A garbage automatic transfer control method and system based on multi-agency cooperative scheduling

Abstract

The application relates to a kind of automatic garbage transfer control method and system based on multi-agency cooperative scheduling, wherein, method includes: according to multi-source data, dynamically allocate unloading port positioning parameter, vehicle unloading window period and vehicle operation time beat, to guide corresponding vehicle unloading;Through push mechanism, the material retained in unloading port is transported to the operation area of lower mechanism;Through laser scanning device, the three-dimensional profile data inside unloading pit before and after unloading is monitored, the motion parameters of lower mechanism are synchronously collected, and the matching state of lower mechanism and vehicle operation time beat is judged;Based on three-dimensional profile data and motion parameters, dynamic volume model is established, and single unloading amount is calculated in real time in combination with material density parameter;When detecting that single unloading amount exceeds tolerance range or beat is out of synchronization, chain plate machine variable speed gradient adjustment, push mechanism intervention compensation and unloading port redistribution adjustment are carried out. Therefore, the automatic operation efficiency of garbage transfer is significantly improved.

Description

Technical Field

[0001] This invention relates to the field of waste transfer operation technology, and in particular to an automatic waste transfer control method and system based on multi-agency collaborative scheduling. Background Technology

[0002] In existing waste transfer stations, the waste compressor unloading method relies on manual operation for unloading and loading. The amount of waste unloaded at one time is controlled by manual observation and the weight of the waste measured by the weighing sensor system equipped with the waste compressor. This process is repeated to achieve the preset weight of waste to be unloaded.

[0003] In manual mode, ensuring that the weight of each truckload falls within the weight control range requires multiple steps of control during material unloading. This relies on the experience of the unloading operators and necessitates cooperation with the unloading supervisor. In the final weight control stage, if the amount of garbage in the pit is too high, it's necessary to wait for a garbage truck of appropriate weight to unload to the unloading port, thus controlling the packaged weight within a reasonable range. While this traditional method can meet certain production needs, it relies on manual judgment. If the operator's attention is not focused, abnormal unloading weights can occur, affecting production efficiency and even shortening the equipment's lifespan. Summary of the Invention

[0004] (a) Technical problems to be solved

[0005] In view of the above-mentioned shortcomings and deficiencies of the prior art, the present invention provides a waste automatic transfer control method and system based on multi-mechanism collaborative scheduling. It solves the technical defects of the existing manual material unloading control mode of waste transfer stations, such as low operating efficiency, poor weight control accuracy and abnormal equipment wear and tear, which are caused by the high dependence on human experience, the sluggish response of multi-link collaborative mechanism and the lack of compensation ability for abnormal working conditions.

[0006] (II) Technical Solution

[0007] To achieve the above objectives, the main technical solutions adopted by the present invention include:

[0008] In a first aspect, embodiments of the present invention provide an automatic waste transfer control method based on multi-agency collaborative scheduling, comprising:

[0009] Based on the obtained data on the load of garbage transport vehicles, the spatial distribution information of unloading pits, the space occupancy information, and the unloading port information, the unloading port positioning parameters of the unloading pits, the vehicle unloading window period, and the vehicle operation time rhythm are dynamically allocated to guide the corresponding vehicles to unload.

[0010] The material retained at the discharge port is transported to the working area of ​​the unloading mechanism by the pushing mechanism, so that the unloading mechanism can discharge the material into the discharge pit;

[0011] Collect motion parameters and load data of the unloading mechanism, and determine the matching status of the unloading mechanism and the vehicle's operating time cycle;

[0012] The laser scanning device monitors the three-dimensional contour data inside the unloading pit before and after material feeding in real time. A dynamic volume model is established based on the three-dimensional contour data and motion parameters. The amount of material fed in a single operation is calculated in real time in combination with the preset material density parameters.

[0013] When the single feeding amount exceeds the preset tolerance range or the cycle time is out of sync, a multi-level control command sequence is triggered to adjust the speed gradient of the feeding mechanism, compensate for the intervention of the pushing mechanism, and redistribute the material discharge port.

[0014] Optionally, based on the acquired load data of garbage transport vehicles, spatial distribution information of unloading pits, space occupancy information, and unloading port information, the unloading port positioning parameters of the unloading pits, vehicle unloading window periods, and vehicle operation time rhythms are dynamically allocated to guide the corresponding vehicles to unload, including:

[0015] Real-time acquisition of data on the load of garbage trucks, spatial distribution of unloading pits, space occupancy, and unloading ports;

[0016] Based on the load data of garbage transport vehicles, the spatial distribution information and space occupancy information of unloading pits, the path distance, load matching degree and anti-collision margin between each unloading pit and the current vehicle are calculated. The spatial adaptability is generated by weighted scoring. Unloading pits with spatial adaptability higher than the set threshold are selected and the unloading port corresponding to the unloading pit is regarded as a candidate unloading port.

[0017] Based on a pre-trained dynamic programming algorithm model, with the goal of maximizing continuous utilization, the available time window of each candidate unloading port is solved recursively from the terminal time to the initial time. The available time window includes the start timestamp, duration and efficiency weight coefficient.

[0018] A conflict resolution tree model is constructed, and the candidate discharge port and available time window combination is used as the decision node. The node weight is quantified by the product of spatial fitness and efficiency weight coefficient. After traversing the conflict resolution tree model and pruning the branches with weight values ​​below the critical value layer by layer, the global optimal solution containing the optimal discharge port and time window combination is output.

[0019] The duration of the time window in the global optimal solution is divided into several basic time slices based on the vehicle operation time cycle. Each vehicle operation time cycle corresponds to the baseline time consumption of the standard action sequence of the vehicle at the unloading port for feeding positioning, unloading execution, and shifting and avoiding.

[0020] The optimal combination of unloading port and time window, vehicle operation time cycle and corresponding basic time slice are encoded into a structured instruction stream and pushed to the corresponding vehicle.

[0021] Optionally, collecting motion parameters and load data of the unloading mechanism and determining the matching status of the unloading mechanism and the vehicle's operating time cycle includes:

[0022] The operating speed is collected by a speed sensor installed on the drive shaft of the unloading mechanism;

[0023] Extract the time markers of material feeding and positioning completion, unloading execution start and end, and displacement and avoidance action triggering in the vehicle operation time cycle, and establish a three-stage time sequence benchmark for the vehicle operation time cycle;

[0024] The periodic arrival time of the receiving section of the unloading mechanism is determined based on the operating speed of the unloading mechanism. The periodic arrival time of the receiving section of the unloading mechanism is compared with the three-stage time series benchmark to calculate the overlap duration between the start and end time of unloading and the transportation window of the receiving section. In addition, by monitoring the accumulation thickness and distribution pattern of the material on the surface of the unloading mechanism, the matching status of the unloading mechanism's operating time rhythm and the vehicle's operating time rhythm is determined. The unloading mechanism's operating time rhythm is the time span of the periodic transportation window of the receiving section.

[0025] Optionally, a laser scanning device is used to monitor the three-dimensional contour data inside the unloading pit in real time before and after material feeding. A dynamic volume model is established based on the three-dimensional contour data and motion parameters. Combined with preset material density parameters, the amount of material fed in a single operation is calculated in real time, including:

[0026] The three-dimensional contour data of the unloading pit before and after material feeding is collected in real time by a laser scanning device. The height distribution of the garbage accumulation surface at the beginning and end of the feeding stage is extracted, and the average height value of the garbage accumulation surface is generated based on multi-point height sampling.

[0027] Based on the pre-set trapezoidal structure parameters and average height of the unloading pit, the cross-sectional area of ​​the waste flow is constructed;

[0028] The operating speed and duration of a single feeding operation of the feeding mechanism are acquired synchronously. The material pushing distance is obtained by multiplying the operating speed of the feeding mechanism by the duration of a single feeding operation, and the real-time volume change is calculated by combining the cross-sectional area of ​​the waste flow to obtain a dynamic volume model.

[0029] The system retrieves the corresponding waste material density parameters from the historical database, maps the dynamic volume model to the waste material density parameters, and outputs the weight of a single feeding operation.

[0030] Optionally, when the single feeding amount exceeds the preset tolerance range or the cycle time is out of sync, a multi-level control command sequence is triggered to perform speed gradient adjustment of the feeding mechanism, compensation by the pushing mechanism, and redistribution adjustment of the unloading port, including:

[0031] When the single feeding quantity exceeds the preset tolerance range or the matching status is out of sync, a multi-level control command sequence is triggered to perform the following steps:

[0032] Based on the direction and absolute value of the deviation in the cycle time matching, the deviation is divided into multiple control levels. Among them, positive deviation indicates that the material feed exceeds the limit, and negative deviation indicates that the supply is insufficient.

[0033] When the amount of material fed in a single operation exceeds the preset threshold, the operating speed is increased step by step according to the positive deviation level, with each level of speed increase being 5%-15% of the operating speed of the feeding mechanism.

[0034] When the material supply is insufficient, a negative deviation is triggered, and the operating speed of the conveying and unloading mechanism is reduced in a step-by-step manner according to the control level, with each reduction not exceeding the maximum allowable deceleration threshold.

[0035] Based on the accumulation height and retention time of the material in the working area of ​​the feeding mechanism, the pushing mechanism is activated to perform directional pushing operations, and continuous pushing or intermittent pulse pushing compensation is implemented for the local retention area.

[0036] Based on the obtained material accumulation thickness on the surface of the unloading mechanism, when the local accumulation thickness exceeds the safety threshold, the vehicle access permission of the corresponding unloading port is temporarily blocked, and the audible and visual warning is activated to guide the vehicle to the unoccupied unloading port with the best path accessibility among the candidate unloading ports.

[0037] The speed gradient adjustment amount of the chain conveyor, the intervention frequency of the pushing mechanism, and the distribution information of the unloading port are synchronously correlated, and the material flow oscillation during the adjustment process is suppressed through closed-loop feedback;

[0038] Within a preset time window, monitor the fluctuation value of the corrected feed rate and the cycle time matching status. If the feed rate does not recover to the tolerance range or the cycle time is not synchronized, trigger an iterative multi-level control instruction sequence.

[0039] Optionally, cycle time desynchronization refers to a job timing misalignment state triggered by at least one of the following conditions:

[0040] The duration of overlap between the vehicle unloading execution period and the material receiving section transportation window of the unloading mechanism is less than the preset overlap threshold.

[0041] The thickness of the material accumulation on the surface of the unloading mechanism exceeds the morphological safety threshold, and the distribution pattern indicates that the unloading action was not completed within the transport window of the receiving section;

[0042] The total time from the completion of the vehicle's feeding and positioning to the triggering of the displacement and avoidance action deviates from the baseline time and exceeds the preset vehicle cycle time tolerance range.

[0043] Unplanned interruptions occur in the periodic arrival time sequence of the material receiving section of the unloading mechanism, making it impossible to continuously match the vehicle operation time rhythm.

[0044] Optionally, it also includes:

[0045] When the cumulative material discharge reaches the target value, the waste material compression and baling operation program is automatically triggered, and the vehicle access permission of the corresponding unloading port area is locked simultaneously.

[0046] After the packaging operation is completed, the cumulative material feeding counter is reset, and the packaging threshold for the next cycle is dynamically updated based on the compressed material volume.

[0047] The data generated by the single feeding quantity, cycle time matching status, multi-level control instruction sequence, and instruction execution process calculated in the current cycle are integrated as a reference scheme for the next work cycle.

[0048] Secondly, embodiments of the present invention provide an automatic waste transfer control system based on multi-mechanism collaborative scheduling, comprising:

[0049] The unloading mechanism includes a chain conveyor for transporting unloaded materials to the unloading pit, wherein the unloading section of the chain conveyor extends into the unloading pit to form a continuous unloading channel.

[0050] The pushing mechanism is located in the transfer corridor between the unloading port and the receiving section, and is used to push the garbage to the working area of ​​the chain conveyor.

[0051] A laser scanning device is installed at the feed inlet of the chain conveyor.

[0052] Gravity meter, installed in the area where garbage trucks enter the site;

[0053] In addition, a control platform is connected to the pressing mechanism, the unloading mechanism, the laser scanning device, and the gravity meter, respectively, for executing the method described above.

[0054] Optionally, the control platform includes: a main control unit and a chain conveyor control unit, a pusher control unit, and a laser scanner control unit connected to the main controller.

[0055] Optionally, the chain conveyor control unit includes: a chain conveyor drive subunit connected to the chain conveyor and the main control unit respectively, and a motion feedback subunit connected to the chain conveyor and the main control unit respectively;

[0056] The pusher control unit includes: a pusher mechanism drive subunit connected to the pusher mechanism and the main control unit respectively;

[0057] The laser scanning control unit includes a scanning control subunit that is connected to the laser scanning device and the main control unit, respectively.

[0058] (III) Beneficial Effects

[0059] The beneficial effects of this invention are as follows: The automatic unloading control method provided by this invention significantly improves the operational efficiency of the waste transfer system through multi-dimensional technological collaboration. First, based on a dynamic unloading port allocation strategy using multi-source data such as vehicle load and pit space occupancy, it can autonomously generate optimal unloading window periods and operation cycle parameters, effectively eliminating decision delays and vehicle waiting time wastage common in manual collaborative scheduling. This improves the cycle connection accuracy of continuous unloading operations to the inherent response limit of the equipment, significantly increasing the waste throughput per unit time. Second, through a real-time dynamic modeling mechanism that integrates laser scanning three-dimensional contour data and material density parameters, it can accurately calculate the volume and weight of a single unloading operation. Simultaneously, combined with feedback compensation of the unloading mechanism's motion parameters, it achieves closed-loop control of quality errors, avoiding measurement inaccuracies caused by human experience-based judgment bias. Furthermore, when unloading volume exceeds tolerance or cycle synchronization is detected, it autonomously triggers multi-level collaborative control commands. Through a combination of gradient speed adjustment, push-pressure compensation intervention, and unloading port reallocation strategies, it not only achieves adaptive repair of abnormal operating conditions but also avoids equipment impact loads caused by traditional manual intervention, significantly reducing the risk of mechanical wear. Attached Figure Description

[0060] Figure 1 This is a schematic diagram of the overall process of the method proposed in the embodiments of the present invention;

[0061] Figure 2 This is a schematic diagram of the specific process of step S1 of the method proposed in the embodiment of the present invention;

[0062] Figure 3 This is a schematic diagram of the specific process of step S3 of the method proposed in the embodiment of the present invention;

[0063] Figure 4 This is a schematic diagram of the specific process of step S4 of the method proposed in the embodiment of the present invention;

[0064] Figure 5 A schematic diagram of a trapezoidal cross-section of waste according to the method proposed in this embodiment of the invention;

[0065] Figure 6 This is a schematic diagram of the specific process of step S5 of the method proposed in the embodiment of the present invention;

[0066] Figure 7 This is a schematic diagram of the system composition proposed in an embodiment of the present invention. Detailed Implementation

[0067] To better explain and facilitate understanding of the present invention, the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0068] like Figure 1As shown in the embodiment of the present invention, an automatic waste transfer control method based on multi-mechanism collaborative scheduling includes: dynamically allocating the unloading port positioning parameters, vehicle unloading window period, and vehicle operation time rhythm of the unloading pit according to the acquired load data of waste transport vehicles, spatial distribution information of unloading pits, space occupancy information, and unloading port information, so as to guide the corresponding vehicles to unload; directionally transporting the material retained at the unloading port to the working area of ​​the feeding mechanism through a pushing mechanism, so that the feeding mechanism can feed the material into the unloading pit; collecting the motion parameters and load data of the feeding mechanism, and judging the matching status of the feeding mechanism and the vehicle operation time rhythm; monitoring the three-dimensional contour data inside the unloading pit before and after feeding in real time through a laser scanning device, establishing a dynamic volume model based on the three-dimensional contour data and motion parameters, and calculating the single feeding amount in real time in combination with the preset material density parameters; when it is detected that the single feeding amount exceeds the preset tolerance range or the rhythm is out of sync, triggering a multi-level control command sequence to perform speed gradient adjustment of the feeding mechanism, intervention compensation of the pushing mechanism, and reallocation adjustment of the unloading port.

[0069] The automatic unloading control method provided by this invention significantly improves the operational efficiency of waste transfer systems through multi-dimensional technological collaboration. First, a dynamic unloading port allocation strategy based on multi-source data such as vehicle load and pit space occupancy can autonomously generate optimal unloading window periods and operational cycle parameters. This effectively eliminates decision-making delays and vehicle waiting time wastage common in manual collaborative scheduling, raising the cycle connection accuracy of continuous unloading operations to the inherent response limit of the equipment and significantly increasing the waste throughput per unit time. Second, through a real-time dynamic modeling mechanism that integrates laser scanning 3D contour data and material density parameters, the volume and weight of a single unloading operation can be accurately calculated. Simultaneously, combined with feedback compensation of the unloading mechanism's motion parameters, closed-loop control of quality errors is achieved, avoiding measurement inaccuracies caused by human experience-based judgment biases. Furthermore, when unloading volume exceeds tolerance or cycle synchronization is detected, multi-level collaborative control commands are autonomously triggered. Through a combination of gradient speed regulation, push-pressure compensation intervention, and unloading port reallocation strategies, not only is adaptive repair of abnormal operating conditions achieved, but also the impact load on equipment caused by traditional manual intervention is avoided, significantly reducing the risk of mechanical wear.

[0070] To better understand the above technical solutions, exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present invention are shown in the drawings, it should be understood that the present invention can be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that the present invention can be understood more clearly and thoroughly, and that the scope of the present invention can be fully conveyed to those skilled in the art.

[0071] Specifically, the present invention provides an automatic waste transfer control method based on multi-agency collaborative scheduling, which includes:

[0072] S1. Based on the obtained load data of garbage transport vehicles, spatial distribution information of unloading pits, space occupancy information and unloading port information, dynamically allocate the unloading port positioning parameters of unloading pits, vehicle unloading window period and vehicle operation time rhythm to guide the corresponding vehicles to unload.

[0073] Furthermore, such as Figure 2 As shown, step S1 includes:

[0074] S11. Real-time acquisition of load data of garbage transport vehicles, spatial distribution information of unloading pits, space occupancy information and unloading port information.

[0075] S12. Based on the load data of the garbage transport vehicle, the spatial distribution information and space occupancy information of the unloading pit, calculate the path distance, load matching degree and anti-collision margin between each unloading pit and the current vehicle. Generate spatial adaptability through weighted scoring, filter unloading pits with spatial adaptability higher than a set threshold, and regard the unloading port corresponding to the filtered unloading pit as a candidate unloading port. Among them, the path distance is: the shortest feasible path length from the current position of the vehicle to the target unloading pit; the load matching degree is: vehicle load / (1 - real-time space occupancy information of the unloading pit), normalized to the [0,1] interval to represent unloading feasibility, 1 = perfect match; the anti-collision margin is: the theoretical minimum distance between adjacent unloading pits that can be safely operated, determined by the combined pit operation area space and vehicle size.

[0076] S13. Based on a pre-trained dynamic programming algorithm model, with the goal of maximizing continuous utilization, the available time window of each candidate unloading port is solved recursively from the terminal time to the initial time. The available time window includes the start timestamp, duration and efficiency weight coefficient.

[0077] In one embodiment, the dynamic programming algorithm model employs a pre-trained spatiotemporal feature fusion network. A bidirectional gated recursive unit (BiGRU) extracts the periodic variation of material accumulation at the unloading port, outputting a temporal feature vector representing long-term and short-term load trends. A lightweight convolutional layer (Depthwise CNN) is used to extract local features from sensor signals at the unloading port (such as photoelectric switch pulse sequence encoding the vehicle unloading time distribution, infrared sensors capturing the spatial distribution of material accumulation, and current waveform analysis of the pushing mechanism to determine the pushing operation intensity). This generates a spatial feature tensor reflecting dynamic transportation behavior. A graph attention network (GAT) is then used to analyze the path dependency of material transport between unloading ports, generating node embedding vectors.

[0078] The temporal feature vector, spatial feature tensor, and node embedding vector are dimensionally aligned and feature-concatenated to form a dedicated state descriptor for waste transportation scheduling. Based on this descriptor, the following inverse recursive decision-making is performed: First, starting from the preset end time of the operation cycle, an initial state value function is generated based on the full load rate constraint of the terminal unloading port. Second, for each candidate unloading port, the global utilization gain from the current time to the previous time is calculated based on the start timestamp, duration, and efficiency weight coefficient of its time window (the efficiency weight coefficient reflects the efficiency weight coefficient of the real-time operation efficiency of the unloading port, which is adaptively adjusted by comprehensively considering the periodic change trend of material accumulation and the intensity characteristics of the pushing operation). Then, through iterative updates of the value function, the path that maximizes continuous utilization is selected, and the activation sequence and time window occupancy mark of each unloading port are recorded simultaneously.

[0079] This invention innovatively embeds a pre-trained network into a reverse recursive framework to achieve online self-learning generation of weight coefficients. This deep integration of data-driven and operations research optimization can capture nonlinear relationships under complex working conditions while strictly adhering to the temporal constraints of the work process, ultimately achieving a dual improvement in global scheduling robustness and resource utilization efficiency.

[0080] S14. Construct a conflict resolution tree model, using candidate unloading ports and available time windows as decision nodes. Node weights are quantified by the product of spatial fitness and efficiency weight coefficients. After traversing the conflict resolution tree model and pruning branches with weight values ​​below the critical value layer by layer, the global optimal solution containing the optimal unloading port and time window combination is output. In this step, a tree-like decision model is constructed based on the permutations and combinations of candidate unloading ports and their available time windows. Each node represents a feasible pairing scheme of "unloading port-time window," and the priority of the node is quantified by the joint contribution value of spatial fitness and efficiency weights. By traversing the decision tree layer by layer, inefficient paths with contribution values ​​below a preset safety threshold are dynamically eliminated, and finally, the unloading port and time window combination with the highest global contribution value is retained as the optimal scheduling scheme.

[0081] S15. The duration of the time window in the global optimal solution is divided into several basic time slices based on the vehicle operation time cycle. Each vehicle operation time cycle corresponds to the baseline time consumption of the standard action sequence of the vehicle at the unloading port, including feeding positioning, unloading execution, and shifting and avoiding obstacles.

[0082] S16. Encode the optimal unloading port and time window combination, vehicle operation time cycle and corresponding basic time slice into a structured instruction stream and push it to the target vehicle in real time.

[0083] S2. The material retained at the discharge port is transported to the working area of ​​the unloading mechanism by the pushing mechanism, so that the unloading mechanism can discharge the material into the discharge pit.

[0084] S3. Collect motion parameters and load data of the unloading mechanism, and determine the matching status of the unloading mechanism and the vehicle's operating time rhythm.

[0085] Furthermore, such as Figure 3 As shown, step S3 includes:

[0086] S31. The running speed is collected by a speed sensor installed on the drive shaft of the unloading mechanism.

[0087] S32. Extract the time markers for the completion of feeding and positioning, the start and end of unloading, and the triggering of shifting and avoiding actions in the vehicle operation time cycle, and establish a three-stage time sequence reference for the vehicle operation time cycle.

[0088] S33. Based on the operating speed of the unloading mechanism, determine the periodic arrival time of the receiving section of the unloading mechanism. Compare the periodic arrival time of the receiving section of the unloading mechanism with the three-stage time series benchmark, calculate the overlap duration between the start and end time of unloading execution and the transportation window of the receiving section, and combine the monitoring of the accumulation thickness and distribution pattern of the material on the surface of the unloading mechanism to determine the matching status between the unloading mechanism's operating time rhythm and the vehicle's operating time rhythm. The unloading mechanism's operating time rhythm is the time span of the periodic transportation window of the receiving section.

[0089] S4. Real-time monitoring of the three-dimensional contour data inside the unloading pit before and after material feeding using a laser scanning device. A dynamic volume model is established based on the three-dimensional contour data and motion parameters. The amount of material fed in a single operation is calculated in real time in combination with the preset material density parameters.

[0090] Furthermore, such as Figure 4 As shown, step S4 includes:

[0091] S41. The three-dimensional contour data of the unloading pit before and after unloading is collected in real time by a laser scanning device. The height distribution of the garbage accumulation surface at the beginning and end of the unloading stage is extracted, and the average height value of the garbage accumulation surface is generated based on multi-point height sampling.

[0092] S42. Based on the preset trapezoidal structure parameters and average height of the unloading pit, construct the cross-sectional area of ​​the waste flow.

[0093] S43. Simultaneously acquire the operating speed of the feeding mechanism and the duration of a single feeding, multiply the operating speed of the feeding mechanism by the duration of a single feeding to obtain the material pushing distance, and combine it with the cross-sectional area of ​​the waste flow to calculate the real-time volume change to obtain a dynamic volume model.

[0094] S44. Retrieve the corresponding waste material density parameters from the historical database, associate and map the dynamic volume model with the waste material density parameters, and output the weight of a single feeding.

[0095] In one specific embodiment, a laser scanning device is used to acquire the real-time height curve of the waste during waste feeding. Within a single feeding cycle, features are extracted from the height curve from the starting end to the ending end. Multiple height points are taken on the real-time height curve to calculate the average height value, which is used as the height information for a single feeding operation. Preferably, reference is made to... Figure 5 Alternatively, the definite integral of the real-time height curve can be used as the height information for a single feeding, thus yielding:

[0096]

[0097] In the formula, f(x) is the real-time height curve, d is half the difference between the upper and lower bases of the isosceles trapezoid, h is the height of the isosceles trapezoid. Since the shape of the unloading pit is fixed, d and h are both detectable parameters; x1 and x2 are the first and second ends of the garbage accumulation formed by unloading.

[0098] Based on the height of a single discharge, the bottom width of the unloading pit, and the base angle of its trapezoidal structure, the cross-sectional area of ​​the waste flow is calculated. Wherein, the cross-sectional area S... t For: S t =L b ·A(h)+A(h) 2 ·cotθ, where L b Let A(h) be the bottom width of the unloading pit, and θ be the base angle of the trapezoidal structure.

[0099] The operating speed of the feeding mechanism and the duration of a single feeding cycle are obtained. The material pushing distance is calculated, and the volume of a single feeding cycle is obtained by combining this with the trapezoidal cross-sectional area of ​​the waste. The volume of a single feeding cycle, V, is: V = v·t·S t In the formula, v is the running speed of the feeding mechanism, and t is the running time of the feeding mechanism.

[0100] Based on the pre-retrieved average waste density value and single-discharge volume, the single-discharge weight is calculated. The single-discharge weight M is: M = ρ·V, where ρ is the average waste density value, and the range of values ​​obtained through data analysis of multiple discharges is 0.65-0.9 g / cm3.

[0101] Finally, if the volume or weight of a single feeding exceeds the preset range, the feeding mechanism will stop the current feeding operation. If neither the volume nor the weight of a single feeding exceeds the preset range, the feeding operation will be repeated multiple times until the total weight of the fed waste is met, at which point the feeding mechanism will stop feeding.

[0102] S5. When the single feeding amount exceeds the preset tolerance range or the cycle time is out of sync, a multi-level control command sequence is triggered to adjust the speed gradient of the feeding mechanism, compensate for the intervention of the pushing mechanism, and redistribute the unloading port.

[0103] It is important to emphasize that cycle time desynchronization refers to a state of misalignment in job timing triggered by at least one of the following conditions:

[0104] (1) The duration of overlap between the vehicle unloading execution period and the material receiving section transportation window of the unloading mechanism is less than the preset overlap threshold. For example, unloading only covers 30% of the material receiving window, which is lower than the preset minimum overlap threshold requirement of 50%.

[0105] (2) The thickness of the material accumulation on the surface of the feeding mechanism exceeds the morphological safety threshold, and the distribution pattern indicates that the unloading action was not completed within the material receiving section transportation window, such as detecting sudden thickness changes or edge accumulation.

[0106] (3) The total time from the completion of the vehicle's feeding and positioning to the triggering of the displacement and avoidance action deviates from the baseline time and exceeds the preset vehicle cycle tolerance range. For example, the baseline time is 10 seconds, the actual time is 15 seconds, and the upper limit of the tolerance is ±2 seconds.

[0107] (4) Unplanned interruptions (such as equipment jamming) occur in the periodic arrival time sequence of the material receiving section of the unloading mechanism, resulting in a failure to continuously match the vehicle operation time rhythm.

[0108] Furthermore, such as Figure 6 As shown, step S5 includes:

[0109] S51. When the single feeding quantity is detected to exceed the preset tolerance range or the matching status is out of sync, a multi-level control command sequence is triggered to perform the following steps:

[0110] S52. Based on the direction and absolute value of the deviation in the cycle time matching, the deviation is divided into multiple control levels, where a positive deviation indicates that the material feed exceeds the limit, and a negative deviation indicates that the supply is insufficient.

[0111] S53. When the amount of material fed in a single operation exceeds the preset threshold, the operating speed is increased step by step according to the positive deviation level, with each level of speed increase being 5%-15% of the operating speed of the feeding mechanism; when the material supply is insufficient, a negative deviation is triggered, and the operating speed of the feeding mechanism is reduced step by step according to the control level, with each level of reduction not exceeding the maximum allowable deceleration threshold.

[0112] S54. Based on the accumulation height and retention time of the material in the working area of ​​the feeding mechanism, start the directional pushing operation of the pushing mechanism to compensate for the local retention area with continuous pushing or intermittent pulse pushing.

[0113] S55. Based on the obtained material accumulation thickness on the surface of the unloading mechanism, when the local accumulation thickness exceeds the safety threshold, temporarily lock the vehicle access permission of the corresponding unloading port, and activate the audible and visual warning to guide the vehicle to the unoccupied unloading port with the best path accessibility among the candidate unloading ports.

[0114] S56, synchronously correlates the speed gradient adjustment amount of the chain conveyor, the intervention frequency of the pushing mechanism and the distribution information of the unloading port, and suppresses the material flow oscillation during the adjustment process through closed-loop feedback.

[0115] S57. Monitor the fluctuation value of the corrected feed rate and the cycle time matching status within the preset time window. If it is not restored to the tolerance range or the cycle time is synchronized, trigger an iterative multi-level control instruction sequence.

[0116] In addition, after step S5, the following steps are also included: when the cumulative material feeding reaches the target value, the waste material compression and baling operation program is automatically triggered, and the vehicle access permission of the corresponding unloading port area is simultaneously locked; after the baling operation is completed, the cumulative material feeding counter is reset, and the baling threshold for the next cycle is dynamically updated according to the volume of the compressed material (e.g., the volume is reduced by 30% after compression); the single material feeding volume, cycle time matching status, and multi-level control command sequence and command execution process data calculated in the current cycle are integrated as a reference scheme for the next operation cycle.

[0117] like Figure 7 As shown, this embodiment of the invention also provides an automatic waste transfer control system based on multi-mechanism collaborative scheduling, including: a feeding mechanism, comprising a chain conveyor for transporting waste to the unloading pit, the unloading section of the chain conveyor extending to the unloading pit to form a continuous feeding channel; a pushing mechanism, disposed in the transfer corridor between the unloading port and the receiving section, for pushing waste to the working area of ​​the chain conveyor; a laser scanning device, disposed at the unloading port of the chain conveyor, preferably a single-line laser scanner, characterized by linear scanning to obtain a real-time curve of the waste height at the unloading port, and due to its single-line nature, the laser scanning efficiency is high; a gravity meter, disposed in the waste transport vehicle entry area; and a control platform, respectively connected to the pushing mechanism, the feeding mechanism, the laser scanning device and the gravity meter, for executing the method described above; wherein, the unloading pit has a truncated pyramidal structure that is wider at the top and narrower at the bottom, optimizing the natural sliding and storage efficiency of materials.

[0118] Furthermore, the control platform includes: a main control unit and a chain conveyor control unit, a pusher control unit, and a laser scanner control unit connected to the main controller. The chain conveyor control unit includes: a chain conveyor drive subunit connected to the chain conveyor and the main control unit, and a motion feedback subunit connected to the chain conveyor and the main control unit, respectively; the pusher control unit includes: a pusher mechanism drive subunit connected to the pusher mechanism and the main control unit, respectively; the laser scanner control unit includes: a scan control subunit connected to the laser scanner and the main control unit, respectively.

[0119] Since the systems / devices described in the above embodiments of the present invention are systems / devices used to implement the methods of the above embodiments of the present invention, those skilled in the art can understand the specific structure and modifications of the systems / devices based on the methods described in the above embodiments of the present invention, and therefore will not be repeated here. All systems / devices used in the methods of the above embodiments of the present invention fall within the scope of protection of the present invention.

[0120] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0121] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, as well as combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions.

[0122] It should be noted that any reference numerals placed between parentheses in the claims should not be construed as limiting the claims. The word "comprising" does not exclude the presence of components or steps not listed in the claims. The word "a" or "an" preceding a component does not exclude the presence of a plurality of such components. The invention can be implemented by means of hardware comprising several different components and by means of a suitably programmed computer. In claims that enumerate several means, several of these means may be embodied by the same hardware. The use of the terms first, second, third, etc., is merely for convenience of expression and does not indicate any order. These terms can be understood as part of the component names.

[0123] Furthermore, it should be noted that in the description of this specification, the terms "one embodiment," "some embodiments," "embodiment," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Furthermore, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0124] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the claims should be interpreted to include both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0125] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, then this invention should also include these modifications and variations.

Claims

1. A method for automatic waste transfer control based on multi-agency collaborative scheduling, characterized in that, include: Based on the acquired data on the load of garbage trucks, the spatial distribution information, space occupancy information, and unloading port information of the unloading pits, the system dynamically allocates the unloading port positioning parameters, vehicle unloading window period, and vehicle operation time rhythm to guide the corresponding vehicles in unloading. This includes: real-time acquisition of the load data of garbage trucks, the spatial distribution information, space occupancy information, and unloading port information of the unloading pits; calculation of the path distance, load matching degree, and collision avoidance margin between each unloading pit and the current vehicle based on the load data of garbage trucks, the spatial distribution information, and space occupancy information of the unloading pits, generating a spatial fit degree through weighted scoring, filtering unloading pits with a spatial fit degree higher than a set threshold, and considering the unloading port corresponding to the unloading pit as a candidate unloading port; and, based on a pre-trained dynamic programming algorithm model, regressing from the terminal time to the initial time with the goal of maximizing continuous utilization. The system calculates the available time window for each candidate unloading port, which includes a start timestamp, duration, and efficiency weight coefficient. A conflict resolution tree model is constructed, combining candidate unloading ports with available time windows as decision nodes. Node weights are quantified by the product of spatial fitness and efficiency weight coefficients. After traversing the conflict resolution tree model and pruning branches with weights below the critical value layer by layer, the system outputs the global optimal solution containing the optimal unloading port and time window combination. The duration of the time window in the global optimal solution is divided into several basic time slices, using the vehicle operation time cycle as the base unit. Each vehicle operation time cycle corresponds to the base time consumption of the standard action sequence of the vehicle's feeding positioning, unloading execution, and shifting avoidance at the unloading port. The optimal unloading port and time window combination, vehicle operation time cycle, and corresponding basic time slices are encoded into a structured instruction stream and pushed to the corresponding vehicle. The material retained at the discharge port is transported to the working area of ​​the unloading mechanism by the pushing mechanism, so that the unloading mechanism can discharge the material into the discharge pit; The system collects motion parameters and load data of the unloading mechanism and determines the matching status of the unloading mechanism and the vehicle's operating time cycle. This includes: collecting the running speed through a speed sensor installed on the drive shaft of the unloading mechanism; extracting time markers from the vehicle's operating time cycle for the completion of feeding positioning, the start and end of unloading execution, and the triggering of shifting and avoidance actions, and establishing a three-stage time sequence benchmark for the vehicle's operating time cycle; determining the periodic arrival time of the receiving section of the unloading mechanism based on the running speed of the unloading mechanism; comparing the periodic arrival time of the receiving section of the unloading mechanism with the three-stage time sequence benchmark; calculating the overlap duration between the start and end time of unloading execution and the transportation window of the receiving section; and combining this with monitoring the accumulation thickness and distribution pattern of the material on the surface of the unloading mechanism to determine the matching status of the unloading mechanism's operating time cycle and the vehicle's operating time cycle. The unloading mechanism's operating time cycle is the time span of the periodic transportation window of the receiving section. The laser scanning device monitors the three-dimensional contour data inside the unloading pit before and after material feeding in real time. A dynamic volume model is established based on the three-dimensional contour data and motion parameters. The amount of material fed in a single operation is calculated in real time in combination with the preset material density parameters. When the single feeding amount exceeds the preset tolerance range or the cycle time is out of sync, a multi-level control command sequence is triggered to adjust the speed gradient of the feeding mechanism, compensate for the intervention of the pushing mechanism, and redistribute the material discharge port.

2. The automatic waste transfer control method based on multi-agency collaborative scheduling as described in claim 1, characterized in that, The three-dimensional contour data inside the unloading pit before and after material feeding is monitored in real time using a laser scanning device. A dynamic volume model is established based on the three-dimensional contour data and motion parameters. Combined with preset material density parameters, the amount of material fed in a single batch is calculated in real time, including: The three-dimensional contour data of the unloading pit before and after material feeding is collected in real time by a laser scanning device. The height distribution of the garbage accumulation surface at the beginning and end of the feeding stage is extracted, and the average height value of the garbage accumulation surface is generated based on multi-point height sampling. Based on the pre-set trapezoidal structure parameters and average height of the unloading pit, the cross-sectional area of ​​the waste flow is constructed; The operating speed and duration of a single feeding operation of the feeding mechanism are acquired synchronously. The material pushing distance is obtained by multiplying the operating speed of the feeding mechanism by the duration of a single feeding operation, and the real-time volume change is calculated by combining the cross-sectional area of ​​the waste flow to obtain a dynamic volume model. The system retrieves the corresponding waste material density parameters from the historical database, maps the dynamic volume model to the waste material density parameters, and outputs the weight of a single feeding operation.

3. The automatic waste transfer control method based on multi-agency collaborative scheduling as described in claim 1, characterized in that, When the single feeding amount exceeds the preset tolerance range or the cycle time is out of sync, a multi-level control command sequence is triggered to adjust the speed gradient of the feeding mechanism, compensate for the intervention of the pushing mechanism, and redistribute the unloading port, including: When the single feeding quantity exceeds the preset tolerance range or the matching status is out of sync, a multi-level control command sequence is triggered to perform the following steps: Based on the direction and absolute value of the deviation in the cycle time matching, the deviation is divided into multiple control levels. Among them, positive deviation indicates that the material feed exceeds the limit, and negative deviation indicates that the supply is insufficient. When the amount of material fed in a single operation exceeds the preset threshold, the operating speed is increased step by step according to the positive deviation level, with each level of speed increase being 5%-15% of the operating speed of the feeding mechanism; When the material supply is insufficient, a negative deviation is triggered, and the operating speed of the conveying and unloading mechanism is reduced in a step-by-step manner according to the control level, with each reduction not exceeding the maximum allowable deceleration threshold. Based on the accumulation height and retention time of the material in the working area of ​​the feeding mechanism, the pushing mechanism is activated to perform directional pushing operations, and continuous pushing or intermittent pulse pushing compensation is implemented for the local retention area. Based on the obtained material accumulation thickness on the surface of the unloading mechanism, when the local accumulation thickness exceeds the safety threshold, the vehicle access permission of the corresponding unloading port is temporarily blocked, and the audible and visual warning is activated to guide the vehicle to the unoccupied unloading port with the best path accessibility among the candidate unloading ports. The speed gradient adjustment amount of the chain conveyor, the intervention frequency of the pushing mechanism, and the distribution information of the unloading port are synchronously correlated, and the material flow oscillation during the adjustment process is suppressed through closed-loop feedback; Within a preset time window, monitor the fluctuation value of the corrected feed rate and the cycle time matching status. If the feed rate does not recover to the tolerance range or the cycle time is not synchronized, trigger an iterative multi-level control instruction sequence.

4. The automatic waste transfer control method based on multi-agency collaborative scheduling as described in claim 3, characterized in that, Cyclic timing desynchronization refers to a state of misalignment in job timing triggered by at least one of the following conditions: The duration of overlap between the vehicle unloading execution period and the material receiving section transportation window of the unloading mechanism is less than the preset overlap threshold. The thickness of the material accumulation on the surface of the unloading mechanism exceeds the morphological safety threshold, and the distribution pattern indicates that the unloading action was not completed within the transport window of the receiving section; The total time from the completion of the vehicle's feeding and positioning to the triggering of the displacement and avoidance action deviates from the baseline time and exceeds the preset vehicle cycle time tolerance range. Unplanned interruptions occur in the periodic arrival time sequence of the material receiving section of the unloading mechanism, making it impossible to continuously match the vehicle operation time rhythm.

5. The automatic waste transfer control method based on multi-agency collaborative scheduling as described in any one of claims 1-4, characterized in that, Also includes: When the cumulative material discharge reaches the target value, the waste material compression and baling operation program is automatically triggered, and the vehicle access permission of the corresponding unloading port area is locked simultaneously. After the packaging operation is completed, the cumulative material feeding counter is reset, and the packaging threshold for the next cycle is dynamically updated based on the compressed material volume. The data generated by the single feeding quantity, cycle time matching status, multi-level control instruction sequence, and instruction execution process calculated in the current cycle are integrated as a reference scheme for the next work cycle.

6. An automatic waste transfer control system based on multi-mechanism collaborative scheduling, characterized in that, include: The unloading mechanism includes a chain conveyor for transporting unloaded materials to the unloading pit, wherein the unloading section of the chain conveyor extends into the unloading pit to form a continuous unloading channel. The pushing mechanism is located in the transfer corridor between the unloading port and the receiving section, and is used to push the garbage to the working area of ​​the chain conveyor. A laser scanning device is installed at the feed inlet of the chain conveyor. Gravity meter, installed in the area where garbage trucks enter the site; In addition, a control platform is connected to the pressing mechanism, the unloading mechanism, the laser scanning device and the gravity meter, respectively, for performing the method as described in any one of claims 1-5.

7. The automatic waste transfer control system based on multi-mechanism collaborative scheduling as described in claim 6, characterized in that, The control platform includes: a main control unit and a chain conveyor control unit, a pusher control unit, and a laser scanner control unit connected to the main controller.

8. The automatic waste transfer control system based on multi-mechanism collaborative scheduling as described in claim 7, characterized in that, The chain conveyor control unit includes: a chain conveyor drive subunit connected to the chain conveyor and the main control unit respectively, and a motion feedback subunit connected to the chain conveyor and the main control unit respectively; The pusher control unit includes: a pusher mechanism drive subunit connected to the pusher mechanism and the main control unit respectively; The laser scanning control unit includes a scanning control subunit that is connected to the laser scanning device and the main control unit, respectively.

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