A food safety detection process control method and system

Abstract

The application discloses a food safety detection process control method and system, and relates to the technical field of food safety detection. The method comprises the following steps: acquiring current motion state information; acquiring the real-time position of the tail end of a food safety execution device in a preset space, and distinguishing the stage of the action of the food safety execution device according to the real-time position; acquiring a physical quantity reflecting the acceptance condition of the food safety detection device to determine whether the acceptance condition of the food safety detection device changes; when the acceptance condition of the food safety detection device changes, obtaining change information and associating the change information with the stage of the action of the food safety execution device to obtain an association result, performing risk level division on the change of the acceptance condition according to the association result, and obtaining a risk level division result; and determining and executing an intervention strategy according to the risk level division result. The application can improve the safety, stability and automation level of the food safety detection process.

Description

Technical Field

[0001] This application relates to the field of food safety testing technology, and more specifically, to a food safety testing process control method and system. Background Technology

[0002] In the field of food safety testing, to achieve continuous collaborative testing by multiple instruments, a process control system is typically used to periodically scan the status signals of each instrument. When an instrument is confirmed to be idle, a robotic arm or other transfer mechanism is dispatched to transfer the pre-treated sample to the inlet of the target instrument. In this automated sample loading and unloading scenario involving multiple instruments in series, there is a time dependency between the robotic arm's actions and the updating of instrument status indicators. When the robotic arm receives an instruction and begins moving the sample, its action process often takes several seconds. During this brief execution window, downstream instruments may automatically trigger protective column balancing or self-test procedures due to minor fluctuations in column pressure or residual samples from the previous sample. At this time, the instrument status will instantly change from idle to busy, and the inlet will close. However, existing process control systems have limitations in terms of status refresh cycles, typically on the order of seconds. If the change in instrument status occurs precisely between two refreshes, the system will issue a sample loading instruction based on the previously read expired idle status. In the uninterrupted loading process, the robotic arm will continue to deliver the sample vial to the locked inlet due to inertia, resulting in physical interference. This conventional process control method relies primarily on a global clock or periodic polling to obtain instrument status, lacking a real-time capture and action termination mechanism for sudden changes in the target instrument status during transmission actions. This control logic struggles to identify instantaneous timing deviations between physical actions and logical state confirmations, resulting in emergency braking triggered only by overload detection from the robotic arm's force sensor when an anomaly occurs. This not only easily damages sample vials or inlets but also forces the entire testing line to halt due to localized mechanical conflicts, requiring lengthy manual intervention for recovery. Therefore, in multi-instrument serial testing, the technical problem of mechanical conflicts and multi-instrument collaborative failures caused by downstream instruments instantly becoming busy due to delayed status updates when the robotic arm performs sample placement based on the idle status of expired instruments urgently needs to be addressed. Summary of the Invention

[0003] This application aims to address at least one of the technical problems existing in the prior art. To this end, this application proposes a food safety testing process control method and system, aiming to solve the technical problem in existing food safety testing process control systems where, in multi-instrument collaborative testing, the timing dependency between the robotic arm and instrument state updates leads to sudden changes in the downstream instrument state during sample processing, causing mechanical conflicts and multi-instrument collaborative failure.

[0004] In a first aspect, embodiments of this application provide a food safety testing process control method, including: Acquire the current operating status information of food safety testing equipment and the current motion status information of food safety execution equipment; Based on the current operating status information of the food safety testing equipment and the current motion status information of the food safety execution equipment, determine whether to issue a sample processing task instruction to the food safety execution equipment; When the instruction to perform sample processing task is issued to the food safety execution device, the real-time position of the end of the food safety execution device in the preset space is obtained, and the stage of the action of the food safety execution device is distinguished based on the real-time position; Acquire physical quantities reflecting the acceptance conditions of the food safety testing equipment, and determine whether the acceptance conditions of the food safety testing equipment have changed based on the physical quantities. The physical quantities include the sample inlet access control signal, internal pressure sensor data, and self-test status register flag of the food safety testing equipment. When the operating conditions of the food safety testing equipment change, change information is obtained. The change information is then correlated with the stage in which the food safety execution equipment is operating to obtain a correlation result. Based on the correlation result, the risk level of the change in the operating conditions is classified to obtain a risk level classification result. Based on the risk level classification results, intervention strategies are determined and implemented for the actions of the food safety enforcement equipment.

[0005] According to some embodiments of this application, determining whether to issue a sample processing task instruction to the food safety execution device based on the current operating status information of the food safety testing device and the current motion status information of the food safety execution device includes: Based on the current operating status information of the food safety testing equipment and the current motion status information of the food safety execution equipment, it is determined whether the start-up conditions are met. The start-up conditions are met when the food safety testing equipment is in an idle state and the food safety execution equipment is in a standby position; otherwise, the start-up conditions are not met. When the activation conditions are met, an instruction to perform sample processing tasks is issued to the food safety execution device; If the activation conditions are not met, an instruction is sent to the food safety execution device not to execute the sample processing task.

[0006] According to some embodiments of this application, obtaining the real-time position of the end effector of the food safety execution device in a preset space includes: Obtain the center of the sample inlet of the food safety testing equipment; A local coordinate system is established with the center of the sample inlet of the food safety testing equipment as the origin to obtain a preset space; The real-time position of the end effector of the food safety execution device is obtained by calculating its three-dimensional spatial coordinates in the preset space in real time.

[0007] According to some embodiments of this application, distinguishing the stage of the operation of the food safety execution device based on the real-time location includes: Calculate the absolute distance from the end of the food safety execution device to the center of the sample inlet based on the real-time location; When the absolute distance is greater than the preset stable transmission zone boundary threshold, it is determined to be in the stable transmission stage; When the absolute distance is between the preset deceleration approach zone boundary threshold and the preset smooth transmission zone boundary threshold, it is determined to be in the deceleration approach stage; When the absolute distance is less than the preset high-risk contact zone boundary threshold, it is determined to be a high-risk contact stage, wherein the preset high-risk contact zone boundary threshold is less than the preset deceleration approach zone boundary threshold, and the preset deceleration approach zone boundary threshold is less than the preset smooth transmission zone boundary threshold.

[0008] According to some embodiments of this application, obtaining a physical quantity reflecting the operating conditions of the food safety testing equipment, and determining whether the operating conditions of the food safety testing equipment have changed based on the physical quantity, includes: Obtain the model information of the food safety testing equipment; Based on the model information, load the corresponding interface description file; According to the interface description file, obtain the inlet access control signal, internal pressure sensor data and self-test status register flag of the food safety testing equipment; The system performs real-time correlation analysis on the inlet access signal, the internal pressure sensor data, and the self-test status register flag to obtain analysis results and determine whether the acceptance conditions of the food safety testing equipment have changed.

[0009] According to some embodiments of this application, the real-time correlation analysis of the sample inlet access signal, the internal pressure sensor data, and the self-test status register flag to obtain the analysis results and determine whether the acceptance conditions of the food safety testing equipment have changed includes: When the analysis results indicate that the inlet access signal is open, and the internal pressure sensor data shows a continuous upward trend within a preset time and exceeds the preset initial warning threshold, it is determined that the acceptance conditions of the food safety testing equipment have changed. When the analysis results indicate that the inlet access signal is open, the self-test status register flag is set, and the internal pressure sensor data simultaneously shows a change, it is determined that the acceptance conditions of the food safety testing equipment have changed. Otherwise, it is determined that the acceptance conditions for the food safety testing equipment have not changed.

[0010] According to some embodiments of this application, when the operating conditions of the food safety testing equipment change, change information is obtained, the change information is correlated with the stage in which the food safety execution equipment is operating, and a correlation result is obtained. Based on the correlation result, the change in operating conditions is classified into risk levels, resulting in a risk level classification result, including: When the acceptance conditions of the food safety testing equipment change, obtain the timestamp and type of the change in the acceptance conditions of the food safety testing equipment; Align the occurrence timestamp with the time intervals of each stage of the food safety execution device's operation to determine the stage of the food safety execution device's operation when the conditions for accepting the food safety testing device change, and use the stage of the operation and the type of change in the conditions for accepting the food safety device together as the association result; The correlation results are mapped and searched in a preset two-dimensional classification and determination matrix to obtain the risk level classification results. The horizontal axis of the preset two-dimensional classification and determination matrix represents the stage of the operation of the food safety execution equipment, and the vertical axis represents the type of change in the acceptance conditions of the food safety testing equipment.

[0011] According to some embodiments of this application, determining and implementing intervention strategies for the actions of the food safety enforcement equipment based on the risk level classification results includes: Based on the risk level classification results, a target intervention strategy is determined from multiple preset intervention strategies. The multiple preset intervention strategies include at least one of the following: trajectory pause command, trajectory reverse operation command, emergency braking command, safety torque cut-off and brake locking command. The target intervention strategy is transformed into control instructions for the actions of the food safety execution equipment and then issued for execution.

[0012] According to some embodiments of this application, determining the target intervention strategy from multiple preset intervention strategies based on the risk level classification results includes: When the risk level classification result is the first risk level, the target intervention strategy is determined to be a trajectory pause instruction. The trajectory pause instruction is used to instruct the food safety execution device to remain hovered at the current spatial coordinate position and start a waiting timer. When the risk level classification result is the second risk level, the target intervention strategy is determined to be the trajectory reverse operation instruction. The trajectory reverse operation instruction is used to drive the food safety execution equipment to retreat back to the preset safety buffer along the original sampling path. When the risk level classification result is the third risk level, the target intervention strategy is determined to be an emergency braking command. The emergency braking command is used to send a torque control signal to the gripper controller to maintain the maximum clamping force. When the risk level classification result is the fourth risk level, the target intervention strategy is determined to be a safety torque cut-off and brake locking command. The safety torque cut-off and brake locking command is used to cut off the normal trajectory interpolation cycle of the motion controller of the food safety execution device, trigger the safety torque cut-off function of the servo driver, and activate the electromagnetic brakes of each joint. The first risk level is lower than the second risk level, the second risk level is lower than the third risk level, and the third risk level is lower than the fourth risk level.

[0013] Secondly, this application also discloses a food safety testing process control system, including: The acquisition module is used to acquire the current operating status information of food safety testing equipment and the current motion status information of food safety execution equipment; The target instruction module is used to determine, based on the current operating status information of the food safety testing equipment and the current motion status information of the food safety execution equipment, whether to issue an instruction to the food safety execution equipment to perform sample processing tasks. The differentiation module is used to obtain the real-time position of the end of the food safety execution device in a preset space when the instruction to execute the sample processing task is issued to the food safety execution device, and to differentiate the stage of the action of the food safety execution device based on the real-time position; The judgment module is used to acquire physical quantities reflecting the acceptance conditions of the food safety testing equipment, and to determine whether the acceptance conditions of the food safety testing equipment have changed based on the physical quantities. The physical quantities include the sample inlet access control signal, internal pressure sensor data, and self-test status register flag of the food safety testing equipment. The association module is used to obtain change information when the acceptance conditions of the food safety testing equipment change, associate the change information with the stage of the food safety execution equipment's operation, obtain an association result, and classify the risk level of the change in acceptance conditions based on the association result to obtain a risk level classification result. The determination module is used to determine and execute intervention strategies for the actions of the food safety enforcement equipment based on the risk level classification results.

[0014] The technical solution according to the embodiments of this application has at least the following beneficial effects: The food safety testing process control method disclosed in this application effectively avoids blindly starting tasks when the equipment status does not meet the conditions by acquiring the real-time operating status information of the food safety testing equipment and the food safety execution equipment, and determining whether to issue sample processing task instructions based on this information. During task execution, the method can acquire the position of the end of the food safety execution equipment in a preset space in real time, and distinguish the stage of the execution equipment's action based on the position, thereby enabling refined management of the execution equipment's actions. More importantly, this application can determine in real time whether the acceptance conditions of the testing equipment have changed by acquiring physical quantities such as the sampling port access control signal, internal pressure sensor data, and self-test status register flags of the food safety testing equipment. When the acceptance conditions change, the method can associate the change information with the stage of the execution equipment's action, and classify the risk level of the change in acceptance conditions based on the association result. Finally, based on the risk level classification result, an intervention strategy for the action of the food safety execution equipment is determined and executed. This application's method overcomes the limitations of traditional process control systems in terms of state refresh cycles, solving the technical problem that instrument state jumps occurring between two refreshes lead to the system issuing sample release commands based on expired states, resulting in physical interference between the robotic arm and the locked sample inlet. Through real-time, multi-dimensional state perception and dynamic risk assessment, this application can promptly identify instantaneous timing deviations between physical actions and logical state confirmations. In the event of an anomaly, it no longer relies solely on overload detection by the robotic arm's force sensor to trigger emergency braking; instead, it can take earlier and more precise intervention measures based on the risk level, such as trajectory suspension, trajectory reversal, emergency braking, or safety torque cutoff and brake locking. This not only effectively avoids damage to sample bottles or sample inlets and reduces the stalling of the entire testing line due to localized mechanical conflicts, but also significantly reduces the frequency and time of manual intervention for recovery, thereby greatly improving the safety, stability, and automation level of the food safety testing process.

[0015] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0016] The accompanying drawings are used to provide a further understanding of the technical solutions of this application and constitute a part of the specification. They are used together with the embodiments of this application to explain the technical solutions of this application and do not constitute a limitation on the technical solutions of this application.

[0017] Figure 1 A schematic flowchart of a food safety testing process control method provided in one embodiment of this application; Figure 2This is a flowchart illustrating a method for determining whether to issue a command to a food safety execution device to perform a sample processing task, as provided in one embodiment of this application. Figure 3 This is a schematic diagram of a food safety testing process control system provided in one embodiment of this application. Detailed Implementation

[0018] To make the objectives, technical methods, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0019] It should be noted that the meaning of "multiple" (or "more than") in the description of the embodiments of this application refers to two or more, and "greater than," "less than," "exceeding," etc. are understood to exclude the number itself, while "above," "below," "within," etc. are understood to include the number itself. If "first," "second," etc. are used in the description, they are only for the purpose of distinguishing technical features and should not be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated or the order of the technical features indicated.

[0020] In this application embodiment, "at least one" refers to one or more, and "more than one" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent the existence of A alone, the simultaneous existence of A and B, or the existence of B alone. A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one of the following" and similar expressions refer to any combination of these items, including any combination of singular or plural items. For example, at least one of a, b, and c can represent: the existence of a alone, the existence of b alone, the existence of c alone, the simultaneous existence of a and b, the simultaneous existence of a and c, the simultaneous existence of b and c, or the simultaneous existence of a, b, and c, where a, b, and c can be single or multiple.

[0021] In the description of this application, unless otherwise expressly defined, terms such as "setup," "installation," and "connection" should be interpreted broadly, and those skilled in the art can reasonably determine the specific meaning of the above terms in this application in conjunction with the specific content of the technical solution.

[0022] The food safety testing process control method provided in this application can be applied to a terminal, a server, or software running on either a terminal or a server. In some embodiments, the terminal can be a smartphone, tablet, laptop, desktop computer, etc.; the server can be configured as an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDN), and big data and artificial intelligence platforms; the software can be an application that implements the food safety testing process control method, but is not limited to the above forms.

[0023] The embodiments of this application can be used in numerous general-purpose or special-purpose computer system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics devices, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, etc. This application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform specific tasks or implement specific abstract data types. This application can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In a distributed computing environment, program modules can reside in local and remote computer storage media, including storage devices.

[0024] See Figure 1 , Figure 1 This is a schematic flowchart illustrating a food safety testing process control method according to an embodiment of this application. The food safety testing process control method provided in this embodiment includes, but is not limited to, steps S110 to S160, which will be described in detail below.

[0025] Step S110: Obtain the current operating status information of the food safety testing equipment and the current motion status information of the food safety execution equipment; Step S120: Based on the current operating status information of the food safety testing equipment and the current motion status information of the food safety execution equipment, determine whether to issue a sample processing task instruction to the food safety execution equipment; Step S130: When issuing a sample processing task instruction to the food safety execution device, obtain the real-time position of the end of the food safety execution device in the preset space, and distinguish the stage of the action of the food safety execution device based on the real-time position. Step S140: Obtain physical quantities reflecting the acceptance conditions of the food safety testing equipment, and determine whether the acceptance conditions of the food safety testing equipment have changed based on the physical quantities. The physical quantities include the sampling port access control signal, internal pressure sensor data, and self-test status register flag of the food safety testing equipment. Step S150: When the acceptance conditions of the food safety testing equipment change, obtain the change information, associate the change information with the stage of the food safety execution equipment's operation, obtain the association result, classify the risk level of the change in acceptance conditions based on the association result, and obtain the risk level classification result. Step S160: Based on the risk level classification results, determine and implement intervention strategies for the actions of food safety enforcement equipment.

[0026] It should be noted that "food safety testing equipment" refers to various instruments used for analyzing and testing food samples, such as liquid chromatographs and mass spectrometers. These instruments have components such as sample inlets and internal pressure sensors, and can generate physical quantities such as access control signals, internal pressure data, and self-test status register flags. "Food safety execution equipment" refers to automated equipment responsible for sample transfer and processing, such as robotic arms, whose end effectors are typically equipped with grippers for grasping and placing sample bottles. First, it is necessary to obtain the current operating status information of the food safety testing equipment and the current motion status information of the food safety execution equipment. The operating status information of the food safety testing equipment can be manually entered, for example, by the operator selecting the current instrument status as "idle" or "busy" on the control interface. Alternatively, it can be obtained by reading specific registers or status words within the food safety testing equipment. These registers or status words are usually provided by the equipment manufacturer and indicate the equipment's current operating mode, error status, or ready status. The motion status information of the food safety execution equipment can be directly provided by its motion controller, for example, by querying the motion controller's API interface to obtain whether the robotic arm is currently in standby, moving, or faulty state. Alternatively, visual sensors can be installed on the food safety execution equipment to identify its current posture and position in real time, thereby inferring its motion state. Based on the acquired current operating status information of the food safety testing equipment and the current motion state information of the food safety execution equipment, it is necessary to determine whether to issue a sample processing task instruction to the food safety execution equipment. A simple logical judgment can be set: if the food safety testing equipment is in an idle state and the food safety execution equipment is in a standby position, the start condition is met, and the sample processing task instruction can be issued. Otherwise, the start condition is not met, and the sample processing task instruction is not executed. When issuing a sample processing task instruction to the food safety execution equipment, it is necessary to obtain the real-time position of the end effector of the food safety execution equipment in a preset space, and distinguish the stage of the action of the food safety execution equipment based on the real-time position. For example, a local coordinate system can be established at the center of the sample inlet of the food safety testing equipment, and this coordinate system can be defined as the preset space. The three-dimensional spatial coordinates of the end effector of the food safety execution equipment (e.g., the center point of the gripper) in the preset space can be calculated in real time using the kinematic model of the robotic arm. By calculating the absolute distance from the end effector to the center of the sample inlet in real time, the action stage can be distinguished according to different distance thresholds. For example, when the absolute distance is greater than a certain threshold, it is determined to be a stable transmission phase; when the absolute distance is between two thresholds, it is determined to be a deceleration approach phase; and when the absolute distance is less than a certain threshold, it is determined to be a high-risk contact phase. Simultaneously, it is necessary to acquire physical quantities reflecting the acceptance conditions of the food safety testing equipment and determine whether these conditions have changed based on these quantities. These physical quantities include the inlet access control signal of the food safety testing equipment, internal pressure sensor data, and self-test status register flags.For example, the interface description file provided by the food safety testing equipment can be read, which defines how to access and parse these physical quantities. The inlet access control signal can be a digital input, indicating the open or closed state of the access control. Internal pressure sensor data can be an analog input, reflecting pressure changes within the equipment. The self-test status register flag can be a bit flag, indicating whether the equipment is performing a self-test or if an internal fault exists. By performing real-time correlation analysis on these physical quantities, it can be determined whether the operating conditions of the food safety testing equipment have changed.

[0027] In one embodiment, when the acceptance conditions change, the timestamp of the change and the type of change (e.g., inlet closure, abnormal increase in internal pressure, self-test activation, etc.) can be recorded. Then, this timestamp is aligned with the time intervals of each stage of the food safety execution device's operation to determine the stage of the food safety testing device's operation when the acceptance conditions change. The stage of the operation and the type of change in acceptance conditions are used as the correlation result. Finally, this correlation result is mapped and searched in a preset two-dimensional classification matrix to obtain the risk level classification result. The horizontal axis of this matrix represents the stage of the food safety execution device's operation, and the vertical axis represents the type of change in the food safety testing device's acceptance conditions. Each cell in the matrix corresponds to a preset risk level. Multiple intervention strategies can be preset, including trajectory pause commands, trajectory reverse operation commands, emergency braking commands, safety torque cutoff and brake locking commands, etc. When the risk level classification result is the first risk level, the target intervention strategy can be determined as a trajectory pause command, instructing the food safety execution device to remain hovered at the current spatial coordinate position and start a waiting timer. When the risk level is classified as Level 2, the target intervention strategy is determined to be a trajectory reverse movement command, driving the food safety execution equipment to retreat back to the preset safety buffer along the original sampling path. When the risk level is classified as Level 3, the target intervention strategy is determined to be an emergency braking command, sending a torque control signal to the gripper controller to maintain maximum clamping force. When the risk level is classified as Level 4, the target intervention strategy is determined to be a safety torque cut-off and brake locking command, cutting off the normal trajectory interpolation cycle of the motion controller of the food safety execution equipment, triggering the safety torque cut-off function of the servo driver, and activating the electromagnetic brakes of each joint. Finally, the determined target intervention strategy is converted into control commands for the action of the food safety execution equipment and executed.

[0028] It should be noted that this application introduces a real-time differentiation of the operational stages of food safety execution equipment, as well as a real-time monitoring and risk level classification mechanism for changes in the acceptance conditions of food safety testing equipment. By acquiring the real-time position of the end effector of the food safety execution equipment in a preset space, and distinguishing its operational stage ("smooth transmission stage," "deceleration approach stage," and "high-risk contact stage") based on this position, this application can accurately grasp the spatial relationship between the robotic arm and the testing equipment. Simultaneously, by acquiring and correlating physical quantities such as the sample inlet access control signal, internal pressure sensor data, and self-test status register flags in real time, this application can instantly determine changes in the acceptance conditions of the food safety testing equipment. This application correlates the information on changes in acceptance conditions with the stage of the robotic arm's operation and classifies the risk level accordingly. This correlation analysis enables the system to dynamically determine and execute corresponding intervention strategies based on the urgency and potential hazard level of the risk, such as trajectory suspension, trajectory reversal, emergency braking, or safety torque cutoff and brake locking. This graded intervention mechanism far surpasses the single passive response method in existing technologies that relies solely on force sensors to detect overload and trigger emergency braking. Therefore, this application enables early warning and proactive intervention for potential conflicts in automated testing processes, fundamentally solving the problems of mechanical conflicts and multi-instrument collaborative failures caused by delayed state updates in existing technologies. This real-time, intelligent, and hierarchical control strategy not only effectively protects sample vials and instrument inlets from damage, but also significantly reduces downtime in the testing line caused by mechanical conflicts, improving testing efficiency and data reliability.

[0029] See Figure 2 , Figure 2 This is a flowchart illustrating a method for determining whether to issue a sample processing task instruction to a food safety execution device according to an embodiment of this application. The steps for determining whether to issue a sample processing task instruction to the food safety execution device include, but are not limited to, steps S210 to S230, which will be described in detail below.

[0030] Step S210: Based on the current operating status information of the food safety testing equipment and the current motion status information of the food safety execution equipment, determine whether the start-up conditions are met. The start-up conditions are met when the food safety testing equipment is in an idle state and the food safety execution equipment is in a standby position; otherwise, the start-up conditions are not met. Step S220: When the activation conditions are met, issue a command to the food safety execution device to perform the sample processing task; Step S230: When the start-up conditions are not met, issue an instruction to the food safety execution device not to perform the sample processing task.

[0031] Specifically, the activation conditions refer to the preparatory state that food safety testing equipment and food safety execution equipment must reach before performing sample processing tasks. The idle state of food safety testing equipment can be understood as the equipment not currently performing any testing tasks, its internal system being in a standby or ready-to-receive-new-sample state; for example, its testing channels are empty, sensors are reset, and there is no ongoing analysis process. The standby position of food safety execution equipment refers to the end effector of the equipment (e.g., a robotic arm) being in a preset safe, initial, or reset position. This position typically does not interfere with the food safety testing equipment or other peripheral equipment and facilitates the initiation of new sample grabbing or placement operations. In practical applications, the current operating status information of food safety testing equipment can include the equipment's working mode, task queue status, internal sensor readings, etc., while the current motion status information of food safety execution equipment can include its joint angles, end effector position, speed, acceleration, and whether there are any abnormal alarms. By comprehensively analyzing this information, it is possible to accurately determine whether the two devices are ready. This technical solution effectively avoids blindly issuing task commands when food safety testing equipment or food safety execution equipment is not ready, thereby significantly improving the stability and safety of the entire food safety testing process. This solution ensures that task instructions are issued based on the actual readiness of the equipment, reducing the risk of erroneous operations, equipment damage, or sample contamination caused by mismatched equipment status, thereby improving the reliability and operational efficiency of the automated testing system.

[0032] Specifically, in the above-mentioned food safety testing process control method, the step of obtaining the real-time position of the end effector of the food safety execution device in the preset space may further include the following: Obtain the center of the sample inlet of the food safety testing equipment; A local coordinate system is established with the center of the sample inlet of the food safety testing equipment as the origin to obtain a preset space; The three-dimensional spatial coordinates of the end effector of the food safety execution device in the preset space are calculated in real time to obtain the real-time position.

[0033] Establishing a local coordinate system refers to constructing a relative coordinate system using the center of the food safety testing equipment's inlet as a reference point. This local coordinate system can be a Cartesian coordinate system, with its origin coinciding with the inlet center, and defining the directions of the X, Y, and Z axes. Its purpose is to provide a precise and stable spatial reference for the operation of the food safety execution equipment near the inlet. Furthermore, real-time calculation of the three-dimensional spatial coordinates of the food safety execution equipment's end effector in the preset space refers to continuously acquiring the precise position information of its end effector within the aforementioned local coordinate system through the equipment's own kinematic model, encoder data, or external visual positioning system. For example, the inverse kinematics algorithm for robots can be used, combined with joint angle sensor data, to calculate the (x, y, z) coordinates of the end effector in three-dimensional space. Its purpose is to dynamically track the precise position of the food safety execution equipment's end effector within the critical operating area, providing fundamental data for subsequent action phase judgments and risk assessments. This application's solution establishes a local coordinate system with the center of the food safety testing equipment's inlet as the origin, and calculates the three-dimensional spatial coordinates of the food safety execution device's end effector within this preset space in real time, thereby achieving precise and real-time monitoring of the end effector's position. This method avoids the complexity and error accumulation that may arise from using a global coordinate system, making the determination of the relative position between the food safety execution device and the food safety testing equipment more intuitive and accurate. By obtaining precise real-time positions, reliable input can be provided for subsequent differentiation of the stage of the food safety execution device's actions, thereby supporting more refined risk level classification and the formulation of intervention strategies.

[0034] In some embodiments described above in this application, a method is proposed to obtain the real-time position of the end effector of a food safety execution device in a preset space, and to distinguish the stage of the operation of the food safety execution device based on the real-time position. Specifically, distinguishing the stage of the operation of the food safety execution device can be further refined. Distinguishing the stage of the operation of the food safety execution device based on the real-time position includes: Calculate the absolute distance from the end of the food safety execution device to the center of the sample inlet based on the real-time location; When the absolute distance is greater than the preset threshold of the stable transmission zone boundary, it is determined to be in the stable transmission phase; When the absolute distance is between the preset deceleration approach zone boundary threshold and the preset smooth transmission zone boundary threshold, it is determined to be the deceleration approach phase; When the absolute distance is less than the preset high-risk contact zone boundary threshold, it is determined to be a high-risk contact stage. The preset high-risk contact zone boundary threshold is less than the preset deceleration approach zone boundary threshold, and the preset deceleration approach zone boundary threshold is less than the preset smooth transmission zone boundary threshold.

[0035] Specifically, after obtaining the real-time position of the end effector of the food safety execution device in the preset space, it is necessary to calculate the absolute distance from the end effector to the center of the sample inlet of the food safety testing device. This absolute distance is a key parameter for determining the operational stage of the food safety execution device. For example, when the end effector of the food safety execution device is far from the center of the sample inlet, it is in the stable transmission stage, and the absolute distance at this time will be greater than the preset stable transmission zone boundary threshold. As the end effector of the food safety execution device gradually approaches the center of the sample inlet, its operation will enter the deceleration approach stage, and the absolute distance at this time will be between the preset deceleration approach zone boundary threshold and the preset stable transmission zone boundary threshold. When the end effector of the food safety execution device is very close to or may even come into contact with the sample inlet, it enters the high-risk contact stage, and the absolute distance at this time will be less than the preset high-risk contact zone boundary threshold. To ensure the logic and safety of the stage division, the preset high-risk contact zone boundary threshold is set to be less than the preset deceleration approach zone boundary threshold, and the preset deceleration approach zone boundary threshold is less than the preset stable transmission zone boundary threshold, thus forming a stage division from far to near with increasing risk. This application's solution achieves precise differentiation of the operational stages of a food safety execution device by comparing the absolute distance from the end of the device to the center of the sample inlet with a series of preset boundary thresholds. This distance-based stage division mechanism can reflect the relative positional relationship between the food safety execution device and the food safety testing device in real time, providing accurate contextual information for subsequent risk assessment and intervention strategies. By setting different distance thresholds, the different states of the device can be clearly defined, from smooth movement at a long distance, to decelerating approach at a medium distance, and then to high-risk contact at close range. This allows the system to dynamically adjust its understanding and response to the device's actions based on actual changes in physical distance.

[0036] Specifically, obtaining the physical quantities reflecting the operating conditions of the food safety testing equipment and determining whether the operating conditions of the food safety testing equipment have changed based on these physical quantities may include the following steps: Obtain the model information of food safety testing equipment; Load the corresponding interface description file based on the model information; Based on the interface description file, obtain the inlet access control signal, internal pressure sensor data, and self-test status register flag of the food safety testing equipment; Real-time correlation analysis is performed on the inlet access control signal, internal pressure sensor data, and self-test status register flags to obtain analysis results and determine whether the acceptance conditions of the food safety testing equipment have changed.

[0037] The model information refers to the unique identifier assigned to the food safety testing equipment during production or shipment, used to distinguish different types or batches of equipment. By obtaining this model information, the system can identify the specific specifications and characteristics of the currently connected food safety testing equipment. The interface description file is a configuration file corresponding to a specific model of food safety testing equipment. It contains detailed definitions of the communication protocols, data formats, read addresses, and normal ranges for various physical quantities of the equipment (such as the inlet access signal, internal pressure sensor data, self-test status register flags, etc.). Loading the corresponding interface description file ensures that the system can correctly interact with and parse data from the food safety testing equipment. The inlet access signal indicates the physical status of the food safety testing equipment's inlet, such as whether it is open or closed. The internal pressure sensor data reflects the real-time pressure value inside the equipment, which is crucial for determining whether the internal environment is stable or whether there are any abnormalities (such as leaks). The self-test status register flag is a status bit generated by the equipment's internal self-diagnostic function, used to indicate whether the equipment is operating normally, such as whether there are hardware faults or software errors. Real-time correlation analysis of the inlet access signal, internal pressure sensor data, and self-test status register flags refers to the system's continuous monitoring and comprehensive evaluation of these physical quantities. By performing logical judgments and trend analysis on this data, it is possible to more comprehensively and accurately determine whether the operating conditions of the food safety testing equipment have changed.

[0038] It should be noted that the solution in this application first obtains the model information of the food safety testing equipment and then loads a dedicated interface description file accordingly, ensuring that the system can accurately parse data and acquire status for different equipment models. As a result, the system can accurately read and understand key physical quantities such as the inlet access control signal, internal pressure sensor data, and self-test status register flags. Furthermore, by performing real-time correlation analysis on these physical quantities, rather than making isolated judgments, the system can comprehensively assess the overall acceptance status of the equipment. For example, a single pressure fluctuation may not be sufficient to determine changes in acceptance conditions, but by combining the open status of the inlet access control signal and the anomaly of the self-test flag, potential risks can be identified more reliably, thereby improving the accuracy and robustness of judging changes in the acceptance conditions of food safety testing equipment.

[0039] Specifically, the real-time correlation analysis of the inlet access control signal, internal pressure sensor data, and self-test status register flags of the food safety testing equipment, to obtain the analysis results and determine whether the acceptance conditions of the food safety testing equipment have changed, can include the following specific judgment logic. The real-time correlation analysis of the inlet access control signal, internal pressure sensor data, and self-test status register flags, to obtain the analysis results and determine whether the acceptance conditions of the food safety testing equipment have changed, includes: When the analysis results indicate that the inlet access control signal is open and the internal pressure sensor data shows a continuous upward trend within a preset time and exceeds the preset initial warning threshold, it is determined that the acceptance conditions of the food safety testing equipment have changed. When the analysis results indicate that the inlet gate signal is open, the self-test status register flag is set, and the internal pressure sensor data shows a change, it is determined that the acceptance conditions of the food safety testing equipment have changed. Otherwise, it can be determined that the conditions for accepting food safety testing equipment have not changed.

[0040] The "open" status of the sample inlet access signal indicates that the sample inlet of the food safety testing equipment is physically open, allowing external objects to enter or leave. A continuous upward trend in internal pressure sensor data within a preset time, exceeding the preset initial warning threshold, can be interpreted as an abnormal increase in internal pressure within the testing equipment, reaching a dangerous level. This typically indicates potential blockage, leakage, or other abnormalities within the equipment. A set self-test status register flag indicates that the food safety testing equipment has detected a fault or abnormality through its internal self-test program and activated the corresponding status flag. Simultaneous changes in internal pressure sensor data indicate abnormal fluctuations or deviations from the normal range in internal pressure at the same time as the self-test flag is set. Both of these situations are considered changes in the acceptance conditions of the food safety testing equipment, suggesting that the equipment may be unable to safely and effectively receive or process samples. Conversely, if none of the above conditions are met, the acceptance conditions are considered unchanged, and the equipment is in normal standby mode. This technical solution enables accurate judgment of changes in the acceptance conditions of food safety testing equipment. By comprehensively considering the inlet access signal, internal pressure sensor data, and self-test status register flags, and by setting specific judgment thresholds and logic, potential risks during the sample introduction process can be effectively identified, such as internal blockage, abnormal pressure, or equipment self-test malfunctions. This refined judgment mechanism avoids false alarms or missed alarms that may result from judging based on a single physical quantity, thereby improving the accuracy and reliability of risk identification. This provides a solid foundation for subsequent risk level classification and the implementation of intervention strategies, ensuring the stability and safety of the food safety testing process.

[0041] In response, this application further proposes that when the operating conditions of food safety testing equipment change, information about the change is obtained, and this information is correlated with the stage at which the food safety execution equipment is operating to obtain a correlation result. Based on the correlation result, the risk level of the change in operating conditions is classified to obtain a risk level classification result, specifically including: When the conditions for undertaking food safety testing equipment change, obtain the timestamp and type of the change. Align the timestamps with the time intervals of each stage of the food safety execution equipment's operation to determine the stage of the food safety execution equipment's operation when the conditions under which the food safety testing equipment is operating change. Combine the stage of the operation with the type of change in the conditions under which the conditions are operating as the correlation result. The correlation results are mapped and searched in a preset two-dimensional classification judgment matrix to obtain the risk level classification results. The horizontal axis of the preset two-dimensional classification judgment matrix represents the stage of the food safety execution equipment's operation, and the vertical axis represents the type of change in the acceptance conditions of the food safety testing equipment.

[0042] Specifically, when the conditions under which food safety testing equipment operates change, the system records the timestamp of the change and the specific type of change in real time. For example, the type of change may include the abnormal opening of the inlet gate signal, a sharp fluctuation in the internal pressure sensor, or the setting of the self-test status register flag. This information forms the basis for subsequent risk assessment. Aligning the timestamp with the time intervals of each stage of the food safety equipment's operation means accurately determining which specific stage the equipment was in when the conditions changed by comparing the time of the event with the corresponding time periods of different operation stages (e.g., smooth transmission stage, deceleration approach stage, high-risk contact stage). This alignment ensures an accurate grasp of the dynamic environment at the time of the event. Therefore, using both the stage of the operation and the type of change in the conditions as a correlation result means that risk assessment is no longer a single-dimensional consideration but integrates the two key factors of "when the change occurred" and "what kind of change occurred." In practical applications, the preset two-dimensional hierarchical judgment matrix is ​​a predefined lookup table or rule set, where the horizontal axis represents the stage of the food safety equipment's operation, and the vertical axis represents the type of change in the conditions under which the food safety testing equipment operates. By using the aforementioned correlation results (i.e., action stage and change type) as input and performing a mapping lookup in this matrix, the corresponding risk level classification results can be obtained objectively and systematically. The matrix is ​​designed to simplify complex dynamic interaction scenarios into quantifiable risk levels, thus providing a clear basis for subsequent intervention strategies. This application enables a more refined, objective, and systematic assessment of the risks associated with changes in the operating conditions of food safety testing equipment. Compared to methods that only perform simple correlations, this solution significantly improves the accuracy and reliability of risk level classification by introducing timestamps, change types, and a two-dimensional classification judgment matrix. This allows the system to identify potential safety hazards more promptly and accurately, providing a solid data foundation and decision-making basis for subsequently determining and implementing intervention strategies for food safety equipment actions. This effectively improves the level of automated safety control throughout the entire food safety testing process, reducing operational risks and potential equipment damage risks.

[0043] To address this, this application proposes an optimized solution. Based on risk level classification, a target intervention strategy is determined from multiple pre-defined intervention strategies, and this strategy is then transformed into control instructions for the actions of food safety execution equipment and issued for execution, thereby achieving more refined and safer process control. Based on the aforementioned risk level classification results, the intervention strategy for the actions of food safety execution equipment is determined and executed, including: Based on the risk level classification results, a target intervention strategy is determined from multiple preset intervention strategies. The multiple preset intervention strategies include at least one of the following: trajectory pause command, trajectory reverse operation command, emergency braking command, safety torque cut-off and brake locking command. Transform the target intervention strategy into control instructions for the actions of food safety enforcement equipment and issue them for execution.

[0044] Specifically, the aforementioned pre-defined intervention strategies refer to a set of pre-defined operational instructions for different risk levels. Their purpose is to select the most appropriate response measure based on the severity and urgency of the risk when the conditions of the food safety testing equipment change. These strategies are designed to be progressive, addressing situations ranging from minor anomalies to serious safety threats. The trajectory pause instruction instructs the food safety execution equipment to remain hovered at its current spatial coordinates and start a waiting timer. This instruction is suitable for low-risk situations, such as when the conditions of the testing equipment change slightly but do not yet pose a direct danger. Pausing the execution equipment's actions provides the system with time for further evaluation or to wait for conditions to recover. The trajectory reverse movement instruction drives the food safety execution equipment back along its original sampling path to a pre-defined safety buffer zone. This instruction is suitable for medium-risk situations, such as when the conditions of the testing equipment change and the execution equipment is in the deceleration approach phase. By causing the execution equipment to retreat to a safe area, potential collisions or damage can be effectively avoided. The emergency braking instruction sends a torque control signal to the gripper controller to maintain maximum clamping force. This instruction is applicable to higher-risk situations, such as when the conditions of the testing equipment change drastically and the execution equipment is in a high-risk contact phase. Emergency braking and maintaining clamping force can prevent samples from falling or further damage to the equipment. The safety torque cut-off and brake locking instruction is a control instruction that cuts off the normal trajectory interpolation cycle of the motion controller of the food safety execution equipment, triggers the safety torque cut-off function of the servo drive, and activates the electromagnetic brakes of each joint. This instruction is applicable to the highest-risk situations, such as when the conditions of the testing equipment change catastrophically and the execution equipment is in a high-risk contact phase. By completely cutting off power and locking the joints, the safety of personnel and equipment can be maximized. Converting the target intervention strategy into control instructions for the actions of the food safety execution equipment and issuing them for execution refers to converting the specific intervention strategy determined according to the risk level classification into low-level instructions that the food safety execution equipment controller can recognize and execute, and sending them to the execution equipment through the communication interface. For example, a trajectory pause instruction may be converted into a series of axis stop instructions and timer start instructions; the safety torque cut-off and brake locking instruction may be converted into a safety relay disconnect signal and a brake activation signal. This conversion process ensures that the intervention strategy can be accurately understood and executed by the execution equipment.

[0045] It should be noted that this application addresses the issues of overly generalizable and insufficiently precise responses in basic solutions by introducing multi-level pre-set intervention strategies and precisely matching them based on risk level classification. Specifically, when the conditions for the food safety testing equipment change, and this change is correlated with the stage of the equipment's operation and classified into risk levels, the system no longer simply executes a uniform intervention action. Instead, it selects the most suitable target intervention strategy from pre-set strategies such as trajectory pause commands, trajectory reverse operation commands, emergency braking commands, safety torque cutoff and brake locking commands, based on the severity of the risk level. For example, for lower risks, only pausing the equipment operation is necessary to avoid unnecessary equipment retraction or shutdown; for higher risks, immediate activation of emergency braking or safety torque cutoff and brake locking may be required to prevent potential serious accidents. This tiered intervention mechanism enables the system to achieve maximum safety at minimal cost, avoiding efficiency losses caused by excessive intervention, and ensuring the most decisive measures are taken at critical moments. By translating the target intervention strategy into control commands for food safety execution equipment and issuing them for execution, it is ensured that the selected strategy can be accurately and promptly responded to by the execution equipment, thereby effectively controlling risks.

[0046] In some preferred embodiments, it is assumed that during a food safety testing process, a food safety execution device is feeding a sample into the inlet of a food safety testing device. When the food safety execution device is in a stable transmission phase, the inlet gate signal of the food safety testing device suddenly shows a half-open state, and the internal pressure sensor data shows slight fluctuations, but does not reach the severe threshold. At this time, the system, through correlation analysis and risk level classification, determines it to be at the first risk level. Based on this risk level, the system determines the target intervention strategy as a trajectory pause command. This command is converted into a control signal and sent to the food safety execution device, causing it to remain hovering at its current position and start a waiting timer, waiting for operator inspection or automatic system recovery. When the food safety execution device is in a deceleration approach phase, and its end is close to the center of the inlet, the self-test status register flag of the food safety testing device is set, and the internal pressure sensor data shows a continuous rise and exceeds the initial warning threshold. At this time, the system determines it to be at the second risk level. Based on this risk level, the system determines the target intervention strategy as a trajectory reverse operation command. This command is converted into a control signal and sent to the food safety execution device, causing it to reverse along the original path back to the preset safety buffer to avoid collision with the testing device. When the food safety execution device is in a high-risk contact phase, and its end is very close to or in contact with the sample inlet, the sample inlet gate signal of the food safety testing device suddenly opens completely, and the internal pressure sensor data drops sharply, indicating a possible serious seal failure or structural damage. At this point, the system classifies it as a third-risk level. Based on this risk level, the system determines the target intervention strategy as an emergency braking command. This command is converted into a control signal and sent to the gripper controller, causing it to immediately maintain maximum clamping force to prevent the sample from falling and to quickly stop the execution device. When the food safety execution device is in a high-risk contact phase, and the internal pressure sensor data of the testing device shows abnormally drastic fluctuations, while the self-test status register flag is set, it indicates that the testing device may have a serious malfunction or structural damage. At this point, the system classifies it as a fourth-risk level. Based on this risk level, the system determines the target intervention strategy as a safety torque cut-off and brake locking command. This command is converted into a control signal and sent to the food safety execution device, immediately cutting off the normal trajectory interpolation cycle of its motion controller, triggering the safety torque cut-off function of the servo drive, and activating the electromagnetic brakes of each joint to ensure the device completely stops and locks, maximizing the safety of personnel and equipment.

[0047] In response, this application further proposes determining the target intervention strategy from multiple pre-set intervention strategies based on the risk level classification results, specifically including: When the risk level classification result is the first risk level, the target intervention strategy is determined to be the trajectory pause instruction. This trajectory pause instruction is used to instruct the food safety execution equipment to remain hovered at the current spatial coordinate position and start a waiting timer. When the risk level classification result is the second risk level, the target intervention strategy is determined to be the trajectory reverse operation instruction. This trajectory reverse operation instruction is used to drive the food safety execution equipment to retreat back to the preset safety buffer along the original sampling path. When the risk level classification result is the third risk level, the target intervention strategy is determined to be an emergency braking command. This emergency braking command is used to send a torque control signal to the gripper controller to maintain the maximum clamping force. When the risk level is classified as Level 4, the target intervention strategy is determined to be a safety torque cut-off and brake locking command. This command is used to cut off the normal trajectory interpolation cycle of the motion controller of the food safety actuator, trigger the safety torque cut-off function of the servo drive, and activate the electromagnetic brakes of each joint. The first risk level is lower than the second risk level, the second risk level is lower than the third risk level, and the third risk level is lower than the fourth risk level.

[0048] Specifically, the first risk level typically indicates a low level of risk, such as slight fluctuations in the conditions under which food safety testing equipment operates but do not yet pose an immediate threat. In this case, the purpose of the trajectory pause command is to give the system or operators time to assess and adjust, avoiding unnecessary process interruptions or sample damage. The food safety execution equipment is instructed to remain stationary in its current position, while a waiting timer is started to ensure rapid resumption of operation once the risk has subsided. The second risk level indicates a moderate level of risk, such as persistent abnormalities or potential signs of malfunction in the conditions under which the food safety testing equipment operates. In this situation, the trajectory reverse run command is used to safely evacuate the food safety execution equipment and its held samples from the high-risk area, returning them to a pre-defined safety buffer zone. This helps protect the samples from further potential damage and provides space for troubleshooting. The third risk level indicates a high level of risk, such as a severe change in the conditions under which the food safety testing equipment operates, potentially causing immediate damage to the samples or equipment. In this case, the emergency braking command is triggered, the core of which is sending a torque control signal to the gripper controller to maintain maximum clamping force. This ensures that the food safety execution equipment can firmly hold the samples during an emergency stop, preventing accidental drop or damage, thereby minimizing losses. Level 4 risk represents the highest level of risk, typically indicating a serious system malfunction, safety hazard, or irreversible damage. The safety torque cut-off and brake locking command is a top-level safety intervention measure. It prevents any further motion commands from being executed by interrupting the normal trajectory interpolation cycle of the motion controller of the food safety actuator; simultaneously, it triggers the safety torque cut-off function of the servo drive, immediately removing the motor drive torque; and activates the electromagnetic brakes of each joint, mechanically locking the actuator in its current position.

[0049] It should be noted that this application enables refined and intelligent management of potential risks in the food safety testing process. Compared to single or extensive intervention strategies, the tiered intervention mechanism provided by this application allows the system to flexibly select the most appropriate response measures based on the actual severity of the risk. This not only significantly improves the safety of the food safety testing process and effectively avoids sample damage, equipment failure, or personnel injury caused by risk events, but also optimizes process efficiency. For example, for low-risk events, only a pause strategy is adopted, avoiding unnecessary complete shutdowns and resets, thereby reducing non-productive time; for high-risk events, the highest level of safety protection can be quickly activated to minimize losses. This differentiated intervention strategy enables food safety execution equipment to exhibit higher adaptability and robustness when facing changes in operating conditions, thereby ensuring the continuity, accuracy, and reliability of food safety testing tasks.

[0050] See Figure 3 , Figure 3 This is a schematic diagram of a food safety testing process control system provided in one embodiment of this application. The food safety testing process control system 300 includes: The acquisition module 310 is used to acquire the current operating status information of the food safety testing equipment and the current motion status information of the food safety execution equipment; The target instruction module 320 is used to determine whether to issue an instruction to the food safety execution device to perform sample processing tasks based on the current operating status information of the food safety testing equipment and the current motion status information of the food safety execution equipment. The differentiation module 330 is used to obtain the real-time position of the end of the food safety execution device in a preset space when a sample processing task instruction is issued to the food safety execution device, and to differentiate the stage of the action of the food safety execution device based on the real-time position. The judgment module 340 is used to acquire physical quantities that reflect the acceptance conditions of the food safety testing equipment, and to determine whether the acceptance conditions of the food safety testing equipment have changed based on the physical quantities. The physical quantities include the sampling port access control signal, internal pressure sensor data and self-test status register flag of the food safety testing equipment. The association module 350 is used to obtain change information when the acceptance conditions of the food safety testing equipment change, associate the change information with the stage of the food safety execution equipment's operation, obtain the association result, and classify the risk level of the change in acceptance conditions based on the association result to obtain the risk level classification result. The 360-degree determination module is used to determine and execute intervention strategies for food safety enforcement equipment actions based on the risk level classification results.

[0051] It should be noted that the information interaction and execution process between the above modules are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, which will not be repeated here.

[0052] It will be understood by those skilled in the art that all or some of the steps and systems in the methods disclosed above can be implemented as software, firmware, hardware, and suitable combinations thereof. Some or all of the physical components can be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit. Such software can be distributed on a computer-readable medium, which can include computer storage media (or non-transitory media) and communication media (or transient media). As is known to those skilled in the art, the term computer storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data). Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disc (DVD) or other optical disc storage, magnetic cartridges, magnetic tape, disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and is accessible to a computer. Furthermore, as is known to those skilled in the art, communication media typically include computer-readable instructions, data structures, program modules, or other data in modulated data signals such as carrier waves or other transmission mechanisms, and may include any information delivery medium.

[0053] The above provides a detailed description of the preferred embodiments of this application. However, this application is not limited to the above-described embodiments. Those skilled in the art can make various equivalent modifications or substitutions without departing from the spirit of this application. All such equivalent modifications or substitutions are included within the scope defined in this application.

Claims

1. A method for controlling the food safety testing process, characterized in that, include: Acquire the current operating status information of food safety testing equipment and the current motion status information of food safety execution equipment; Based on the current operating status information of the food safety testing equipment and the current motion status information of the food safety execution equipment, determine whether to issue a sample processing task instruction to the food safety execution equipment; When the instruction to perform sample processing task is issued to the food safety execution device, the real-time position of the end of the food safety execution device in the preset space is obtained, and the stage of the action of the food safety execution device is distinguished based on the real-time position; Acquire physical quantities reflecting the acceptance conditions of the food safety testing equipment, and determine whether the acceptance conditions of the food safety testing equipment have changed based on the physical quantities. The physical quantities include the sample inlet access control signal, internal pressure sensor data, and self-test status register flag of the food safety testing equipment. When the operating conditions of the food safety testing equipment change, change information is obtained. The change information is then correlated with the stage in which the food safety execution equipment is operating to obtain a correlation result. Based on the correlation result, the risk level of the change in the operating conditions is classified to obtain a risk level classification result. Based on the risk level classification results, intervention strategies are determined and implemented for the actions of the food safety enforcement equipment.

2. The method according to claim 1, characterized in that, The step of determining whether to issue a sample processing task instruction to the food safety execution device based on the current operating status information of the food safety testing equipment and the current motion status information of the food safety execution device includes: Based on the current operating status information of the food safety testing equipment and the current motion status information of the food safety execution equipment, it is determined whether the start-up conditions are met. The start-up conditions are met when the food safety testing equipment is in an idle state and the food safety execution equipment is in a standby position; otherwise, the start-up conditions are not met. When the activation conditions are met, an instruction to perform sample processing tasks is issued to the food safety execution device; If the activation conditions are not met, an instruction is sent to the food safety execution device not to execute the sample processing task.

3. The method according to claim 1, characterized in that, The step of obtaining the real-time position of the end effector of the food safety execution device in a preset space includes: Obtain the center of the sample inlet of the food safety testing equipment; A local coordinate system is established with the center of the sample inlet of the food safety testing equipment as the origin to obtain a preset space; The real-time position of the end effector of the food safety execution device is obtained by calculating its three-dimensional spatial coordinates in the preset space in real time.

4. The method according to claim 3, characterized in that, The step of distinguishing the stage of the food safety execution device's operation based on the real-time location includes: Calculate the absolute distance from the end of the food safety execution device to the center of the sample inlet based on the real-time location; When the absolute distance is greater than the preset stable transmission zone boundary threshold, it is determined to be in the stable transmission stage; When the absolute distance is between the preset deceleration approach zone boundary threshold and the preset smooth transmission zone boundary threshold, it is determined to be in the deceleration approach stage; When the absolute distance is less than the preset high-risk contact zone boundary threshold, it is determined to be a high-risk contact stage, wherein the preset high-risk contact zone boundary threshold is less than the preset deceleration approach zone boundary threshold, and the preset deceleration approach zone boundary threshold is less than the preset smooth transmission zone boundary threshold.

5. The method according to claim 1, characterized in that, The step of acquiring physical quantities reflecting the operating conditions of the food safety testing equipment, and determining whether the operating conditions of the food safety testing equipment have changed based on the physical quantities, includes: Obtain the model information of the food safety testing equipment; Based on the model information, load the corresponding interface description file; According to the interface description file, obtain the inlet access control signal, internal pressure sensor data and self-test status register flag of the food safety testing equipment; The system performs real-time correlation analysis on the inlet access signal, the internal pressure sensor data, and the self-test status register flag to obtain analysis results and determine whether the acceptance conditions of the food safety testing equipment have changed.

6. The method according to claim 5, characterized in that, The real-time correlation analysis of the sample inlet access signal, the internal pressure sensor data, and the self-test status register flag, to obtain the analysis results and determine whether the acceptance conditions of the food safety testing equipment have changed, includes: When the analysis results indicate that the inlet access signal is open, and the internal pressure sensor data shows a continuous upward trend within a preset time and exceeds the preset initial warning threshold, it is determined that the acceptance conditions of the food safety testing equipment have changed. When the analysis results indicate that the inlet access signal is open, the self-test status register flag is set, and the internal pressure sensor data simultaneously shows a change, it is determined that the acceptance conditions of the food safety testing equipment have changed. Otherwise, it is determined that the acceptance conditions for the food safety testing equipment have not changed.

7. The method according to claim 1, characterized in that, When the operating conditions of the food safety testing equipment change, change information is obtained. This change information is then correlated with the stage at which the food safety execution equipment is operating to obtain a correlation result. Based on the correlation result, the change in operating conditions is classified into risk levels to obtain risk level classification results, including: When the acceptance conditions of the food safety testing equipment change, obtain the timestamp and type of the change in the acceptance conditions of the food safety testing equipment; Align the occurrence timestamp with the time intervals of each stage of the food safety execution device's operation to determine the stage of the food safety execution device's operation when the conditions for accepting the food safety testing device change, and use the stage of the operation and the type of change in the conditions for accepting the food safety device together as the association result; The correlation results are mapped and searched in a preset two-dimensional classification and determination matrix to obtain the risk level classification results. The horizontal axis of the preset two-dimensional classification and determination matrix represents the stage of the operation of the food safety execution equipment, and the vertical axis represents the type of change in the acceptance conditions of the food safety testing equipment.

8. The method according to claim 1, characterized in that, The step of determining and implementing intervention strategies for the actions of the food safety enforcement equipment based on the risk level classification results includes: Based on the risk level classification results, a target intervention strategy is determined from multiple preset intervention strategies. The multiple preset intervention strategies include at least one of the following: trajectory pause command, trajectory reverse operation command, emergency braking command, safety torque cut-off and brake locking command. The target intervention strategy is transformed into control instructions for the actions of the food safety execution equipment and then issued for execution.

9. The method according to claim 1, characterized in that, The step of determining a target intervention strategy from multiple preset intervention strategies based on the risk level classification results includes: When the risk level classification result is the first risk level, the target intervention strategy is determined to be a trajectory pause instruction. The trajectory pause instruction is used to instruct the food safety execution device to remain hovered at the current spatial coordinate position and start a waiting timer. When the risk level classification result is the second risk level, the target intervention strategy is determined to be the trajectory reverse operation instruction. The trajectory reverse operation instruction is used to drive the food safety execution equipment to retreat back to the preset safety buffer along the original sampling path. When the risk level classification result is the third risk level, the target intervention strategy is determined to be an emergency braking command. The emergency braking command is used to send a torque control signal to the gripper controller to maintain the maximum clamping force. When the risk level classification result is the fourth risk level, the target intervention strategy is determined to be a safety torque cut-off and brake locking command. The safety torque cut-off and brake locking command is used to cut off the normal trajectory interpolation cycle of the motion controller of the food safety execution device, trigger the safety torque cut-off function of the servo driver, and activate the electromagnetic brakes of each joint. The first risk level is lower than the second risk level, the second risk level is lower than the third risk level, and the third risk level is lower than the fourth risk level.

10. A food safety testing process control system, characterized in that, include: The acquisition module is used to acquire the current operating status information of food safety testing equipment and the current motion status information of food safety execution equipment; The target instruction module is used to determine, based on the current operating status information of the food safety testing equipment and the current motion status information of the food safety execution equipment, whether to issue an instruction to the food safety execution equipment to perform sample processing tasks. The differentiation module is used to obtain the real-time position of the end of the food safety execution device in a preset space when the instruction to execute the sample processing task is issued to the food safety execution device, and to differentiate the stage of the action of the food safety execution device based on the real-time position; The judgment module is used to acquire physical quantities reflecting the acceptance conditions of the food safety testing equipment, and to determine whether the acceptance conditions of the food safety testing equipment have changed based on the physical quantities. The physical quantities include the sample inlet access control signal, internal pressure sensor data, and self-test status register flag of the food safety testing equipment. The association module is used to obtain change information when the acceptance conditions of the food safety testing equipment change, associate the change information with the stage of the food safety execution equipment's operation, obtain an association result, and classify the risk level of the change in acceptance conditions based on the association result to obtain a risk level classification result. The determination module is used to determine and execute intervention strategies for the actions of the food safety enforcement equipment based on the risk level classification results.

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