A method for maintaining and managing orthopedic surgery robot equipment based on digital twinning

Abstract

This invention relates to the field of equipment maintenance technology, specifically to a maintenance and management method for orthopedic surgical robots integrating digital twins. The method involves comparing motion and force characteristics to classify joints into different levels, generating a set of work indicator markers, analyzing the digital twin model to identify force concentration effects, establishing an inspection sequence, comparing angular displacement and lead screw travel direction according to the sequence to mark abnormal offset sections, then comparing friction and torque changes within the sections to identify wear-prone sections, verifying torque and clamping pressure changes to determine the repair scope, and forming equipment maintenance management results. This invention, by synchronously comparing motor speed, angular displacement, and torque data in real time, can identify joint motion synchronicity and assess component health, analyze the coupling relationship between motion paths and friction, and capture wear and force concentration effects, thereby generating accurate inspection sequences and monitoring sections, effectively improving detection accuracy and maintenance efficiency, and reducing equipment downtime.

Description

Technical Field

[0001] This invention relates to the field of equipment maintenance technology, and in particular to a method for maintaining and managing orthopedic surgical robot equipment that integrates digital twins. Background Technology

[0002] The field of equipment maintenance technology encompasses the identification of the status of various electromechanical equipment during its service life, fault prevention, and maintenance planning. The core of this technology lies in the continuous observation and recording of equipment structural components, operational behavior, and key parameters to form traceable maintenance data, thereby enabling systematic management of the entire equipment operation process. This field typically involves the collection of equipment operation data, quantitative description of equipment status, decomposition and evaluation of equipment lifecycles, and configuration of maintenance strategies based on specific maintenance criteria. Its overall system covers continuous technical content from equipment status confirmation to maintenance sequence planning and execution process management, using basic information such as structural characteristics, performance change trends, and operational stability as the basis for technical judgment to complete the construction of the maintenance management process.

[0003] Among them, the maintenance and management method of orthopedic surgical robot equipment integrating digital twins refers to a management method that collects, compares, and analyzes the joint motion trajectory, drive unit load changes, structural component wear characteristics, and sensor output parameters of the robot during use, based on the synchronous correlation between the physical structure of the orthopedic surgical robot and its virtual corresponding model. Its technical aspects include establishing virtual mapping models of key robot components for real-time status correspondence, recording joint angle change rate curves and repetitive positioning offsets for dynamic consistency verification, identifying the force change law of drive units to form a basis for component health, and comparing the differences in movement between the virtual model and the physical equipment to complete the equipment status determination. It mainly relies on basic means such as data collection, modeling association, calculation relationship construction, and operational behavior comparison to complete the formation of maintenance and management methods.

[0004] Existing technologies cannot capture the dynamic changes of equipment in real time during use, relying mainly on periodic inspections and data recording. This results in an inability to fully reflect potential problems that may arise during equipment operation. The lack of continuous tracking and in-depth analysis of key components throughout the entire service life of the equipment often leads to the inability to accurately identify subtle signs of failure or trends of change. Consequently, potential faults in equipment operation cannot be detected in a timely manner. In traditional maintenance models, the assessment of equipment health status is usually based on static data and cannot be effectively adjusted according to real-time operational feedback. This results in maintenance decisions that do not fully match the actual operating status, thereby affecting the operational stability and maintenance efficiency of the equipment. Summary of the Invention

[0005] To address the technical problems existing in the prior art, this invention provides a method for maintaining and managing orthopedic surgical robot equipment that integrates digital twins. The technical solution is as follows:

[0006] A method for maintaining and managing orthopedic surgical robot equipment integrating digital twins, comprising the following steps:

[0007] S1: Acquire joint motor speed, angular displacement and torque data and align timing, correlate and compare speed and angular displacement direction and rhythm, identify synchronization or mismatch state, analyze force coordination with torque changes, classify state levels, organize by joint number, and generate a joint working sign mark set;

[0008] S2: Based on the joint number and maintenance level in the joint working sign mark set, extract the lead screw stroke, guide rail friction and clamping pressure data, analyze the stroke and friction trends, and verify the force concentration effect with the pressure at the same position point. Sort by recurrence frequency and level to generate an inspection sorting sequence.

[0009] S3: Based on the inspection sequence, extract angular displacement and lead screw travel data, divide the angular displacement into segments according to the angular displacement time sequence, record the correspondence between the start and end points, compare the angular displacement direction with the travel direction, mark the inconsistent segments, and generate a set of maintenance monitoring segments.

[0010] S4: Based on the start and end boundaries of each monitoring segment in the set of maintenance monitoring segments, set a data window, extract friction changes and torque fluctuations within the window, compare the change directions of adjacent points to identify continuous and consistent segments, mark the start and end positions, and generate a wear trend entry sequence.

[0011] As a further aspect of the present invention, the joint working sign marker set includes a motion mismatch time index, a force abnormality feature descriptor, and a joint health level classification label. The inspection sorting sequence specifically includes the coordinates of the force concentration location, the statistical value of the frequency of abnormal recurrence, and the inspection priority sequence table. The maintenance monitoring section set includes the start and end boundaries of the offset abnormal section, the difference item of angular displacement travel direction, and the segmented trajectory monitoring identifier. The wear trend entry sequence specifically refers to the wear attention time window, the record of the same direction change of friction torque, and the feature code of the resistance evolution trend.

[0012] As a further aspect of the present invention, the step of obtaining the joint working sign marker set is as follows:

[0013] S101: Acquire the rotational speed data of the joint drive motor, the angular displacement data of the joint encoder, and the output value of the torque sensor of the orthopedic surgical robot. Align the three data items according to the time recording points. Determine the directional consistency of the rotational speed change and angular displacement change at the same time recording point. Then, determine the corresponding directional association markers based on the rising, falling, and fluctuating changes shown by the torque sensor output at the same time position.

[0014] S102: Based on the direction association identifier, call the joint drive motor rotation speed data and the joint encoder angular displacement data, divide the time recording point corresponding to the direction association identifier into several continuous segments, and call the torque sensor output value for each segment to judge the force performance, classify the force coordination and force abnormality within the segment range, and generate force performance partitions.

[0015] S103: Based on the stress performance partition, call the coordinated and abnormal sections within the stress performance partition for each joint number, mark the coordinated sections as stable, mark some abnormal sections as attention, mark continuous abnormal sections as maintenance, and organize them into maintenance records according to the joint number order to generate a joint working sign mark set.

[0016] As a further aspect of the present invention, the step of obtaining the inspection sorting sequence is as follows:

[0017] S201: Obtain the joint number and maintenance level recorded in the joint working sign marker set; extract the lead screw component stroke position feedback, guide rail component friction resistance change data and end effector clamping mechanism pressure feedback from the digital twin model of the orthopedic surgical robot according to the joint number; analyze the coupling relationship between the lead screw stroke position and guide rail friction change along the joint motion path; and generate a coupling relationship mapping.

[0018] S202: Based on the coupling relationship mapping, determine whether the screw stroke position and the guide rail friction change show a synchronous increasing or decreasing trend, and verify the increasing or decreasing trend with the pressure change at the same position point of the end effector clamping mechanism pressure feedback, determine whether there is a force concentration effect, and generate a force concentration effect identifier.

[0019] S203: Based on the stress concentration effect identifier, the recurrence frequency of the stress concentration effect is mapped to the maintenance level, and the inspection sequence is formed according to the joint number. An inspection sorting sequence is established and an inspection sorting sequence is generated.

[0020] As a further aspect of the present invention, the step of obtaining the set of maintenance monitoring sections is as follows:

[0021] S301: Based on the inspection sequence and corresponding joint number recorded in the inspection sorting sequence, obtain the joint encoder angular displacement data and the lead screw assembly stroke position feedback. Within the joint corresponding range of the inspection sorting mapping, divide the angular displacement change sequence into angular segments, record the starting and ending angular displacement values ​​of each segment, and correspondingly obtain the lead screw stroke position to obtain the angular displacement stroke mapping set.

[0022] S302: Call the angular displacement stroke mapping set, compare the direction of angular displacement change in each angular segment with the direction of movement of the lead screw stroke position segment by segment, and determine whether they are consistent. If the directions are inconsistent, mark the segment as an offset abnormal segment, and record the start and end boundaries of the offset segment and the corresponding joint number to generate an offset abnormal segment set.

[0023] S303: Based on the set of offset anomaly segments, organize the offset anomaly segments corresponding to each joint number, and arrange them in the order of the inspection sorting sequence according to the joint number and the offset anomaly frequency to generate a set of maintenance monitoring segments.

[0024] As a further aspect of the present invention, the step of obtaining the wear trend entry sequence is as follows:

[0025] S401: Based on the start and end boundaries of the monitoring sections recorded in the set of maintenance monitoring sections, obtain the friction resistance change data of the guide rail assembly and the output value of the torque sensor, set the start and end boundaries of each monitoring section as the data interception window, and extract the friction evolution data and torque fluctuation data in each window along the time sequence dimension to obtain the friction torque data set.

[0026] S402: Call the friction torque data group, compare the change direction of friction evolution data and torque fluctuation data in adjacent time points within each time window, identify the time period in which the change direction is consistent within multiple consecutive time points, record it as wear concern segment, and mark the start and end positions to obtain the wear concern segment set;

[0027] S403: Based on the set of wear-concerned segments, arrange all wear-concerned segments in the order of monitoring segments, classify each wear-concerned segment according to its start and end positions, and generate an entry sequence by the order of all wear-concerned segments to obtain a wear trend entry sequence.

[0028] As a further aspect of the present invention, the method further includes:

[0029] S5: Based on the start and end positions of each wear concern segment recorded in the wear trend entry sequence, call up the torque and clamping pressure data, compare the directional continuity and consistency of the two at adjacent time points, determine the maintenance level range, and record the joint number and component identification to obtain the equipment maintenance management results;

[0030] The equipment maintenance management results include the scope of the maintenance level, the index of the names of faulty transmission components, and the maintenance details associated with the monitoring section.

[0031] As a further aspect of the present invention, the step of obtaining the equipment maintenance management results is as follows:

[0032] S501: Based on the start and end positions of each wear concern segment recorded in the wear trend entry sequence, obtain the torque sensor output value and the end effector clamping mechanism pressure feedback data. Within the time range covered by the wear concern segment, extract the torque change direction and clamping pressure change direction at each time point in chronological order to obtain the torque and pressure change direction set.

[0033] S502: Call the set of torque and pressure change directions, compare the torque change direction with the clamping pressure change direction at each time point, determine whether the change direction at adjacent time points remains continuous and consistent, and record the time period of consistent direction to obtain a set of continuous and consistent time periods.

[0034] S503: Based on the set of continuous and consistent time periods and mapping them to the positions of the wear-concerned segments in the inspection sequence, determine whether the continuous and consistent time periods meet the conditions for maintenance level, and organize the corresponding joint numbers, transmission component names and monitoring segment identifiers according to the maintenance level and inspection sequence to obtain the equipment maintenance management results.

[0035] As a further aspect of the present invention, the extraction process of the torque change direction and clamping pressure change direction at each time point in the torque and pressure change direction set is specifically as follows:

[0036] Within the time range covered by the wear concern section, the output value of the torque sensor and the pressure feedback data of the end effector clamping mechanism are differentially calculated at fixed time intervals to obtain the directional change at adjacent time points;

[0037] The process of obtaining the continuous and consistent time period set is as follows:

[0038] In the case of torque and pressure change direction concentration, the consistency of the direction at three adjacent time points is used as the criterion for continuous and consistent direction change. The time period of consistent direction is determined and the corresponding start and end positions are recorded.

[0039] As a further aspect of the present invention, the condition for determining whether a continuous and consistent time period meets the maintenance level is specifically as follows:

[0040] The duration of a continuous and consistent time period is compared with the position of the wear-concerned segment in the inspection sequence. The continuous and consistent time periods are filtered using a preset duration threshold to determine the continuous and consistent time periods that meet the maintenance level.

[0041] The process of organizing according to maintenance level and inspection sequence is as follows:

[0042] The joint numbers, transmission component names, and monitoring section identifiers corresponding to consecutive and consistent time periods that meet the maintenance level conditions are arranged in the order of the inspection sequence to form the equipment maintenance management results.

[0043] The beneficial effects of the technical solutions provided in the embodiments of the present invention include at least the following:

[0044] In this invention, by comparing data such as the rotational speed, angular displacement, and torque of the joint drive motor in real time, it is possible to accurately identify whether the joint movement is synchronized. By combining the joint's motion state with the mechanical characteristics output by the sensors, a dynamic and continuous component health assessment is formed. The coupling relationship between the joint's motion path and friction changes is analyzed in depth, which can promptly capture potential wear, mechanical anomalies, and force concentration effects. This generates specific inspection sequences and monitoring sections, avoiding misjudgments of equipment status due to data lag or lack of dynamic correlation. This effectively improves the accuracy of equipment status detection, ensures the orderly and precise execution of maintenance work, improves maintenance efficiency, and reduces unnecessary equipment downtime. Attached Figure Description

[0045] Figure 1 This is a flowchart of the method of the present invention;

[0046] Figure 2 This is a flowchart illustrating the acquisition of the joint working sign marker set according to the present invention.

[0047] Figure 3 This is a flowchart illustrating the process of obtaining the inspection sorting sequence in this invention.

[0048] Figure 4 This is a flowchart illustrating the process of obtaining the monitoring segment set in this invention.

[0049] Figure 5 This is a flowchart illustrating the process of obtaining the wear trend entry sequence in this invention.

[0050] Figure 6 This is a flowchart illustrating the process of obtaining equipment maintenance and management results according to the present invention. Detailed Implementation

[0051] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0052] In embodiments of the present invention, words such as "exemplarily," "for example," etc., are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" in the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the word "exemplary" is intended to present the concept in a concrete manner. Furthermore, in embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one.

[0053] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0054] Please see Figure 1 This invention provides a technical solution: a method for maintenance and management of orthopedic surgical robot equipment integrating digital twins, comprising the following steps:

[0055] S1: Acquire the rotational speed data of the joint drive motor, the angular displacement data of the joint encoder, and the output value of the torque sensor of the orthopedic surgical robot. Align and arrange them in chronological order. Compare the directional consistency and rhythm of the rotational speed change and the angular displacement change at the same time recording point to identify the motion synchronization state or motion mismatch state. Map and match the motion synchronization state or motion mismatch state with the rising, falling, or fluctuating change characteristics of the torque sensor output at the same time recording point to identify the force coordination characteristics or force abnormal characteristics. Divide the joint status into stability level, attention level, and maintenance level. Organize the joints according to the joint number to form a maintenance record and generate a set of joint working sign markers.

[0056] S2: Based on the joint number and maintenance level recorded in the joint working sign marker set, extract the travel position feedback of the lead screw assembly, the friction resistance change data of the guide rail assembly, and the pressure feedback of the clamping mechanism of the end effector in the digital twin model of the orthopedic surgical robot. Analyze the coupling relationship between the travel position of the lead screw and the friction change of the guide rail under the same joint number along the joint motion path, determine whether the friction change and the travel position show a synchronous increasing or decreasing trend, and verify the correlation between the increasing or decreasing trend and the pressure change of the clamping mechanism of the end effector at the same position point. Identify whether there is a force concentration effect at the same position point, map the recurrence frequency of the force concentration effect to the maintenance level to form an inspection order, and establish an inspection sorting sequence.

[0057] S3: Based on the inspection sequence and corresponding joint number recorded in the inspection sorting sequence, extract the joint encoder angular displacement data and lead screw assembly stroke position feedback. Within the joint range mapped by the inspection sorting, divide the joint into several continuous angle segments according to the angular displacement change sequence. Record the angular displacement values ​​of the start and end points of each angle segment and the lead screw stroke position. Compare the direction of change of angular displacement within each segment with the direction of movement of the lead screw stroke position. Mark the segments with inconsistent change directions as offset abnormal segments. Mark the start and end boundaries and joint number corresponding to the offset abnormal segments to generate a set of maintenance monitoring segments.

[0058] S4: Based on the start and end boundaries of each monitoring segment in the maintenance monitoring segment set, extract the friction resistance change data of the orthopedic surgical robot guide rail component and the torque sensor output value. Set the start and end boundaries of each monitoring segment as the data interception window. Extract the friction evolution data and torque fluctuation data within the data interception window along the time dimension. Compare the change direction of the friction evolution data at adjacent time points with the change direction of the torque fluctuation data at the same time point. Identify the time period in which the change direction is consistent within multiple consecutive time points, record it as the wear concern segment, and mark the start and end positions. Arrange all wear concern segments into an item sequence according to the monitoring segment order to generate a wear trend item sequence.

[0059] S5: Based on the start and end positions of each wear concern segment recorded in the wear trend entry sequence, call the torque sensor output value and the end effector clamping mechanism pressure feedback. Within the time range covered by the wear concern segment, compare the direction of change of torque reading and the direction of change of clamping pressure reading along the time sequence, and determine whether the direction change at adjacent time points remains continuous and consistent. The range showing continuous and consistent characteristics is determined as the maintenance level range, and the corresponding joint number, transmission component name and monitoring section identifier are recorded. The maintenance record entries are organized according to the maintenance level and inspection sequence to obtain the equipment maintenance management results.

[0060] The joint working sign marker set includes an index of motion mismatch moments, descriptors of abnormal force characteristics, and classification labels for joint health levels. The inspection sorting sequence specifically includes the coordinates of the force concentration location, statistical values ​​of the frequency of abnormal recurrence, and an inspection priority sequence list. The maintenance monitoring section set includes the start and end boundaries of the abnormal offset section, the difference in angular displacement travel direction, and segmented trajectory monitoring identifiers. The wear trend item sequence specifically refers to the wear attention time window, records of friction torque changes in the same direction, and feature codes of resistance evolution trends. The equipment maintenance management results include the scope of maintenance level, the index of names of faulty transmission components, and the maintenance details associated with the monitoring section.

[0061] Please see Figure 2 The steps for obtaining the joint working sign marker set are as follows:

[0062] S101: Acquire the rotational speed data of the joint drive motor, the angular displacement data of the joint encoder, and the output value of the torque sensor of the orthopedic surgical robot. Align the three data items according to the time recording points. Determine the directional consistency of the rotational speed change and angular displacement change at the same time recording point. Then, determine the corresponding directional association markers based on the rising, falling, and fluctuating changes shown by the torque sensor output at the same time position.

[0063] The system acquires rotational speed data of the joint drive motor, angular displacement data of the joint encoder, and output values ​​of the torque sensor of the orthopedic surgical robot. Through a high-speed bus interface (such as EtherCAT) within the controller, it synchronously acquires real-time speed values ​​from the motor driver encoder interface, angle values ​​from the joint end-effector absolute encoder (such as a photoelectric encoder), and readings from a dynamic torque sensor (such as a strain gauge) connected in series in the transmission chain at a frequency of 1000Hz. The three independent data streams are indexed and aligned according to a unified system clock timestamp, establishing a four-dimensional data matrix containing time index, speed value, angle value, and torque value. Time recording points are then selected. As the current analysis frame, extract the motor rotation speed corresponding to that point. encoder angular displacement at the current moment and call the previous time record point. angular displacement ;

[0064] Perform subtraction to calculate the change in angular displacement The motor rotation speed With angular displacement change The direction determination value is obtained by performing a product operation. Set the zero threshold for direction determination to 0. If the value is greater than 0, it is determined to be a record point with the same direction. If the value is less than or equal to 0, it is determined to be a record point with inconsistent direction, and record points at the same time are extracted. Torque sensor output value Compared with the output value at the previous time point Calculate the difference in torque variation The dead zone threshold for torque variation is set to 0.05 Nm. If it is greater than 0.05 Nm, it is judged as an upward change. If it is less than -0.05 Nm, it is judged as a decreasing change. If the absolute value is between 0 and 0.05 Nm, then further fetching... The variance of the torque values ​​at 10 consecutive time points is calculated. If the variance is greater than the preset fluctuation baseline value of 0.02, it is judged as a fluctuation change; otherwise, it is considered as static maintenance. For example, in the test of the knee joint module of the surgical robot, the motor command speed is 2 rad / s in the positive direction.

[0065] The encoder feedback angle increases from 30.1 degrees to 30.2 degrees. The product of the two is positive, which is considered consistent. At the same time, the torque sensor reading jumps sharply from 15.0 Nm to 15.8 Nm. The difference of 0.8 Nm exceeds the threshold and is considered an upward change. This time point is marked as a combination feature of "consistency-increase". The above logic is repeated for all acquisition time points to generate direction association identifiers.

[0066] S102: Based on the direction association identifier, call the rotational speed data of the joint drive motor and the angular displacement data of the joint encoder, divide the time recording point corresponding to the direction association identifier into several continuous segments, and call the output value of the torque sensor for each segment to judge the force performance. Classify the force coordination and force abnormality within the segment range to generate force performance partitions.

[0067] Based on the orientation association identifier, the rotational speed data of the joint drive motor and the angular displacement data of the joint encoder are retrieved, and the orientation association identifier of each recording point in step S101 is scanned in time sequence, comparing adjacent time points. and Are the contents of the identifiers completely identical? The time is "consistent-rising" and If a time point is also "consistent-ascending," it is grouped into the same continuous segment. If a change in the identifier type is detected between adjacent time points, the current time point is used as the end point of the previous segment and the starting point of the next segment. This divides the complete timeline into several continuous segments with a single characteristic attribute. For each segment, the number of all time records contained within that segment is counted. The cumulative mechanical work is calculated by multiplying the torque sensor output value and the angular displacement change within that section. Simultaneously calculate the actual angular displacement change within this section. Compared with the theoretical change in angular displacement The difference (obtained by integrating the motor speed);

[0068] Calculate the cumulative position error The formula for determining force compatibility is set as the normalized error ratio. The coordination coefficient threshold is set at 0.15. When the calculated judgment index... If the index is less than 0.15 and the directional association identifier of the segment contains the "consistent" attribute, the segment is determined to be in a state of force coordination, indicating that the joint transmission chain moves smoothly under load. For example, if the motor drives smoothly within a 100ms segment and the cumulative mechanical work is 5.0J, the cumulative position error is 0.1 degrees, and the calculated index is 0.02, it is classified as force coordination. Conversely, if the index is less than 0.15, the segment is classified as force coordination. If the value is greater than or equal to 0.15, or if the directional association identifier of the segment explicitly contains the attributes of "inconsistency" or "fluctuation", then the segment is determined to be in an abnormal stress state. In particular, for segments with "inconsistency-fluctuation" characteristics, they are directly defined as hard anomalies. All the divided time segments are labeled "coordinated" or "abnormal" according to the above logic to generate stress performance partitions.

[0069] S103: Based on the stress performance zoning, call the coordinated and abnormal sections within the stress performance zoning for each joint number, mark the coordinated sections as stable level, mark some abnormal sections as attention level, mark continuous abnormal sections as maintenance level, and organize them into maintenance records according to the joint number order, generating a joint working sign mark set.

[0070] Based on the force performance partitions, the coordinated and abnormal segments within each joint number are retrieved. All joint IDs of the orthopedic surgical robot (e.g., J1 to J6) are traversed. For each joint, a full-time force performance partition list is extracted. Continuous time slices marked with the "coordinated" attribute are identified in the list, and their corresponding state values ​​are directly mapped to "stability level." Segments marked with the "abnormal" attribute are then carefully screened, and the duration of each abnormal segment is extracted. and the peak moment within this section The attention level trigger threshold duration is set to 200ms and the peak torque threshold is 120% of the rated torque. If the duration of a certain abnormal segment is... If the duration is less than 200ms and the peak torque does not exceed 120% of the rated torque, it is considered a transient disturbance and marked as "Level of Concern," indicating that it needs to be monitored in subsequent cycles. If the duration of an abnormal segment is found to be... The peak torque exceeds 200ms, or at any duration. If the torque exceeds 120% of the rated torque, or if more than three independent abnormal segments occur consecutively within a 1-second time window, these segments are uniformly labeled as "maintenance level". For example, in the record of the J3 hip joint, a 500ms "inconsistency-fluctuation" segment was found, accompanied by a torque spike. It was immediately determined to be a maintenance level. All classification results are structured and assembled with the corresponding joint number, occurrence timestamp, and abnormality type description to form a detailed equipment health status log and generate a joint working sign marker set.

[0071] Please see Figure 3 The steps to obtain the inspection sorting sequence are as follows:

[0072] S201: Obtain the joint number and maintenance level recorded in the joint working sign marker set, extract the lead screw component stroke position feedback, guide rail component friction resistance change data and end effector clamping mechanism pressure feedback from the digital twin model of the orthopedic surgical robot based on the joint number, analyze the coupling relationship between the lead screw stroke position and guide rail friction change along the joint motion path, and generate a coupling relationship mapping.

[0073] Retrieve the joint IDs and maintenance levels recorded in the joint activity indicator set, traverse all stored entries, and extract the joint IDs recorded in each entry. (e.g., J1, J2, J3) and their corresponding maintenance levels (Stability, Monitoring, or Maintenance) Establish communication connection with the digital twin system of the orthopedic surgical robot, utilizing joint numbering. As an index key, a data request command is sent to the digital twin database, setting the data retrieval time window to the operation cycle of the past 24 hours, and parsing the real-time travel position sequence of the lead screw component corresponding to the joint from the returned data packet. (Unit: mm, obtained via linear displacement sensor) Sequence of frictional resistance variation of guide rail assembly calculated by digital twin model. (Unit: N) and the pressure feedback sequence of the clamping mechanism of the end effector. (Unit: N, obtained via a thin-film pressure sensor) Check if the timestamps of these three sequences correspond one-to-one. If there is a time discrepancy, perform linear interpolation alignment based on the timestamp of the lead screw travel position. Using the horizontal axis as the abscissa, the corresponding guide rail friction resistance is plotted. Mapping to the ordinate axis to construct a position-resistance two-dimensional data pair According to the position of the lead screw stroke, starting from the minimum stroke Up to maximum travel The numerical values ​​are sorted in ascending order for all data pairs. For example, for the J2 knee joint module, whose stroke range is 0mm to 150mm, a frictional resistance value recorded every 0.5mm within this range is extracted to form a continuous discrete point set. Simultaneously, the clamping pressure of the end effector is... As a third dimension of data, it is added to the corresponding location points to form a triplet dataset containing location, friction, and pressure. Repeat the above extraction and mapping operations for each joint, index and store all the processed triplet datasets according to the joint number, and generate a coupling relationship mapping.

[0074] S202: Based on the coupling relationship mapping, determine whether the screw stroke position and the guide rail friction change show a synchronous increasing or decreasing trend. Correlate the increasing or decreasing trend with the pressure change at the same position point of the end effector clamping mechanism pressure feedback to determine whether there is a force concentration effect and generate a force concentration effect identifier.

[0075] Based on the coupling relationship mapping, the triplet dataset for each joint in step S201 is called. Set the length of the sliding window For 5 sampling points (corresponding to a travel distance of approximately 2.5 mm), index the position along the edge of the dataset. Move the window point by point;

[0076] Calculate the frictional resistance of the guide rail within the window. average rate of change Set a threshold for friction growth The value is 0.2 N / mm. If the calculated value is... If the frictional resistance is greater than 0.2 N / mm, it is determined that the frictional resistance in that section is increasing. In this case, the end effector clamping pressure data corresponding to the same window should be extracted immediately. ;

[0077] Calculate its average rate of change ;

[0078] Set pressure linkage threshold The value is 0.5 N / mm. and Perform a numerical comparison, if The coefficient of friction is also greater than 0.5 N / mm, indicating that the clamping pressure increases significantly at the same time as the frictional force. Further calculation of the Pearson correlation coefficient between the two is performed. ,like If the value is greater than 0.8, a strong correlation is confirmed, and the starting position of the window is marked. For example, when analyzing the 80mm to 85mm travel range of the J3 joint, it was found that the guide rail friction increased linearly from 2.0N to 3.5N (rate of change 0.3N / mm > 0.2N / mm), while the clamping pressure increased from 10N to 14N (rate of change 0.8N / mm > 0.5N / mm), and the correlation coefficient between the two was 0.92. Therefore, it was determined that there was a force concentration effect at the 80mm position. The position coordinates of all force concentration points that met the above conditions, the corresponding friction increment value and pressure increment value were recorded, and a unique event ID was assigned to generate a force concentration effect identifier.

[0079] S203: Based on the force concentration effect identifier, the recurrence frequency of the force concentration effect is mapped to the maintenance level, and the inspection sequence is formed according to the joint number, and an inspection sorting sequence is established and generated.

[0080] Based on the force concentration effect identifier, the recurrence frequency of force concentration effect is mapped to the maintenance level, and the number of each joint is counted. The total number of times the event is labeled as "force concentration effect" is denoted as the recurrence frequency. For example, if a total of 5 force concentration points are detected in joint J3 throughout its entire stroke, then... Call the maintenance level of each joint determined in step S103. Set basic weight scores for different levels. Set the weight corresponding to the "stability level". The weight is 10, corresponding to the "attention level". The weight is 30, corresponding to the "maintenance level". It is 80;

[0081] Constructing an inspection priority scoring formula ,in The weighting coefficient for the ranking is set to 1.0. Set the frequency weighting coefficient to 2.0, and substitute the values ​​to calculate the inspection priority score for each joint;

[0082] For example, joint J3 is at a "level of concern" ( ), with a frequency of 5;

[0083] but The J1 joint is rated as "stable" ( ), while the J1 joint is rated as "stable" ( ). ), but its frequency is 20, then After the score is calculated, all joints are assigned to scores. Sort in descending order from highest to lowest score, with higher scores indicating greater urgency for inspection. If two items have the same score, sort by frequency of recurrence. The higher-ranking joints are placed first, and the sorted list of joint numbers is defined as the inspection execution queue. For example, if the queue order is J1, J3, J2, an inspection sorting sequence is generated.

[0084] Please see Figure 4 The steps for obtaining the set of monitoring sections are as follows:

[0085] S301: Based on the inspection sequence and corresponding joint number recorded in the inspection sorting sequence, obtain the joint encoder angular displacement data and the lead screw assembly stroke position feedback. Within the joint range corresponding to the inspection sorting mapping, divide the angular displacement change time sequence into angle segments, record the starting and ending angular displacement values ​​of each segment, and correspond them to the lead screw stroke position to obtain the angular displacement stroke mapping set.

[0086] Based on the inspection sequence and corresponding joint numbers recorded in the digital twin inspection sorting sequence, the list of joint IDs with higher priority in the sequence (e.g., J1, J3, J2) is parsed, and each selected joint ID is treated as the current processing object in this order. By accessing the historical operation database of the orthopedic surgical robot through a high-speed data interface, the time series of the joint encoder angular displacement corresponding to that joint can be extracted. (Unit: degrees, obtained via absolute encoder) and time series of lead screw component stroke position feedback. (Unit: mm, acquired via linear displacement sensor), ensuring both sets of data have the same timestamp index. Set the angle segmentation benchmark threshold Initialize the segmentation cursor to 5.0 degrees. Initialize the cumulative variable as the starting point index of the current segment. Along the time axis from Begin by iterating through the angular displacement data point by point, calculating the absolute value of the angular displacement difference between adjacent points and summing them up. That is, execution Real-time Compared to the baseline threshold of 5.0 degrees, once If the value is greater than or equal to 5.0 degrees, or if the data has been traversed to the end, then the current index is immediately reset. Mark the end point index of this segment and extract the start point index. Corresponding angular displacement value Screw position value index of the endpoint Corresponding angular displacement value Screw position value This set of data is packaged and recorded as an independent angular segment unit. Reset Set the index to 0 and set the starting point index to 0. Updated to Continue the next round of traversal and segmentation until the data for the entire time period of the joint is covered. For example, for the execution data of a certain run of the J1 joint, at time point... to If the cumulative rotation is 5.2 degrees, with a starting position of 10.0 mm and an ending position of 10.5 mm, a standard segment record is generated. This operation is repeated for all joints in the sequence, and all generated segment units are summarized and stored to obtain the angular displacement travel mapping set.

[0087] S302: Call the angular displacement stroke mapping set, compare the direction of angular displacement change in each angular segment with the direction of movement of the lead screw stroke position segment by segment, and determine whether they are consistent. If the directions are inconsistent, mark the segment as an offset abnormal segment, and record the start and end boundaries of the offset segment and the corresponding joint number to generate an offset abnormal segment set.

[0088] Call the angular displacement travel map set and iterate through each angular segment unit stored in the set. Extract the initial angular displacement of this section. Termination angular displacement Starting screw position With the position of the stop screw Perform a difference operation to calculate the net change in angular displacement within the segment. and the net change in lead screw stroke Call the preset joint kinematic parameter table to obtain the theoretical transmission direction coefficient corresponding to the joint number. (If designed for forward rotation to drive forward extension, then) (conversely, -1), using the sign function. Extract separately and The sign of the changing direction is used to construct the direction consistency verification logic: calculate the direction determination product. Set the micro-motion dead zone threshold To filter sensor noise to 0.01mm, if Less than 0.01mm and A value greater than 0.5 degrees is directly classified as "abnormal loss of movement". Greater than 0.01 mm and calculated A value of -1 indicates that the actual movement direction of the lead screw is opposite to the motor drive direction, which is judged as "reverse slip abnormality". Both of these situations are classified as inconsistency in direction. For example, in the 5th segment of the J1 joint, the motor rotates 5 degrees in the forward direction ( Theoretically, the lead screw should extend ( However, actual feedback shows that the lead screw position has retracted by 0.05mm. ),at this time If an error is detected, and a segment is determined to have inconsistent directions, the timestamp range of that segment is immediately read. The corresponding joint number is defined as a fault feature segment that requires special attention, and a unique abnormal event ID is assigned to generate a set of offset abnormal segments.

[0089] S303: Based on the set of offset anomaly sections, organize the offset anomaly sections corresponding to each joint number, and arrange them in the order of joint number and offset anomaly frequency in the inspection sorting sequence to generate a set of maintenance monitoring sections;

[0090] Based on the set of offset anomaly segments, all anomaly records in the set are categorized and statistically analyzed according to their joint numbers, and the total number of offset anomaly segments contained under each joint number is calculated. As a health deterioration index for the joint, for example, if joint J1 has 3 abnormal segments, joint J3 has 0, and joint J2 has 1, the original inspection sorting sequence in step S203 is called. While maintaining the basic priority of the original sequence, the frequency of offset anomalies is introduced as a dynamic adjustment weight to construct a corrected sorting rule: if two joints are adjacent in the original sequence, but the subsequent joint has... If the value is more than 3 higher than the preceding joint, then swap their inspection positions, or directly remove all existing joints. The joints according to Extracted in descending order, these anomalies are prioritized and placed at the forefront of the inspection sequence, forming a dynamic monitoring queue with an "anomaly priority." For each node in the queue, all its offset anomaly segments are listed in chronological order, and the start and end time boundaries of each segment are extracted. As a data extraction window for subsequent refined analysis, the joint number, segment ID, and start and end timestamps are combined into standardized monitoring task entries. For example, the first task entry generated is "J1 joint - abnormal segment #5 - time range 10:00:01.200 to 10:00:01.500". All the sorted entries are assembled according to the new sorting to generate a set of maintenance monitoring segments.

[0091] Please see Figure 5 The steps for obtaining the wear trend entry sequence are as follows:

[0092] S401: Based on the start and end boundaries of the monitoring sections recorded in the maintenance monitoring section set, obtain the friction resistance change data of the guide rail assembly and the output value of the torque sensor, set the start and end boundaries of each monitoring section as the data interception window, and extract the friction evolution data and torque fluctuation data in each window along the time sequence dimension to obtain the friction torque data set.

[0093] Based on the start and end boundaries of each monitoring segment in the maintenance monitoring segment set, each standardized monitoring task item in the set is traversed, and the key index information corresponding to each item is parsed and extracted, including the joint number. (e.g., J1 joint), start timestamp of abnormal segment (e.g., 10:00:01.200) and the end timestamp (e.g., 10:00:01.500), using this index information as the data retrieval key, a targeted query request is simultaneously initiated to the digital twin database and physical sensor database of the orthopedic surgical robot, locating and extracting the joint within the specified time range from the digital twin database. The model-derived sequence of guide rail assembly friction resistance estimation (Unit: N), and simultaneously extract the real-time output sequence of joint torque sensors (such as dynamic torque sensors) within the same time window from the physical sensor database. (Unit: Nm) Perform data integrity verification to check the total number of data points in the two sequences. To check for consistency, if frame drops or frequency mismatches exist, linear interpolation is used to resample the friction resistance data using the time axis of the torque sensor as a reference, ensuring that the two are consistent at each index. ( Strictly corresponding to the same physical moment, a multi-dimensional data matrix is ​​constructed containing time index, frictional resistance value, and torque output value. For each monitoring segment in the set, repeat the above extraction and alignment operations. All the obtained matrices are independently encapsulated according to the corresponding segment ID. For example, for a monitoring segment of the J3 joint that lasts for 300ms, extract 300 friction-torque pairs of sampling points. If the segment crosses the motor forward and reverse switching point, further divide the data matrix into sub-matrices according to the zero velocity point to avoid interference from dynamic characteristics. Define the set of all processed data matrices as the friction torque data group.

[0094] S402: Call the friction torque data group, compare the change direction of friction evolution data and torque fluctuation data in adjacent time points within each time window, identify the time period in which the change direction is consistent within multiple consecutive time points, record it as wear concern segment, and mark the start and end positions to obtain the wear concern segment set;

[0095] Call the friction torque data set, and for each data matrix in the data set. Initialize a state flag array corresponding to the data length. Set the timing sliding cursor Traverse from 1 to For each time step, calculate the instantaneous change in the frictional resistance of the guide rail. Instantaneous change in the output of the torque sensor Introducing symbolic functions Extract the direction of change and construct a direction consistency determination operator. ,like and If the signs are the same (i.e., both increasing or both decreasing), then A value of 1 indicates the same direction; if the signs are opposite, then... A value of -1 indicates a deviation in direction; if any change is 0, then... If the value is 0, it is ignored. After performing point-by-point judgment, the generated value is scanned. Sequence, finding consecutive occurrences For subsequences, set a continuity threshold for counting. The value is 15 (corresponding to a duration of 15ms, assuming a sampling rate of 1kHz). If a continuous index interval is detected... satisfy And all within the interval If the interval is determined to be a wear characteristic segment with strong coupling between friction and load, the cumulative increase in frictional resistance within this segment is calculated. Cumulative Increment of Torque If both absolute values ​​exceed the preset micro-noise threshold (e.g., friction increment > 0.05 N and torque increment > 0.02 Nm), then the segment is officially confirmed as a valid wear concern segment, and its absolute start time on the original time axis is recorded. and the end time The data includes the corresponding joint travel position (obtained by associating position data with timestamps). For example, in an analysis of the J2 joint, it was found that from the 50th point to the 100th point, the friction force continuously increased and the torque increased synchronously, lasting for 50ms. This met the threshold condition and was immediately marked as a wear-related segment. After traversing all data matrices to complete the identification, all marked segments were summarized to obtain the wear-related segment set.

[0096] S403: Based on the wear concern segment set, arrange all wear concern segments in the order of monitoring segments, classify each wear concern segment according to its start and end positions, and generate an entry sequence by the order of all wear concern segments to obtain the wear trend entry sequence;

[0097] Based on the set of wear-related segments, the discretely distributed wear-related segments in the set are structured and organized. Using the monitoring segment order determined in step S303 as the primary index, all wear-related segments belonging to the same monitoring segment are arranged in chronological order. Spatial location classification analysis is performed to extract the starting joint position recorded for each wear-related segment. With the termination joint position Calculate the center position of this segment. Set the aggregation radius of the location For a thickness of 2.0 mm, scan the center location of all wear-prone sections and... Multiple segments of interest with a distance of less than 2.0 mm are grouped into a specific "wear hotspot region." The number of segments of interest contained within this region is used as a wear frequency index. For each independent wear segment of interest or the aggregated wear hotspot region, a standardized descriptive entry is constructed. The entry includes the joint number, physical location range, corresponding time span, and friction-torque cross-correlation coefficient (calculated within this segment). and The Pearson coefficient and wear frequency are used to generate entries, such as "J3 joint - position range 45.5mm to 48.0mm - frequency 5 times - strong correlation". Finally, all generated entries are sorted according to the principle of "frequency priority, position continuity", that is, entries with high wear frequency are prioritized, and those with the same frequency are arranged according to the order of joint movement paths, forming an orderly list that reflects the distribution of the severity of equipment wear, and generating a wear trend entry sequence.

[0098] Please see Figure 6 The steps for obtaining equipment maintenance management results are as follows:

[0099] S501: Based on the start and end positions of each wear concern segment recorded in the wear trend entry sequence, obtain the torque sensor output value and the end effector clamping mechanism pressure feedback data. Within the time range covered by the wear concern segment, extract the torque change direction and clamping pressure change direction at each time point in chronological order to obtain the torque and pressure change direction set.

[0100] Based on the start and end positions of each wear concern segment recorded in the wear trend entry sequence, the joint numbers contained in each entry in the sequence are read sequentially. (e.g., J2 joint) and the spatial coordinate range of the wear-concerned segment. (For example, a travel range of 45.5mm to 48.0mm). Using the historical operation logs of the orthopedic surgical robot control system, the above spatial coordinate range is converted into the corresponding time span through a position-time mapping table. Accurate to the millisecond level (e.g., 14:20:05.100 to 14:20:05.600), data extraction instructions are constructed based on this time span to extract a real-time torque reading sequence with a sampling frequency of 1kHz from the data stream of a torque sensor (e.g., a dynamic torque sensor). (Unit: Nm), and simultaneously extract the pressure feedback (such as thin-film pressure sensor) sequence of the clamping mechanism from the end effector feedback channel. (Unit: N), ensure the number of data points in both sets. Equal and time-aligned, iterate through each time point. (from 2 to ), calculate the difference in the torque sensor output at the current moment relative to the previous moment. and the difference in clamping pressure feedback Set the dead zone threshold to determine the direction of torque change. The dead zone threshold for determining the direction of pressure change is set to 0.02 Nm. For 0.1N, a ternary logic function is introduced. ,when Output 1 (increasing) when Output -1 (decreasing) when the torque changes, otherwise output 0 (fluctuating / stationary). Substitute these values ​​into the calculation to obtain the torque change direction marker. Marking the direction of clamping pressure change At the same time point The two direction markers are combined to form a binary vector. For example, at the 50th sampling point, the torque increases by 0.1 Nm (>0.02), and the pressure increases by 0.5 N (>0.1). Then the vector at that point is... If the torque changes slightly by 0.01 Nm (<0.02), and the pressure decreases by 0.3 N (<-0.1), then the vector is... The calculation and combination of all sampling points within the wear-concerned section are completed to generate a set of torque and pressure change directions.

[0101] S502: Call the set of torque and pressure change directions, compare the torque change direction with the clamping pressure change direction at each time point, determine whether the change direction at adjacent time points remains continuous and consistent, and record the time period when the direction is consistent to obtain a set of continuous and consistent time periods.

[0102] Call the set of torque and pressure change directions, and iterate through each time point in the set. The generated binary vector:

[0103] Construct a directional consistency verification operator Only when and When both values ​​are equal and neither is 0 (i.e., both are 1 or both are -1), it is determined that the time point exhibits the characteristic of "force-pressure synchronous linkage," and a value is assigned. Otherwise, assign a value. Generated by scanning along the time axis Find a sequence of consecutive "1" values ​​and initialize a counter. with the starting index ;

[0104] When encounter hour, Incrementing, if Change from 0 to 1 to record the current state. As a potential starting point, when encountering and Immediately calculate the duration of the current continuous segment and set a valid threshold for continuity consistency. For 20 sampling points (corresponding to a duration of 20ms), if the settlement... If this time period is confirmed as a valid "abnormal force linkage segment," it indicates that the resistance changes caused by wear inside the joint have been directly transmitted and affected the stability of the end clamping force. Record the start and end timestamps of this segment. Duration And the cumulative variation of torque and pressure during the period. For example, when analyzing a wear-related segment of the J3 joint, it was found that from 120ms to 180ms, the torque and pressure at 60 consecutive sampling points all showed a synchronous upward trend. ), and satisfy If the data is synchronized at only 3 points and then interrupted, it is considered random noise and removed. After processing all the data, the selected valid segments are summarized to obtain a set of continuous and consistent time periods.

[0105] S503: Based on the set of continuous and consistent time periods and mapping them to the position of the wear-concerned section in the inspection sequence, determine whether the continuous and consistent time periods meet the conditions of the maintenance level, and organize the corresponding joint number, transmission component name and monitoring section identifier according to the maintenance level and inspection sequence to obtain the equipment maintenance management results.

[0106] Based on the set of continuous and consistent time periods, and mapping them to the positions of wear-concerned segments in the inspection sequence, the total duration of the continuous and consistent time periods contained under each joint number is calculated. and the maximum duration of a single attack Establish maintenance level judgment criteria: if the maximum duration of a single operation of a certain joint is... Exceeding 150ms, or its total duration If the proportion of wear and tear on the monitored segment exceeds 40% of the total time, the joint is determined to be in an "emergency repair state." If the time interval is between 50ms and 150ms, it is determined to be in "preventive maintenance state"; otherwise, it is marked as "routine monitoring state". The digital twin inspection sorting sequence established in step S203 is invoked to obtain the preset inspection priority of each joint. The BOM (Bill of Materials) database of the orthopedic surgical robot is queried, and the specific transmission component name (e.g., "J3-ball screw pair-Z-axis") is retrieved according to the joint number. The final maintenance task entries are constructed, and each entry includes the joint number, transmission component name, corresponding monitoring section identifier (from step S303), and the determined value. The maintenance level and recommended intervention order are sorted in a multi-level manner, with "Maintenance Level (Emergency > Prevention > Routine)" as the first sorting key and "Inspection Sequence Priority" as the second sorting key. For example, although joint J3 is ranked second in the inspection sequence, it is classified as "Emergency Maintenance" because a continuous force abnormality of 200ms was detected. Therefore, it is moved to the first place in the final result. Joint J1 is ranked first, but only requires "Routine Monitoring", so it is arranged in order. A structured list containing specific fault location, component information and urgency of handling is generated to obtain the equipment maintenance management results.

[0107] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for maintenance and management of orthopedic surgical robot equipment integrating digital twins, characterized in that, Includes the following steps: S1: Acquire joint motor speed, angular displacement and torque data and align timing, correlate and compare speed and angular displacement direction and rhythm, identify synchronization or mismatch state, analyze force coordination with torque changes, classify state levels, organize by joint number, and generate a joint working sign mark set; S2: Based on the joint number and maintenance level in the joint working sign mark set, extract the lead screw stroke, guide rail friction and clamping pressure data, analyze the stroke and friction trends, and verify the force concentration effect with the pressure at the same position point. Sort by recurrence frequency and level to generate an inspection sorting sequence. S3: Based on the inspection sequence, extract angular displacement and lead screw travel data, divide the angular displacement into segments according to the angular displacement time sequence, record the correspondence between the start and end points, compare the angular displacement direction with the travel direction, mark the inconsistent segments, and generate a set of maintenance monitoring segments. S4: Based on the start and end boundaries of each monitoring section in the maintenance monitoring section set, set a data window, extract friction changes and torque fluctuations within the window, compare the change directions of adjacent points to identify continuous and consistent sections, mark the start and end positions, and generate a wear trend entry sequence. The steps for obtaining the joint working indicator set are as follows: S101: Acquire the rotational speed data of the joint drive motor, the angular displacement data of the joint encoder, and the output value of the torque sensor of the orthopedic surgical robot. Align the three data items according to the time recording points. Determine the directional consistency of the rotational speed change and angular displacement change at the same time recording point. Then, determine the corresponding directional association markers based on the rising, falling, and fluctuating changes shown by the torque sensor output at the same time position. S102: Based on the direction association identifier, call the joint drive motor rotation speed data and the joint encoder angular displacement data, divide the time recording point corresponding to the direction association identifier into several continuous segments, and call the torque sensor output value for each segment to judge the force performance, classify the force coordination and force abnormality within the segment range, and generate force performance partitions. S103: Based on the stress performance partition, call the coordinated and abnormal sections within the stress performance partition for each joint number, mark the coordinated sections as stable, mark some abnormal sections as attention, mark continuous abnormal sections as maintenance, and organize them into maintenance records according to the joint number order to generate a joint working sign mark set.

2. The method for maintenance and management of orthopedic surgical robot equipment integrating digital twins according to claim 1, characterized in that: The joint working sign marker set includes a motion mismatch time index, a force abnormality feature descriptor, and a joint health level classification label. The inspection sorting sequence specifically includes the coordinates of the force concentration location, the statistical value of the frequency of abnormal recurrence, and the inspection priority sequence table. The maintenance monitoring section set includes the start and end boundaries of the offset abnormal section, the difference item of angular displacement travel direction, and the segmented trajectory monitoring identifier. The wear trend entry sequence specifically refers to the wear attention time window, the record of the same direction change of friction torque, and the feature code of the resistance evolution trend.

3. The method for maintenance and management of orthopedic surgical robot equipment integrating digital twins according to claim 1, characterized in that: The steps for obtaining the inspection sorting sequence are as follows: S201: Obtain the joint number and maintenance level recorded in the joint working sign marker set; extract the lead screw component stroke position feedback, guide rail component friction resistance change data and end effector clamping mechanism pressure feedback from the digital twin model of the orthopedic surgical robot according to the joint number; analyze the coupling relationship between the lead screw stroke position and guide rail friction change along the joint motion path; and generate a coupling relationship mapping. S202: Based on the coupling relationship mapping, determine whether the screw stroke position and the guide rail friction change show a synchronous increasing or decreasing trend, and verify the increasing or decreasing trend with the pressure change at the same position point of the end effector clamping mechanism pressure feedback, determine whether there is a force concentration effect, and generate a force concentration effect identifier. S203: Based on the stress concentration effect identifier, the recurrence frequency of the stress concentration effect is mapped to the maintenance level, and the inspection sequence is formed according to the joint number. An inspection sorting sequence is established and an inspection sorting sequence is generated.

4. The method for maintenance and management of orthopedic surgical robot equipment integrating digital twins according to claim 1, characterized in that: The steps for obtaining the set of maintenance and monitoring sections are as follows: S301: Based on the inspection sequence and corresponding joint number recorded in the inspection sorting sequence, obtain the joint encoder angular displacement data and the lead screw assembly stroke position feedback. Within the joint corresponding range of the inspection sorting mapping, divide the angular displacement change sequence into angular segments, record the starting and ending angular displacement values ​​of each segment, and correspondingly obtain the lead screw stroke position to obtain the angular displacement stroke mapping set. S302: Call the angular displacement stroke mapping set, compare the direction of angular displacement change in each angular segment with the direction of movement of the lead screw stroke position segment by segment, and determine whether they are consistent. If the directions are inconsistent, mark the segment as an offset abnormal segment, and record the start and end boundaries of the offset segment and the corresponding joint number to generate an offset abnormal segment set. S303: Based on the set of offset anomaly segments, organize the offset anomaly segments corresponding to each joint number, and arrange them in the order of the inspection sorting sequence according to the joint number and the offset anomaly frequency to generate a set of maintenance monitoring segments.

5. The method for maintenance and management of orthopedic surgical robot equipment integrating digital twins according to claim 1, characterized in that: The steps for obtaining the wear trend entry sequence are as follows: S401: Based on the start and end boundaries of the monitoring sections recorded in the set of maintenance monitoring sections, obtain the friction resistance change data of the guide rail assembly and the output value of the torque sensor, set the start and end boundaries of each monitoring section as the data interception window, and extract the friction evolution data and torque fluctuation data in each window along the time sequence dimension to obtain the friction torque data set. S402: Call the friction torque data group, compare the change direction of friction evolution data and torque fluctuation data in adjacent time points within each time window, identify the time period in which the change direction is consistent within multiple consecutive time points, record it as wear concern segment, and mark the start and end positions to obtain the wear concern segment set; S403: Based on the set of wear-concerned segments, arrange all wear-concerned segments in the order of monitoring segments, classify each wear-concerned segment according to its start and end positions, and generate an entry sequence by the order of all wear-concerned segments to obtain a wear trend entry sequence.

6. The method for maintenance and management of orthopedic surgical robot equipment integrating digital twins according to claim 1, characterized in that: The method further includes: S5: Based on the start and end positions of each wear concern segment recorded in the wear trend entry sequence, call up the torque and clamping pressure data, compare the directional continuity and consistency of the two at adjacent time points, determine the maintenance level range, and record the joint number and component identification to obtain the equipment maintenance management results; The equipment maintenance management results include the scope of the maintenance level, the index of the names of faulty transmission components, and the maintenance details associated with the monitoring section.

7. The method for maintenance and management of orthopedic surgical robot equipment integrating digital twins according to claim 6, characterized in that: The steps for obtaining the equipment maintenance management results are as follows: S501: Based on the start and end positions of each wear concern segment recorded in the wear trend entry sequence, obtain the torque sensor output value and the end effector clamping mechanism pressure feedback data. Within the time range covered by the wear concern segment, extract the torque change direction and clamping pressure change direction at each time point in chronological order to obtain the torque and pressure change direction set. S502: Call the set of torque and pressure change directions, compare the torque change direction with the clamping pressure change direction at each time point, determine whether the change direction at adjacent time points remains continuous and consistent, and record the time period of consistent direction to obtain a set of continuous and consistent time periods. S503: Based on the set of continuous and consistent time periods and mapping them to the positions of the wear-concerned segments in the inspection sequence, determine whether the continuous and consistent time periods meet the conditions for maintenance level, and organize the corresponding joint numbers, transmission component names and monitoring segment identifiers according to the maintenance level and inspection sequence to obtain the equipment maintenance management results.

8. The method for maintenance and management of orthopedic surgical robot equipment integrating digital twins according to claim 7, characterized in that: The extraction process of the torque change direction and clamping pressure change direction at each time point in the torque and pressure change direction set is as follows: Within the time range covered by the wear concern section, the output value of the torque sensor and the pressure feedback data of the end effector clamping mechanism are differentially calculated at fixed time intervals to obtain the directional change at adjacent time points; The process of obtaining the continuous and consistent time period set is as follows: In the case of torque and pressure change direction concentration, the consistency of the direction at three adjacent time points is used as the criterion for continuous and consistent direction change. The time period of consistent direction is determined and the corresponding start and end positions are recorded.

9. The method for maintenance and management of orthopedic surgical robot equipment integrating digital twins according to claim 7, characterized in that: The specific conditions for determining whether a continuous and consistent time period meets the maintenance level are as follows: The duration of a continuous and consistent time period is compared with the position of the wear-concerned segment in the inspection sequence. The continuous and consistent time periods are filtered using a preset duration threshold to determine the continuous and consistent time periods that meet the maintenance level. The process of organizing according to maintenance level and inspection sequence is as follows: The joint numbers, transmission component names, and monitoring section identifiers corresponding to consecutive and consistent time periods that meet the maintenance level conditions are arranged in the order of the inspection sequence to form the equipment maintenance management results.

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