyor belt load-bearing idler of the transfer machine; the tilt sensor is installed on the fixed bracket of the transfer machine guide chute; and the strain sensor is installed on the load-bearing beam of the transfer machine frame. The material storage bin acquisition module includes a first weight sensor and a feeding speed sensor; The feeding speed sensor is installed above the feeding position of the storage hopper.

[0036] Example 3 The material unloading adjustment method for transshipment storage bins based on horizontal continuous loading includes the following steps: S1. The transfer machine analysis module collects the transport data of the transfer machine, analyzes the transport data to generate transport parameters, and transmits the transport parameters to the transfer machine and the storage silo to control the operation of the transfer machine and the storage silo. S2, The storage bin acquisition module collects the operating data inside the storage bin; S3. The analysis and control module analyzes the operating data inside the storage silo and the transport data output by the transfer machine to obtain the actual weight of the material discharged by the transfer machine.

[0037] Example 4 The material unloading adjustment method for transshipment storage bins based on horizontal continuous loading includes the following steps: S1. The transfer machine analysis module collects the transport data of the transfer machine, analyzes the transport data to generate transport parameters, and transmits the transport parameters to the transfer machine and the storage silo to control the operation of the transfer machine and the storage silo. The payload data is as follows: Discrete point cloud on the surface of a material body measured by a three-dimensional laser rangefinder; Inertial sensors collect the triaxial acceleration and triaxial angular velocity of the transfer machine in real time; The first weight sensor collects the weight of the material in the storage bin; the second weight sensor collects the weight of the material being transported by the lifting mechanism of the transfer machine, the bucket support point, or the load-bearing idler of the conveyor belt.

[0038] The process of analyzing transport data is as follows: The discrete point cloud of the material surface on the transfer machine measured by the three-dimensional laser ranging device is... ,in For planar grid coordinates, The stacking height of the corresponding points; using point cloud. Fit the height distribution function of the stacked surface ; Using point clouds Fitting the height distribution function of the stacked surface The process is as follows: In the geometric analysis model, the discrete point cloud of the accumulated surface obtained by three-dimensional laser scanning is P(x i y j , z ij ), where (x i y j ) represents the planar grid coordinates, z ij This represents the stacking height of the corresponding points. The scanned point cloud is regularly distributed across planar grid nodes. The grid has a total height of m in the x-direction. x There are 1 equally spaced nodes, with a node spacing of Δx; there are m nodes in the y-direction. y There are 12 equally spaced nodes, with a node spacing of Δy. Each planar mesh node (x...) i ,y j ) corresponds to a height value z ij For any point (x, y) within the scanned point cloud region, calculate the index of the nearest grid node based on its position in the grid: i =round(x x0 / Δx),j =round(y y0 / Δy); where (x0, y0) are the starting reference coordinates of the point cloud region, and round(·) represents rounding to the nearest integer; the height of this point is defined as the height value of the nearest mesh node:

[0039] The resulting height function It is a piecewise constant function. Within each small rectangular region centered on a grid node and with dimensions Δx×Δy, the height value remains constant. However, at the boundaries of adjacent regions, the height changes abruptly, exhibiting a step characteristic. This height function is discontinuous overall.

[0040] By analyzing the height function Calculate the theoretical volume V of the transported material by performing a double integral over the projected area A of the material accumulation. r ,Right now:

[0041] Among them, is the shape correction factor, used to correct volume deviations caused by irregular stacking, with a value range of 0.8 to 1.0; A is the projected area of ​​the material stacking; , All are spatial integral variables; The real-time three-axis attitude angle data of the transfer machine are calculated by using inertial sensors to collect the three-axis acceleration and three-axis angular velocity data in real time, forming an attitude vector group: ,in The pitch angle of the transfer machine. The roll angle of the transfer machine. This refers to the yaw angle of the transfer aircraft; Using attitude vector groups Establish the attitude transformation matrix T(α) t ,β t γ t The attitude compensation of the stacked surface model is performed so that it can return to the horizontal reference coordinate system under any tilt state. After attitude compensation, the geometric analysis model is used to solve for the center of gravity of the material accumulation, and the coordinates of the center of gravity (x) are calculated. c y c , z c Then, based on the distribution of the center of gravity height and geometric shape, calculate the key morphological parameters of the accumulation; Combined with the load weight W from the transfer machine's load weight sensor signal m Mapping function with material feeding position The local volume of the material feeding area is divided into V sections. d Mapped to theoretical volume V r The material weight W at the material feeding position is obtained. d ; The weight W of the theoretical volume is obtained based on the analysis of height, length, width, and theoretical density. t The real-time weighing data of the transfer machine is obtained from the second weight sensor, and then the actual unloading weight W is obtained. a The transport parameters are calculated by the ratio of theoretical weight to actual weight; the transport parameters are compactness coefficients. and control coefficient ; Based on the compactness coefficient The calculation results control the vibration equipment below the transfer machine; based on the adjustment coefficient... The calculation results are used to adjust the reprint speed.

[0042] S2, The storage bin acquisition module collects the operating data inside the storage bin; S3. The analysis and control module analyzes the operating data inside the storage silo and the transport data output by the transfer machine to obtain the actual weight of the material discharged by the transfer machine.

[0043] Example 5 The material unloading adjustment method for transshipment storage bins based on horizontal continuous loading includes the following steps: S1. The transfer machine analysis module collects the transport data of the transfer machine, analyzes the transport data to generate transport parameters, and transmits the transport parameters to the transfer machine and the storage silo to control the operation of the transfer machine and the storage silo. The payload data is as follows: Material shape data measured by a three-dimensional laser rangefinder; Inertial sensors collect the three-axis acceleration and three-axis angular velocity of the transfer machine in real time, calculate the real-time three-attitude angle data of the transfer machine, and form an attitude vector group: ,in The pitch angle of the transfer machine. The roll angle of the transfer machine. This refers to the yaw angle of the transfer aircraft; The first weight sensor collects the weight of the material in the storage bin; the second weight sensor collects the weight of the material being transported by the transfer machine.

[0044] The process of analyzing transport data is as follows: The discrete point cloud of the material surface on the transfer machine measured by the three-dimensional laser ranging device is... ,in For planar grid coordinates, The stacking height of the corresponding points; using point cloud. Fit the height distribution function of the stacked surface ; Using point clouds Fitting the height distribution function of the stacked surface The process is as follows: In the geometric analysis model, the discrete point cloud of the accumulated surface obtained by three-dimensional laser scanning is P(x i y j , z ij ), where (x i y j ) represents the planar grid coordinates, z ij This represents the stacking height of the corresponding points. The scanned point cloud is regularly distributed across planar grid nodes. The grid has a total height of m in the x-direction. x There are 1 equally spaced nodes, with a node spacing of Δx; there are m nodes in the y-direction. y There are 12 equally spaced nodes, with a node spacing of Δy. Each planar mesh node (x...) i ,y j ) corresponds to a height value z ij For any point (x, y) within the scanned point cloud region, calculate the index of the nearest grid node based on its position in the grid: i =round(x x0 / Δx),j =round(y y0 / Δy); where (x0, y0) are the starting reference coordinates of the point cloud region, and round(·) represents rounding to the nearest integer; the height of this point is defined as the height value of the nearest mesh node:

[0045] The resulting height function It is a piecewise constant function. Within each small rectangular region centered on a grid node and with dimensions Δx×Δy, the height value remains constant. However, at the boundaries of adjacent regions, the height changes abruptly, exhibiting a step characteristic. This height function is discontinuous overall.

[0046] By analyzing the height function Calculate the theoretical volume V of the transported material by performing a double integral over the projected area A of the material accumulation. r ,Right now:

[0047] Among them, is the shape correction factor, used to correct volume deviations caused by irregular stacking, with a value range of 0.8 to 1.0; A is the projected area of ​​the material stacking; , All are spatial integral variables; A represents the projected area of ​​the material accumulation. The specific method involves using all points in the scanned surface point cloud... Effective height points > 0 are vertically projected onto the xy horizontal plane to form a two-dimensional point set; the outermost boundary of these points is identified using a contour extraction algorithm to obtain a closed polygonal region, and the area of ​​this polygonal region is the projected area A of the material accumulation. The real-time three-axis attitude angle data of the transfer machine are calculated by using inertial sensors to collect the three-axis acceleration and three-axis angular velocity data in real time, forming an attitude vector group: ,in The pitch angle of the transfer machine. The roll angle of the transfer machine. This refers to the yaw angle of the transfer aircraft; Using attitude vector groups Establish the attitude transformation matrix T(α) t ,β t γ t The attitude compensation of the stacked surface model is performed so that it can return to the horizontal reference coordinate system under any tilt state. After attitude compensation, the geometric analysis model is used to solve for the center of gravity of the material accumulation, and the coordinates of the center of gravity (x) are calculated. c y c , z c Then, based on the vertical coordinates of the stacked centroid... Based on the distribution of geometric shapes, calculate the key morphological parameters of the accumulation; Calculate the coordinates of the centroid ( , , The formula for ) is:

[0048] in, This represents the material density at grid cell (i, j); Let x represent the x-coordinate of the i-th grid cell; This represents the y-coordinate of the i-th row of grid cells; Represents the z-coordinate of the grid cell (i,j); The formula for calculating the key morphological parameters of the deposit is:

[0049] in: The height of the center of gravity is the vertical coordinate of the stacked center of gravity minus the reference height of the transfer machine's base plate. ; The average effective width is the maximum width of the stack in the lateral direction. The average effective length is denoted as , and the maximum projected length of the accumulation body along the transfer direction is denoted as .

[0050] Combined with the load weight W from the transfer machine's load weight sensor signal m Mapping function F with material feeding position p (x, y) divides the local volume of the material feeding area into V regions. d Mapped to theoretical volume V r The material weight W at the material feeding position is obtained. d ; The weight of theoretical volume The calculation formula is:

[0051] in The height of the center of gravity; This represents the average effective width. The average effective length; This is the theoretical density of the material; Material weight for:

[0052] in, The spatial mapping weight function is determined based on the relative positional relationship between the unloading point of the transfer machine and the discharge port of each storage bin. Its value range is [0,1], and it satisfies that the sum of the weights of the discharge ports of each storage bin corresponding to the same unloading point is 1. This refers to the local volume division of the material feeding area; This represents the theoretical volume of the transported material. The first weight sensor collects the unloading weight from the storage bin; Spatial mapping weight function Determined by the following formula:

[0053] in, This is the horizontal distance from the unloading point of the transfer machine to the discharge port of the corresponding storage bin; The maximum effective mapping distance is preset, and its value is determined according to the structural dimensions of the storage silo, generally ranging from 2m to 6m. This refers to the number of feed inlets. denoted as , which is the horizontal distance between the unloading point of the transfer machine and the center position of the discharge port of the p-th storage silo.

[0054] The weight W of the theoretical volume is obtained based on the analysis of height, length, width, and theoretical density. t The real-time weighing data of the transfer machine is obtained from the second weight sensor, and then the actual unloading weight W is obtained. a The transport parameters are calculated by the ratio of theoretical weight to actual weight; the transport parameters are compactness coefficients. and control coefficient ; Tightness coefficient The calculation formula is:

[0055] in Real-time weighing data collected by the second weight sensor; The weight of the material on the transfer machine is the theoretical volume of the material. Control coefficient The calculation formula is:

[0056] in Real-time material transfer volume; For material transfer volume; Real-time material transfer volume The calculation formula is:

[0057] in This represents the current transfer speed of the transfer machine; The duration of a single feeding operation; Real-time weighing data collected by the second weight sensor.

[0058] Based on the compactness coefficient The calculation results control the vibration equipment below the transfer machine; based on the adjustment coefficient... The calculation results are used to adjust the reprint speed.

[0059] Based on the compactness coefficient The specific process of controlling the vibration device below the transfer machine is as follows: When At that time, vibration is performed by a vibrating device installed below the transfer machine, making the material pile up more compactly; when During normal operation, the vibration equipment should not be started. According to the control coefficient The specific process for adjusting the reprint speed is as follows: When If the value is greater than 1, it indicates that the current reprint rate exceeds the planned rate. Therefore, the reprint speed should be reduced to allow for faster reprinting. =1; when If the value is less than 1, it indicates that the reprint rate is insufficient. The reprint speed should be increased to... =1; when When =1, the transfer machine is in its optimal state.

[0060] S2, The storage bin acquisition module collects the operating data inside the storage bin; S3. The analysis and control module analyzes the operating data inside the storage silo and the transport data output by the transfer machine to obtain the actual weight of the material discharged by the transfer machine.

[0061] Example 6 The material unloading adjustment method for transshipment storage bins based on horizontal continuous loading includes the following steps: S1. The transfer machine analysis module collects the transport data of the transfer machine, analyzes the transport data to generate transport parameters, and transmits the transport parameters to the transfer machine and the storage silo to control the operation of the transfer machine and the storage silo. The payload data is as follows: Material shape data measured by a three-dimensional laser rangefinder; Inertial sensors collect the three-axis acceleration and three-axis angular velocity of the transfer machine in real time, calculate the real-time three-attitude angle data of the transfer machine, and form an attitude vector group: ,in The pitch angle of the transfer machine. The roll angle of the transfer machine. This refers to the yaw angle of the transfer aircraft; The first weight sensor collects the weight of the material in the storage bin; the second weight sensor collects the weight of the material being transported by the transfer machine.

[0062] The process of analyzing transport data is as follows: The discrete point cloud of the material surface on the transfer machine measured by the three-dimensional laser ranging device is... ,in For planar grid coordinates, The stacking height of the corresponding points; using point cloud. Fit the height distribution function of the stacked surface ; Using point clouds Fitting the height distribution function of the stacked surface The process is as follows: In the geometric analysis model, the discrete point cloud of the accumulated surface obtained by three-dimensional laser scanning is P(x i y j , z ij ), where (x i y j ) represents the planar grid coordinates, z ij This represents the stacking height of the corresponding points. The scanned point cloud is regularly distributed across planar grid nodes. The grid has a total height of m in the x-direction. x There are 1 equally spaced nodes, with a node spacing of Δx; there are m nodes in the y-direction. y There are 12 equally spaced nodes, with a node spacing of Δy. Each planar mesh node (x...) i ,y j ) corresponds to a height value z ij For any point (x, y) within the scanned point cloud region, calculate the index of the nearest grid node based on its position in the grid: i =round(x x0 / Δx),j =round(y y0 / Δy); where (x0, y0) are the starting reference coordinates of the point cloud region, and round(·) represents rounding to the nearest integer; the height of this point is defined as the height value of the nearest mesh node:

[0063] The resulting height function It is a piecewise constant function. Within each small rectangular region centered on a grid node and with dimensions Δx×Δy, the height value remains constant. However, at the boundaries of adjacent regions, the height changes abruptly, exhibiting a step characteristic. This height function is discontinuous overall.

[0064] By analyzing the height function Calculate the theoretical volume V of the transported material by performing a double integral over the projected area A of the material accumulation. r ,Right now:

[0065] Among them, is the shape correction factor, used to correct volume deviations caused by irregular stacking, with a value range of 0.8 to 1.0; A is the projected area of ​​the material stacking; , All are spatial integral variables; A represents the projected area of ​​the material accumulation. The specific method involves using all points in the scanned surface point cloud... Effective height points > 0 are vertically projected onto the xy horizontal plane to form a two-dimensional point set; the outermost boundary of these points is identified using a contour extraction algorithm to obtain a closed polygonal region, and the area of ​​this polygonal region is the projected area A of the material accumulation. The real-time three-axis attitude angle data of the transfer machine are calculated by using inertial sensors to collect the three-axis acceleration and three-axis angular velocity data in real time, forming an attitude vector group: ,in The pitch angle of the transfer machine. The roll angle of the transfer machine. This refers to the yaw angle of the transfer aircraft; Using attitude vector groups Establish the attitude transformation matrix T(α) t ,β t γ t The attitude compensation of the stacked surface model is performed so that it can return to the horizontal reference coordinate system under any tilt state. After attitude compensation, the geometric analysis model is used to solve for the center of gravity of the material accumulation, and the coordinates of the center of gravity (x) are calculated. c y c , z c Then, based on the vertical coordinates of the stacked centroid... Based on the distribution of geometric shapes, calculate the key morphological parameters of the accumulation; Calculate the coordinates of the centroid ( , , The formula for ) is:

[0066] in, This represents the material density at grid cell (i, j); Let x represent the x-coordinate of the i-th grid cell; This represents the y-coordinate of the i-th row of grid cells; Represents the z-coordinate of the grid cell (i,j); The formula for calculating the key morphological parameters of the deposit is:

[0067] in: The height of the center of gravity is the vertical coordinate of the stacked center of gravity minus the reference height of the transfer machine's base plate. ; The average effective width is the maximum width of the stack in the lateral direction. The average effective length is denoted as , and the maximum projected length of the accumulation body along the transfer direction is denoted as .

[0068] Combined with the load weight W from the transfer machine's load weight sensor signalm Mapping function F with material feeding position p (x, y) divides the local volume of the material feeding area into V regions. d Mapped to theoretical volume V r The material weight W at the material feeding position is obtained. d ; The weight of theoretical volume The calculation formula is:

[0069] in The height of the center of gravity; This represents the average effective width. The average effective length; This is the theoretical density of the material; Material weight for:

[0070] in, The spatial mapping weight function is determined based on the relative positional relationship between the unloading point of the transfer machine and the discharge port of each storage bin. Its value range is [0,1], and it satisfies that the sum of the weights of the discharge ports of each storage bin corresponding to the same unloading point is 1. This refers to the local volume division of the material feeding area; This represents the theoretical volume of the transported material. The first weight sensor collects the unloading weight from the storage bin; Spatial mapping weight function Determined by the following formula:

[0071] in, This is the horizontal distance from the unloading point of the transfer machine to the discharge port of the corresponding storage bin; The maximum effective mapping distance is preset, and its value is determined according to the structural dimensions of the storage silo, generally ranging from 2m to 6m. This refers to the number of feed inlets. denoted as , which is the horizontal distance between the unloading point of the transfer machine and the center position of the discharge port of the p-th storage silo.

[0072] The weight W of the theoretical volume is obtained based on the analysis of height, length, width, and theoretical density. t The real-time weighing data of the transfer machine is obtained from the second weight sensor, and then the actual unloading weight W is obtained. a The transport parameters are calculated by the ratio of theoretical weight to actual weight; the transport parameters are compactness coefficients. and control coefficient ; Tightness coefficient The calculation formula is:

[0073] in Real-time weighing data collected by the second weight sensor; The weight of the material on the transfer machine is the theoretical volume of the material. Control coefficient The calculation formula is:

[0074] in Real-time material transfer volume; For material transfer volume; Real-time material transfer volume The calculation formula is:

[0075] in This represents the current transfer speed of the transfer machine; The duration of a single feeding operation; Real-time weighing data collected by the second weight sensor.

[0076] Based on the compactness coefficient The calculation results control the vibration equipment below the transfer machine; based on the adjustment coefficient... The calculation results are used to adjust the reprint speed.

[0077] Based on the compactness coefficient The specific process of controlling the vibration device below the transfer machine is as follows: When At that time, vibration is performed by a vibrating device installed below the transfer machine, making the material pile up more compactly; when During normal operation, the vibration equipment should not be started. According to the control coefficient The specific process for adjusting the reprint speed is as follows: When If the value is greater than 1, it indicates that the current reprint rate exceeds the planned rate. Therefore, the reprint speed should be reduced to allow for faster reprinting. =1; when If the value is less than 1, it indicates that the reprint rate is insufficient. The reprint speed should be increased to... =1; when When =1, the transfer machine is in its optimal state.

[0078] S2, The storage bin acquisition module collects the operating data inside the storage bin; S3. The analysis and control module analyzes the operating data inside the storage silo and the transport data output by the transfer machine to obtain the actual weight of the material discharged by the transfer machine.

[0079] The specific calculation process for the actual weight of the material being unloaded by the transfer machine is as follows: Multimodal sensing data was collected by multimodal sensing devices deployed under the frame and bin opening of the transfer conveyor. This data was then input into an impact weight calibration model to calculate and analyze the actual weight of the material discharged from the transfer conveyor. ; The impact weight calibration model calculates the actual weight of the material being fed by the transfer machine. The method is as follows:

[0080] in, The first weight sensor collects the unloading weight from the storage bin; The instantaneous impact force during material feeding; The instantaneous vibration acceleration of the transfer machine platform is collected by the vibration sensor; η t α1 and β1 are impact response correction factors used to characterize the impact characteristics of materials and differences in silo morphology; α1 and β1 are model self-learning parameters, adjusted based on historical sample data.

[0081] The multimodal sensing device includes a vibration sensor, a strain sensor, and a first weight sensor; Vibration sensors collect instantaneous vibration acceleration data from the transfer conveyor platform. The first weight sensor collects the unloading weight of the storage bin. The strain mass of the structure was acquired by the strain sensor. ; Instantaneous impact force during material feeding Data collected by vibration sensors Structural strain mass acquired by strain sensors The calculation is as follows:

[0082] in The strain mass of the structure is obtained by the strain sensor; The instantaneous vibration acceleration of the transfer machine platform is collected by the vibration sensor.

[0083] The operating principle of the impact-weight calibration model is as follows: when material falls from the storage bin to the transfer conveyor, the impact force... With vibration acceleration The raw signal output by the instantaneous second weighing sensor is affected by the combined effect. To avoid overestimation or underestimation of weight due to impact errors, the impact weight calibration model extracts the combined characteristics of impact and vibration and performs nonlinear mapping calculations to output the corrected true weight in real time. .

[0084] Example 7 Based on Example 6, environmental factors, material factors, equipment status factors, and sensor bias factors are further introduced to form a multi-source fusion dynamic self-calibration model, specifically as follows: Environmental factors, material factors, equipment status factors, and sensor bias factors are obtained through various sensors. Environmental factors include the temperature, humidity, and air density inside the warehouse; material factors include particle size distribution parameters, bulk density, and moisture content; equipment status factors include the vibration amplitude of the transfer conveyor, operating stability, and belt tension coefficient, which are used to reflect the correction effect of the equipment's mechanical characteristics on the impact response; sensor bias factors include the force sensor bias coefficient and the weighing sensor drift coefficient, which are used to compensate for errors in the measurement process.

[0085] Material particle size distribution parameter D m A three-dimensional laser rangefinder is used to take high-speed photographs or laser scans of the falling material flow. Image processing algorithms, including edge detection and particle analysis algorithms, are then used to statistically analyze the material's size and shape in real time, and calculate the particle size distribution and bulk density ρ. m Based on the actual weight W r The moisture content η is calculated from the material volume V. m The moisture content was collected by installing a microwave moisture sensor on the material flow path of the transfer machine. Vibration amplitude A of the transfer machine d Through the impact vibration signal S v The corresponding vibration intensity is obtained, and the operational stability S is obtained. d The belt tension coefficient K is obtained by linear weighting based on the standard deviation of velocity, the fluctuation range of vibration intensity, and the coefficient of variation of peak-to-peak stress signal within a time window; d The tensioning stroke is directly measured by installing a displacement sensor on the hydraulic tensioning cylinder of the transfer machine, and then normalized to a coefficient.

[0086] Real-time environmental parameters inside the chamber are acquired based on environmental factors: temperature T. e (t), humidity H e (t) and air density ρ e (t), and form the original environment vector: E1(t)=[T e (t), H e (t), ρ e (t)]; The original environment vector E1(t) is normalized using Z-Score to obtain the standard environment vector E1′(t); then, a sliding window filter is applied to the standard environment vector E1′(t), i.e., using the formula... We obtain the value where L is the length of the time window, such as 1 minute. Next, the output environmental correction coefficient is calculated using a multivariate nonlinear regression algorithm. ,Right now: We obtain, of which: The parameters in E2′(t) are smoothed; k1 is the preset baseline offset, k2, k3, and k4 are the preset linear influence coefficients of each environmental factor, and k5 is the interaction effect coefficient of temperature and humidity during healing; these are determined using the least squares method. Specifically, a large amount of historical calibration data covering different environmental conditions is collected, including standardized environmental observations and their corresponding experimentally obtained true correction coefficients. By solving the normal equation, the optimal parameter estimates that minimize the sum of squared prediction errors of the model are obtained. For example, one possible fitting result is k2=0.05, k5=0.04.

[0087] When the environmental characteristic change ΔE=∥E2′(t) is detected E2′(t 1) || Exceeding the change threshold ε e When this happens, a multiple update mechanism is triggered, and dynamic correction is performed using a recursive least squares algorithm, i.e.: λ e (t+1)=λ e (t)+γ e [E1′(t) E2′(t)] T P(t); where γ e t is the learning rate; P(t) is the environmental feature covariance matrix.

[0088] Based on the material parameters within the material factor: particle size distribution parameter D m Bulk density ρ m and moisture content This forms the material feature vector: M1=[D m , ρ m η m Principal component analysis yields the dimensionality-reduced material feature matrix: M2=W T (M1 μ M ); where W is the PCA transformation matrix, composed of covariance eigenvectors; μ M This is the mean vector of material characteristics.

[0089] Next, the material characteristic matrix is ​​input into the radial basis function network for nonlinear modeling, and the material correction function λ is calculated. m ,Right now: We obtain, where: ω i1 c is the weight of the i1th hidden node; i1 σ is the center value of the RBF network; i1 n is the width of the basis function; n1 is the number of hidden nodes.

[0090] The update rule for the RBF parameter is: ωi1 (t+1)=ω i1 (t)+η m ΔW r λ m / ω i1 Wherein: ΔW r =W r ′ W r Predicted weight error, W r ′ represents the weight currently predicted by the RBF network; λ m / ω i1 This indicates the sensitivity of the error to the weights.

[0091] By obtaining the amplitude value A within the device status factor d Operational stability S d and belt tension coefficient K d This forms the state matrix: D1=[A d S d K d ]; and perform exponentially weighted smoothing to obtain the smoothed state matrix D2(t), that is: D2(t) = α d D1(t)+(1 α d )D2(t 1); where α d This is a smoothing factor (0 to 1) used to adjust the weights of historical data; Next, perform a quadratic regression calculation on the smoothed state matrix D2(t): using the formula Output device stability correction factor Where θ0 is the baseline stability coefficient, θ1, θ2, and θ3 are linear term coefficients, and θ4 is the quadratic term coefficient of the vibration amplitude; these are obtained by fitting historical operating samples. The operating data of the equipment under different health states are analyzed, and the monitored state characteristics are correlated with the reliability deviation of the weight measurement at that time (i.e., the true γ), and the parameters are fitted using the least squares method. For example, the fitting result might be θ1 = 0.08, θ4= 0.025.

[0092] If a decrease in stability is detected, i.e., ΔS d =S d (t) S d (t 1) σ S Then, exception compensation is performed, i.e., λ. d′(t)=λ d (t)×[1 ξ d (1 S d )]; where ξ d The abnormality sensitivity coefficient (0 to 1); σ S This is the threshold for stability changes.

[0093] A dynamic drift compensation term Δs(t) is established based on the sensor bias factor: Δs(t) = β f ΔF i (t)+β ω ΔW m (t), where ΔF i (t)=F i (t) F ref (t) represents the force sensor deviation; F i (t) represents the real-time force value measured by the i-th force sensor at time t; F ref (t) represents the reference force signal, the standard output under calibration or steady-state conditions; ΔW m (t)=W m (t) W ref (t) represents the load cell deviation; W m (t) represents the real-time weighing value of the m-th weighing sensor; W ref (t) represents the standard weighing value of the corresponding load cell under reference conditions; β f and β ω The bias coefficient is updated via a moving average, i.e.: β f (t+1)=β f (t)+η f ΔF i2 (t), β ω (t+1)=β ω (t)+η ω ΔW m (t); where η f η ω All are learning rates.

[0094] By integrating the environmental correction factor, material correction function, and stability correction factor, a final multi-source fusion dynamic self-calibration model is formed: Output the actual blanking weight after multi-source fusion dynamic self-calibration. Where t is the sampling time, The drift compensation amount is the offset correction value caused by long-term accumulated error or sensor zero drift, which is calculated through a time sliding window and residual feedback.

[0095] Based on the actual material feeding weight after multi-source fusion dynamic self-calibration, the weight data of the feeding position is corrected in real time, and the previous historical material feeding data is traced and corrected.

[0096] The method for determining the maximum transfer height based on the type of transferred material is as follows: Based on the type of material being transferred, such as raw coal, iron ore, sand, gravel, or wet clay, parameters are obtained from the material property database, including: angle of repose θ. r The maximum angle between the slope and the horizontal plane when materials are naturally piled up; bulk density ρ m internal friction angle Parameters affecting the internal shear strength of the material; and the coefficient of friction μ of the bin wall. ω This affects the frictional resistance between the material and the wall of the transfer conveyor. The internal friction angle is one such factor. The coefficient of friction μ between the bin and the bin wall ω The angle of repose θ was obtained through experiments conducted by those skilled in the art on different categories of reclaimed materials. r A laser beam is emitted onto the surface of the material pile using a three-dimensional laser rangefinder. By measuring the time it takes for the laser to reflect back, the three-dimensional coordinates of each point are accurately calculated. All these points are combined to form a digital three-dimensional model of the material pile surface. Surfaces that are not naturally deposited, vertical silo walls, and flat silo bottoms are removed. The slope surface formed by the natural accumulation of materials is found, and a vertical cross-section is cut to obtain a contour line that represents the slope change.

[0097] Next, find the straightest section of the slope, fit this section to a straight line, and calculate the angle between this line and the horizontal plane using trigonometric mathematics—the arctangent function. This angle is then used as the angle of accumulation θ. r ; A critical flow height was calculated based on the silo mechanics model. The material-side pressure was calculated using the Janssen formula, and the critical height to prevent arching was derived. : Where R is the hydraulic radius, calculated by dividing the cross-sectional area of ​​the tank by the wetted perimeter; and K is the lateral pressure coefficient. τ0 is the initial shear strength of the material; for non-viscous materials, τ0 = 0; g is the acceleration due to gravity.

[0098] Materials are stacked at a natural angle of repose θr, and a safe clearance ΔH must be maintained between the top of the material and the edge of the silo opening, usually 0.3 to 0.5 meters, to prevent spillage and ensure visibility.

[0099] If the effective average width of the receiving area of ​​the transfer machine is W k The width at which materials can be freely stacked is the geometrically permissible maximum height H, measured from the unloading point. g for: ; The final maximum reload height H max The minimum value between the theoretical flow height and the geometric safety height must be taken, and the maximum allowable load height H of the transfer conveyor structure must also be considered. s H s Provided by the design: ).

Claims

1. A material handling and adjustment system for a horizontally continuous loading transfer and storage silo, comprising a transfer machine and a storage silo, characterized in that, It also includes a transfer machine analysis module, a storage silo data acquisition module, and an analysis and control module; The transfer machine analysis module is used to collect the transport data of the transfer machine, analyze the transport data to generate transport parameters, and transmit the transport parameters to the transfer machine and the storage silo for real-time control of the transfer machine and the storage silo. The storage silo data acquisition module is used to collect operational data inside the storage silo; The analysis and control module acquires the internal operating data of the storage silo and the transport data and parameters of the transfer machine to obtain the real-time impact force of the material being discharged from the storage silo, and then calibrates the discharge weight of the transfer machine in real time.

2. The material handling and adjustment system for a transfer and storage silo based on horizontal continuous loading according to claim 1, characterized in that, The transfer machine analysis module includes a three-dimensional laser rangefinder, an inertial attitude sensor, a vibration sensor, a first weight sensor, a second weight sensor, a strain sensor, and a tilt sensor. The three-dimensional laser rangefinder is installed above the transfer machine, the inertial attitude sensor is fixed to the transfer machine body, the vibration sensor is installed on the transfer machine body, the first weight sensor is installed at the bottom of the storage bin, and the second weight sensor is installed in the lifting mechanism, bucket support point, or conveyor belt load-bearing idler of the transfer machine; the tilt sensor is installed on the fixed bracket of the transfer machine guide chute; and the strain sensor is installed on the load-bearing beam of the transfer machine frame. The material storage bin acquisition module includes a first weight sensor and a feeding speed sensor; The feeding speed sensor is installed above the feeding position of the storage bin.

3. A method for adjusting the unloading of a transfer storage silo based on horizontal continuous loading, employing the unloading adjustment system for a transfer storage silo based on horizontal continuous loading as described in claim 2, characterized in that... Includes the following steps: S1. The transfer machine analysis module collects the transport data of the transfer machine, analyzes the transport data to generate transport parameters, and transmits the transport parameters to the transfer machine and the storage silo to control the operation of the transfer machine and the storage silo. S2, The storage bin acquisition module collects the operating data inside the storage bin; S3. The analysis and control module analyzes the operating data inside the storage silo and the transport data output by the transfer machine to obtain the actual weight of the material discharged by the transfer machine.

4. The material unloading adjustment method for a transfer storage silo based on horizontal continuous loading according to claim 3, characterized in that, The transport data mentioned in S1 is: Discrete point cloud on the surface of a material body measured by a three-dimensional laser rangefinder; Inertial sensors collect real-time data on the triaxial acceleration and triaxial angular velocity of the transfer machine; The first weight sensor collects the weight of the material in the storage bin; the second weight sensor collects the weight of the material being transported by the lifting mechanism of the transfer machine, the bucket support point, or the load-bearing idler of the conveyor belt.

5. The material unloading adjustment method for a transfer storage silo based on horizontal continuous loading according to claim 4, characterized in that, The process of analyzing the transport data is as follows: The discrete point cloud of the material surface on the transfer machine measured by the three-dimensional laser ranging device is... ,in For planar grid coordinates, The stacking height of the corresponding points; using point cloud. Fit the height distribution function of the stacked surface ; By analyzing the height function Calculate the theoretical volume V of the transported material by performing a double integral over the projected area A of the material accumulation. r ,Right now: Among them, is the shape correction factor, used to correct volume deviations caused by irregular stacking, with a value range of 0.8 to 1.0; A is the projected area of ​​the material stacking; , All are spatial integral variables; The real-time three-axis attitude angle data of the transfer machine are calculated by using inertial sensors to collect the three-axis acceleration and three-axis angular velocity data in real time, forming an attitude vector group: ,in The pitch angle of the transfer machine. The roll angle of the transfer machine. This refers to the yaw angle of the transfer aircraft; Using attitude vector groups Establish the attitude transformation matrix T(α) t ,β t γ t The attitude compensation of the stacked surface model is performed so that it can return to the horizontal reference coordinate system under any tilt state. After attitude compensation, the center of gravity of the material accumulation is solved, and the coordinates of the center of gravity are calculated. , , Then, based on the vertical coordinates of the stacked centroid... Based on the distribution of geometric shapes, calculate the key morphological parameters of the accumulation; Combined with the load weight W from the transfer machine's load weight sensor signal m Mapping function with material feeding position The local volume of the material feeding area is divided into V sections. d Mapped to theoretical volume V r The weight of the material at the feeding position is obtained. ; The weight W of the theoretical volume is obtained based on the analysis of height, length, width, and theoretical density. t The actual weight W of the transfer machine is obtained from the second weight sensor. a The transport parameters are calculated by the ratio of theoretical weight to actual weight; the transport parameters are compactness coefficients. and control coefficient ; Based on the compactness coefficient The calculation results control the vibration equipment below the transfer machine; based on the adjustment coefficient... The calculation results are used to adjust the reprint speed.

6. The material unloading adjustment method for a transfer storage silo based on horizontal continuous loading according to claim 5, characterized in that, The calculation method for A is to calculate all points in the surface point cloud obtained by scanning. Effective height points > 0 are vertically projected onto the xy horizontal plane to form a two-dimensional point set. The outermost boundary of these points is identified using a contour extraction algorithm to obtain a closed polygonal region. The area of ​​this polygonal region is the projected area A of the material accumulation. The calculation of the centroid coordinates ( , , The formula for ) is: in, This represents the material density at grid cell (i, j); Let x represent the x-coordinate of the i-th grid cell; This represents the y-coordinate of the i-th row of grid cells; Represents the z-coordinate of the grid cell (i,j); The formula for calculating the key morphological parameters of the accumulation is as follows: in: The height of the center of gravity is the vertical coordinate of the stacked center of gravity minus the reference height of the transfer machine's base plate. ; The average effective width is the maximum width of the stack in the lateral direction. The average effective length is the maximum projected length of the pile along the transfer direction; The weight of the theoretical volume The calculation formula is: in The height of the center of gravity; This represents the average effective width. The average effective length; This is the theoretical density of the material; The weight of the material being fed The calculation formula is: in, The spatial mapping weight function is determined based on the relative positional relationship between the unloading point of the transfer machine and the discharge port of each storage bin. Its value range is [0,1], and it satisfies that the sum of the weights of the discharge ports of each storage bin corresponding to the same unloading point is 1. This refers to the local volume division of the material feeding area; This represents the theoretical volume of the transported material. The first weight sensor collects the unloading weight from the storage bin; The Determined by the following formula: in, This is the horizontal distance from the unloading point of the transfer machine to the discharge port of the corresponding storage silo; The maximum effective mapping distance is preset, and its value is determined according to the structural dimensions of the storage silo, generally ranging from 2m to 6m. This refers to the number of feed inlets. denoted as , which is the horizontal distance between the unloading point of the transfer machine and the center position of the discharge port of the p-th storage silo.

7. The material unloading adjustment method for a transfer storage silo based on horizontal continuous loading according to claim 6, characterized in that, The tightness coefficient The calculation formula is: in Real-time weighing data collected by the second weight sensor; The weight of the material on the transfer machine is the theoretical volume of the material. The control coefficient The calculation formula is: in Real-time material transfer volume; For material transfer volume; The real-time transfer volume of the material The calculation formula is: in This represents the current transfer speed of the transfer machine; The duration of a single feeding operation; Real-time weighing data collected by the second weight sensor.

8. The material unloading adjustment method for a transfer storage silo based on horizontal continuous loading according to claim 7, characterized in that, According to the tightness coefficient The specific process of controlling the vibration equipment below the transfer machine based on the calculation results is as follows: When At that time, vibration is performed by a vibrating device installed below the transfer machine, making the material pile up more compactly; when During normal operation, the vibration equipment should not be started. According to the control coefficient The specific process of adjusting the reprint speed based on the calculation results is as follows: When If the value is greater than 1, it indicates that the current reprint rate exceeds the planned rate. Therefore, the reprint speed should be reduced to allow for faster reprinting. =1; when If the value is less than 1, it indicates that the reprint rate is insufficient. The reprint speed should be increased to... =1; when When =1, the transfer machine is in its optimal state.

9. The material unloading adjustment method for a transfer storage silo based on horizontal continuous loading according to claim 8, characterized in that, The specific calculation process for the actual weight of the material discharged by the transfer machine mentioned in S3 is as follows: Multimodal sensing data was collected by multimodal sensing devices deployed under the frame and bin opening of the transfer conveyor. This data was then input into an impact weight calibration model to calculate and analyze the actual weight of the material discharged from the transfer conveyor. ; The impact weight calibration model calculates the actual weight of the material being discharged from the transfer conveyor. The method is as follows: in, The first weight sensor collects the unloading weight from the storage bin; The instantaneous impact force during material feeding; The instantaneous vibration acceleration of the transfer machine platform is collected by the vibration sensor; α1 and β1 are impact response correction factors used to characterize the impact characteristics of materials and differences in silo morphology; α1 and β1 are model self-learning parameters, adjusted based on historical sample data.

10. The material unloading adjustment method for a transfer storage silo based on horizontal continuous loading according to claim 9, characterized in that... The multimodal sensing device includes a vibration sensor, a strain sensor, and a first weight sensor; The vibration sensor collects the instantaneous vibration acceleration of the transfer platform. The first weight sensor collects the unloading weight of the storage bin. ; Strain sensors acquire structural strain mass ; The instantaneous impact force of the material being fed Data collected by vibration sensors Structural strain mass acquired by strain sensors The calculation is as follows: in The strain mass of the structure is obtained by the strain sensor; The instantaneous vibration acceleration of the transfer machine platform is collected by the vibration sensor.

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