Horizontal compression control method and system of garbage compression truck

Abstract

The application discloses a horizontal compression control method and system of a garbage compression vehicle, and relates to the technical field of engineering equipment control. The method comprises the following steps: obtaining historical operation data and generating historical standard parameters; obtaining garbage picture information of a current garbage pile, performing data matching in the historical standard parameters, and obtaining an optimal compression scheme; detecting resistance change data of a compression head in a horizontal pushing process in real time, and dynamically adjusting the optimal compression scheme; monitoring the pressure at the edges of the two sides of the compression head in real time, and setting the deflection of the compression head; obtaining sound data generated by the garbage pile in the compression process, identifying foreign matters by combining the sound data and the resistance change data, and triggering a device protection mechanism; and triggering an anti-adhesion mechanism to compress the garbage pile to prevent adhesion. The application has the effect of improving the efficiency and intelligence when compressing garbage horizontally.

Description

Technical Field

[0001] This application relates to the technical field of engineering equipment control, and in particular to a horizontal compression control method and system for a garbage compactor truck. Background Technology

[0002] Garbage compactors are a common type of waste disposal equipment in people's lives. Their main function is to compress the garbage inside the vehicle, reducing its space requirements and facilitating transportation.

[0003] In existing technologies, garbage compactors typically employ direct compression when horizontally compressing garbage. This involves gathering the garbage inside the compactor and applying horizontal pressure from one side to the other using a metal plate or other planar compression device. Compression stops when the compactor head reaches its maximum pressure, completing the horizontal compression. However, this method is relatively simple and rudimentary. During horizontal compression, uneven distribution of the garbage can cause the compactor head to deflect, resulting in poor compression. Furthermore, it fails to address issues like foreign object detection and garbage adhesion, further reducing compression effectiveness and resulting in incomplete compaction. Moreover, the compression system cannot effectively adapt to pressure variations when compressing different types of garbage, and there is no data feedback to serve as an adjustment standard for subsequent system compression. Therefore, how to intelligently and efficiently perform horizontal garbage compression is a pressing issue that needs to be addressed. Summary of the Invention

[0004] The purpose of this invention is to provide a horizontal compression control method and system for a garbage compactor truck to solve the problems mentioned in the background art.

[0005] In a first aspect, this application provides a horizontal compression control method for a garbage compactor truck, the method comprising: Obtain historical operation data, and based on the historical operation data, obtain historical waste type, historical waste volume, historical waste density and historical pressure parameters, and generate historical standard parameters; Obtain the garbage image information of the current garbage heap, and perform data matching in the historical standard parameters based on the garbage image information to obtain the optimal compression scheme; The compression process is initiated according to the optimal compression scheme, and the resistance change data of the compression head during the horizontal advancement process is detected in real time. The optimal compression scheme is dynamically adjusted according to the resistance change data. During the compression process, the pressure at both sides of the compression head is monitored in real time to obtain two side pressure values, and the compression head is deflected according to the two side pressure values. Acquire sound data generated by the garbage pile during the compression process, combine the sound data with the resistance change data to identify foreign objects, obtain the garbage foreign objects, and trigger the equipment protection mechanism; The compression head collects humidity and viscosity data of the waste pile, and triggers an anti-adhesion mechanism based on the humidity and viscosity data to compress the waste pile in an anti-adhesion manner.

[0006] Preferably, the step of generating historical standard parameters by obtaining historical waste type, historical waste volume, historical waste density, and historical pressure parameters based on the historical operation data is as follows: Based on the historical operation data, the historical operation data is cleaned to obtain target historical operation data with complete data type. Data is extracted from the target historical operation data to obtain multiple historical waste types, historical waste volumes, historical waste densities, and historical pressure parameters; Waste-side parameters are generated based on multiple historical waste types, historical waste volumes, and historical waste densities; Based on the historical pressure parameters, pressure change identification is performed on the historical pressure parameters to obtain the historical pressure change curve for each historical pressure parameter; The optimal pressure change curve is obtained by performing optimal screening on multiple historical pressure change curves, and equipment-side parameters are generated based on the optimal pressure change curve. Historical standard parameters are generated by combining the waste-side parameters and the equipment-side parameters.

[0007] Preferably, the step of performing data matching based on the garbage image information in the historical standard parameters to obtain the optimal compression scheme specifically includes: Based on the garbage image information, extract the current garbage type, current garbage volume, and current garbage density from the garbage image information; Based on the current waste type, the current waste volume, and the current waste density, the target waste-side parameters of the waste to be compressed are obtained. Based on the target waste-side parameters, parameter matching is performed among multiple device-side parameters to obtain the target device-side parameters; The optimal compression scheme is generated based on the optimal pressure change curve in the target equipment side parameters.

[0008] Preferably, before the step of generating the optimal compression scheme, the following steps are also included: The garbage image information is scanned to obtain the number and distribution of different current garbage types; Based on the current waste type, the quantity of each type, and the distribution of each type, a compression target for the waste pile is generated; Based on the compression target, the compression target is divided into stages to obtain multiple stage compression targets; Based on multiple stage compression objectives, a stage objective table is constructed, and the stage objective table is added to the optimal compression scheme to adjust the target device-side parameters in stages.

[0009] Preferably, the step of real-time detection of resistance changes during the horizontal propulsion of the compression head, and dynamic adjustment of the optimal compression scheme based on the resistance change data, specifically includes: During the compression process, the real-time pressure data borne by the compression head is detected in real time, and the resistance change data generated by the waste pile is determined based on the real-time pressure data. Based on the resistance change data, a resistance change curve is generated, and the resistance change curve is identified to obtain the current resistance change trend; The generation end of the resistance change curve is monitored in real time to determine whether there is a drastic change at the generation end; If it is determined that there is no drastic change at the generating end, then the first scheme optimization parameters are generated based on the current resistance change curve, and the first scheme optimization parameters are substituted into the optimal compression scheme; If it is determined that there is a drastic change at the generation end, the amount and direction of the curve change at the generation end are identified, and second scheme optimization parameters are generated based on the amount and direction of the curve change. The second scheme optimization parameters are then substituted into the optimal compression scheme.

[0010] Preferably, the step of monitoring the pressure at both edges of the compression head in real time to obtain two side pressure values, and then setting the deflection of the compression head based on the two side pressure values, specifically includes: The pressure at both edges of the compression head is monitored in real time to obtain the side pressure values ​​on both sides of the compression head, and marked as the left pressure value and the right pressure value according to the orientation. The pressure values ​​on the left and right are compared to obtain the pressure difference, and it is determined whether the pressure difference is greater than a preset pressure difference threshold. If it is determined that the pressure difference is greater than the pressure difference threshold, the side with greater pressure is marked as the adjustment side, and the lateral hydraulic support force provided by the compression head to the left and right sides is extracted. Extract the target direction of the adjustment side, adjust the lateral hydraulic support force to deflect towards the target direction, and tilt the lateral hydraulic support force towards the adjustment side.

[0011] Preferably, the steps of acquiring sound data generated by the garbage pile during the compression process, combining the sound data with the resistance change data to identify foreign objects, and triggering the equipment protection mechanism are as follows: Acquire sound data generated by the garbage heap during the compression process, perform sound information recognition on the sound data, and obtain voiceprint information and sound trigger frequency; Based on the sound trigger frequency and the voiceprint information, the garbage that generates the sound is characterized to obtain the first foreign object feature; Based on the resistance change data, the feature of the garbage that produces the sound is identified to obtain the second foreign object feature; By combining the first foreign object characteristics and the second foreign object characteristics, the foreign object is identified as a type of waste foreign object, and the equipment protection mechanism is triggered. Based on the device protection mechanism, the compression head stops compressing and temporarily retracts, waiting for the preset stress release period to end before resuming compression.

[0012] Preferably, the step of collecting humidity and viscosity data of the waste pile through a compression head, and triggering an anti-adhesion mechanism based on the humidity and viscosity data to compress the waste pile in an anti-adhesion manner, specifically includes: The humidity and viscosity data of the garbage pile are collected by the compression head, and the adhesion reference value of the garbage pile during the compression process is obtained based on the humidity and viscosity data. Determine whether the adhesion reference value is greater than or equal to a preset standard value; If it is determined that the adhesion reference value is greater than or equal to the standard value, then the compression head is controlled to perform an intermittent retraction-recompression cycle operation; The intermittent retraction-recompression operation includes compressing a certain distance according to a preset target distance, then automatically retracting the compression head and advancing it again.

[0013] Secondly, this application provides a horizontal compression control system for a garbage compactor truck, the system comprising: Standard generation module: used to acquire historical operation data, and based on the historical operation data, obtain historical waste type, historical waste volume, historical waste density and historical pressure parameters, and generate historical standard parameters; Scheme generation module: used to obtain the garbage image information of the current garbage heap, and to perform data matching in the historical standard parameters based on the garbage image information to obtain the optimal compression scheme; Scheme adjustment module: used to start the compression process according to the optimal compression scheme, and to detect the resistance change data of the compression head during the horizontal advancement process in real time, and dynamically adjust the optimal compression scheme according to the resistance change data; Edge adjustment module: used to monitor the pressure at both sides of the compression head in real time during the compression process, obtain two side pressure values, and set the deflection of the compression head according to the two side pressure values; Foreign object protection module: used to acquire sound data generated by the garbage pile during the compression process, combine the sound data and the resistance change data to identify foreign objects, obtain the garbage foreign objects, and trigger the equipment protection mechanism; Adhesion handling module: used to collect humidity and viscosity data of the waste pile through the compression head, and trigger the anti-adhesion mechanism based on the humidity and viscosity data to compress the waste pile in an anti-adhesion manner.

[0014] In summary, this application includes at least one of the following beneficial technical effects: By acquiring and processing historical operational data from the garbage compactor, various standard parameters are obtained, generating historical standard parameters. Then, visual information of the garbage pile is acquired, and based on the identified garbage types, a matching process is performed against the historical standard parameters to generate an optimal compression scheme. The compression process is initiated according to this optimal scheme, and the resistance changes of the compression head during horizontal advancement are monitored in real time, with dynamic adjustments made to the optimal compression scheme based on these changes. During compression, the pressure at both edges of the compression head is monitored. If uneven pressure occurs, the support rods at the rear are adjusted to increase support on the side with excessive pressure. Simultaneously, sound data from the garbage pile is collected during compression. Combining this sound data with resistance change data, the presence of foreign objects that could potentially damage the compression device is identified, triggering a protection mechanism. Furthermore, the humidity and viscosity data of the garbage pile are used to determine if the garbage will stick together during compression. If sticking is likely, an anti-sticking mechanism is activated to compress the garbage pile. This improves the efficiency and intelligence of horizontal garbage compression. Attached Figure Description

[0015] Fig. 1 This is a flowchart illustrating the steps of a horizontal compression control method for a garbage compactor provided in an embodiment of this application; Fig. 2 This is a block diagram of a horizontal compression control system for a garbage compactor provided in an embodiment of this application.

[0016] Explanation of reference numerals in the attached diagram: 1. Standard generation module; 2. Scheme generation module; 3. Scheme adjustment module; 4. Edge adjustment module; 5. Foreign object protection module; 6. Adhesion handling module. Detailed Implementation

[0017] The following is in conjunction with the appendix Figs. 1-2This application will be described in further detail, but the embodiments of the present invention are not limited thereto.

[0018] This application discloses a horizontal compression control method and system for a garbage compactor truck.

[0019] This embodiment relates to a horizontal compression control method for a garbage compactor truck, the method comprising: S100: Obtain historical operation data, and based on the historical operation data, obtain historical waste type, historical waste volume, historical waste density and historical pressure parameters, and generate historical standard parameters; S200: Obtain the garbage image information of the current garbage heap, and perform data matching in historical standard parameters based on the garbage image information to obtain the optimal compression scheme; S300: Starts the compression process according to the optimal compression scheme and monitors the resistance change data of the compression head during horizontal advancement in real time, and dynamically adjusts the optimal compression scheme based on the resistance change data; S400: During the compression process, the pressure at both sides of the compression head is monitored in real time to obtain two side pressure values, and the compression head is deflected according to the two side pressure values. S500: Acquires sound data generated by the garbage pile during the compression process, combines the sound data with resistance change data to identify foreign objects, obtain the garbage foreign objects, and trigger the equipment protection mechanism; S600: Collects humidity and viscosity data of the waste pile through the compression head, and triggers an anti-adhesion mechanism based on the humidity and viscosity data to compress the waste pile in an anti-adhesion manner.

[0020] Based on historical operational data, the steps for obtaining historical waste type, volume, density, and pressure parameters, and generating historical standard parameters are as follows: Based on historical operation data, the historical operation data is cleaned to obtain target historical operation data with complete data types. Data is extracted from the target historical operation data to obtain multiple historical waste types, historical waste volumes, historical waste densities, and historical pressure parameters; Based on multiple historical waste types, historical waste volumes, and historical waste densities, waste-side parameters are generated; Based on historical pressure parameters, pressure changes are identified for each historical pressure parameter, resulting in a historical pressure change curve for each parameter. The optimal pressure change curve is obtained by screening multiple historical pressure change curves, and equipment side parameters are generated based on the optimal pressure change curve. Historical standard parameters are generated by combining waste-side parameters and equipment-side parameters.

[0021] In practice, we take the historical operational data of a certain model of garbage compactor truck operating in City A for one year as an example. First, the historical operational data is cleaned. It is found that due to a sensor malfunction, the pressure parameters were not fully recorded on a certain day. The system marks the data for that day as invalid and deletes it, thus obtaining the target historical operational data with complete data types. Next, multiple historical garbage types are extracted from the target historical operational data, such as plastic, cardboard, and kitchen waste, as well as the corresponding historical garbage volumes, such as the average volume of plastic being 0.5 cubic meters, cardboard being 0.3 cubic meters, and kitchen waste being 0.2 cubic meters; historical garbage densities, such as the density of plastic being 50 kg / m³, cardboard being 80 kg / m³, and kitchen waste being 300 kg / m³; and historical pressure parameters, such as the maximum pressure when compressing plastic being 8 MPa, the maximum pressure when compressing cardboard being 6 MPa, and the maximum pressure when compressing kitchen waste being 10 MPa. Then, based on multiple historical waste types, volumes, and densities, waste-side parameters are generated. For example, kitchen waste has a high average density, and its corresponding waste-side parameter is labeled "high density, easy to compact." Next, based on historical pressure parameters, pressure change identification is performed for each historical pressure parameter, resulting in a historical pressure change curve for each parameter. For instance, when compressing plastic, the pressure steadily increases from 2 MPa to 8 MPa, while when compressing cardboard, the pressure rapidly increases from 1 MPa to 6 MPa and then remains stable. Multiple historical pressure change curves are then optimized to identify the curve with the smoothest pressure increase and lowest energy consumption during each compression process. This curve is then used to generate equipment-side parameters, such as setting the initial pressure to 1 MPa and the propulsion speed to 0.05 meters per second. Finally, combining the waste-side and equipment-side parameters, historical standard parameters are generated and stored in the system for matching and optimizing subsequent compression schemes.

[0022] The steps for obtaining the optimal compression scheme by matching data against historical standard parameters based on garbage image information are as follows: Based on the garbage image information, extract the current garbage type, current garbage volume, and current garbage density from the garbage image information; Based on the current waste type, current waste volume, and current waste density, the target waste-side parameters of the waste to be compressed are obtained; Based on the target waste-side parameters, parameter matching is performed among multiple device-side parameters to obtain the target device-side parameters; The optimal compression scheme is generated based on the optimal pressure change curve in the target equipment side parameters.

[0023] In practice, taking the current garbage pile collected by the same garbage compactor truck in Zone B as an example, the system first acquires the garbage image information of the current garbage pile. Through image recognition technology, it extracts the current garbage type (e.g., plastic bottles, cardboard boxes, and a small amount of leaves), the current garbage volume (e.g., approximately 2 cubic meters), and the current garbage density (e.g., an estimated density of 100 kg / m³). Then, based on the current garbage type, volume, and density, the system obtains the target garbage-side parameters for the garbage to be compressed, labeled as "mixed medium-density garbage." Next, based on the target garbage-side parameters, it performs parameter matching among multiple equipment-side parameters in historical standard parameters to find the optimal equipment-side parameters for processing similar garbage types and densities. For example, the system matches the optimal pressure change curve for processing "mixed medium-density garbage" in the history, where the initial pressure is 2 MPa, increasing by 0.5 MPa for every 0.1 meter of advance, until reaching 7 MPa. Based on this optimal pressure change curve in the matched target equipment-side parameters, the optimal compression scheme is generated. The specific measures include: setting the starting position of the compression head, the initial propulsion pressure of 2 MPa, the propulsion speed of 0.08 meters per second, and planning the entire compression stroke to be 1.5 meters. The pressure is adjusted in three stages to ensure that the waste is compacted and the energy consumption is low.

[0024] Before generating the optimal compression scheme, the following steps are also included: The garbage image information is scanned to obtain the number and distribution of different current garbage types; Based on the current waste type, quantity, and distribution, generate a waste pile compression target; Based on the compression target, the compression target is broken down into stages to obtain multiple stages of compression targets; Based on multiple compression goals, a stage target table is constructed and added to the optimal compression scheme to adjust the target device-side parameters in stages.

[0025] In practice, before generating the optimal compression scheme, the system performs a more detailed scan of the current garbage pile's image information. The scan reveals the quantity and distribution of different types of garbage. For example, it identifies plastic bottles as approximately 50%, cardboard boxes as approximately 30%, and leaves and debris as approximately 20%. Furthermore, plastic bottles are mainly concentrated on the right side of the garbage pile, cardboard boxes on the left, and leaves scattered on the surface. Based on the current garbage types, quantities, and distribution, a compression target for the garbage pile is generated. The target prioritizes compacting the densely packed plastic bottle area on the right, then processes the cardboard boxes on the left, and finally smooths out the leaves on the surface. Next, based on this compression target, the target is broken down into multiple stages: the first stage is compressing the plastic bottles within a 0-0.5 meter range on the right; the second stage is compressing the cardboard boxes within a 0.5-1.0 meter range on the left; and the third stage is overall compaction of the remaining portion. Then, based on these multiple stage compression targets, a stage target table is constructed, listing the starting position, target pressure, and acceleration speed for each stage. Finally, this stage target table is added to the optimal compression scheme, thereby making the target equipment side parameters more targeted and adapting to the uneven distribution inside the waste pile.

[0026] The steps for real-time monitoring of resistance changes during the horizontal propulsion of the compression head, and dynamic adjustment of the optimal compression scheme based on these resistance changes, are as follows: During the compression process, the real-time pressure data of the compression head is detected, and the resistance change data generated by the waste pile is determined based on the real-time pressure data. Based on the resistance change data, a resistance change curve is generated, and the resistance change curve is identified to obtain the current resistance change trend; Real-time monitoring of the generation end of the resistance change curve to determine whether there are drastic changes at the generation end; If it is determined that there is no drastic change at the generation end, the first scheme optimization parameters are generated based on the current resistance change curve, and the first scheme optimization parameters are substituted into the optimal compression scheme. If it is determined that there is a drastic change at the generation end, the amount and direction of the curve change at the generation end are identified, and the second scheme optimization parameters are generated based on the amount and direction of the curve change. The second scheme optimization parameters are then substituted into the optimal compression scheme.

[0027] In application, after initiating the compression process according to the optimal compression scheme, the system monitors the resistance changes of the compression head during horizontal advancement in real time. For example, after the compression process begins, sensors monitor the real-time pressure data experienced by the compression head, initially detecting a resistance of 3 MPa. Based on the real-time pressure data, the system determines the resistance changes generated by the waste pile and generates a resistance change curve. By identifying the resistance change curve, the current resistance change trend is obtained; for example, the curve shows that the resistance rises steadily to 5 MPa within the first 0.3 meters. Simultaneously, the system monitors the generation end of the resistance change curve in real time to determine if there are any drastic changes. Suppose that when the compression reaches 0.4 meters, monitoring shows no drastic changes at the generation end, and the curve continues to rise smoothly. Then, the system generates first-stage optimization parameters based on the current resistance change curve, such as fine-tuning the advancement speed from 0.08 meters per second to 0.09 meters per second to maintain efficiency. This first-stage optimization parameter is then substituted into the optimal compression scheme, updating the compression command in real time. Conversely, if the monitoring detects a drastic change at the generating end when the advance reaches 0.6 meters, with the resistance suddenly jumping from 6 MPa to 9 MPa, the system immediately identifies the magnitude and direction of the curve change at the generating end. The magnitude change is 3 MPa, and the direction is a rapid increase. Based on the magnitude and direction of the curve change, a second optimization parameter is generated, such as immediately reducing the pressure by 2 MPa and pausing the advance for 0.5 seconds. This second optimization parameter is then substituted into the optimal compression scheme to adjust subsequent actions and avoid overloading the equipment.

[0028] The steps for real-time monitoring of the pressure at both edges of the compression head to obtain two side pressure values, and then adjusting the deflection of the compression head based on these two side pressure values, are as follows: The pressure at both edges of the compression head is monitored in real time to obtain the side pressure values ​​on both sides of the compression head, and marked as the left pressure value and the right pressure value according to the orientation. The pressure values ​​on the left and right are compared to obtain the pressure difference, and it is determined whether the pressure difference is greater than the preset pressure difference threshold. If it is determined that the pressure difference is greater than the pressure difference threshold, the side with greater pressure is marked as the adjustment side, and the lateral hydraulic support force provided by the compression head to the left and right sides is extracted. Extract the target direction of the adjustment side, adjust the lateral hydraulic support force to deflect it in the target direction, and tilt the lateral hydraulic support force towards the adjustment side.

[0029] In operation, during the compression process, the system monitors the pressure at both edges of the compression head in real time. For example, pressure sensors installed on the left and right sides of the compression head detect lateral pressure values: 4 MPa on the left and 6 MPa on the right. Based on their location, the system labels these as the left and right pressure values, respectively. Next, the left and right pressure values ​​are compared, yielding a pressure difference of 2 MPa. Then, it is determined whether this pressure difference exceeds a preset pressure difference threshold. Assuming the preset threshold is 1.5 MPa, 2 MPa is greater than 1.5 MPa, therefore the system determines that the pressure difference exceeds the threshold. Consequently, the system labels the side with the higher pressure, the right side, as the adjustment side. Then, the lateral hydraulic support force provided by the compression head to both sides is extracted; for example, the current support force on each side is 50 kN. Finally, the target direction of the adjustment side is extracted, that is, the direction that needs to be strengthened is the right side. The system adjusts the lateral hydraulic support force to deflect in this target direction, increasing the hydraulic support force on the right side to 70 kN and decreasing it on the left side to 30 kN. This causes the compression head to tilt to the right side where the pressure is greater, thereby balancing the pressure on both sides, preventing the compression head from deflecting due to uneven force, and ensuring a smooth compression process.

[0030] The steps for acquiring sound data generated by the garbage pile during the compression process, combining the sound data with resistance change data to identify foreign objects, and triggering the equipment protection mechanism are as follows: Acquire sound data generated by the garbage heap during the compression process, perform sound information recognition on the sound data, and obtain voiceprint information and sound trigger frequency; Based on the sound trigger frequency and voiceprint information, the garbage that produces the sound is characterized to obtain the first foreign object feature; Based on the resistance change data, the characteristics of the garbage that produces the sound are identified to obtain the second foreign object characteristics; By combining the first and second foreign object characteristics, the foreign object is identified as a type of waste foreign object, and the equipment protection mechanism is triggered. Based on the equipment protection mechanism, the compression head stops compressing and temporarily retracts, waiting for the preset stress release period to end before resuming compression.

[0031] In operation, during the compression process, the system acquires sound data generated by the garbage pile. For example, a sharp metallic clanging sound is captured by a microphone. First, sound information recognition is performed on this sound data to obtain voiceprint information, showing that the sound contains a specific high-frequency band and that the sound is triggered twice consecutively within a short period. Based on the sound trigger frequency and voiceprint information, the system performs feature recognition on the garbage that produced the sound, obtaining the first foreign object feature, which is judged to be a hard metal object. At the same time, based on real-time monitoring of resistance change data, a sharp peak is found in the resistance data at the same time as the sound is triggered, jumping from 5 MPa to 9 MPa instantaneously. Based on this resistance change data, the system performs feature recognition on the garbage that produced the sound, obtaining the second foreign object feature, which is judged to be an incompressible hard object. Then, combining the first and second foreign object features, the system performs type recognition of the foreign object, comprehensively judging that there is a metallic foreign object in the garbage. Once the garbage foreign object is identified, the system immediately triggers the equipment protection mechanism. Based on the equipment protection mechanism, the compression head stops the compression action and is controlled to temporarily retract 0.5 meters to release stress. The system waits for a preset stress release period, such as 5 seconds, and then tries to slowly advance and compress again after the period ends, thus protecting the compression device from damage.

[0032] The process involves collecting moisture and viscosity data from the waste pile via a compression head, and then triggering an anti-adhesion mechanism based on this data. The specific steps for compressing the waste pile to prevent adhesion are as follows: The humidity and viscosity data of the waste pile are collected by the compression head. Based on the humidity and viscosity data, the adhesion reference value of the waste pile during the compression process is obtained. Determine whether the adhesion reference value is greater than or equal to the preset standard value; If the adhesion reference value is determined to be greater than or equal to the standard value, the compression head is controlled to perform an intermittent retraction-recompression cycle operation. The intermittent retraction-recompression operation involves compressing a certain distance according to a preset target distance, then automatically retracting the compression head and advancing it again.

[0033] In operation, during the compression process, the system collects moisture and viscosity data of the waste pile using sensors integrated into the compression head. For example, the sensor measures the current moisture content of the waste pile to be 70% and the viscosity to be 0.8 Pa·s. Based on the moisture and viscosity data, the system calculates the adhesion reference value of the waste pile during compression, assuming the calculated adhesion reference value is 0.75. Then, the system determines whether this adhesion reference value is greater than or equal to a preset standard value, assuming the standard value is 0.7. Since 0.75 is greater than 0.7, it is determined that the adhesion reference value is greater than the standard value. Therefore, the system controls the compression head to perform an "intermittent retraction-recompression" cycle to trigger the anti-adhesion mechanism. Specifically, the compression head automatically retracts 0.1 meters after advancing 0.3 meters according to a preset target distance, for example, after each 0.3-meter compression, it advances again. This cycle continues until the compression head completes the entire compression stroke. In this way, wet and sticky waste can be effectively prevented from adhering to the surface of the compression head, ensuring that the compressed waste block is easy to unload, while ensuring the continuity and efficiency of the compression process.

[0034] This invention provides a horizontal compression control system for a garbage compactor truck, using any one of the horizontal compression control methods for a garbage compactor truck described above. The system includes the following: Standard generation module 1: Used to acquire historical operation data, and based on the historical operation data, obtain historical waste type, historical waste volume, historical waste density and historical pressure parameters, and generate historical standard parameters; Scheme generation module 2: Used to obtain the garbage image information of the current garbage heap, and to perform data matching in historical standard parameters based on the garbage image information to obtain the optimal compression scheme; Scheme Adjustment Module 3: Used to start the compression process according to the optimal compression scheme, and to detect the resistance change data of the compression head during the horizontal advancement process in real time, and dynamically adjust the optimal compression scheme according to the resistance change data; Edge adjustment module 4: Used to monitor the pressure at both sides of the compression head in real time during the compression process, obtain two side pressure values, and set the deflection of the compression head according to the two side pressure values. Foreign object protection module 5: It is used to acquire the sound data generated by the garbage pile during the compression process, combine the sound data and resistance change data to identify foreign objects, obtain the garbage foreign objects, and trigger the equipment protection mechanism. Adhesion handling module 6: It is used to collect the humidity and viscosity data of the waste pile through the compression head, and trigger the anti-adhesion mechanism based on the humidity and viscosity data to compress the waste pile in an anti-adhesion manner.

[0035] The above are all preferred embodiments of this application, and are not intended to limit the scope of protection of this application. Therefore, all equivalent changes made in accordance with the structure, shape and principle of this application should be covered within the scope of protection of this application.

Claims

1. A horizontal compression control method for a garbage compactor truck, characterized in that, include: Obtain historical operation data, and based on the historical operation data, obtain historical waste type, historical waste volume, historical waste density and historical pressure parameters, and generate historical standard parameters; Obtain the garbage image information of the current garbage heap, and perform data matching in the historical standard parameters based on the garbage image information to obtain the optimal compression scheme; The compression process is initiated according to the optimal compression scheme, and the resistance change data of the compression head during the horizontal advancement process is detected in real time. The optimal compression scheme is dynamically adjusted according to the resistance change data. During the compression process, the pressure at both sides of the compression head is monitored in real time to obtain two side pressure values, and the compression head is deflected according to the two side pressure values. Acquire sound data generated by the garbage pile during the compression process, combine the sound data with the resistance change data to identify foreign objects, obtain the garbage foreign objects, and trigger the equipment protection mechanism; The compression head collects humidity and viscosity data of the waste pile, and triggers an anti-adhesion mechanism based on the humidity and viscosity data to compress the waste pile in an anti-adhesion manner.

2. The horizontal compression control method for a garbage compactor truck according to claim 1, characterized in that, Based on the historical operational data, the steps for obtaining historical waste type, historical waste volume, historical waste density, and historical pressure parameters, and generating historical standard parameters are as follows: Based on the historical operation data, the historical operation data is cleaned to obtain target historical operation data with complete data type. Data is extracted from the target historical operation data to obtain multiple historical waste types, historical waste volumes, historical waste densities, and historical pressure parameters; Waste-side parameters are generated based on multiple historical waste types, historical waste volumes, and historical waste densities; Based on the historical pressure parameters, pressure change identification is performed on the historical pressure parameters to obtain the historical pressure change curve for each historical pressure parameter; The optimal pressure change curve is obtained by performing optimal screening on multiple historical pressure change curves, and equipment-side parameters are generated based on the optimal pressure change curve. Historical standard parameters are generated by combining the waste-side parameters and the equipment-side parameters.

3. The horizontal compression control method for a garbage compactor truck according to claim 2, characterized in that, The steps for obtaining the optimal compression scheme by matching data in the historical standard parameters based on the garbage image information are as follows: Based on the garbage image information, extract the current garbage type, current garbage volume, and current garbage density from the garbage image information; Based on the current waste type, the current waste volume, and the current waste density, the target waste-side parameters of the waste to be compressed are obtained. Based on the target waste-side parameters, parameter matching is performed among multiple device-side parameters to obtain the target device-side parameters; The optimal compression scheme is generated based on the optimal pressure change curve in the target equipment side parameters.

4. The horizontal compression control method for a garbage compactor truck according to claim 3, characterized in that, Before generating the optimal compression scheme, the following steps are also included: The garbage image information is scanned to obtain the number and distribution of different current garbage types; Based on the current waste type, the quantity of each type, and the distribution of each type, a compression target for the waste pile is generated; Based on the compression target, the compression target is divided into stages to obtain multiple stage compression targets; Based on multiple stage compression objectives, a stage objective table is constructed, and the stage objective table is added to the optimal compression scheme to adjust the target device-side parameters in stages.

5. The horizontal compression control method for a garbage compactor truck according to claim 4, characterized in that, The steps of real-time detection of resistance changes during the horizontal propulsion of the compression head, and dynamic adjustment of the optimal compression scheme based on the resistance change data, are as follows: During the compression process, the real-time pressure data borne by the compression head is detected in real time, and the resistance change data generated by the waste pile is determined based on the real-time pressure data. Based on the resistance change data, a resistance change curve is generated, and the resistance change curve is identified to obtain the current resistance change trend; The generation end of the resistance change curve is monitored in real time to determine whether there is a drastic change at the generation end; If it is determined that there is no drastic change at the generating end, then the first scheme optimization parameters are generated based on the current resistance change curve, and the first scheme optimization parameters are substituted into the optimal compression scheme; If it is determined that there is a drastic change at the generation end, the amount and direction of the curve change at the generation end are identified, and second scheme optimization parameters are generated based on the amount and direction of the curve change. The second scheme optimization parameters are then substituted into the optimal compression scheme.

6. The horizontal compression control method for a garbage compactor truck according to claim 5, characterized in that, The steps of monitoring the pressure at both edges of the compression head in real time to obtain two side pressure values, and then setting the deflection of the compression head based on these two side pressure values, are as follows: The pressure at both edges of the compression head is monitored in real time to obtain the side pressure values ​​on both sides of the compression head, and marked as the left pressure value and the right pressure value according to the orientation. The pressure values ​​on the left and right are compared to obtain the pressure difference, and it is determined whether the pressure difference is greater than a preset pressure difference threshold. If it is determined that the pressure difference is greater than the pressure difference threshold, the side with greater pressure is marked as the adjustment side, and the lateral hydraulic support force provided by the compression head to the left and right sides is extracted. Extract the target direction of the adjustment side, adjust the lateral hydraulic support force to deflect towards the target direction, and tilt the lateral hydraulic support force towards the adjustment side.

7. The horizontal compression control method for a garbage compactor truck according to claim 6, characterized in that, The steps of acquiring sound data generated by the garbage pile during the compression process, combining the sound data with the resistance change data to identify foreign objects, and triggering the equipment protection mechanism are as follows: Acquire sound data generated by the garbage heap during the compression process, perform sound information recognition on the sound data, and obtain voiceprint information and sound trigger frequency; Based on the sound trigger frequency and the voiceprint information, the garbage that generates the sound is characterized to obtain the first foreign object feature; Based on the resistance change data, the feature of the garbage that produces the sound is identified to obtain the second foreign object feature; By combining the first foreign object characteristics and the second foreign object characteristics, the foreign object is identified as a type of waste foreign object, and the equipment protection mechanism is triggered. Based on the device protection mechanism, the compression head stops compressing and temporarily retracts, waiting for the preset stress release period to end before resuming compression.

8. The horizontal compression control method for a garbage compactor truck according to claim 7, characterized in that, The steps of collecting humidity and viscosity data of the waste pile through a compression head, and triggering an anti-adhesion mechanism based on the humidity and viscosity data to compress the waste pile in an anti-adhesion manner, are as follows: The humidity and viscosity data of the garbage pile are collected by the compression head, and the adhesion reference value of the garbage pile during the compression process is obtained based on the humidity and viscosity data. Determine whether the adhesion reference value is greater than or equal to a preset standard value; If it is determined that the adhesion reference value is greater than or equal to the standard value, then the compression head is controlled to perform an intermittent retraction-recompression cycle operation; The intermittent retraction-recompression operation includes compressing a certain distance according to a preset target distance, then automatically retracting the compression head and advancing it again.

9. A horizontal compression control system for a garbage compactor truck, wherein the system uses a horizontal compression control method for a garbage compactor truck as described in any one of claims 1-8, characterized in that, The system includes: Standard generation module: used to acquire historical operation data, and based on the historical operation data, obtain historical waste type, historical waste volume, historical waste density and historical pressure parameters, and generate historical standard parameters; Scheme generation module: used to obtain the garbage image information of the current garbage heap, and to perform data matching in the historical standard parameters based on the garbage image information to obtain the optimal compression scheme; Scheme adjustment module: used to start the compression process according to the optimal compression scheme, and to detect the resistance change data of the compression head during the horizontal advancement process in real time, and dynamically adjust the optimal compression scheme according to the resistance change data; Edge adjustment module: used to monitor the pressure at both sides of the compression head in real time during the compression process, obtain two side pressure values, and set the deflection of the compression head according to the two side pressure values; Foreign object protection module: used to acquire sound data generated by the garbage pile during the compression process, combine the sound data and the resistance change data to identify foreign objects, obtain the garbage foreign objects, and trigger the equipment protection mechanism; Adhesion handling module: used to collect humidity and viscosity data of the waste pile through the compression head, and trigger the anti-adhesion mechanism based on the humidity and viscosity data to compress the waste pile in an anti-adhesion manner.

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