Servo position judgment and alarm processing method and system

Abstract

The invention relates to the technical field of automation control, in particular to a servo position judgment and alarm processing method and system. The processing method comprises the following steps: setting an array (SetPos [n]) of a plurality of target positions, wherein n is the number of the plurality of target positions; the current position (CurrentPos) of the servo is recorded in real time; in the operation process of the equipment, the difference value (delta Pos) between the current position and the target position of the servo is continuously monitored. According to the servo position judgment and alarm processing method and system, a plurality of target position arrays are set, the current servo position is monitored in real time, the position difference value can be continuously calculated in the equipment operation process, and real-time accurate monitoring of the servo position is achieved.

Description

Technical Field

[0001] The present invention relates to the field of automation control technology, and in particular to a servo position judgment and alarm processing method and system. Background Art

[0002] In the actual production process, due to the influence of various external factors, the servo system may have position deviation or abnormality, which not only affects the production efficiency, but also may cause equipment damage or safety accidents. For example: in CVD (chemical vapor deposition) equipment, the product silicon wafer is circulated through supporting automation equipment, and the automation equipment must have servo modules in the lateral and lifting directions. The servo modules and other components realize silicon wafer loading, coating, unloading, etc. through program logic and fast and orderly actions. During the operation of the equipment, there will be abnormalities such as component alarms and product failures. Once they occur, the equipment needs to be suspended. After handling the abnormalities, the equipment is started and the equipment can run immediately. However, in the past, the equipment would generate an alarm due to the servo failure to execute in place. At this time, manual operation is required, which is troublesome and time-consuming. Therefore, there is an urgent need for a method and system that can monitor the servo position in real time, detect abnormalities in time, and provide intelligent alarm processing to improve the reliability and production efficiency of the servo system. Summary of the invention

[0003] The present invention provides a servo position judgment and alarm processing method and system to solve the technical problem that the existing automation equipment cannot perform properly due to untimely servo position monitoring.

[0004] The technical solution of the present invention to solve the above technical problems is as follows:

[0005] On the one hand, a servo position determination and alarm processing method is provided, the processing method comprising:

[0006] Set an array of multiple target positions (SetPos[n]), where n is the number of the multiple target positions;

[0007] Record the current position of the servo in real time (CurrentPos);

[0008] During the operation of the device, the difference (ΔPos) between the current position of the servo and the target position is continuously monitored. The calculation formula of the difference (ΔPos) is:

[0009] ΔPos=∣CurrentPos-SetPos[n]∣;

[0010] When the device triggers a pause signal in the automatic operation state, the servo position at the rising edge of the pause signal is recorded (HistoryPos);

[0011] Set the position threshold (CmpRange). When restarting the device, compare the absolute value of the difference (ΔHistoryPos) between the position (HistoryPos) at the moment of stopping and the current position (CurrentPos) of the servo. The calculation formula of the absolute value of the difference (ΔHistoryPos) is:

[0012] ΔHistoryPos=∣HistoryPos-CurrentPos∣;

[0013] If ΔHistoryPos≤CmpRange, the system allows the device to continue running and move to the target position SetPos[n];

[0014] If ΔHistoryPos>CmpRange, the system generates an alarm signal to indicate that the servo position is abnormal.

[0015] Furthermore, the target position array (SetPos[n]) includes a material taking position, a transfer position and a material discharge position, and each position setting can be dynamically adjusted to meet different process requirements;

[0016] The current position of the servo (CurrentPos) is monitored in real time by a position sensor and fed back to the control system for real-time data processing and statistical analysis;

[0017] The pause signal comes from the physical pause button of the equipment or the pause button on the HMI, and is operated by the production line staff according to production needs or equipment alarm conditions. The current position (CurrentPos) of all servos is recorded on the rising edge of the pause signal.

[0018] Furthermore, the position threshold (CmpRange) is dynamically adjusted based on the equipment use environment, servo system accuracy requirements and historical operation data to adapt to the servo control requirements under different working conditions. The calculation method of the servo control is:

[0019] CmpRange=f(E+S+H), where E represents environmental parameters, S represents system accuracy requirements, and H represents historical operating data.

[0020] Furthermore, the processing method also includes that when the alarm signal is generated, the system automatically records the alarm time, specific location information and equipment status, and stores this information in a database for subsequent fault analysis and prevention.

[0021] Furthermore, the control system displays the current servo position (CurrentPos), the target position (SetPos[n]) and the alarm status through the user interface, monitors the device status in real time and intervenes, and the steps of monitoring the device status in real time and intervening include:

[0022] Collect and display real-time servo position information;

[0023] Calculate and display the difference between the target position and the current position;

[0024] Update and display system alarm status in real time.

[0025] Furthermore, the servo system includes a plurality of independently operated servo motors, each of which has its own target position array (SetPos[n]) and current position (CurrentPos) to achieve multi-point coordinated control within the device, and the calculation method of the coordinated control is:

[0026] ΔPos=|CurrentPos i -SetPos i [n]|, where i represents the different servo motor numbers.

[0027] Furthermore, when the servo system allows the device to continue to run and move to the array of the target position (SetPos[n]), a position pre-compensation algorithm is used to optimize the motion path of the servo motor and reduce jitter and oscillation. The calculation formula of the position pre-compensation algorithm is:

[0028]

[0029] Where PrePos[n] represents the estimated adjusted target position; K p is the proportionality coefficient used for the error of direct gain position control; K i is the integral coefficient, used to accumulate error; K d is the differential coefficient, which is used to reduce excessive response during position adjustment; ΔPos is the displacement difference between the current position and the target position.

[0030] Furthermore, the processing method also includes remote monitoring and diagnosis, and the steps of remote monitoring and diagnosis include:

[0031] Through the network communication module, the control system can send real-time monitoring data to the remote server, including the servo current position (CurrentPos), the array of target positions (SetPos[n]), the displacement difference (ΔPos), alarm information and device status;

[0032] The remote server supports the analysis of received data through cloud services, identifies potential problems and risks, and provides optimization suggestions or remote instructions to the control system;

[0033] Access the remote monitoring interface through a mobile device to view device status and execute the optimization suggestions or remote instructions to ensure system security.

[0034] On the other hand, a servo position determination and alarm processing system is provided, the processing system comprising:

[0035] A control unit, used to execute a servo position determination and alarm processing method, including calculating a position difference, determining a position abnormality, and generating an alarm signal;

[0036] Position sensor, used to monitor the current position of the servo in real time and feed back to the control unit;

[0037] A storage unit for storing target position arrays, historical position data, alarm records, and threshold settings;

[0038] Communication module, used to realize high-speed data transmission and real-time monitoring between control system and servo system;

[0039] Display module, used to display the current servo position, target position and alarm information, and provide a user interface for manual intervention and fault handling;

[0040] Safety protection module, which is automatically activated when an alarm signal is generated, stops the equipment from running and locks the faulty part to ensure the safety of equipment and operation;

[0041] The algorithm optimization module dynamically adjusts the position threshold (CmpRange) and servo operation strategy by analyzing historical data to improve the system response speed and the accuracy of position judgment;

[0042] The position recovery module is used to automatically restore the device to its working state before the device is paused when the servo position is manually confirmed to be within the threshold range after the device is paused, including reloading the target position array, correcting the position error, and allowing the device to continue running.

[0043] Furthermore, the storage unit comprises:

[0044] A target position array storage module is used to store multiple target positions so as to dynamically adjust according to different process requirements;

[0045] A historical position data storage module is used to store the position when the servo is paused to provide data required by the position recovery module;

[0046] Alarm record storage module, used to store alarm time and specific location information to help subsequent fault analysis and prevention;

[0047] A threshold setting module is used to store and adjust the position threshold to ensure the dynamic adaptability of the threshold;

[0048] The steps for displaying the current servo position, target position and alarm information include:

[0049] Collect and display real-time servo position information to provide intuitive monitoring;

[0050] Calculating and displaying the difference between the target position and the current servo position for determining the servo position state;

[0051] Update and display system alarm status in real time to detect and handle problems in a timely manner;

[0052] The step of dynamically adjusting the position threshold (CmpRange) and the servo operation strategy by analyzing historical data includes:

[0053] Collect historical location and alarm data to provide learning materials for the algorithm optimization module;

[0054] Calculate and optimize the position threshold (CmpRange) to adapt to different working environments and conditions;

[0055] Adjust the servo operation strategy to improve the system response speed to ensure efficient operation of the equipment;

[0056] The position recovery module is used for:

[0057] When the device is paused, the current position of all servo motors is automatically recorded (HistoryPos);

[0058] Provide a user interface to confirm whether the servo position is within the allowed threshold (CmpRange);

[0059] If it is confirmed that the absolute value of each difference (ΔHistoryPos) satisfies ΔHistoryPos≤CmpRange, the position recovery module loads the running state before the suspension, including the target position array (SetPos[n]) and the pre-compensation strategy (PrePos[n]);

[0060] Restore the device to run without manually restoring the servo to the corresponding position, which is used to reduce the number of operating steps.

[0061] The beneficial effects of the present invention are:

[0062] The servo position judgment and alarm processing method and system provided by the present invention can continuously calculate the position difference during the operation of the equipment by setting multiple target position arrays and monitoring the current servo position in real time, thereby realizing real-time and accurate monitoring of the servo position.

[0063] Furthermore, by introducing the position recording during pause and the position comparison mechanism during restart, the system can effectively identify the position anomalies that may occur during the equipment pause, thereby improving the sensitivity of fault detection. By adopting the dynamically adjusted position threshold, the system can adaptively adjust the judgment criteria according to the actual operating environment and historical data, thereby improving the reliability of the system. By designing a complete alarm processing flow, including automatically recording alarm information, starting the safety mechanism, etc., the system can not only remind the operator in time, but also automatically take safety measures, thereby minimizing the risk of equipment damage and safety accidents. This makes the present invention have significant advantages in improving the operating stability of the servo system, reducing production interruption time, and enhancing equipment safety, providing more reliable and efficient technical support for industrial automation production.

[0064] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention and implement it according to the contents of the specification, the following is a detailed description of the preferred embodiments of the present invention in conjunction with the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] Figure 1 is a flow chart of a servo position determination and alarm processing method according to an embodiment of the present invention;

[0066] Figure 2 FIG. 4 is a logic diagram of a servo position determination and alarm processing method in one embodiment of the present invention. DETAILED DESCRIPTION

[0067] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0068] The present invention provides the following preferred embodiments:

[0069] Embodiment 1

[0070] In order to solve the position deviation and abnormality problems that may occur in the servo system during operation, this embodiment further refines a servo position judgment and alarm processing method. This method achieves precise control of the servo system position and timely alarm of abnormal situations by setting a target position array, monitoring the current position in real time, calculating the position difference, and performing position comparison during the device pause and restart process.

[0071] like Figure 1 , Figure 2 As shown, the steps of the servo position judgment and alarm processing method include:

[0072] S101. Set an array of multiple target positions (SetPos[n]), where n is the number of the multiple target positions.

[0073] S102. Record the current position of the servo (CurrentPos) in real time.

[0074] S103. During the operation of the equipment, the difference (ΔPos) between the current servo position and the target position is continuously monitored. The calculation formula of the difference (ΔPos) is:

[0075] ΔPos=∣CurrentPos-SetPos[n]∣.

[0076] S104. When the device triggers a pause signal in the automatic operation state, the servo position (HistoryPos) at the rising edge of the pause signal is recorded.

[0077] S105, set the position threshold (CmpRange), when restarting the device, compare the absolute value of the difference (ΔHistoryPos) between the position at the moment of stopping (HistoryPos) and the current position (CurrentPos) of the servo, the calculation formula of the absolute value of the difference (ΔHistoryPos) is:

[0078] ΔHistoryPos=∣HistoryPos-CurrentPos∣.

[0079] S106. If ΔHistoryPos≤CmpRange, the system allows the device to continue running and move to the target position SetPos[n].

[0080] S107. If ΔHistoryPos>CmpRange, the system generates an alarm signal to indicate that the servo position is abnormal.

[0081] Specifically, this embodiment sets an array SetPos[n] containing multiple target positions, where n is the number of the target position. These target positions can be set according to actual production needs. For example, in an automated production line, they may include multiple workstations such as material picking positions, processing positions, and detection positions. By presetting these positions, the system can accurately control the servo system to move to the specified position during operation.

[0082] Furthermore, this embodiment uses a high-precision position sensor to record the current position CurrentPos of the servo system in real time. This real-time monitoring mechanism ensures that the system can grasp the accurate position information of the servo system at any time, and provides basic data support for subsequent position judgment and alarm processing.

[0083] During the operation of the equipment, the system continuously monitors the difference ΔPos between the current position of the servo and the target position. This difference is calculated by the formula ΔPos = |CurrentPos-SetPos[n]|. In this way, the system can evaluate the position accuracy of the servo system in real time and detect possible position deviations in a timely manner.

[0084] It is important to understand that when the device triggers a pause signal for some reason, the system will immediately record the position of the servo system when the pause is triggered. HistoryPos. This step is crucial for position judgment during subsequent restarts because it provides an important reference point for evaluating whether position abnormalities occurred during the pause.

[0085] Furthermore, this embodiment also introduces a position threshold CmpRange, which can be set according to the accuracy requirements of the system and the actual operation conditions. When the device restarts, the system compares the difference ΔHistoryPos between the position HistoryPos when it was paused and the current position CurrentPos, and the calculation formula is ΔHistoryPos = |HistoryPos-CurrentPos|.

[0086] It is understandable that by comparing ΔHistoryPos with CmpRange, the system can determine whether a position change beyond the allowable range has occurred during the pause period. If ΔHistoryPos is less than or equal to CmpRange, it means that the position change is within the allowable range, and the system will allow the device to continue running and control the servo system to move to the next target position SetPos[n]. On the contrary, if ΔHistoryPos is greater than CmpRange, the system will consider that an abnormal situation has occurred and immediately generate an alarm signal to prompt the operator that the servo position is abnormal.

[0087] The benefit of this embodiment is that by real-time monitoring and comparison of the position information of the servo system, combined with the preset target position and position threshold, the precise control of the servo system position and the rapid identification of abnormal situations are achieved. This method not only improves the positioning accuracy of the servo system, but also enhances the system's ability to respond to abnormal situations. At the same time, by performing position comparison during the equipment pause and restart process, the system can effectively prevent production problems caused by unexpected position changes during the pause period, and improve the stability of the production process. In addition, the implementation of this method does not require large-scale transformation of existing equipment, has good practicality and compatibility, and is suitable for various automated production lines using servo systems.

[0088] Embodiment 2

[0089] In order to solve the problem that the position control of the traditional servo system is not flexible enough in a complex process environment, this embodiment further optimizes the setting method of the target position array, and refines the monitoring method of the servo current position and the triggering mechanism of the pause signal. These improvements are intended to improve the adaptability and accuracy of the system so that it can better meet different process requirements and handle abnormal situations.

[0090] In this embodiment, the target position array SetPos[n] is designed to include at least three basic positions: material picking position, transfer position, and material discharge position. This design takes into account the basic needs of most automated production lines and covers the main links of material handling. It should be understood that the setting of each position is not fixed, but can be dynamically adjusted according to actual production needs. This flexibility allows the system to adapt to different process flows and product types, and the production mode can be quickly switched without frequent changes to hardware settings.

[0091] Furthermore, the system uses position sensors to monitor the current position CurrentPos of the servo in real time. These sensors may include but are not limited to photoelectric encoders, magnetic encoders or laser interferometers, etc., and are selected according to the specific application scenario and accuracy requirements. The position data collected by the sensor will be fed back to the control system in real time for data processing and statistical analysis. It can be understood that this real-time monitoring mechanism not only provides accurate position information, but also provides basic data support for the system's self-diagnosis and performance optimization.

[0092] The control system in this embodiment is equipped with data processing algorithms that can quickly analyze the received position data. These algorithms may include techniques such as Kalman filtering and moving average to eliminate signal noise and improve the reliability of position data. At the same time, the system will also perform real-time statistical analysis, such as calculating the standard deviation of position deviation, trend analysis, etc., in order to promptly detect potential system anomalies or performance degradation.

[0093] Furthermore, in terms of the triggering mechanism of the pause signal, this embodiment uses equipment abnormal state sensors to detect equipment failures or abnormal conditions. These sensors may include temperature sensors, vibration sensors, current sensors, etc., which can monitor various operating parameters of the equipment. When these parameters exceed the preset threshold, the sensor will generate a rising edge signal to trigger the system to pause. It should be noted that the system is specially designed with a signal processing circuit to ensure that this rising edge signal can be accurately captured to avoid false triggering due to signal jitter or interference.

[0094] It is understandable that this pause mechanism based on the rising edge signal has high sensitivity and reliability. It can trigger the pause when the abnormal situation just begins, rather than waiting until the problem deteriorates to an irreversible level. The purpose of this is to ensure that the system can promptly record the servo position at the time of the abnormality, providing an important basis for subsequent fault analysis and system recovery.

[0095] Furthermore, this embodiment also takes into account the handling of various abnormal situations. For example, if multiple sensors are detected to trigger abnormal signals at the same time, the system will determine the response order according to the preset priority rules. In addition, in order to prevent false alarms caused by sensor failures, the system also sets a cross-validation mechanism, that is, the pause signal will be triggered only when multiple related sensors detect abnormalities.

[0096] Through the design of this embodiment, the system can control the servo position more accurately and can quickly adapt to different process requirements. At the same time, the real-time monitoring and data analysis functions improve the reliability and maintenance efficiency of the system. The pause mechanism based on the abnormal state sensor further enhances the security and fault handling capability of the system. These improvements enable the entire servo system to show higher flexibility and stability when facing a complex and changeable production environment, thereby improving production efficiency and reducing fault downtime.

[0097] Embodiment 3

[0098] In order to solve the problem that the position threshold setting of the traditional servo system is not flexible enough under different working environments and conditions, this embodiment further optimizes the dynamic adjustment mechanism of the position threshold (CmpRange). It takes into account multiple factors such as the equipment use environment, the servo system accuracy requirements, and historical operation data, aiming to improve the adaptability and accuracy of the system under complex and changeable working conditions.

[0099] This embodiment introduces a composite function f to calculate the position threshold CmpRange, and its expression is CmpRange = f(E+S+H). The function comprehensively considers three main factors: environmental parameters E, system accuracy requirements S, and historical operation data H. It should be understood that this calculation method allows the system to dynamically adjust the position threshold according to actual conditions, thereby ensuring control accuracy while avoiding frequent false alarms or missed alarms caused by improper threshold settings.

[0100] Furthermore, environmental parameters E include external factors such as temperature, humidity, and vibration that affect the performance of the servo system. The system is equipped with a variety of environmental sensors, such as temperature sensors (PT100 or K-type thermocouples), humidity sensors (capacitive or resistive), vibration sensors (piezoelectric accelerometers), etc. These sensors collect environmental data in real time, and perform comprehensive calculations through preset weight coefficients to obtain the influencing factors on the position threshold.

[0101] Furthermore, the system accuracy requirement S reflects the different requirements for servo positioning accuracy in different process stages or product types. It is understandable that this parameter can be dynamically adjusted according to changes in production tasks. For example, in the precision machining stage, the S value may be set smaller to ensure higher positioning accuracy; while in the rough machining or fast moving stage, the S value may be increased accordingly to improve the response speed of the system.

[0102] Furthermore, the introduction of historical operation data H reflects the self-learning and self-adaptive capabilities of the system. This part of data includes position deviation statistics, alarm frequency, equipment failure records, etc. in the past period of time. The system will conduct in-depth analysis of this data and may use machine learning algorithms (such as support vector machines or neural networks) to predict the optimal position threshold. It should be noted that the system will regularly update these historical data to ensure that the calculation results can reflect the latest status of the equipment.

[0103] Furthermore, the specific form of the composite function f is a nonlinear function, such as weighted average, polynomial fitting or a more complex mathematical model. The design of this function needs to consider the mutual influence and weight distribution between various parameters. For example, in some cases, environmental factors may be more important than historical data, in which case function f will give E a higher weight.

[0104] Furthermore, in order to improve the stability of the system, this embodiment also introduces an adaptive adjustment mechanism. The system monitors the actual effect of the position threshold in real time. If frequent false alarms or missed alarms are found, the parameters or structure of the function f will be automatically fine-tuned to optimize the threshold calculation result. This adaptive mechanism enables the system to continuously learn and improve and adapt to various changes that may occur during long-term use.

[0105] Furthermore, this embodiment also takes into account the handling of emergencies. For example, when a dramatic change in environmental parameters is detected (such as a sudden rise in temperature), the system will immediately recalculate the position threshold and may trigger an early warning mechanism to alert the operator to potential abnormalities.

[0106] Through the design of this embodiment, the servo system can adjust the position threshold in real time according to the actual working conditions, which not only improves the adaptability of the system, but also enhances its working stability in complex environments. The dynamic threshold adjustment mechanism reduces the possibility of human setting errors and improves the automation level of the system. In addition, by integrating multiple data sources and adopting advanced computing models, the system can more accurately predict and control the servo position, thereby improving production efficiency while reducing the risk of equipment failure and production errors.

[0107] Embodiment 4

[0108] In order to solve the problem of incomplete alarm information recording and difficulty in fault analysis of the servo system, this embodiment further optimizes the alarm processing mechanism and refines the data recording and storage process, aiming to provide more comprehensive fault information and provide reliable data support for subsequent fault analysis and prevention.

[0109] Specifically, this embodiment introduces an automated data recording system while generating an alarm signal. The system can capture and record the exact time when the alarm occurs, the specific position information of the servo system, and the overall status of the device in real time. It should be understood that the time information not only includes the date and time, but is also accurate to the millisecond level to facilitate subsequent timing analysis. The position information includes the coordinate values ​​of the servo system in the three axes of X, Y, and Z, as well as the angle information. These data are provided in real time by a high-precision encoder to ensure the accuracy of the recording.

[0110] Furthermore, the equipment status records cover multiple aspects. Including but not limited to key parameters such as motor current, temperature, vibration frequency, load conditions, etc. The system uses a variety of sensors, such as Hall current sensors, thermocouples, acceleration sensors, etc., to monitor the equipment operation status in all directions. These data are collected through high-speed data acquisition cards (such as NIPXI-6363), and then stored in the database after preprocessing.

[0111] It is understandable that this embodiment uses a distributed database system to store this information. The main database uses a relational database (such as PostgreSQL) to store structured alarm records. At the same time, a time series database (such as InfluxDB) is used to store high-frequency sampled device status data. This dual database structure not only ensures the integrity of the data, but also improves the query efficiency of a large amount of time series data.

[0112] Furthermore, this embodiment also introduces data compression and hierarchical storage mechanisms. For data that needs to be frequently accessed in the short term, the system stores it in a high-speed cache; for historical data that is stored for a long time, a compression algorithm is used to store it to save storage space. The system will regularly perform data cleanup tasks, archive or delete expired data to maintain database performance.

[0113] Furthermore, in order to facilitate subsequent analysis, the system integrates a data analysis module. This module uses machine learning algorithms (such as random forests or support vector machines) to mine historical data and try to discover failure modes and potential related factors. These analysis results are regularly generated into reports and provided to maintenance personnel and engineers to help them develop preventive maintenance strategies.

[0114] The benefit of this embodiment is that through comprehensive and accurate data recording and storage, a solid data foundation is provided for fault diagnosis and preventive maintenance. System managers can quickly locate the source of the problem by querying these detailed records, thus shortening the fault diagnosis time. At the same time, the long-term accumulated data makes it possible to optimize equipment performance and predictive maintenance, which helps to improve the reliability and efficiency of the entire production system.

[0115] Embodiment 5

[0116] In order to solve the potential safety hazards and equipment damage problems that may be caused by servo system failure, this embodiment further optimizes the alarm processing mechanism and refines the startup process of the safety mechanism to improve the safety of the system and protect the equipment and operators to the maximum extent.

[0117] Specifically, this embodiment immediately triggers a series of safety measures when an abnormality is detected and an alarm signal is generated. First, the system generates a high-priority alarm signal. This signal not only contains standard alarm information, but also carries instructions to trigger the safety mechanism. It should be understood that this alarm signal will be sent simultaneously through multiple redundant channels to ensure that even if a communication channel fails, the safety instructions can still be communicated in a timely manner. The system uses an industrial-grade real-time communication protocol to ensure the real-time and reliability of signal transmission.

[0118] Furthermore, once an alarm signal is generated, the system will immediately execute a full shutdown procedure. This process adopts a graded shutdown strategy, and executes the corresponding shutdown sequence according to the characteristics and current status of different equipment. For some precision equipment that needs to stop slowly, the system will execute a soft shutdown procedure, gradually reducing the operating speed until it stops completely; while for equipment that can stop quickly, a hard shutdown procedure will be executed to directly cut off the power source. It can be understood that this graded shutdown strategy can not only ensure the safe stop of the equipment, but also minimize the damage caused by sudden shutdown.

[0119] Furthermore, during the shutdown process, the system will also activate the emergency brake device at the same time. These devices include electromagnetic brakes, hydraulic brake systems or pneumatic brake systems, which are selected according to the specific characteristics of the equipment. In order to improve reliability, the brake system usually adopts a redundant design to ensure that the equipment can stop safely even if a brake device fails.

[0120] Furthermore, after the shutdown is completed, the system will automatically lock the part where the fault occurred. This locking process includes two levels: physical locking and logical locking. Physical locking may involve activating mechanical locks or electromagnetic locks to prevent the equipment from accidentally starting or moving. Logical locking is controlled by software to disable related control interfaces and operation buttons to prevent personnel from operating them incorrectly. It should be noted that the locking mechanism is designed with multiple security protections, and only authorized maintenance personnel can unlock it.

[0121] Furthermore, this embodiment can also introduce intelligent zone isolation technology. The system will automatically divide the safety zone according to the nature and impact range of the fault. Under the premise of ensuring safety, the unaffected area is allowed to continue to operate, minimizing the production loss caused by downtime. This function is achieved through advanced zone control algorithms and safety PLC.

[0122] Furthermore, the system can also integrate an automatic alarm push function. Once the safety mechanism is triggered, the system will immediately send an alarm notification to the maintenance personnel through multiple channels (such as SMS, email, and mobile application push). The notification not only contains basic alarm information, but also provides preliminary fault diagnosis results and response suggestions to help maintenance personnel respond quickly. Through the design of this embodiment, the system can respond quickly when an abnormality is detected, minimizing safety risks. The automated safety mechanism reduces the risk of human misjudgment.

[0123] Embodiment 6

[0124] In order to solve the problem that the servo system monitoring is not intuitive and the operators find it difficult to find and handle abnormal situations in time, this embodiment further optimizes the user interface design and real-time monitoring function to provide a more intuitive and real-time system status display and provide operators with time for timely intervention.

[0125] Specifically, this embodiment designs a multifunctional user interface that integrates data acquisition, processing and visualization functions. The interface adopts a modular design, mainly including a real-time position display area, a position deviation calculation area and a system status display area. It should be understood that this modular design not only improves the readability of the interface, but also facilitates later maintenance and upgrades.

[0126] Furthermore, in the real-time position display area, the system continuously collects the position information of the servo motor through the encoder. The acquisition frequency can reach more than 1kHz, ensuring the real-time nature of the position data. The collected raw data is filtered to eliminate noise and then converted into engineering units. It is understandable that this conversion process takes into account factors such as mechanical transmission ratio and pitch to ensure that the displayed position information accurately reflects the actual workbench position. The position information is displayed in digital form, supplemented by dynamic graphic representation, so that the operator can intuitively grasp the current status of the equipment.

[0127] Furthermore, the position deviation calculation area calculates and displays the difference between the target position SetPos[n] and the current position CurrentPos in real time. This calculation process uses high-precision floating-point operations to ensure the accuracy of the calculation results. The difference is displayed in both absolute value and relative percentage form, which is convenient for operators to evaluate system performance from different angles. In addition, the system also introduces a trend chart function to display the trend of position deviation changes over a period of time, helping operators identify potential system drift or performance degradation problems.

[0128] Furthermore, in the system status display area, the alarm status of the system is updated and displayed in real time. This area can adopt a multi-level color coding system, with different colors representing different levels of alarms. For example, green indicates normal operation, yellow indicates warnings, and red indicates serious errors. Each alarm message is accompanied by a timestamp and a brief description, which makes it easy for operators to quickly locate the problem. In addition, the system also integrates an alarm history function, allowing operators to look back at past alarm messages, which helps analyze the long-term operation trend of the system.

[0129] Furthermore, this embodiment can also introduce an intelligent alarm filtering mechanism. The system uses a machine learning algorithm to analyze and classify alarm information in real time, filter out possible false alarms, and only display alarms that really need attention to the operator. This mechanism can effectively reduce the workload of operators and improve response efficiency.

[0130] Furthermore, in order to facilitate timely intervention by operators, this embodiment integrates a quick response function in the user interface. Operators can directly adjust the target position, modify control parameters, or perform emergency stop operations through the interface. These operations are transmitted to the control system through a secure communication protocol to ensure reliable execution of instructions. At the same time, the system can also set up operation authority management, so that only authorized personnel can perform specific high-risk operations.

[0131] The benefit of this embodiment is that by providing intuitive, real-time system status information, operators can more quickly discover and respond to potential problems. Integrated data processing and visualization functions make complex system status easy to understand, while intelligent alarm and rapid response functions improve system safety. This design not only improves the efficiency of daily operations, but also provides strong support for system optimization and fault diagnosis. Through this embodiment, the monitoring and intervention capabilities of the servo system are significantly enhanced, which helps to improve the stability of the entire production system.

[0132] Embodiment 7

[0133] In order to solve the problem of coordinated control of multiple servo motors in complex equipment, this embodiment further optimizes the structure and control algorithm of the servo system, aiming to achieve precise coordinated control of multiple points inside the equipment and improve the motion accuracy and stability of the overall system.

[0134] Specifically, this embodiment designs a multi-axis servo system, including multiple independently running servo motors. Each servo motor is equipped with an encoder and a servo driver. It should be understood that this configuration allows each motor to operate independently while being coordinated by a central controller. The system adopts a distributed control architecture, with each servo driver responsible for local position loop and speed loop control, while the central controller is responsible for coordinating the movement of each axis.

[0135] Furthermore, for each servo motor, the system maintains an independent target position array SetPos[n] and current position CurrentPos. The target position array stores predefined motion trajectory points, which may come from the processing path generated by the CAD / CAM system or input by the operator through the human-machine interface. The current position is read from the encoder in real time and obtained after filtering and compensation. It can be understood that this design allows the system to dynamically adjust the target position during operation to adapt to complex processing requirements or real-time process adjustments.

[0136] Furthermore, the system can use a multi-axis collaborative control algorithm to calculate the position deviation ΔPos of each motor, that is, the absolute difference between the current position and the target position. The calculation formula is ΔPos = |CurrentPos i -SetPos i [n]|, where i represents the different servo motor numbers. This calculation process is performed in the industrial controller, and the calculation frequency can reach more than 1kHz, ensuring that the system can respond to position changes in real time.

[0137] Furthermore, in order to deal with the mutual influence between multiple axes, the system also integrates the cross-coupling control CCC algorithm. This algorithm takes into account the dynamic coupling relationship between each axis and achieves more accurate trajectory tracking control by establishing a multi-dimensional error model. It should be noted that the parameters of the cross-coupling control CCC algorithm need to be obtained through system identification, and the system will perform the identification process regularly to adapt to changes in mechanical characteristics.

[0138] Furthermore, this embodiment can also introduce adaptive feedforward control. The system predicts the position deviation that may occur in each axis at the next moment by analyzing historical motion data, and compensates in advance. This method can effectively reduce the following error and improve the dynamic response performance of the system. The adaptive algorithm uses recursive least squares (RLS), which can update the model parameters in real time and adapt to the slow changes in system characteristics.

[0139] The benefit of this embodiment is that through precise multi-axis coordinated control, the system can achieve complex spatial trajectory tracking and precise positioning. The introduction of dynamic weight distribution and cross-coupling control enables the system to better adapt to different working conditions and processing requirements. Adaptive feedforward control further improves the dynamic performance of the system.

[0140] Embodiment 8

[0141] In order to solve the problems of communication reliability and real-time performance between the servo system and the control system, this embodiment further optimizes the design of the communication module and the data transmission strategy.

[0142] Specifically, this embodiment designs a multi-protocol compatible communication module that supports a variety of industrial communication protocols, including EtherCAT, PROFINET RT / IRT, Modbus TCP / IP, etc. This enables the system to flexibly adapt to different industrial environments and equipment requirements. The communication module uses a programmable logic controller as the core processing unit and is equipped with a high-performance Ethernet switching chip to ensure high bandwidth and low latency for data transmission. It should be understood that this multi-protocol support not only improves the compatibility of the system, but also facilitates future upgrades and expansions.

[0143] Furthermore, in terms of data transmission, the system adopts a layered data encapsulation strategy. The servo position data is first preprocessed locally, including filtering, unit conversion, and data compression. The preprocessed data is encapsulated into a standard industrial Ethernet frame and transmitted to the control system via the real-time Ethernet protocol. It can be understood that this preprocessing and encapsulation strategy not only reduces the network load, but also improves the reliability of the data. The system also introduces a cyclic redundancy check CRC mechanism to detect and correct data errors that may occur during transmission.

[0144] Furthermore, the control system uses a multi-level buffering mechanism when receiving data. First, the hardware level uses a FIFO (first-in-first-out) buffer to receive data, and then the software level uses a ring buffer to manage data. This design can effectively handle data bursts and network delays. After the received data is verified, it is processed by a special parsing algorithm. The parsing algorithm uses parallel computing technology and can process data from multiple servo axes at the same time, significantly improving the data processing speed.

[0145] Furthermore, this embodiment also introduces a dynamic bandwidth allocation mechanism. The system dynamically adjusts the data transmission priority and bandwidth allocation according to the importance and current working status of different servo axes. For example, for servo axes that are performing critical actions, the system will allocate higher transmission priority and larger bandwidth to ensure the real-time performance of data. This mechanism is implemented through software-defined network SDN technology, which can dynamically adjust the network configuration without interrupting communication.

[0146] Furthermore, in terms of real-time status monitoring, the system adopts a distributed monitoring architecture. Each servo drive is equipped with a local monitoring module, which is responsible for collecting parameters such as motor current, speed, and temperature. These parameters are transmitted to the central control system in real time through the above-mentioned communication channel. The central system uses data analysis algorithms to process these data and evaluate the working status of each servo axis in real time. It should be noted that the system also integrates predictive maintenance functions, which predict possible failures by analyzing historical data and current status, and arrange maintenance work in advance.

[0147] Furthermore, in order to improve the fault tolerance of the system, this embodiment implements a communication redundancy design. The system adopts a dual-ring network topology, and each communication node is connected to two independent network loops. When the main channel fails, the system can seamlessly switch to the backup channel to ensure the continuity of communication. This greatly improves the reliability of the system and is particularly suitable for industrial environments that require high availability.

[0148] The benefit of this embodiment is that, through multi-protocol support and optimized data transmission strategy, the system can achieve more reliable and real-time servo position data transmission. Dynamic bandwidth allocation and distributed monitoring architecture improve the flexibility and response speed of the system. The predictive maintenance function helps to reduce equipment downtime and improve production efficiency. Through this embodiment, the communication performance between the servo system and the control system is significantly improved, providing a solid foundation for precision control and intelligent manufacturing.

[0149] Embodiment 9

[0150] In order to solve the challenges of position accuracy control, real-time monitoring, safety protection, and system optimization of the servo system in a complex industrial environment, this embodiment proposes an overall architecture and functional modules of a servo position judgment and alarm processing system.

[0151] Specifically, this embodiment designs an integrated servo position judgment and alarm processing system, which is composed of multiple functional modules, and each module realizes data exchange and collaborative work through a high-speed bus. The core of the system is the control unit, which uses an industrial-grade embedded processor and is equipped with a real-time operating system (such as VxWorks). It should be understood that this configuration not only ensures the real-time performance of the system, but also provides sufficient computing resources to support complex control algorithms and data analysis.

[0152] Furthermore, the position sensor module uses a high-precision photoelectric encoder (such as Renishaw's RESOLUTE series) with a resolution of nanometers. The sensor is connected to the control unit via a high-speed serial interface (such as BiSS-C) to ensure real-time transmission and low latency of position data. The system also integrates multi-sensor fusion technology, combining the data of the acceleration sensor and gyroscope, and further improves the accuracy of position estimation through the Kalman filter algorithm.

[0153] Furthermore, the storage unit adopts a hierarchical storage architecture, including high-speed SRAM for temporary data caching and large-capacity flash memory for storing historical data and system parameters. The system is also equipped with an industrial-grade solid-state drive for long-term data storage and logging. This hierarchical storage design not only meets the needs of real-time data processing, but also provides a reliable data foundation for long-term data analysis and system optimization. The storage unit uses RAID technology to ensure data integrity and reliability.

[0154] Furthermore, the communication module uses an industrial Ethernet controller that supports multiple protocols, including EtherCAT, PROFINET and other mainstream industrial communication protocols. The communication module also integrates the time-sensitive network TSN technology to ensure deterministic communication in complex network environments. The system adopts a redundant communication link design, which can automatically switch to the backup channel when the main channel fails, thus improving the reliability of communication.

[0155] Furthermore, the display module uses a high-resolution industrial touch screen (such as Pro-face's SP5000 series) that supports multi-touch and gesture operation. The interface design follows the principles of ergonomics and uses an intuitive graphical interface to display system status and alarm information. The system also supports remote access, and operators can monitor and control the system in real time through mobile devices. It should be noted that the remote access function requires multiple encryption and identity authentication mechanisms to ensure system security.

[0156] Furthermore, the safety protection module adopts a redundant design, including hardware safety relays and software safety monitoring. When the system detects an abnormality, the safety protection module can respond in milliseconds, cut off the power supply of the servo drive, and activate the mechanical brake system. The system also integrates a safety PLC to achieve functional safety that meets the SIL3 level. In addition, the safety protection module also has a self-diagnosis function, which regularly checks its own working status to ensure the reliability of the safety function.

[0157] Furthermore, the algorithm optimization module uses machine learning technology to continuously optimize system performance. The module uses a deep neural network DNN to analyze historical operating data and automatically adjust the position threshold CmpRange and servo control parameters. The system uses a reinforcement learning algorithm to continuously optimize the control strategy by simulating different working scenarios. It is important to understand that this adaptive optimization capability enables the system to adapt to different working conditions and load changes to maintain optimal performance.

[0158] Furthermore, the system also includes a position recovery module, which is used to automatically restore the device to the working state before the pause when the servo position is manually confirmed to be within the threshold range after the device is paused, including reloading the target position array, correcting the position error, and allowing the device to continue to run. The position recovery module is used to: automatically record the current position (HistoryPos) of all servo motors after the device is paused; provide a user interface to confirm whether the servo position is within the allowable threshold (CmpRange); if it is confirmed that the absolute value of each difference (ΔHistoryPos) satisfies ΔHistoryPos≤CmpRange, the position recovery module loads the operating state before the pause, including the target position array (SetPos[n]) and the pre-compensation strategy (PrePos[n]); immediately and automatically restore the device operation without the operator manually restoring the servo to the corresponding position, which is used to reduce the operation steps.

[0159] Furthermore, this embodiment can also introduce a predictive maintenance function. The system analyzes the servo motor's current, temperature, vibration and other multi-dimensional data, combined with machine learning algorithms, to predict possible failures. This predictive maintenance strategy can significantly reduce the unplanned downtime of the equipment and improve the overall availability of the system.

[0160] Furthermore, in order to cope with complex industrial environments, the system also integrates an environmental adaptability module. This module contains a temperature compensation algorithm that can automatically adjust the position control parameters according to changes in ambient temperature to offset the impact of thermal expansion on accuracy. At the same time, the system also uses active vibration suppression technology, which effectively reduces the impact of external vibration on positioning accuracy through piezoelectric actuators and real-time control algorithms.

[0161] The benefit of this embodiment is that, by integrating multiple advanced technologies and functional modules, a highly intelligent and reliable servo position judgment and alarm processing system is realized. High-precision position sensing and multi-sensor fusion technology provide the basis for precise positioning; multi-level security protection mechanisms ensure the safety of system operation.

[0162] Embodiment 10

[0163] In order to solve the challenges of data management, real-time display and adaptive optimization of servo systems in complex industrial environments, this embodiment further refines the structural design of the storage unit, the implementation method of the display function and the system self-optimization strategy to improve the data processing efficiency of the system, the intuitiveness of information presentation and the adaptability of the control strategy.

[0164] Specifically, this embodiment designs a multi-level storage architecture, including a target position array storage module, a historical position data storage module, an alarm record storage module, and a threshold setting module. The target position array storage module uses high-speed SRAM, combined with cache prefetch technology, to achieve fast access to multiple target positions. The module supports dynamic array management and can update the target position sequence in real time according to task requirements. The historical position data storage module uses a large-capacity flash memory and a circular buffer structure to ensure that the position information can be quickly recorded and restored when the servo is paused. It should be understood that this design not only improves the response speed of the system, but also enhances the power-off protection capability.

[0165] Furthermore, the alarm record storage module uses a time series database to store alarm time and specific location information. This database structure optimizes the storage and query efficiency of time series data, facilitating subsequent data analysis and trend prediction. The threshold setting module adopts a parametric design to store key parameters such as the position threshold CmpRange in an independent non-volatile memory, supporting online adjustment and power-off protection. It can be understood that this modular storage design not only improves the flexibility of data management, but also provides a reliable data foundation for the adaptive optimization of the system.

[0166] Furthermore, in terms of display function implementation, the system adopts multi-threaded parallel processing technology. The acquisition of real-time servo position information is processed by an independent high-priority thread, and the position data is directly transferred to the display buffer through DMA (direct memory access) technology, which minimizes CPU intervention and ensures the real-time nature of data acquisition. The calculation of the difference between the target position and the current position is completed by a dedicated digital signal processor, which uses its parallel computing capabilities to achieve high-speed, low-latency difference calculation. The update of system status and alarm information adopts an event-driven mechanism, which triggers display updates only when the status changes, reducing unnecessary refresh operations and improving system efficiency.

[0167] Furthermore, the display interface adopts a layered design, uses OpenGL ES for graphics rendering, and supports hardware acceleration. Interface elements use vector graphics to ensure clear display at different resolutions. The system also implements an adaptive layout algorithm that can automatically adjust the interface layout according to the characteristics of the display device, improving the system's versatility and user experience. It should be noted that the system supports multi-language switching and custom themes to meet the needs of different users.

[0168] Furthermore, in terms of the system self-optimization strategy, this embodiment implements a complex data analysis and machine learning framework. The collection of historical location and alarm data adopts a distributed data acquisition system that supports high-concurrency data writing and reading. The sliding window algorithm is used in the data preprocessing stage for data smoothing and outlier detection. The optimization of the position threshold CmpRange adopts a hybrid method of genetic algorithm combined with particle swarm optimization PSO, which can achieve a balance between global optimality and local optimality. The fitness function of the algorithm comprehensively considers multiple factors such as positioning accuracy, response speed and false alarm rate.

[0169] Furthermore, the adjustment of the servo operation strategy adopts reinforcement learning methods, such as the deep Q network DQN algorithm. The system continuously optimizes the control strategy by simulating different working scenarios to improve the response speed and stability of the system. In order to cope with the complexity of the actual industrial environment, the system also introduces transfer learning technology, which can quickly adapt the strategies learned in the simulation environment to the actual working environment.

[0170] Furthermore, this embodiment also implements an adaptive filter for dynamically adjusting the filter parameters of the position signal. The filter is based on the Kalman filter algorithm and can adjust the filter parameters in real time according to the changes in the system state and environmental noise, thereby minimizing system delay while ensuring the accuracy of the position signal.

[0171] The benefit of this embodiment is that by optimizing the storage structure, realizing efficient display functions and introducing advanced self-optimization strategies, the performance and adaptability of the servo position judgment and alarm processing system are greatly improved. The multi-level storage architecture and efficient data management mechanism provide a reliable data foundation for the system; the real-time and intuitive display function enhances the operability and monitoring effect of the system; and the self-optimization strategy based on machine learning enables the system to continuously adapt to complex working environments and continuously improve its performance. Through this embodiment, the data processing capability, user interaction experience and adaptive performance of the servo system are significantly improved, providing strong technical support for modern industrial automation and intelligent manufacturing.

[0172] The above embodiments further illustrate the purpose, technical solutions and beneficial effects of the present invention. It should be understood that the above are only specific implementation methods of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made on the basis of the technical solutions of the present invention should be included in the scope of protection of the present invention.

Claims

1. A servo position judgment and alarm processing method, characterized in that: The processing method comprises: Set an array of multiple target positions (SetPos[n]), where n is the number of the multiple target positions; Record the current position of the servo in real time (CurrentPos); During the operation of the device, the difference (ΔPos) between the current position of the servo and the target position is continuously monitored. The calculation formula of the difference (ΔPos) is: ΔPos=∣CurrentPos-SetPos[n]∣; When the device triggers a pause signal in the automatic operation state, the servo position at the rising edge of the pause signal is recorded (HistoryPos); Set the position threshold (CmpRange). When restarting the device, compare the absolute value of the difference (ΔHistoryPos) between the position (HistoryPos) at the moment of stopping and the current position (CurrentPos) of the servo. The calculation formula of the absolute value of the difference (ΔHistoryPos) is: ΔHistoryPos=∣HistoryPos-CurrentPos∣; If ΔHistoryPos≤CmpRange, the system allows the device to continue running and move to the target position SetPos[n]; If ΔHistoryPos>CmpRange, the system generates an alarm signal to indicate that the servo position is abnormal.

2. The servo position determination and alarm processing method according to claim 1, characterized in that: The target position array (SetPos[n]) includes the material taking position, transfer position and material discharge position, and each position setting can be dynamically adjusted to meet different process requirements; The current position of the servo (CurrentPos) is monitored in real time by a position sensor and fed back to the control system for real-time data processing and statistical analysis; The pause signal comes from the physical pause button of the equipment or the pause button on the HMI, and is operated by the production line staff according to production needs or equipment alarm conditions. The current position (CurrentPos) of all servos is recorded on the rising edge of the pause signal.

3. The servo position determination and alarm processing method according to claim 1, characterized in that: The position threshold (CmpRange) is dynamically adjusted based on the equipment use environment, servo system accuracy requirements and historical operation data to adapt to the servo control requirements under different working conditions. The calculation method of the servo control is: CmpRange=f(E+S+H), where E represents environmental parameters, S represents system accuracy requirements, and H represents historical operating data.

4. The servo position determination and alarm processing method according to claim 1, characterized in that: The processing method also includes that when the alarm signal is generated, the system automatically records the alarm time, specific location information and equipment status, and stores this information in a database for subsequent fault analysis and prevention.

5. The servo position determination and alarm processing method according to claim 1, characterized in that: The control system displays the current servo position (CurrentPos), the target position (SetPos[n]) and the alarm status through the user interface, monitors the device status in real time and intervenes. The steps of monitoring the device status in real time and intervening include: Collect and display real-time servo position information; Calculate and display the difference between the target position and the current position; Update and display system alarm status in real time.

6. The servo position determination and alarm processing method according to claim 3, characterized in that: The servo system includes multiple independently operated servo motors, each of which has its own target position array (SetPos[n]) and current position (CurrentPos) to achieve multi-point collaborative control within the device. The calculation method of the collaborative control is: ΔPos=|CurrentPos i -SetPos i [n]|, where i represents the different servo motor numbers.

7. The servo position determination and alarm processing method according to claim 6, characterized in that: When the servo system allows the device to continue to run and move to the array of the target position (SetPos[n]), a position pre-compensation algorithm is used to optimize the motion path of the servo motor and reduce jitter and oscillation. The calculation formula of the position pre-compensation algorithm is: Where PrePos[n] represents the estimated adjusted target position; K p is the proportionality factor used for the error of direct gain position control; K i is the integral coefficient, used to accumulate error; K d is the differential coefficient, which is used to reduce excessive response during position adjustment; ΔPos is the displacement difference between the current position and the target position.

8. The servo position determination and alarm processing method according to claim 1, characterized in that: The processing method further includes remote monitoring and diagnosis, and the steps of remote monitoring and diagnosis include: Through the network communication module, the control system can send real-time monitoring data to the remote server, including the servo current position (CurrentPos), the array of target positions (SetPos[n]), the displacement difference (ΔPos), alarm information and device status; The remote server supports the analysis of received data through cloud services, identifies potential problems and risks, and provides optimization suggestions or remote instructions to the control system; Access the remote monitoring interface through a mobile device to view device status and execute the optimization suggestions or remote instructions to ensure system security.

9. A servo position determination and alarm processing system, characterized in that: The processing system comprises: A control unit, used to execute a servo position determination and alarm processing method, including calculating a position difference, determining a position abnormality, and generating an alarm signal; Position sensor, used to monitor the current position of the servo in real time and feed back to the control unit; A storage unit for storing target position arrays, historical position data, alarm records, and threshold settings; Communication module, used to realize high-speed data transmission and real-time monitoring between control system and servo system; Display module, used to display the current servo position, target position and alarm information, and provide a user interface for manual intervention and fault handling; Safety protection module, which is automatically activated when an alarm signal is generated, stops the equipment from running and locks the faulty part to ensure the safety of equipment and operation; The algorithm optimization module dynamically adjusts the position threshold (CmpRange) and servo operation strategy by analyzing historical data to improve the system response speed and the accuracy of position judgment; The position recovery module is used to automatically restore the device to its working state before the device is paused when the servo position is manually confirmed to be within the threshold range after the device is paused, including reloading the target position array, correcting the position error, and allowing the device to continue running.

10. The servo position determination and alarm processing system according to claim 9, characterized in that: The storage unit comprises: A target position array storage module is used to store multiple target positions so as to dynamically adjust according to different process requirements; A historical position data storage module is used to store the position when the servo is paused to provide data required by the position recovery module; Alarm record storage module, used to store alarm time and specific location information to help subsequent fault analysis and prevention; A threshold setting module is used to store and adjust the position threshold to ensure the dynamic adaptability of the threshold; The steps for displaying the current servo position, target position and alarm information include: Collect and display real-time servo position information to provide intuitive monitoring; Calculating and displaying the difference between the target position and the current servo position for determining the servo position state; Update and display system alarm status in real time to detect and handle problems in a timely manner; The step of dynamically adjusting the position threshold (CmpRange) and the servo operation strategy by analyzing historical data includes: Collect historical location and alarm data to provide learning materials for the algorithm optimization module; Calculate and optimize the position threshold (CmpRange) to adapt to different working environments and conditions; Adjust the servo operation strategy to improve the system response speed to ensure efficient operation of the equipment; The position recovery module is used for: When the device is paused, the current position of all servo motors is automatically recorded (HistoryPos); Provide a user interface to confirm whether the servo position is within the allowed threshold (CmpRange); If it is confirmed that the absolute value of each difference (ΔHistoryPos) satisfies ΔHistoryPos≤CmpRange, the position recovery module loads the running state before the suspension, including the target position array (SetPos[n]) and the pre-compensation strategy (PrePos[n]); Restore the device to run without manually restoring the servo to the corresponding position, which is used to reduce the number of operating steps.

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