Tightening curve comprehensive score judgment method and device, equipment and storage medium

Abstract

A tightening curve comprehensive score determination method, apparatus and device, and a storage medium, the method comprising: acquiring torque data and angle data of a target object during tightening operation to generate a tightening curve, and dividing the tightening curve into each stage curve based on the tightening degree in the tightening operation; calculating the curve quantization characteristics of the curves in each stage, calculating the overall slope characteristics of the tightening curve, and performing weighted quantitative scoring on the curve quantization characteristics and the overall slope characteristics based on a preset scoring rule to obtain a tightening curve comprehensive score; performing abnormal risk classification according to the curve quantization features and a preset feature threshold to obtain an abnormal classification result; and determining a final judgment result according to the curve comprehensive score and the anomaly classification result. According to the invention, comprehensive and systematic whole-process quantitative evaluation of the tightening curve is realized, and the quality of tightening operation can be evaluated more accurately and objectively.

Description

Technical Field

[0001] This application relates to the field of tightening operation quality assessment, specifically to a method, apparatus, equipment, and storage medium for determining a comprehensive score of tightening curves. Background Technology

[0002] In industrial production, tightening is a crucial step in mechanical assembly, widely used in industries such as automotive manufacturing, aerospace, and precision instruments. Its quality directly impacts product safety, reliability, and lifespan. Traditionally, tightening quality is judged by whether the final torque or angle reaches a preset range. However, in actual production, relying solely on endpoint parameters is insufficient to fully reflect the dynamic characteristics and potential defects of the tightening process. Therefore, it is necessary to evaluate and analyze the tightening process to ensure its quality and guarantee product reliability.

[0003] Currently, common methods for assessing the quality of tightening operations mainly involve using sensors to collect torque and angle data during the tightening process and judging compliance based on set thresholds. Alternatively, torque and angle data can be plotted as tightening curves, and manual comparison of the curves' shapes can be used to identify obvious abnormal patterns.

[0004] However, current evaluation methods mostly focus on the local characteristics or endpoint state of the tightening curve, lacking a systematic deconstruction and comprehensive analysis of the characteristics of each stage of the curve. Furthermore, manual comparison and identification are easily influenced by individual subjective experience, and different evaluators may draw different conclusions about the same tightening curve. Therefore, existing technologies lack a comprehensive and systematic evaluation system for tightening curves, making it impossible to accurately and objectively assess the quality of tightening operations. Summary of the Invention

[0005] This application provides a method, apparatus, equipment, and storage medium for determining the comprehensive score of tightening curves, which can solve the technical problem in the prior art of lacking a comprehensive and systematic evaluation system for tightening curves and being unable to accurately and objectively assess the quality of tightening operations.

[0006] In a first aspect, embodiments of this application provide a method for determining a comprehensive score of a tightening curve, including: The torque and angle data of the target object during the tightening operation are collected to generate a tightening curve, and the tightening curve is divided into stage curves based on the degree of tightening during the tightening operation. Calculate the curve quantification characteristics of each stage curve, calculate the overall slope characteristics of the tightening curve, and obtain the comprehensive score of the tightening curve by weighted quantitative scoring of the curve quantification characteristics and the overall slope characteristics based on the preset scoring rules. Anomaly classification results are obtained by classifying anomalies based on curve quantification features and preset feature thresholds. The final judgment result is determined based on the comprehensive score of the curve and the anomaly classification results.

[0007] In conjunction with the first aspect, in one implementation, the tightening curve is divided into stage curves based on the degree of tightening during the tightening operation, including: Based on the degree of tightening during the tightening operation, the tightening curve is divided into the pre-tightening stage curve, the final tightening stage curve, and the tightening completion stage curve. The degree of tightening is determined based on torque and angle data. The final tightening stage curve includes curve points from the end of the pre-tightening stage curve to the peak torque value.

[0008] In conjunction with the first aspect, in one implementation, a comprehensive score for the tightening curve is obtained by weighted quantitative scoring of the curve's quantitative features and overall slope features based on preset scoring rules, including: Quantitative scoring is performed based on the curve's quantitative characteristics, overall slope characteristics, and corresponding preset feature reference values ​​to obtain scores for each feature. The feature scores are weighted and merged according to the preset importance weights corresponding to each feature score to obtain the curve comprehensive score; The preset feature reference values ​​include the maximum and minimum feature values.

[0009] In conjunction with the first aspect, in one implementation, the curve quantification features include the slope of the stage curve, the projection ratio, the number of steep descents, the number of flat descents, the proportion of flat length, the viscosity, the number of viscosity-slip descents, and the proportion of viscosity-slip length. The overall slope characteristics include the overall curve slope, the overall slope change rate, and the overall window slope.

[0010] In conjunction with the first aspect, in one implementation, torque and angle data are collected during the tightening operation of the target object to generate a tightening curve, including: Collect torque data, angle data, and corresponding timestamp information of the target object during tightening operations; An initial tightening curve is generated based on torque data, angle data, and timestamp information; The initial tightening curve is cleaned of invalid curves to obtain the final tightening curve.

[0011] In conjunction with the first aspect, in one implementation, the stage curve further includes a hat-finding stage curve, and the method further includes: The quantitative characteristics of hat-finding are calculated based on the hat-finding stage curve, and the deduction items for the comprehensive score of tightening curve are determined based on the quantitative characteristics of hat-finding.

[0012] In conjunction with the first aspect, in one implementation method, the final judgment result is determined based on the curve comprehensive score and the anomaly classification result, including: If the overall score of the curve is lower than the preset passing score or the abnormality classification result is that any one of the abnormalities exists, the final judgment result is that the tightening curve is unqualified.

[0013] Secondly, embodiments of this application provide a tightening curve comprehensive scoring and determination device, comprising: The stage division module is used to collect torque and angle data during the tightening operation of the target object to generate a tightening curve, and divide the tightening curve into stage curves based on the degree of tightening during the tightening operation. The quantitative scoring module is used to calculate the curve quantitative characteristics of each stage curve, calculate the overall slope characteristics of the tightening curve, and perform weighted quantitative scoring on the curve quantitative characteristics and overall slope characteristics based on preset scoring rules to obtain the comprehensive score of the tightening curve. The anomaly classification module is used to classify anomalies based on curve quantization features and preset feature thresholds to obtain anomaly classification results. The curve determination module is used to determine the final determination result based on the comprehensive curve score and the anomaly classification result.

[0014] Thirdly, embodiments of this application provide a tightening curve comprehensive scoring determination device, which includes a processor, a memory, and a tightening curve comprehensive scoring determination program stored in the memory and executable by the processor. When the tightening curve comprehensive scoring determination program is executed by the processor, it implements the steps of the tightening curve comprehensive scoring determination method as described above.

[0015] Fourthly, embodiments of this application provide a computer-readable storage medium storing a tightening curve comprehensive scoring determination program, wherein when the tightening curve comprehensive scoring determination program is executed by a processor, it implements the steps of the tightening curve comprehensive scoring determination method as described above.

[0016] The beneficial effects of the technical solutions provided in this application include: This application divides the tightening curve into multiple stages, calculates the quantitative characteristics of the curve at each stage and the overall slope characteristics at the overall level, and applies a weighted quantitative score to each characteristic to obtain a comprehensive score for the tightening curve. Simultaneously, it combines abnormal risk classification to determine the final judgment result of the tightening curve. This achieves a comprehensive and systematic quantitative evaluation of the entire tightening process, enabling a more accurate and objective assessment of the quality of tightening operations. Attached Figure Description

[0017] Figure 1 This is a flowchart illustrating an embodiment of the tightening curve comprehensive scoring method of this application; Figure 2 This is a schematic diagram of the process for generating a tightening curve according to an embodiment of this application; Figure 3 This is a schematic diagram of the process for weighted quantitative scoring of the tightening curve in an embodiment of this application; Figure 4 This is a schematic diagram of the functional modules of an embodiment of the tightening curve comprehensive scoring and determination device of this application; Figure 5 This is a schematic diagram of the hardware structure of the tightening curve comprehensive scoring and determination device involved in the embodiment of this application. Detailed Implementation

[0018] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present application.

[0019] First, some of the technical terms used in this application will be explained to help those skilled in the art understand this application.

[0020] Tightening curve: refers to a set of data collected at a fixed frequency (e.g., 0.01 seconds) during the bolt tightening process, which is a combination of real-time values ​​from sensors such as torque and angle of the tightening tool.

[0021] To make the objectives, technical solutions, and advantages of this application clearer, the embodiments of this application will be described in further detail below with reference to the accompanying drawings.

[0022] Firstly, embodiments of this application provide a method for determining a comprehensive score of a tightening curve.

[0023] In one embodiment, reference is made to Figure 1 , Figure 1 This is a flowchart illustrating an embodiment of the tightening curve comprehensive scoring method of this application. Figure 1 As shown, the comprehensive scoring method for tightening curves includes: S101. Collect torque and angle data of the target object during tightening operation to generate a tightening curve, and divide the tightening curve into stage curves based on the degree of tightening during the tightening operation. S102. Calculate the curve quantification characteristics of each stage curve, calculate the overall slope characteristics of the tightening curve, and obtain the comprehensive score of the tightening curve by weighted quantitative scoring of the curve quantification characteristics and the overall slope characteristics based on the preset scoring rules. S103. Based on the curve quantification features and preset feature thresholds, perform anomaly risk classification to obtain anomaly classification results; S104. Determine the final judgment result based on the comprehensive score of the curve and the anomaly classification results.

[0024] Specifically, in the comprehensive scoring method for tightening curves proposed in this application, the embodiment first collects torque and angle data of the target object to be evaluated during tightening operations, and generates a tightening curve by combining the timestamp information corresponding to each data point. Then, based on the degree of tightening during the tightening process, the tightening curve is divided into various stage curves, including the pre-tightening stage, the final tightening stage, and the tightening completion stage.

[0025] The pre-tightening stage is the initial step in bolt connection. The torque applied during this stage is primarily to overcome the friction between the threads and the resistance to thread formation or locking. The final tightening stage begins after the pre-tightening and continues until the peak torque is reached. This stage mainly aims to overcome the friction between the threads and apply the necessary clamping force. The final tightening stage begins after the final tightening and continues until the entire tightening process is complete. During this stage, the torque value decreases rapidly, while the angle value remains essentially constant, representing a stress relief process.

[0026] Furthermore, it should be noted that, in addition to the stages mentioned above, some embodiments may also include a nut-finding stage, which refers to the process of aligning the bolt with the nut. The nut-finding stage is not mandatory, as the bolts in some scenarios have already been pre-tightened and nut-finding is unnecessary.

[0027] Then, for each stage of the tightening curve, the corresponding curve quantification characteristics need to be calculated, including the stage curve slope, projection ratio, number of steep drops, number of flat drops, flat length ratio, viscosity, number of viscosity drops, and viscosity length ratio. For the overall tightening curve, the overall slope characteristics need to be calculated, including the overall curve slope, the overall slope change rate, and the overall window slope.

[0028] Then, based on the calculated features, the score value of each feature is calculated according to the set scoring rules, and the scores are weighted and merged together to obtain the curve comprehensive score.

[0029] It should be noted that, among all stages, the final tightening stage has the greatest impact on the tightening quality as it is the stage with the greatest impact on the tightening quality throughout the entire tightening process. Therefore, the final tightening stage has the highest weight among all stages.

[0030] Furthermore, for the obtained curve quantification features, it is necessary to compare each feature value with the set threshold range according to the defined anomaly and risk classification criteria to determine whether the curve has anomalies or risks. For each feature value, the set thresholds include risk thresholds and anomaly thresholds. The risk threshold indicates that when a feature value exceeds this threshold, there may be some risk, but it does not affect the final judgment result; it is only used to generate log information for reference in process analysis and improvement. The anomaly threshold indicates that when a feature value exceeds this threshold, the tightening curve is abnormal and the test fails.

[0031] Finally, the final judgment result of the tightening curve is determined by the comprehensive score of the comprehensive curve and the anomaly classification results. When the comprehensive score of the comprehensive curve does not reach the qualified score, or when the anomaly classification results determine that there is an anomaly, the final judgment result is that the tightening curve is unqualified and the tightening operation quality does not meet the standard.

[0032] In this embodiment, the tightening curve is divided into multiple stages. The quantitative characteristics of the curve at each stage and the overall slope characteristics at the overall level are calculated. A weighted quantitative score is applied to each characteristic to obtain a comprehensive score for the tightening curve. Simultaneously, anomaly risk classification is combined to determine the final judgment result of the tightening curve. This achieves a comprehensive and systematic quantitative evaluation of the entire tightening process, enabling a more accurate and objective assessment of the quality of the tightening operation.

[0033] Furthermore, in one embodiment, Figure 2 This is a schematic diagram of the process for generating a tightening curve according to an embodiment of this application, as shown below. Figure 2 As shown, torque and angle data are collected during the tightening operation of the target object to generate a tightening curve, including: S201. Collect torque data, angle data, and corresponding timestamp information of the target object during tightening operation; S202. Generate an initial tightening curve based on torque data, angle data, and timestamp information; S203. The initial tightening curve is cleaned by invalid curve cleaning to obtain the tightening curve.

[0034] Specifically, the embodiment involves installing devices such as torque sensors and angle sensors at the tightening site to collect torque and angle data in real time during the tightening process. This data is then correlated with timestamps to generate a tightening curve. This curve can also be generated in real time by the tightening equipment during operation and then transmitted externally in a specified format.

[0035] Then, the generated tightening curves need to be cleaned to filter out invalid curves. During the curve cleaning process, the algorithm identifies curves that are spinning idly, curves that are not fully tightened, and curves that are fully tightened but not properly tightened by judging the start and end states of the curves, and removes them from the data.

[0036] In this embodiment, curve cleaning can remove obviously unqualified curves in the tightening curve in the early stage, reducing the amount of calculation in the subsequent tightening curve analysis process.

[0037] Furthermore, in one embodiment, the tightening curve is divided into stage curves based on the degree of tightening during the tightening operation, including: Based on the degree of tightening during the tightening operation, the tightening curve is divided into the pre-tightening stage curve, the final tightening stage curve, and the tightening completion stage curve. The degree of tightening is determined based on torque and angle data. The final tightening stage curve includes curve points from the end of the pre-tightening stage curve to the peak torque value.

[0038] Furthermore, the stage curve also includes the cap-finding stage curve, and the comprehensive judgment and scoring method for the tightening curve also includes: The quantitative characteristics of hat-finding are calculated based on the hat-finding stage curve, and the deduction items for the comprehensive score of tightening curve are determined based on the quantitative characteristics of hat-finding.

[0039] Specifically, taking a single curve with 500 sampling points as an example, each point corresponds to an index, abbreviated as I, which is counted starting from 0. Here, T represents torque (Torque) and A represents angle (Angle).

[0040] In the stage division of tightening curves, the tightening curve can be divided into four stages according to the degree of tightening during the tightening operation: pre-tightening (Pre), final tightening (Fin), and tightening completion (Com). Tightening is determined based on torque and angle data. Additionally, some tightening curves include a jog stage, but the jog stage is not mandatory because in some scenarios the bolts have already been pre-tightened and jog is unnecessary. Furthermore, the jog stage is only a deduction item in the subsequent comprehensive quantitative scoring of the tightening curve. The general principles for stage division are as follows: The "nut-finding" stage involves alternating positive and negative 180° rotations of the bolt to align it with the nut. In this embodiment, a stop torque is set based on the target torque, such as 0.255 Nm. Before the real-time torque falls below the stop torque, if two consecutive negative angles (i.e., reverse rotation) occur, and the value continuously decreases (actually, the reverse rotation angle increases), and then the angle becomes positive (i.e., forward rotation), it is considered that one nut-finding operation has been performed. The nut-finding stage and the number of nut-finding operations are identified using this method.

[0041] The pre-tightening stage is the initial step in a bolted connection, where the bolt or nut first contacts the component being fastened, but the necessary clamping force has not yet been applied. The torque applied in this stage is mainly to overcome the friction between the threads and the resistance to thread formation or locking.

[0042] The steps for dividing the pre-tightening stage are as follows: First, determine the starting point of pre-tightening: if there is a cap-finding stage, the end of the cap-finding stage is the starting point of pre-tightening; if there is no cap-finding stage, the starting point of the curve index is the starting point of pre-tightening. Then, determine the ending point of the pre-tightening stage as follows: First, find the peak torque index in the tightening curve. From this, we can know the cumulative angle value corresponding to the index point. Subtract the final tightened angle value from the cumulative angle value. Calculate the angle difference In peak torque index Find the cumulative angle value at which the angle recording begins. The first index value This is the index for the end of the pre-tightening stage.

[0043] The final tightening stage refers to the period from the end of pre-tightening until the torque reaches its peak. During this stage, the main task is to overcome the friction between the threads and apply the necessary clamping force.

[0044] The final tightening stage refers to the period from the end of the final tightening to the completion of the entire tightening process. During this stage, the torque value decreases rapidly, while the angle value remains essentially unchanged; this is a process of releasing stress.

[0045] In this embodiment, by dividing the tightening curve into multiple stages, a more comprehensive and systematic quantitative evaluation of the entire tightening process can be performed in subsequent analysis.

[0046] Furthermore, in one embodiment, Figure 3 This is a schematic diagram of the process for weighted quantitative scoring of the tightening curve in an embodiment of this application, as shown below. Figure 3 As shown, a comprehensive score for the tightening curve is obtained by weighting and quantitatively scoring the curve's quantitative features and overall slope features based on preset scoring rules, including: S301. Quantitative scoring is performed based on the curve quantification features, overall slope features, and corresponding preset feature reference values ​​to obtain the scores for each feature. S302. The feature scores are weighted and merged according to the preset importance weights corresponding to each feature score to obtain the curve comprehensive score; The preset feature reference values ​​include the maximum and minimum feature values.

[0047] Furthermore, in one embodiment, the curve quantification features include the slope of the stage curve, the projection ratio, the number of steep descents, the number of flattenings, the proportion of flattening length, the stickiness, the number of stickinesses, and the proportion of stickiness length. The overall slope characteristics include the overall curve slope, the overall slope change rate, and the overall window slope.

[0048] Specifically, after the phase division is completed, it is necessary to calculate various features that characterize the quality of the tightening operation for each phase and the overall curve.

[0049] It should be noted that the tightening curve in this application includes information in three dimensions: torque, angle, and time. The characteristics of the torque-angle curve and the torque-time curve were comprehensively analyzed during the analysis process.

[0050] For each stage of tightening curves, the quantitative characteristics of the curves include the stage curve slope, projection ratio, number of steep drops, number of flat drops, percentage of flat length, viscosity, number of stick-slips, and percentage of stick-slip length.

[0051] The slope of the stage curve refers to the change in torque per unit time (calculated by the number of curve points) or per unit angle, usually the latter. By monitoring the change in this characteristic value, it is determined whether the bolt has been "tightened in place," and the tightening quality is also fed back.

[0052] Projection ratio refers to the proportion of the projection length of the pre-tightening, final tightening, and tightening completion stages in the entire tightening curve.

[0053] The number of steep descents refers to a sudden drop in torque values ​​at several adjacent points (at least 3 points) on the torque-time curve after a gradual upward trend, with the difference in the drop exceeding the steep descent torque threshold. The steep descent torque threshold is taken as 10% of the peak torque of the curve. Each occurrence that meets the criteria is counted as one.

[0054] The flattening count refers to the number of times the torque difference between two adjacent points in the tightening curve is less than the flattening torque threshold. The flattening torque threshold is 1% of the peak torque of the curve, and the number of times the flattening count occurs is counted as 1 if this situation occurs at 3 consecutive points.

[0055] The percentage of flat length refers to the percentage of the total number of flat points in the projected length of the entire tightening curve.

[0056] In determining the number of stick-slip occurrences, the stick-slip torque threshold is 0.15 Nm, or 0.5% of the peak torque. During the pre-tightening, final tightening, and tightening completion stages, the absolute value of the difference between two adjacent points is determined. If it is greater than the stick-slip torque threshold and the torque increases first and then decreases, it is counted as one stick-slip occurrence.

[0057] The stick-slip length ratio refers to the proportion of the cumulative stick-slip points in the total projected length of the entire tightening curve during the number of stick-slip cycles.

[0058] Stickiness refers to the ratio of the sum of the absolute values ​​of the differences between the peak torque point and the starting horizontal point in the stickiness-slip count calculation to 5% of the current maximum value.

[0059] For the overall tightening curve, the overall slope characteristics include the overall curve slope, the overall slope change rate, and the overall window slope.

[0060] The rate of change of slope is calculated by taking the second derivative of torque with respect to angle, which reflects the rate of change of the first derivative. For discrete points, the second derivative is approximated using a "second-order difference": Mole: Second-order difference of torque (Reflects the change in the rate of torque change); Denominator: Square of the average angle difference (in approximate continuous functions) ).

[0061] Overall window slope: The slope of the curve calculated by the specified angle difference (default is 16°).

[0062] Furthermore, if a cap-finding phase exists, the number of cap-finding attempts and the cap-finding efficiency need to be calculated as the characteristic curve features of the cap-finding phase. The number of cap-finding attempts is only for display and does not contribute to the score; the cap-finding efficiency is used to calculate the deduction item in the overall score of the tightening curve.

[0063] The number of times the cap is searched refers to the number of times the cap is searched, which is calculated by monitoring the changes in the angle value.

[0064] Hat-finding efficiency is the percentage of the hat-finding process (from the first negative angle to the last negative angle) in the entire hat-finding phase. The higher the percentage, the lower the efficiency. The number of hat-finding attempts can also reflect the efficiency of hat-finding from another perspective.

[0065] Then, during the scoring process, for each feature type, a maximum and minimum value are set as reference values ​​for calculating the score. The maximum and minimum values ​​for each feature can be adjusted according to different business needs. The calculated score also needs to be multiplied by a weight to obtain the final score value for that feature.

[0066] In the scoring process, the embodiment sets the total weight to 100, and the weights of each stage and the overall slope feature are set to 5 for finding the cap (calculating the deduction item), 20 for pre-tightening, 40 for final tightening, 20 for tightening completion, and 20 for the overall slope.

[0067] Final score It can be represented as:

[0068] in, This indicates the score for the pre-tightening stage. This indicates the score for the final tightening stage. This indicates the score for completing the tightening phase. This represents the score for the slope characteristic of the overall tightening curve. This represents the score during the hat-finding phase, and is used as a deduction item in the final score.

[0069] For each section, the score is a weighted sum of the scores for each feature. This applies to the three stages: pre-tightening, final tightening, and tightening completion. For each feature type, slope and projection percentage are given higher weights because they have greater reference value in assessing tightening quality. In the cap-finding stage, only cap-finding efficiency is used to calculate the score; the number of cap-finding attempts is not used in the score calculation but is only displayed.

[0070] For the slope characteristics and projection ratio characteristics of the stage curves at each stage, as well as the overall curve slope and overall slope change rate of the overall tightening curve, there are maximum and minimum characteristic values ​​for scoring reference. Taking the slope characteristics of the pre-tightening stage as an example, the score can be expressed as:

[0071] in, Represents the slope characteristic value. This represents the maximum eigenvalue corresponding to the slope eigenvalue. This represents the minimum eigenvalue corresponding to the slope eigenvalue. This indicates the weighting of the slope feature during the pre-tightening stage. This indicates the weighting of the pre-tightening stage in the overall tightening curve score.

[0072] For the characteristics of steep descent frequency, flattening frequency, and stick-slip frequency at each stage, the minimum value of this type of feature is 0. Taking the steep descent frequency characteristic in the pre-tightening stage as an example, the score can be expressed as:

[0073] in, This represents the characteristic value of the number of steep drops. This represents the maximum value of the feature corresponding to the number of steep drops. This indicates the weighting percentage of the steep descent frequency characteristic during the pre-tightening stage.

[0074] For the flat length ratio, stickiness, and stickiness length ratio characteristics at each stage, the maximum value is 1, and the minimum value is 0. Taking the flat length ratio characteristic in the pre-tightening stage as an example, the score can be expressed as:

[0075] in, This represents the characteristic value indicating the proportion of flat length. This indicates the weighting of the flat length percentage feature value during the pre-tightening stage.

[0076] For the overall window slope characteristic of the overall tightening curve, considering its different properties from other characteristics, the score calculation can be expressed as follows:

[0077] in, This represents the overall window slope characteristic. The largest eigenvalue representing the overall window slope feature. This indicates the weighting of the overall window slope feature within the overall slope feature. This indicates the weight of the overall slope feature in the overall tightening curve score.

[0078] Furthermore, during the hat-finding phase, the score of the hat-finding efficiency feature can be expressed as:

[0079] in, This represents the hat-finding efficiency eigenvalue. The largest eigenvalue represents the hat-finding efficiency feature. This indicates the weighting of the hat-finding efficiency feature in the hat-finding stage. This indicates the weighting of the cap-finding stage relative to the overall tightening curve score.

[0080] In this embodiment, by comprehensively considering multiple stages and characteristics of the tightening curve, a thorough and detailed analysis of the tightening process is conducted, avoiding the limitations of single-dimensional evaluation. By establishing a scientific and reasonable weight allocation for different characteristics, a comprehensive and systematic quantitative evaluation of the entire tightening process is achieved, enabling a more accurate and objective assessment of the quality of the tightening operation.

[0081] Furthermore, in one embodiment, determining the final judgment result based on the curve comprehensive score and the anomaly classification result includes: If the overall score of the curve is lower than the preset passing score or the abnormality classification result is that any one of the abnormalities exists, the final judgment result is that the tightening curve is unqualified.

[0082] Specifically, in addition to the comprehensive score of the tightening curve, the embodiment also performs anomaly risk classification, and combines the comprehensive score of the tightening curve and the anomaly risk classification to determine the final judgment result.

[0083] Among them, the abnormal risk classification sets thresholds for each feature value, including risk thresholds and abnormal thresholds.

[0084] The embodiment compares the actual feature value with a set threshold. When the actual feature value reaches the risk threshold but not the anomaly threshold, the anomaly risk classification result is marked as having risk, but this does not affect the final judgment result; only the feature record is used as a reference value for subsequent analysis. When the actual feature value reaches the anomaly threshold, the anomaly risk classification result is marked as having an anomaly. In this case, due to the presence of an anomaly, the final judgment result is that the tightening curve is unqualified.

[0085] For example, for the number of steep drops during the pre-tightening stage, the risk threshold is set to 1 time, and the abnormal threshold is set to 10 times. When the number of steep drops exceeds the risk threshold but does not meet the abnormal threshold, the abnormal risk classification result is "risk exists"; when the number of steep drops exceeds the abnormal threshold, the abnormal risk classification result is "abnormal exists".

[0086] In the embodiments, the feature values ​​that need to be classified for abnormal risks also include features such as the number of stick-slip events, the number of flat events, the proportion of flat length, the slope, and the proportion of projection at each stage.

[0087] It's important to note that the number of times the flattening occurs and the percentage of flattening length are used together to classify abnormal risks. Taking the pre-tightening stage as an example, if the number of times the flattening occurs is greater than 1 (risk threshold) and the percentage of flattening length is greater than 0.1 (risk threshold), a risk is considered to exist. At this point, the torque value at the 20th point in the pre-tightening stage is assessed. If it is greater than 1 Nm, the risk type is considered "pre-tightening flat, low torque value"; if it is less than or equal to 1 Nm, the risk type is considered "significant plateau period in pre-tightening". Furthermore, the process for determining whether the number of times the flattening occurs and the percentage of flattening length are abnormal is the same as the process for determining whether a risk exists, except that the criteria are now a number of times the flattening occurs greater than 10 (abnormal threshold) and a percentage of flattening length greater than 0.15 (abnormal threshold).

[0088] In addition, the risk assessment in the embodiment also includes risks such as: low cap-finding efficiency; final torque close to the upper limit; final torque close to the lower limit; final angle close to the upper limit; final angle close to the lower limit; suspected repeated tightening; angle release greater than 5° after tightening. These risks are only assessed by setting corresponding risk thresholds for the corresponding tightening curve characteristics, without setting abnormal thresholds.

[0089] Furthermore, when determining the final judgment result of each tightening curve, in addition to the curve comprehensive score and anomaly risk classification, the embodiment also incorporates information such as the tightening tool feedback result and the maximum torque value. However, it should be noted that once a tightening curve is determined to be unqualified based on the tightening tool feedback result and the maximum torque value, generally, the curve comprehensive score and anomaly risk classification process are no longer necessary. A tightening curve is considered unqualified if the tightening tool feedback result is unqualified, the maximum torque value is deemed unqualified, the curve comprehensive score is below the passing score of 60, or the anomaly classification result indicates the presence of any of the above conditions.

[0090] It should also be noted that the comprehensive curve score obtained in this application, in addition to determining whether the tightening curve is qualified, can be further graded, such as: 90 to 100 points for excellent, 80 to 90 points for good, 70 to 80 points for average, and 60 to 70 points for poor. The graded comprehensive tightening curve score can be used in tightening operation-related analysis applications. For example, when improving the tightening operation process, the grading of the comprehensive curve score and the abnormal risk classification results can be combined. If the tightening curve score of a certain tightening operation is poor, or if the characteristic value is determined to be risky, then the tightening operation needs further analysis to improve the process flow. Alternatively, if the tightening curve score of a certain tightening operation is excellent, and the characteristic value is determined to be risk-free, then the operation quality of the tightening operation is high, and it can be used as a reference for process improvement as a high-quality operation process.

[0091] In this embodiment, the final judgment result of the tightening curve is determined by combining the curve comprehensive score and the anomaly classification result, which further improves the accuracy of identifying tightening operations with potential risks and ensures the reliability of the identification and assessment. At the same time, the quantitative scoring result can provide clear guidance for the optimization and improvement of the tightening process, which helps to improve production efficiency and product quality.

[0092] Secondly, embodiments of this application also provide a comprehensive scoring device for tightening curves.

[0093] In one embodiment, reference is made to Figure 4 , Figure 4 This is a functional module diagram of an embodiment of the tightening curve comprehensive scoring and determination device of this application. Figure 4 As shown, the tightening curve comprehensive scoring and judgment device includes: The stage division module 401 is used to collect torque and angle data during the tightening operation of the target object to generate a tightening curve, and divide the tightening curve into stage curves based on the degree of tightening during the tightening operation. The quantitative scoring module 402 is used to calculate the curve quantitative characteristics of each stage curve, calculate the overall slope characteristics of the tightening curve, and perform weighted quantitative scoring on the curve quantitative characteristics and overall slope characteristics based on preset scoring rules to obtain the comprehensive score of the tightening curve. Anomaly classification module 403 is used to classify anomalies based on curve quantization features and preset feature thresholds to obtain anomaly classification results. The curve determination module 404 is used to determine the final determination result based on the curve comprehensive score and the anomaly classification result.

[0094] The functions of each module in the above-mentioned tightening curve comprehensive scoring and judgment device correspond to the steps in the above-mentioned tightening curve comprehensive scoring and judgment method embodiment, and their functions and implementation processes will not be described in detail here.

[0095] Thirdly, embodiments of this application provide a comprehensive scoring device for tightening curves. The comprehensive scoring device for tightening curves can be a personal computer (PC), a laptop computer, a server, or other device with data processing capabilities.

[0096] Reference Figure 5 , Figure 5 This is a schematic diagram of the hardware structure of the tightening curve comprehensive scoring and determination device involved in the embodiments of this application. In the embodiments of this application, the tightening curve comprehensive scoring and determination device may include a processor, a memory, a communication interface, and a communication bus.

[0097] The communication bus can be of any type and is used to interconnect the processor, memory, and communication interface.

[0098] The communication interface includes input / output (I / O) interfaces, physical interfaces, and logical interfaces used for interconnecting components within the tightening curve comprehensive scoring and judging device, as well as interfaces used for interconnecting the tightening curve comprehensive scoring and judging device with other devices (such as other computing devices or user equipment). Physical interfaces can be Ethernet interfaces, fiber optic interfaces, ATM interfaces, etc.; user equipment can be displays, keyboards, etc.

[0099] Memory can be various types of storage media, such as random access memory (RAM), read-only memory (ROM), non-volatile RAM (NVRAM), flash memory, optical storage, hard disk, programmable ROM (PROM), erasable PROM (EPROM), electrically erasable PROM (EEPROM), etc.

[0100] The processor can be a general-purpose processor, which can call the tightening curve comprehensive scoring determination program stored in the memory and execute the tightening curve comprehensive scoring determination method provided in the embodiments of this application. For example, the general-purpose processor can be a central processing unit (CPU). The method executed when the tightening curve comprehensive scoring determination program is called can refer to the various embodiments of the tightening curve comprehensive scoring determination method of this application, and will not be repeated here.

[0101] Those skilled in the art will understand that Figure 5The hardware structure shown does not constitute a limitation of this application and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0102] Fourthly, embodiments of this application also provide a computer-readable storage medium.

[0103] The computer-readable storage medium of this application stores a tightening curve comprehensive scoring determination program, wherein when the tightening curve comprehensive scoring determination program is executed by a processor, it implements the steps of the tightening curve comprehensive scoring determination method as described above.

[0104] The method implemented when the tightening curve comprehensive scoring determination procedure is executed can be referred to in various embodiments of the tightening curve comprehensive scoring determination method of this application, and will not be repeated here.

[0105] It should be noted that the sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0106] The terms "comprising" and "having," and any variations thereof, in the specification, claims, and accompanying drawings of this application are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to such process, method, product, or apparatus. The terms "first," "second," and "third," etc., are used to distinguish different objects, etc., and do not indicate a sequence, nor do they limit "first," "second," and "third" to different types.

[0107] In the description of the embodiments of this application, terms such as "exemplary," "for example," or "for instance" are used to indicate examples, illustrations, or explanations. Any embodiment or design described as "exemplary," "for example," or "for instance" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of terms such as "exemplary," "for example," or "for instance" is intended to present the relevant concepts in a concrete manner.

[0108] In the description of the embodiments of this application, unless otherwise stated, " / " means "or". For example, A / B can mean A or B. The "and / or" in the text is merely a description of the relationship between related objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist simultaneously, and B exists alone. In addition, in the description of the embodiments of this application, "multiple" means two or more.

[0109] In some processes described in the embodiments of this application, multiple operations or steps are included in a specific order. However, it should be understood that these operations or steps may not be executed in the order they appear in the embodiments of this application, or they may be executed in parallel. The sequence number of the operation is only used to distinguish different operations, and the sequence number itself does not represent any execution order. In addition, these processes may include more or fewer operations, and these operations or steps may be executed sequentially or in parallel, and these operations or steps may be combined.

[0110] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes several instructions to cause a terminal device to execute the methods of the various embodiments of this application.

[0111] The above are merely preferred embodiments of this application and do not limit the patent scope of this application. Any equivalent structural or procedural transformations made using the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of this application.

Claims

1. A method for comprehensively evaluating tightening curves, characterized in that, include: Torque and angle data of the target object during tightening operation are collected to generate a tightening curve, and the tightening curve is divided into stage curves based on the degree of tightening during the tightening operation. Calculate the curve quantification features of each stage curve, calculate the overall slope features of the tightening curve, and obtain a comprehensive score for the tightening curve by weighted quantitative scoring of the curve quantification features and the overall slope features based on preset scoring rules. Anomaly classification results are obtained by classifying anomalies based on the curve quantization features and preset feature thresholds. The final judgment result is determined based on the comprehensive score of the curve and the anomaly classification result.

2. The method for determining the comprehensive score of tightening curves according to claim 1, characterized in that, The tightening curve is divided into stages based on the degree of tightening during the tightening operation, including: Based on the degree of tightening during the tightening operation, the tightening curve is divided into a pre-tightening stage curve, a final tightening stage curve, and a tightening completion stage curve. The tightening degree is determined based on the torque data and the angle data, and the final tightening stage curve includes curve points from the end of the pre-tightening stage curve to the peak torque value.

3. The method for determining the comprehensive score of tightening curves according to claim 1, characterized in that, The step of obtaining a comprehensive score for the tightening curve by weighting and quantitatively scoring the curve's quantitative features and the overall slope features based on preset scoring rules includes: Each feature score is obtained by quantitatively scoring the curve quantification features, the overall slope features, and the corresponding preset feature reference values. The feature scores are weighted and merged according to the preset importance weights corresponding to each feature score to obtain a curve comprehensive score; The preset feature reference values ​​include the maximum feature value and the minimum feature value.

4. The method for determining the comprehensive score of tightening curves according to claim 1, characterized in that, The curve quantification features include the slope of the stage curve, the proportion of projection, the number of steep drops, the number of flat spots, the proportion of flat length, the viscosity, the number of stick-slips, and the proportion of stick-slip length. The overall slope characteristics include the overall curve slope, the overall slope change rate, and the overall window slope.

5. The method for determining the comprehensive score of tightening curves according to claim 1, characterized in that, The process of collecting torque and angle data during the tightening operation of the target object to generate a tightening curve includes: Collect torque data, angle data, and corresponding timestamp information of the target object during tightening operations; An initial tightening curve is generated based on the torque data, the angle data, and the timestamp information; The initial tightening curve is cleaned of invalid curves to obtain the tightening curve.

6. The method for determining the comprehensive score of tightening curves according to claim 1, characterized in that, The stage curve also includes a hat-finding stage curve, and the method further includes: The cap-finding quantitative characteristics are calculated based on the cap-finding stage curve, and the deduction items for the comprehensive score of the tightening curve are determined based on the cap-finding quantitative characteristics.

7. The method for determining the comprehensive score of tightening curves according to claim 1, characterized in that, The step of determining the final judgment result based on the comprehensive score of the curve and the anomaly classification result includes: If the overall score of the curve is lower than the preset passing score or the abnormality classification result indicates the presence of any abnormality, the final judgment result is that the tightening curve is unqualified.

8. A comprehensive scoring and determination device for tightening curves, characterized in that, include: The stage division module is used to collect torque and angle data during the tightening operation of the target object to generate a tightening curve, and divide the tightening curve into stage curves based on the degree of tightening during the tightening operation. The quantitative scoring module is used to calculate the curve quantitative characteristics of each stage curve, calculate the overall slope characteristics of the tightening curve, and perform weighted quantitative scoring on the curve quantitative characteristics and the overall slope characteristics based on preset scoring rules to obtain a comprehensive score of the tightening curve. The anomaly classification module is used to classify anomaly risks based on the curve quantization features and preset feature thresholds to obtain anomaly classification results; The curve determination module is used to determine the final determination result based on the comprehensive score of the curve and the anomaly classification result.

9. A comprehensive scoring and evaluation device for tightening curves, characterized in that, The tightening curve comprehensive scoring and determination device includes a processor, a memory, and a tightening curve comprehensive scoring and determination program stored in the memory and executable by the processor, wherein when the tightening curve comprehensive scoring and determination program is executed by the processor, it implements the steps of the tightening curve comprehensive scoring and determination method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a tightening curve comprehensive scoring determination program, wherein when the tightening curve comprehensive scoring determination program is executed by a processor, it implements the steps of the tightening curve comprehensive scoring determination method as described in any one of claims 1 to 7.

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