Online Detection-Based Multi-Faceted Oil Spraying Feedback Control Method and System for Door Locks

Abstract

The present invention discloses a multi-sided oil spraying feedback control method and system for door locks based on online detection, which relates to the technical field of intelligent control. The method includes: collecting the door lock oil spraying scenario and determining the door lock structure and oil spraying configuration; developing an oil spraying decision-making module in the oil spraying control system according to the door lock structure and oil spraying configuration, and based on the oil spraying decision-making module, performing periodic oil spraying decision-making in the fixed posture of the door lock and reverse parameter control derivation based on the oil spraying configuration to determine the periodic oil spraying strategy; driving the oil spraying configuration to execute oil spraying control according to the periodic oil spraying strategy, synchronously performing visual acquisition and tracking to locate abnormal control points; for the abnormal control points, combining with the oil spraying decision-making module to make an abnormal feedback decision to determine the feedback oil spraying strategy. It solves the technical problems in the prior art that the control accuracy of the door lock oil spraying process is low and the oil spraying uniformity is poor, resulting in low oil spraying quality of the door lock. Through real-time feedback and precise control of the oil spraying amount, the technical effect of improving the oil spraying quality of the door lock is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent control, and particularly to a multi-faceted oil spraying feedback control method and system for door locks based on on-line detection. Background Art

[0002] In the manufacturing process of door locks, the oil spraying process is one of the key links, directly affecting the appearance quality and durability of the products. The traditional door lock oil spraying method usually relies on fixed programs or manual operations, with defects such as uneven spraying, paint waste, environmental pollution, and lack of real-time feedback adjustment. In addition, due to the complex structure of door locks, including different-shaped surfaces and various materials, the existing oil spraying process is difficult to accurately adjust the spraying angle and spraying amount according to the morphology of different door locks, resulting in unstable quality, high rework rate, and affecting production efficiency and cost control. Summary of the Invention

[0003] This application provides a multi-faceted oil spraying feedback control method and system for door locks based on on-line detection, solving the technical problems of low control accuracy and poor oil spraying uniformity in the existing door lock oil spraying process, resulting in low oil spraying quality of door locks.

[0004] In the first aspect of this application, a multi-faceted oil spraying feedback control method for door locks based on on-line detection is provided. The method includes:

[0005] Collect the door lock oil spraying scenario, determine the door lock structure and oil spraying configuration, where the oil spraying configuration includes an oil spraying mechanism and a lock clamping mechanism, and the oil spraying mechanism is a double-axis drive mechanism; develop an oil spraying decision-making module in the oil spraying control system according to the door lock structure and oil spraying configuration, and perform periodic oil spraying decision-making in the fixed posture of the door lock and reverse parameter control derivation based on the oil spraying configuration based on the oil spraying decision-making module to determine the periodic oil spraying strategy; drive the oil spraying configuration to execute oil spraying control according to the periodic oil spraying strategy, and synchronously perform visual acquisition and tracking to locate abnormal control points, where the main control mechanisms of the lock clamping mechanism and the oil spraying mechanism are used as control targets; for the abnormal control points, combine the oil spraying decision-making module to make an abnormal feedback decision to determine the feedback oil spraying strategy, where the slave control mechanism of the oil spraying mechanism is used as the control target.

[0006] In the second aspect of this application, a multi-faceted oil spraying feedback control system for door locks based on on-line detection is provided. The system includes:

[0007] Scene acquisition component, used to acquire the door lock oil spraying scene and determine the door lock structure and oil spraying configuration. Among them, the oil spraying configuration includes an oil spraying mechanism and a lock clamping mechanism, and the oil spraying mechanism is a dual-axis drive mechanism; an oil spraying strategy determination component, used to develop an oil spraying decision-making module in the oil spraying control system according to the door lock structure and oil spraying configuration, and perform periodic oil spraying decision-making in the fixed posture of the door lock and reverse parameter control derivation based on the oil spraying configuration based on the oil spraying decision-making module to determine the periodic oil spraying strategy; a control component, used to drive the oil spraying configuration to execute oil spraying control according to the periodic oil spraying strategy, synchronously perform visual acquisition and tracking, and locate abnormal control points, where the main control mechanisms of the lock clamping mechanism and the oil spraying mechanism are the control targets; a feedback decision-making component, used to perform abnormal feedback decision-making in combination with the oil spraying decision-making module for the abnormal control points to determine the feedback oil spraying strategy, where the slave control mechanism of the oil spraying mechanism is the control target.

[0008] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0009] First, acquire the door lock oil spraying scene, determine the door lock structure and oil spraying configuration. Among them, the oil spraying configuration includes an oil spraying mechanism and a lock clamping mechanism, and the oil spraying mechanism is a dual-axis drive mechanism. Then, develop an oil spraying decision-making module in the oil spraying control system according to the door lock structure and oil spraying configuration, and perform periodic oil spraying decision-making in the fixed posture of the door lock and reverse parameter control derivation based on the oil spraying configuration based on the oil spraying decision-making module to determine the periodic oil spraying strategy. Then, drive the oil spraying configuration to execute oil spraying control according to the periodic oil spraying strategy, synchronously perform visual acquisition and tracking, and locate abnormal control points, where the main control mechanisms of the lock clamping mechanism and the oil spraying mechanism are the control targets. Finally, perform abnormal feedback decision-making in combination with the oil spraying decision-making module for the abnormal control points to determine the feedback oil spraying strategy, where the slave control mechanism of the oil spraying mechanism is the control target. It solves the technical problems of low control accuracy and poor oil spraying uniformity in the existing door lock oil spraying process, resulting in low door lock oil spraying quality. Through real-time feedback, the fuel injection volume is accurately controlled, achieving the technical effect of improving the door lock oil spraying quality. Description of the Drawings

[0010] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0011] Figure 1 Schematic diagram of the process of the multi-sided oil spraying feedback control method for door locks based on online detection provided by the embodiments of this application;

[0012] Figure 2Schematic structural diagram of the multi-sided oil spraying feedback control system for door locks based on online detection provided by the embodiments of the present application.

[0013] Explanation of reference numerals: Scene acquisition component 11, oil spraying strategy determination component 12, control component 13, feedback decision-making component 14. Detailed implementation manners

[0014] By providing a multi-sided oil spraying feedback control method and system for door locks based on online detection, the present application solves the technical problems in the prior art that the control accuracy of the door lock oil spraying process is low and the oil spraying uniformity is poor, resulting in low oil spraying quality of door locks.

[0015] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present application without creative efforts shall fall within the protection scope of the present application.

[0016] It should be noted that the terms "include" and "have" are intended to cover non-exclusive inclusion. For example, a process, method, system, product or server that includes a series of steps or units does not necessarily have to be limited to those clearly listed steps or units, but may include other steps or modules that are not clearly listed or are inherent to these processes, methods, products or devices.

[0017] Embodiment 1, as Figure 1 shown, the present application provides a multi-sided oil spraying feedback control method for door locks based on online detection, wherein the method includes:

[0018] Collect the door lock oil spraying scene, and determine the door lock structure and oil spraying configuration, wherein the oil spraying configuration includes an oil spraying mechanism and a lock clamping mechanism, and the oil spraying mechanism is a biaxial drive mechanism.

[0019] By collecting the door lock oil spraying scene, the structure information of the door lock and its oil spraying requirements can be obtained. Specifically, industrial cameras, 3D laser scanning devices, etc. can be used to comprehensively collect the surface of the door lock to obtain the geometric shape, material characteristics and surface complexity information of the door lock. At the same time, record the fixing method, installation angle of the door lock and its movement trajectory on the production line; combine the collected data, and construct a three-dimensional model of the door lock through computer vision algorithms or three-dimensional modeling software, and analyze its key structural features, including but not limited to the lock body, lock core, panel, handle and other areas that may need to be sprayed.

[0020] After clarifying the door lock structure, a suitable oil spraying device is configured in combination with the morphological characteristics and spraying requirements of the door lock. Among them, the oil spraying configuration mainly includes an oil spraying mechanism and a lock clamping mechanism. The oil spraying mechanism is driven by two axes and includes linear sliding rails or robotic arms for the X-axis and Y-axis, so as to flexibly adjust the position and angle of the nozzle in two directions and achieve all-round and multi-angle spraying. The oil spraying mechanism is equipped with a high-precision stepper motor or servo motor to ensure the stability and accuracy of the nozzle movement, and at the same time, the spraying trajectory can be adjusted according to the morphology of the door lock. The lock clamping mechanism is used to fix the door lock to ensure that the door lock does not displace or vibrate during the spraying process. This clamping mechanism can be an adjustable mechanical clamping device that supports the fixation of door locks of different specifications, or a rotating platform can be used to cooperate with spraying parts at different angles.

[0021] Furthermore, the oil spraying mechanism is a two-axis drive mechanism, including a first oil spraying mechanism and a second oil spraying mechanism with a mirror-image structure. Among them, it includes a nozzle, a rotating disk, a rotating connecting rod, and a rotating regulator, and the rotating connecting rod is at least one section.

[0022] The oil spraying mechanism is a two-axis drive mechanism, including a first oil spraying mechanism and a second oil spraying mechanism with a mirror-image structure to ensure synchronous or independent spraying on multiple sides of the door lock, improving spraying efficiency and uniformity. Each oil spraying mechanism includes a nozzle, a rotating disk, a rotating connecting rod, and a rotating regulator. Among them, the nozzle is used to control the spraying direction and spraying amount of the paint, the rotating disk is used to provide the rotational movement of the nozzle to adapt to different spraying angles of the door lock, the rotating connecting rod is used to connect the nozzle and the rotating disk, and provides support and flexible adjustment ability when driven. The rotating connecting rod consists of at least one section and can be a single-section or multi-section structure to meet the spraying requirements of door locks of different sizes and ensure the adjustable range of the nozzle. The rotating regulator is used to control the rotation angle of the rotating disk and the movement amplitude of the rotating connecting rod, so that the nozzle can spray at an accurate position, ensuring that the coating evenly covers all parts of the door lock, while reducing overspray and spraying dead corners, improving spraying quality and material utilization rate. Through this two-axis drive mirror-image oil spraying mechanism, the oil spraying strategy can be adjusted according to the morphology of the door lock, realizing synchronous spraying or step-by-step spraying, meeting the spraying requirements of different door lock structures, and adapting to various production process requirements.

[0023] Furthermore, the oil spraying mechanism is a two-axis drive mechanism, including:

[0024] Set the master-slave control for the oil spraying mechanism. Among them, the master control mechanism is the first oil spraying mechanism or the second oil spraying mechanism. The master control mechanism performs multi-sided oil spraying on the door lock, and the slave control mechanism performs feedback compensation based on the master control; according to the master-slave control setting, initialize the oil spraying configuration.

[0025] The oil injection mechanism is a dual-axis drive mechanism, including master-slave control settings for the oil injection mechanism. Among them, the master control mechanism is the first oil injection mechanism or the second oil injection mechanism, which is automatically selected by the system according to the shape of the door lock and the spraying requirements. The master control mechanism is responsible for performing multi-sided oil injection on the door lock. According to the preset spraying trajectory and spraying parameters, it realizes precise spraying on each area of the door lock surface; the slave control mechanism executes feedback compensation based on the master control. That is, after the master control mechanism completes the basic spraying, the slave control mechanism adjusts the spraying angle, pressure and spraying time through real-time monitoring data, and corrects the spraying on the areas with uneven spraying, insufficient coverage or defects, ensuring the consistency and integrity of the spraying quality.

[0026] According to the master-slave control settings, initialize the oil injection configuration, including the motion parameters of the oil injection mechanism, spraying trajectory, spraying pressure, nozzle opening and closing rhythm, and flow control, etc., so that the master control mechanism can accurately execute periodic spraying, and at the same time enable the slave control mechanism to have the ability of autonomous adjustment to ensure spraying accuracy and coating uniformity.

[0027] According to the door lock structure and oil injection configuration, develop an oil injection decision-making module in the oil injection control system. Based on the oil injection decision-making module, perform periodic oil injection decision-making in the fixed posture of the door lock and reverse parameter control derivation based on the oil injection configuration to determine the periodic oil injection strategy.

[0028] According to the door lock structure and oil injection configuration, develop an oil injection decision-making module in the oil injection control system. This module combines the geometric shape, surface characteristics, spraying requirements of the door lock and the configuration parameters of the oil injection mechanism to form an intelligent spraying control strategy.

[0029] Based on the fuel injection decision-making module, when the door lock is in a fixed posture, periodic fuel injection decisions are executed, that is, spraying is carried out at set time intervals and along predefined trajectories to ensure uniform spraying coverage and avoid problems of overspraying or under-spraying. The periodic fuel injection decisions are based on the morphological characteristics of the door lock and the spraying requirements, and different areas are partitioned for spraying, so that the nozzle covers each spraying area of the door lock in turn along the optimized path, and the spraying time and spraying flow rate are dynamically adjusted according to the coating thickness requirements. In addition, the fuel injection decision-making module adopts reverse parameter control derivation based on fuel injection configuration, that is, during the spraying process, the system real-time monitors the motion state of the fuel injection mechanism, the coating thickness on the surface of the door lock, and possible spraying deviations, and combines the master-slave control settings to dynamically adjust the fuel injection trajectory and spraying parameters. This reverse parameter control derivation generates adjustment signals by analyzing the spraying quality in real time, optimizes the nozzle position, spraying time, and flow rate parameters during the spraying process, ensures the uniformity of the coating, and reduces overspray and spraying dead spots. Based on the periodic fuel injection decisions and the reverse parameter control derivation, the periodic fuel injection strategy is finally determined. This strategy includes the optimized spraying path, time arrangement, pressure control, and feedback adjustment scheme, enabling the fuel injection process to balance efficiency and precision, adapt to the spraying requirements of different door lock structures, and improve the overall spraying quality and consistency.

[0030] Furthermore, the fuel injection decision-making module includes a periodic decision-making unit and a parameter control derivation unit. Based on the fuel injection decision-making module, the periodic fuel injection decision under the fixed posture of the door lock is executed, including:

[0031] According to the fuel injection scenario of the door lock, determine the first door lock posture based on the lock clamping mechanism and the door lock structure; determine the fuel injection requirements through interactive fuel injection work orders; take the first door lock posture as the fixed door lock posture and the fuel injection requirements as the guidance to determine the periodic fuel injection sequence, where the periodic fuel injection sequence is determined based on the fuel injection path and the oil layer thickness; and the fuel injection mode is single-layer fuel injection or composite-layer fuel injection.

[0032] The fuel injection decision-making module includes a periodic decision-making unit and a parameter control derivation unit. Through the collaborative work of these two units, intelligent fuel injection decisions based on the door lock structure and fuel injection configuration are realized. Specifically, the geometric shape, structure, clamping method, etc. of the door lock are modeled according to the fuel injection scenario of the door lock, and the first door lock posture based on the lock clamping mechanism and the door lock structure is determined. The first door lock posture is the standard positioning state of the door lock in the fixed clamping mechanism. Through this posture, the relative angle, position, and surface orientation of the door lock can be clarified. Through interactive fuel injection work orders, the specific requirements for door lock spraying are obtained, including parameters such as the coating thickness requirement, spraying area, spraying sequence, and fuel injection volume.

[0033] The periodic decision-making unit calculates the injection path based on the fixed posture of the door lock and the injection demand, and determines the thickness of each sprayed oil layer and the injection volume in combination with the thickness requirement of the coating. The system selects the injection mode according to the actual spraying demand. If it is single-layer injection, the system will perform a single spraying process to cover the required area on the surface of the door lock and reach the required thickness; if it is composite-layer injection, the system will perform multiple sprayings within the set cycle, and each spraying will be followed by a curing step to ensure the adhesion, uniformity, and durability of the coating. The system will set the time, flow rate, and speed of each spraying according to the injection mode to ensure the quality of the coating and the stability of the spraying process.

[0034] The periodic decision-making unit is responsible for formulating the injection plan according to the injection demand and the door lock posture during this process, mainly including determining the spraying path, spraying sequence, spraying time, and the thickness of each sprayed oil layer. The reference control derivation unit adjusts and optimizes the spraying process according to the real-time feedback. When problems such as uneven spraying, insufficient or excessive thickness occur during the spraying process, the reference control derivation unit will perform real-time correction based on the feedback data obtained from devices such as the visual inspection system and the thickness sensor. Specifically, the reference control derivation unit will derive a correction plan according to the real-time spraying data, including adjusting parameters such as the injection path, spraying speed, and injection volume, to ensure that the spraying quality is consistent with the expected goal. Through such feedback adjustment, the reference control derivation unit enables the spraying process to be dynamically optimized according to the actual situation, avoiding the accumulation of spraying errors and the instability of quality. Through the collaborative work of the periodic decision-making unit and the reference control derivation unit, the injection decision module can improve the spraying efficiency while ensuring the spraying quality, and ensure that the coating on the surface of the door lock reaches the best effect.

[0035] The periodic decision-making unit is responsible for determining the periodic injection sequence according to the injection scenario of the door lock, and planning the spraying path, spraying frequency, spraying time, and injection volume at each stage. The periodic decision-making unit calculates the required spraying parameters in the first door lock posture of the door lock (which refers to the standard state after the door lock is fixed in the clamping mechanism) by analyzing factors such as the structure of the door lock, spraying demand, and fixed state of the clamping mechanism. Specifically, the periodic decision-making unit will determine the injection path, spraying sequence, and time interval according to the shape of the door lock, spraying area, and target coating thickness to ensure the uniformity and efficiency of the spraying process. In addition, the periodic decision-making unit will also set the spraying frequency and number of layers according to different injection modes (such as single-layer injection or composite-layer injection) to ensure that the quality and adhesion of each coating layer meet the requirements. Through these decisions, the periodic decision-making unit can formulate an optimal spraying plan to ensure that each spraying step meets the injection demand.

[0036] The parameter control and derivation unit is responsible for adjusting and optimizing the fuel injection scheme set by the periodic decision-making unit in real time during the fuel injection process. The parameter control and derivation unit dynamically adjusts the spraying process according to the feedback data (such as spraying thickness, coating uniformity, fuel injection deviation, etc.) obtained by the system in real time. Specifically, when uneven spraying, insufficient or excessive spraying amount occurs during the spraying process, the parameter control and derivation unit analyzes the abnormality through the feedback mechanism and derives appropriate corrective measures. At this time, the parameter control and derivation unit adjusts the fuel injection path, spraying angle, spraying pressure or spraying time according to the real-time feedback to ensure that the spraying effect meets the expected quality standards. Through this closed-loop control, the parameter control and derivation unit can timely correct the spraying scheme of the periodic decision-making unit, thereby improving the spraying accuracy and quality.

[0037] Furthermore, performing reverse parameter control derivation based on the fuel injection configuration includes:

[0038] Invoking the fuel injection record of the door lock, mining the common rail electronic control relationship and the fuel injection electronic control relationship; using the periodic fuel injection effect as the input, based on the common rail electronic control relationship and the fuel injection electronic control relationship, and taking the fuel injection control parameters as the output, performing sample-driven training based on the door lock fuel injection record to construct the parameter control and derivation unit; according to the parameter control and derivation unit, performing reverse parameter control derivation on the periodic fuel injection sequence to determine the periodic fuel injection strategy.

[0039] The system calls the door lock injection records and conducts in-depth analysis based on historical injection data to uncover the common rail electronic control relationship and the injection electronic control relationship. During this process, the system extracts the mutual influence relationships between multiple injection channels or injection mechanisms by analyzing the collaborative work and injection control process among different injection mechanisms. The common rail electronic control relationship refers to how multiple injection mechanisms cooperate through the electronic control system during operation to achieve the best matching of the injection path and the spraying effect. The injection electronic control relationship refers to the relationship between the electronic control parameters (such as injection volume, spraying time, injection pressure, etc.) during the injection process and the actual spraying effect. Through the analysis of historical data, the system can understand and model the key control factors during the injection process and their impact on the spraying quality, providing a basis for subsequent spraying control. Next, the system takes the periodic injection effect as input and combines the common rail electronic control relationship and the injection electronic control relationship to perform sample-driven training based on the door lock injection records, and then constructs a parameter control derivation unit. In this process, the system uses historical injection data as samples for training, adopts algorithms such as machine learning or regression analysis to uncover the quantitative relationship between control parameters (such as injection flow rate, spraying time, spraying path, etc.) and the spraying effect. Through sample-driven training, the parameter control derivation unit can learn from a large number of injection records how to optimize control according to different injection configurations (including injection path, oil layer thickness, etc.). The parameter control derivation unit finally forms a mathematical model that can adjust the control strategy according to the real-time spraying effect, enabling the system to efficiently and precisely control the spraying process in complex spraying scenarios. After completing the training of the parameter control derivation unit, the system performs reverse parameter control derivation on the periodic injection sequence according to the parameter control derivation unit. At this time, the core task of reverse parameter control derivation is to reverse-derive the control parameters that affect the spraying effect based on the periodic injection effect and feedback data, and make adjustments to optimize the subsequent spraying process. Specifically, the parameter control derivation unit will deduce which control factors have a significant impact on the spraying effect based on the spraying results (such as spraying thickness, coating uniformity, spraying quality, etc.). For example, when it is detected that the coating thickness in a certain spraying area is insufficient, the system will adjust the injection flow rate, spraying time, or spraying path according to the feedback information to ensure that the coating thickness reaches the expected value. The process of reverse derivation enables the system to dynamically adjust the spraying strategy, continuously optimize the control parameters during the spraying process, and ensure that the final spraying effect meets the quality standards.

[0040] Furthermore, uncovering the common rail electronic control relationship and the injection electronic control relationship includes:

[0041] Taking the relative spatial position between the lock clamping mechanism and the nozzle as the first common rail, and the relative driving positions of the various structures of the fuel injection mechanism as the second common rail; guiding by the fuel injection path and combining the lock fuel injection records, excavating the common rail electronic control relationship based on the first common rail - second common rail; guiding by the oil layer thickness and combining the lock fuel injection records, excavating the fuel injection electronic control relationship based on the fuel injection volume - fuel injection pressure.

[0042] The system defines the relative spatial position between the lock clamping mechanism and the nozzle as the first common rail, and the relative driving positions of the various structures of the fuel injection mechanism as the second common rail. In this process, the system accurately models the relative positions between the lock clamping mechanism and the nozzle to ensure that the nozzle can align with the corresponding spraying area of the lock at different spatial positions. The first common rail mainly describes the spatial relationship between the lock clamping mechanism and the nozzle, such as the positioning method of the nozzle, the spraying angle, and the position of the nozzle from the surface of the lock. The second common rail involves the relative positions between the various driving components inside the fuel injection mechanism, such as the driving device of the nozzle, the regulating mechanism of the fuel injection flow rate, and the selection of the fuel injection path. Through the collaborative action of these two common rails, the fuel injection system can accurately control the relative movement between the nozzle and the surface of the lock, thus ensuring the position accuracy and spraying effect during the spraying process. Next, the system guides by the fuel injection path and combines the lock fuel injection records to excavate the common rail electronic control relationship based on the first common rail and the second common rail. The fuel injection path refers to the trajectory that the nozzle follows along the surface of the lock during the spraying process, and this trajectory determines the coverage range of the fuel injection and the uniformity of the spraying area. Combining the fuel injection records, the system analyzes how the first common rail and the second common rail cooperate with each other under different fuel injection paths, and thus deduces the common rail electronic control relationship. For example, under a certain specific fuel injection path, the position of the nozzle in the first common rail needs to cooperate with the driving method of the fuel injection mechanism in the second common rail to achieve an efficient and uniform spraying effect. In addition, the system also guides by the oil layer thickness and combines the lock fuel injection records to excavate the fuel injection electronic control relationship based on the fuel injection volume and the fuel injection pressure. The oil layer thickness is an important indicator of the spraying quality, and the fuel injection volume and the fuel injection pressure are important parameters affecting the oil layer thickness and uniformity. The system analyzes the lock fuel injection records to explore the spraying effects under different fuel injection volumes and fuel injection pressures, and establishes the control relationship between the fuel injection volume and the fuel injection pressure. For example, at a certain pressure, the fuel injection volume needs to be adjusted to ensure that the coating reaches the specified thickness, or under different fuel injection pressures, the change in the fuel injection volume will directly affect the uniformity of the coating.

[0043] Furthermore, after determining the periodic fuel injection strategy, it includes:

[0044] Install a Hall sensor, where the Hall sensor is installed in the fuel injection mechanism or the lock clamping mechanism; as the periodic fuel injection strategy is executed, the Hall sensor is synchronously activated; based on the Hall sensor, with the fuel injection path as the guide, the mechanical motion state of the fuel injection configuration is detected to generate a feedback command; according to the feedback command, in response to the fuel injection control system, fuel injection feedback adjustment is performed.

[0045] Install a Hall sensor at an appropriate position in the fuel injection mechanism or the lock clamping mechanism. The Hall sensor is a sensor that can detect magnetic field changes and can sense the relative position changes of the fuel injection mechanism or the lock clamping mechanism in real time. By installing the Hall sensor, the system can monitor the dynamic position changes of the fuel injection mechanism and the lock clamping mechanism in real time.

[0046] As the periodic fuel injection strategy is executed, the Hall sensor is synchronously activated. At this time, the fuel injection control system starts to work according to the predetermined periodic fuel injection strategy, and at the same time, the Hall sensor starts to detect and record the position and motion state of the fuel injection mechanism or the lock clamping mechanism during the spraying process in real time. The Hall sensor will detect the motion trajectory of the fuel injection mechanism or the lock clamping mechanism and transmit the data to the fuel injection control system for subsequent dynamic monitoring and feedback. By synchronously activating the Hall sensor, the system can grasp the motion of the fuel injection mechanism in real time and provide data support for subsequent control adjustment. Based on the real-time data obtained by the Hall sensor, with the fuel injection path as the guide, the mechanical motion state of the fuel injection configuration is detected to generate a feedback command. At this time, with the fuel injection path as the control direction, the system will compare the motion data obtained by the Hall sensor with the predetermined fuel injection path. Through this comparison, the system can determine whether the actual motion trajectory of the fuel injection mechanism or the lock clamping mechanism conforms to the set fuel injection path. If a deviation in the motion trajectory is found, the system will evaluate the degree and impact of the deviation and then generate feedback commands, which may include adjusting the position of the fuel injection mechanism, the fuel injection flow rate, the spraying angle, or other fuel injection parameters to ensure that each part of the spraying process can be accurately executed. According to the generated feedback command, the fuel injection control system performs feedback adjustment on the fuel injection process. The system adjusts the parameter settings during the fuel injection process in real time according to the feedback data provided by the Hall sensor and the generated feedback command. If there is a deviation in the motion of the fuel injection mechanism, the system may need to adjust control parameters such as the driving position of the fuel injection mechanism, the fuel injection flow rate, and the spraying time. For example, when the Hall sensor detects that the nozzle fails to move along the predetermined path, the system can adjust the driving motor of the nozzle to correct the motion direction and speed of the nozzle to ensure that the fuel injection mechanism continues to operate along the predetermined path.

[0047] According to the periodic fuel injection strategy, drive the fuel injection configuration to execute fuel injection control, synchronously perform visual acquisition and tracking, and locate abnormal control points, where the main control mechanisms of the lock clamping mechanism and the fuel injection mechanism are used as the control targets.

[0048] According to the described periodic injection strategy, the system first drives the injection configuration to start executing injection control, ensuring that the injection mechanism operates according to the predetermined spraying requirements. Specifically, the injection mechanism adjusts spraying parameters such as injection flow rate, spraying angle, injection pressure, etc. according to the set periodic injection strategy to ensure that each layer of the coating meets the required quality and uniformity. At the same time as the spraying process starts, the system synchronously performs visual acquisition and tracking, using visual sensors (such as high-resolution cameras or laser sensors) to monitor the injection area in real time. The visual system captures image data of the spraying surface and analyzes the thickness, uniformity, injection path, etc. of the coating to detect possible abnormalities.

[0049] During the visual acquisition process, the system performs real-time analysis of key parameters during the spraying process through image processing techniques. For example, the system detects problems such as uneven spraying, missed spraying, excessive or insufficient coating thickness, etc., and promptly identifies and locates these abnormal control points. When the system locates these abnormalities, it analyzes and judges the specific location and nature of the abnormalities, determines whether they affect the spraying quality, and adjusts the spraying process according to the preset quality standards. During this process, the system takes the main control mechanisms of the lock clamping mechanism and the injection mechanism as the control targets for abnormal feedback adjustment. The main control mechanisms of the lock clamping mechanism and the injection mechanism are usually responsible for the core control functions of the entire spraying process, including the adjustment of key parameters such as injection path, injection flow rate, injection angle, etc. Therefore, once the visual acquisition and tracking system discovers an abnormal control point, the system will automatically perform feedback adjustment on the spraying process through the main control mechanism. For example, if the system detects that the spraying path deviates, the main control mechanism will readjust the injection path to restore the correct spraying trajectory; if it detects that the coating thickness does not meet the requirements, the system may correct this problem by adjusting the injection flow rate or spraying pressure; if it is found that the position of the nozzle is incorrect, the system will also promptly adjust the driving parameters of the nozzle to ensure precise spraying.

[0050] Furthermore, synchronously performing visual acquisition and tracking and locating abnormal control points includes:

[0051] Determining the real-time injection characteristics through visual acquisition and tracking; according to the real-time injection characteristics, traversing the periodic injection sequence for matching and calculating the difference of eigenvalue to determine the injection difference; determining whether the injection difference meets the preset accuracy, if not, determining the abnormal control point.

[0052] The system monitors the spraying characteristics during the oil injection process in real time through visual acquisition and tracking. Visual sensors (such as high-resolution cameras, laser scanners, etc.) collect real-time image data during the spraying process and extract real-time oil injection characteristics through image processing techniques. These characteristics include the uniformity of the coating, the accuracy of the spraying path, the coverage of the spraying area, etc. Then, the system traverses and matches the periodic oil injection sequence based on the obtained real-time oil injection characteristics. Specifically, the system compares the actually collected oil injection characteristics with the predetermined periodic oil injection sequence, calculates the difference according to the characteristic values of each spraying cycle and the actual oil injection characteristic values, and then obtains the oil injection difference. The oil injection difference represents the deviation degree between the actual oil injection effect and the predetermined oil injection strategy. After obtaining the oil injection difference, the system determines whether the oil injection difference meets the preset accuracy. The system judges whether the oil injection difference is within the allowable error range according to the predetermined accuracy requirement. If the oil injection difference exceeds the preset accuracy range, the system will identify an abnormal control point at this time, that is, there is a situation that does not meet the quality standard in a certain link or area during the spraying process. At this time, the system will further analyze the specific location and nature of the abnormal control point and adjust the oil injection control strategy accordingly to ensure that the spraying quality is corrected in time. If the oil injection difference meets the preset accuracy requirement, it means that the spraying process is normal and no adjustment is required. The system continues to perform spraying control according to the predetermined periodic oil injection sequence. If the difference exceeds the standard, the system will correct the oil injection parameters through a feedback mechanism, such as adjusting the oil injection flow rate, oil injection pressure, spraying path, etc., to solve the abnormal problems that occur during the spraying process and ensure that the spraying quality meets the standards.

[0053] For the abnormal control point, combined with the oil injection decision-making module, make an abnormal feedback decision to determine the feedback oil injection strategy, where the slave control mechanism of the oil injection mechanism is the control target.

[0054] When the system locates the abnormal control point during the spraying process through visual acquisition and tracking, the system analyzes the nature and degree of the abnormality. These abnormal control points may be problems such as inaccurate oil injection path, uneven coating thickness, insufficient or excessive oil injection volume, etc. The system inputs this abnormal information into the oil injection decision-making module for further analysis. The oil injection decision-making module consists of a periodic decision-making unit and a parameter control derivation unit, and can formulate an appropriate feedback oil injection strategy according to the known oil injection strategy, spraying quality standard, and information of the abnormal control point. Specifically, the system adjusts various control parameters during the oil injection process according to the different characteristics of the abnormal point, combined with the decision-making rules of the oil injection decision-making module. These control parameters may include the oil injection volume, oil injection pressure, spraying angle, spraying speed, etc., to ensure that the spraying process can correct the abnormality and return to the predetermined quality standard.

[0055] During the feedback decision-making process, the system selects the slave control mechanism of the appropriate fuel injection mechanism as the control target. The slave control mechanism usually serves as an auxiliary or compensation system for the fuel injection mechanism and is responsible for finely adjusting the detailed control during the fuel injection process. For example, the slave control mechanism may compensate for the errors that occur during the spraying process by finely adjusting the position of the fuel injection nozzle, adjusting the fuel injection flow rate, etc. Through the fine adjustment of the slave control mechanism, the system can quickly respond to the subtle problems during the fuel injection process and ensure that the spraying quality is effectively corrected under the influence of abnormal control points. For example, if it is detected during the spraying process that the coating thickness does not meet the predetermined standard, the fuel injection decision-making module will combine the feedback information of the abnormal point to determine the feedback fuel injection strategy such as increasing the fuel injection volume or adjusting the fuel injection pressure. At this time, the system will instruct the slave control mechanism to adjust the fuel injection parameters, thereby achieving compensation for the abnormal control point.

[0056] Furthermore, the determination of the feedback fuel injection strategy includes:

[0057] Import the abnormal control point into the periodic decision-making unit, and determine the re-spray information according to the fuel injection difference; transfer the re-spray information to the parameter control derivation unit, and output the feedback fuel injection strategy, where, according to the feedback fuel injection strategy, drive the slave control mechanism to perform re-spray feedback control on the abnormal control point.

[0058] When the system locates the abnormal control point during the spraying process and after preliminary analysis, the system will import the information of this abnormal control point into the periodic decision-making unit for further processing. The periodic decision-making unit, as a part of the fuel injection decision-making module, is responsible for making adjustments to the fuel injection strategy according to the fuel injection difference obtained in real time (i.e., the deviation between the actual effect and the predetermined standard during the spraying process). According to the fuel injection difference, the periodic decision-making unit can calculate the re-spray information, which refers to the adjustment suggestions for some areas that need to be re-sprayed or the fuel injection parameters during the spraying process. The re-spray information includes, but is not limited to, increasing the fuel injection volume, adjusting the spraying path, changing the spraying angle, or extending the spraying time, etc. These re-spray information can accurately guide the system to compensate for the abnormal control point and ensure that the spraying quality is restored to the predetermined standard.

[0059] Once the re-spray information is generated, the system will transfer it to the parameter control derivation unit, which is responsible for further deriving the specific feedback fuel injection strategy based on the re-spray information and the feedback rules of the fuel injection configuration. The parameter control derivation unit combines the historical records and empirical data of fuel injection control, and based on the common rail electronic control relationship, the control relationship between the fuel injection volume and the fuel injection pressure, etc., comprehensively evaluates the re-spray information and generates the final feedback fuel injection strategy. This strategy includes the adjustment details of the fuel injection parameters, the specific area of re-spraying, the spraying angle, and the spraying speed, etc., to ensure that the abnormal area can be accurately compensated and the spraying defects can be repaired.

[0060] According to the determined feedback fuel injection strategy, the system will drive the slave control mechanism to execute the re-spray feedback control. The slave control mechanism is an auxiliary control part in the fuel injection mechanism and is responsible for the fine control of local adjustments during the fuel injection process. Specifically, the system will instruct the slave control mechanism to perform supplementary spraying or adjustment in the corresponding area of the abnormal control point according to the feedback fuel injection strategy. The re-spray feedback control ensures the quality of the spraying area is restored and finally achieves the consistency between the spraying effect and the predetermined standard by fine-tuning the fuel injection volume, adjusting the fuel injection time, correcting the position of the nozzle, etc. For example, if it is detected that the coating thickness in a certain spraying area is insufficient, the system will instruct the slave control mechanism to increase the fuel injection volume or adjust the position of the nozzle through the re-spray information to ensure that the spraying area is evenly covered. If there is a deviation in the fuel injection path, the system will adjust the spraying angle and recalibrate the trajectory of the nozzle through the feedback fuel injection strategy to ensure that the fuel injection path meets the predetermined requirements. Through this feedback mechanism, the system can automatically correct any deviation during the spraying process and ensure that the quality of each spraying area meets the standard.

[0061] In summary, the embodiments of the present application at least have the following technical effects:

[0062] First, collect the door lock fuel injection scenario, determine the door lock structure and fuel injection configuration, where the fuel injection configuration includes a fuel injection mechanism and a lock clamping mechanism, and the fuel injection mechanism is a double-axis drive mechanism. Then, according to the door lock structure and fuel injection configuration, develop a fuel injection decision-making module in the fuel injection control system, and based on the fuel injection decision-making module, perform periodic fuel injection decision-making in the fixed posture of the door lock and reverse parameter control derivation based on the fuel injection configuration to determine the periodic fuel injection strategy. Next, according to the periodic fuel injection strategy, drive the fuel injection configuration to execute fuel injection control, and simultaneously perform visual acquisition and tracking to locate abnormal control points, where the main control mechanisms of the lock clamping mechanism and the fuel injection mechanism are used as control targets. Finally, for abnormal control points, combine the fuel injection decision-making module to make abnormal feedback decisions and determine the feedback fuel injection strategy, where the slave control mechanism of the fuel injection mechanism is used as the control target. This solves the technical problems in the prior art of low control accuracy and poor fuel injection uniformity during the door lock fuel injection process, resulting in low door lock fuel injection quality, and achieves the technical effect of improving the door lock fuel injection quality through real-time feedback and precise control of the fuel injection volume.

[0063] Embodiment 2, based on the same inventive concept as the method for online detection-based multi-faceted fuel injection feedback control of door locks in the foregoing embodiment, as Figure 2 shown, the present application provides an online detection-based multi-faceted fuel injection feedback control system for door locks, where the system includes:

[0064] The scene acquisition component 11 is used to acquire the door lock oil spraying scene and determine the door lock structure and oil spraying configuration. Among them, the oil spraying configuration includes an oil spraying mechanism and a lock clamping mechanism, and the oil spraying mechanism is a double-axis drive mechanism; the oil spraying strategy determination component 12 is used to develop an oil spraying decision module in the oil spraying control system according to the door lock structure and oil spraying configuration, and perform periodic oil spraying decision-making in the fixed posture of the door lock and reverse parameter control derivation based on the oil spraying configuration based on the oil spraying decision module to determine the periodic oil spraying strategy; the control component 13 is used to drive the oil spraying configuration to execute oil spraying control according to the periodic oil spraying strategy, and synchronously perform visual acquisition and tracking to locate abnormal control points, where the main control mechanisms of the lock clamping mechanism and the oil spraying mechanism are used as the control targets; the feedback decision component 14 is used to perform abnormal feedback decision-making in combination with the oil spraying decision module for the abnormal control points to determine the feedback oil spraying strategy, where the slave control mechanism of the oil spraying mechanism is used as the control target.

[0065] Further, the scene acquisition component 11 is used to execute the following method:

[0066] The oil spraying mechanism is a double-axis drive mechanism, including a first oil spraying mechanism and a second oil spraying mechanism with a structural mirror image. Among them, it includes a nozzle, a rotating disk, a rotating connecting rod and a rotating regulator, and the rotating connecting rod is at least one section.

[0067] Further, the scene acquisition component 11 is used to execute the following method:

[0068] Perform master-slave control setting on the oil spraying mechanism. Among them, the master control mechanism is the first oil spraying mechanism or the second oil spraying mechanism. The master control mechanism performs multi-sided oil spraying on the door lock, and the slave control mechanism performs feedback compensation based on the master control; according to the master-slave control setting, perform initialization setting on the oil spraying configuration.

[0069] Further, the oil spraying strategy determination component 12 is used to execute the following method:

[0070] According to the door lock oil spraying scene, determine the first door lock posture based on the lock clamping mechanism and the door lock structure; determine the oil spraying requirement through an interactive oil spraying work order; use the first door lock posture as the fixed posture of the door lock and the oil spraying requirement as the guide to determine the periodic oil spraying sequence, where the periodic oil spraying sequence is determined based on the oil spraying path and the oil layer thickness; among them, the oil spraying mode is single-layer oil spraying or composite-layer oil spraying.

[0071] Further, the oil spraying strategy determination component 12 is used to execute the following method:

[0072] The door lock injection record is called to mine the common rail electronic control relationship and the injection electronic control relationship; taking the periodic injection effect as input, the common rail electronic control relationship and the injection electronic control relationship as basis, and the injection control parameter as output, the sample drive training based on the door lock injection record is carried out to construct the parameter control derivation unit; according to the parameter control derivation unit, the periodic injection sequence is reversely deduced to determine the periodic injection strategy.

[0073] Furthermore, the injection strategy determination component 12 is used to execute the following method:

[0074] The relative spatial position of the lock clamping mechanism and the nozzle is taken as the first common rail, and the relative driving position of each structure of the injection mechanism is taken as the second common rail; guided by the injection path and combined with the door lock injection record, the common rail electronic control relationship based on the first common rail-the second common rail is explored; guided by the oil layer thickness and combined with the door lock injection record, the injection electronic control relationship based on the injection amount-injection pressure is explored.

[0075] Furthermore, the injection strategy determination component 12 is used to execute the following method:

[0076] Assemble a Hall sensor, wherein the Hall sensor is mounted on the fuel injection mechanism or the lock clamping mechanism; with the execution of the periodic fuel injection strategy, the Hall sensor is synchronously activated; according to the Hall sensor, guided by the fuel injection path, the mechanical motion state of the fuel injection configuration is detected to generate a feedback instruction; according to the feedback instruction, the fuel injection feedback adjustment is performed in response to the fuel injection control system.

[0077] Furthermore, the control component 13 is used to execute the following method:

[0078] The real-time fuel injection characteristics are determined through visual acquisition and tracking; based on the real-time fuel injection characteristics, the periodic fuel injection sequence is traversed to perform matching and characteristic value difference to determine the fuel injection difference; it is determined whether the fuel injection difference meets the preset accuracy, and if not, the abnormal control point is determined.

[0079] Furthermore, the feedback decision component 14 is used to execute the following method:

[0080] The abnormal control point is imported into the periodic decision unit, and the re-injection information is determined according to the injection difference; the re-injection information is transferred to the parameter and control derivation unit, and the feedback injection strategy is output, wherein, according to the feedback injection strategy, the slave control mechanism is driven to perform re-injection feedback control on the abnormal control point.

[0081] It should be noted that the above order of the embodiments of the present application is only for description and does not represent the superiority or inferiority of the embodiments. And the above description of specific embodiments of this specification has been made. The processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0082] The above are only the preferred embodiments of the present application and are not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present application shall be included within the protection scope of the present application.

[0083] This specification and the drawings are only exemplary descriptions of the present application and are considered to have covered any and all modifications, variations, combinations or equivalents within the scope of the present application. Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalent technologies, the present application is intended to include these changes and modifications.

Claims

1. A multi-faceted injection feedback control method for door locks based on online detection, characterized in that: The method comprises: Collect door lock oil injection scenarios and determine the door lock structure and oil injection configuration, wherein the oil injection configuration includes an oil injection mechanism and a lock clamping mechanism, and the oil injection mechanism is a dual-axis drive mechanism; According to the door lock structure and the fuel injection configuration, an injection decision module is developed in the fuel injection control system, and based on the injection decision module, a periodic fuel injection decision is executed under a fixed door lock posture and a reverse parameter control deduction based on the fuel injection configuration is performed to determine the periodic fuel injection strategy; According to the periodic injection strategy, the injection configuration is driven to execute the injection control, and visual acquisition and tracking are performed synchronously to locate the abnormal control point, wherein the main control mechanism of the lock clamping mechanism and the injection mechanism is taken as the control target; For the abnormal control point, in combination with the injection decision module, an abnormal feedback decision is made to determine a feedback injection strategy, wherein the slave control mechanism of the injection mechanism is taken as the control target; Wherein, the oil injection mechanism is a dual-axis drive mechanism, including a first oil injection mechanism and a second oil injection mechanism in a mirror-image structure, wherein the mechanism includes a spray head, a rotating disk, a rotating connecting rod and a rotating regulator, and the rotating connecting rod is at least one section; Wherein, the oil injection mechanism is a dual-axis drive mechanism, comprising: The injection mechanism is set to be a master-slave control mechanism, wherein the master control mechanism is the first injection mechanism or the second injection mechanism, the master control mechanism performs multi-faceted injection of the door lock, and the slave control mechanism performs feedback compensation based on the master control; The fuel injection configuration is initialized according to the master-slave control setting.

2. The door lock multi-surface injection feedback control method based on online detection as claimed in claim 1, characterized in that: The fuel injection decision module includes a periodic decision unit and a parameter control derivation unit. The periodic fuel injection decision under the fixed door lock posture is executed based on the fuel injection decision module, including: According to the door lock oil injection scenario, determining a first door lock posture based on the lock clamping mechanism and the door lock structure; Determine fuel injection requirements through interactive fuel injection work orders; Taking the first door lock posture as the door lock fixed posture and taking the injection demand as a guide, determining a periodic injection sequence, wherein the periodic injection sequence is determined based on an injection path and an oil layer thickness; Among them, the injection mode is single-layer injection or composite-layer injection.

3. The door lock multi-surface injection feedback control method based on online detection as claimed in claim 2, characterized in that: Perform reverse parameter derivation based on injection configuration, including: Call the door lock injection records to explore the relationship between common rail electronic control and injection electronic control; Taking the periodic injection effect as input, the common rail electronic control relationship and the injection electronic control relationship as basis, and the injection control parameter as output, sample drive training based on the door lock injection record is performed to construct the parameter control derivation unit; According to the parameter control derivation unit, reverse parameter control derivation is performed on the periodic injection sequence to determine the periodic injection strategy.

4. The door lock multi-surface injection feedback control method based on online detection as claimed in claim 3 is characterized in that: Explore the relationship between common rail electronic control and fuel injection electronic control, including: The relative spatial position between the lock clamping mechanism and the spray head is the first common rail, and the relative driving position of each structure of the injection mechanism is the second common rail; Guided by the injection path and combined with the door lock injection record, the common rail electronic control relationship based on the first common rail and the second common rail is mined; Guided by the thickness of the oil layer and combined with the door lock injection record, the injection electronic control relationship based on the injection quantity-injection pressure is explored.

5. The door lock multi-faceted injection feedback control method based on online detection as claimed in claim 2, characterized in that: After determining the periodic injection strategy, including: Installing a Hall sensor, wherein the Hall sensor is installed on the fuel injection mechanism or the lock clamping mechanism; As the periodic fuel injection strategy is executed, the Hall sensor is synchronously activated; According to the Hall sensor, guided by the injection path, the mechanical motion state of the injection configuration is detected to generate a feedback instruction; According to the feedback instruction, the fuel injection control system performs fuel injection feedback adjustment in response to the fuel injection control system.

6. The door lock multi-surface injection feedback control method based on online detection as claimed in claim 2, characterized in that: Simultaneously conduct visual acquisition and tracking to locate abnormal control points, including: Determine real-time fuel injection characteristics through visual acquisition and tracking; According to the real-time fuel injection characteristics, the periodic fuel injection sequence is traversed to perform matching and characteristic value difference, and the fuel injection difference is determined; Determine whether the injection difference satisfies a preset accuracy, and if not, determine the abnormal control point.

7. The door lock multi-surface injection feedback control method based on online detection as claimed in claim 6, characterized in that: The determining of the feedback injection strategy comprises: Importing the abnormal control point into the periodic decision unit, and determining the re-injection information according to the injection difference; The re-injection information flow is transferred to the parameter control derivation unit, and the feedback injection strategy is output, wherein, according to the feedback injection strategy, the slave control mechanism is driven to perform re-injection feedback control on the abnormal control point.

8. Door lock multi-faceted injection feedback control system based on online detection, characterized in that: The system is used to implement the door lock multi-surface injection feedback control method based on online detection according to any one of claims 1 to 7, and the system comprises: A scene acquisition component, used to acquire the door lock oil injection scene, determine the door lock structure and oil injection configuration, wherein the oil injection configuration includes an oil injection mechanism and a lock clamping mechanism, and the oil injection mechanism is a dual-axis drive mechanism; The fuel injection strategy determination component is used to develop a fuel injection decision module in the fuel injection control system according to the door lock structure and the fuel injection configuration, and to perform periodic fuel injection decision under the fixed posture of the door lock and reverse parameter control derivation based on the fuel injection configuration based on the fuel injection decision module to determine the periodic fuel injection strategy; A control component is used to drive the injection configuration to perform injection control according to the periodic injection strategy, and simultaneously perform visual acquisition and tracking to locate abnormal control points, wherein the main control mechanism of the lock clamping mechanism and the injection mechanism is the control target; The feedback decision component is used to make an abnormal feedback decision for the abnormal control point in combination with the injection decision module to determine the feedback injection strategy, wherein the slave control mechanism of the injection mechanism is taken as the control target.

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