An intelligent detection system and method for integrally stamped composite springs

Abstract

The present invention relates to the field of spring detection technology, and in particular to an intelligent detection system and method for an integrally stamped composite spring. The system comprises: a data acquisition module; a primary detection module for performing a primary detection on the composite spring to obtain detection data; a processing and analysis module for determining the state of the composite spring according to the detection abnormality and abnormal correlation, and determining a processing method according to the composite spring state; a secondary detection module for determining a simulation method according to the complexity of the working condition and the multi-directional uniformity in the secondary detection analysis, and determining an application setting method according to a use influence threshold; a non-destructive detection module for determining a non-destructive detection method according to a deformation coefficient and a relaxation slip coefficient, and determining an adjustment method according to the detection point correlation and an instability threshold. The present invention can improve the detection accuracy of the composite spring.

Description

Technical Field

[0001] The present invention relates to the technical field of spring detection, and in particular to an intelligent detection system and method for an integrally stamped composite spring. Background Art

[0002] In modern industrial manufacturing, integrally stamped composite springs, due to their unique advantages, have become indispensable key components in many industries. However, during the composite spring manufacturing process, fluctuations in material properties, difficulty in precisely controlling stamping process parameters, and differences in heat treatment processes can lead to significant deviations in the spring's mechanical properties. Therefore, how to test composite springs to improve detection accuracy is a technical problem that needs to be urgently addressed by those skilled in the art.

[0003] Chinese patent application CN118549068A discloses a tool for testing composite parameters of springs, comprising: a support plate; a spring support rod; a guide rail; a telescopic mechanism; a fixing mechanism; the right surface of the support plate is fixedly connected to the spring support rod, the right surface of the support plate is fixedly connected to the guide rail, the support plate spring support rod is provided with a telescopic mechanism, the telescopic mechanism is provided with a fixing mechanism, the telescopic mechanism includes a movable rail, the movable rail passes through the guide rail and is slidably connected to the guide rail, the right surface of the movable rail is fixedly connected to the left surface of the movable plate, the tool for testing composite parameters of springs, by using the arrangement of the support plate, the spring support rod, the guide rail, and the pitch measuring block, realizes the same-station composite detection of the number of turns, outer diameter, spacing, and free length, reduces the time of switching detection tools, and can simultaneously detect the contour of the spring lift and quickly determine whether the spring is qualified. It can be seen that the above technical solution has the following problems: it is unable to simulate the actual use scenario of the composite spring, resulting in poor detection accuracy of the composite spring. Summary of the Invention

[0004] To this end, the present invention provides an intelligent detection system and method for an integrally stamped composite spring to overcome the problems in the prior art.

[0005] To achieve the above objectives, the present invention provides an intelligent detection system for an integrally stamped composite spring, comprising:

[0006] Data acquisition module, used to obtain operation monitoring data;

[0007] A primary inspection module, used to perform a primary inspection on the composite spring to obtain inspection data;

[0008] a processing and analysis module connected to the primary detection module, configured to determine a state of the composite spring based on a degree of abnormality and an abnormality correlation, and to determine a processing method, based on the composite spring state, as secondary detection and analysis or adjustment of the fiber winding angle;

[0009] a secondary detection module, connected to the data acquisition module and the processing and analysis module, respectively, for determining a simulation method according to the complexity of the working condition and the multi-directional uniformity, and determining an application setting method according to a usage impact threshold, in the secondary detection and analysis;

[0010] The simulation mode is to determine the simulation application point according to the distance coefficient and the action similarity or to determine the application simulation mode according to the feature point category, the application simulation mode is interval application or continuous application, and the application setting mode is span adjustment detection or constant threshold detection;

[0011] A nondestructive testing module is connected to the secondary testing module and is used to determine, under preset testing conditions, whether the nondestructive testing method is to set nondestructive testing points in an associated manner or to set nondestructive testing points evenly according to the deformation coefficient and the relaxation and dislocation coefficient, and to determine, according to the correlation degree of the testing points and the instability threshold, whether the adjustment method is to adjust the gradient reference value or to perform local strengthening according to the defect coefficient.

[0012] Furthermore, when the composite spring state has a detection abnormality greater than or equal to a preset detection abnormality and an abnormality correlation greater than or equal to a preset abnormality correlation, the processing and analysis module determines that the processing method is to reduce the fiber winding angle.

[0013] The reduction value of the fiber winding angle is positively correlated with the abnormal coefficient.

[0014] Furthermore, when the composite spring state has a detection abnormality degree less than a preset detection abnormality degree or an abnormality correlation degree less than a preset abnormality correlation degree, the processing and analysis module determines that the processing method is secondary detection and analysis.

[0015] Furthermore, when the working condition complexity is less than the preset working condition complexity and the multidirectional uniformity is greater than or equal to the preset multidirectional uniformity, the secondary detection module determines that the simulation method is to determine the simulation application point according to the distance coefficient and the action similarity.

[0016] Furthermore, when the complexity of the working condition is greater than or equal to the preset complexity of the working condition or the multidirectional uniformity is less than the preset multidirectional uniformity, the secondary detection module determines that the simulation mode is to be applied according to the category of the feature points;

[0017] If the characteristic point type is a characteristic point whose action duration coefficient is less than the preset action duration coefficient or whose change response value is greater than or equal to the preset change response value, the application simulation mode is interval application;

[0018] If the feature point category is a second-category feature point whose action duration coefficient is greater than or equal to the preset action duration coefficient and whose change response value is less than the preset change response value, the application simulation mode is continuous application.

[0019] Furthermore, the secondary detection module determines the application setting mode according to the usage impact threshold, including:

[0020] If the usage impact threshold is greater than or equal to the preset usage impact threshold, the setting mode applied is span adjustment detection;

[0021] If the usage impact threshold is less than the preset usage impact threshold, the setting mode applied is constant threshold detection.

[0022] Furthermore, the nondestructive testing module determines a nondestructive testing method according to the deformation coefficient and the relaxation dislocation coefficient, including:

[0023] If the deformation coefficient is greater than or equal to the preset deformation coefficient or the relaxation displacement coefficient is greater than or equal to the preset relaxation displacement coefficient, the non-destructive testing method is to set the non-destructive testing point in association;

[0024] If the deformation coefficient is less than the preset deformation coefficient and the relaxation displacement coefficient is less than the preset relaxation displacement coefficient, the nondestructive testing method is to evenly set the nondestructive testing points.

[0025] Furthermore, the nondestructive testing module determines that the adjustment method is to reduce the gradient reference value when the detection point correlation degree is greater than or equal to the preset detection point correlation degree and the instability threshold is greater than or equal to the preset instability threshold;

[0026] The reduction value of the gradient reference value is positively correlated with the comprehensive evaluation coefficient.

[0027] Furthermore, when the detection point correlation degree is less than a preset detection point correlation degree or the instability threshold is less than a preset instability threshold, the nondestructive testing module determines that the adjustment method is to perform local strengthening according to the defect coefficient.

[0028] The present invention also provides an intelligent detection method for an integrally stamped composite spring, comprising:

[0029] Acquire operation monitoring data and perform a test on the composite spring to obtain test data;

[0030] Determine the composite spring status based on the abnormality degree and abnormality correlation, and determine the treatment method based on the composite spring status, such as secondary detection and analysis or adjustment of the fiber winding angle;

[0031] In the secondary detection analysis, the simulation method is determined according to the complexity of the working conditions and the degree of multi-directional uniformity, and the application setting method is determined according to the use impact threshold;

[0032] The simulation mode is to determine the simulation application point according to the distance coefficient and the action similarity or to determine the application simulation mode according to the feature point category, the application simulation mode is interval application or continuous application, and the application setting mode is span adjustment detection or constant threshold detection;

[0033] Under the preset detection conditions, the non-destructive testing method is determined as associated setting of non-destructive testing points or uniform setting of non-destructive testing points according to the deformation coefficient and the relaxation dislocation coefficient, and the adjustment method is determined as adjustment based on the gradient reference value or local strengthening based on the defect coefficient according to the correlation degree of the detection points and the instability threshold.

[0034] Compared with the prior art, the beneficial effect of the present invention lies in that, in the technical solution of the present invention, the basic data of the composite spring is obtained through a single detection, and the state of the composite spring is determined based on the detection abnormality and abnormal correlation. The detection abnormality and abnormal correlation effectively reflect the initial performance and potential problems of the composite spring, and then different processing methods are adaptively selected according to the state of the composite spring, so that the selection of processing method is more in line with the actual application scenario, and the material ratio can be adjusted to improve the spring performance; through secondary detection and analysis, further in-depth detection can be carried out to accurately locate the fault point or performance deficiency, providing a basis for subsequent precise repair or improvement.

[0035] Furthermore, the present invention effectively determines the complexity of the working conditions and the uniformity of the composite spring through the complexity of the working conditions and the multi-directional uniformity, and then adaptively selects different simulation methods according to the complexity of the working conditions and the multi-directional uniformity, so that the selection of simulation methods is more in line with the actual application scenario, and can improve the simulation efficiency while ensuring the accuracy of the simulation, which helps to improve the detection accuracy of the composite spring and thus improve the accuracy of quality control.

[0036] Furthermore, the present invention uses an influence threshold to effectively reflect the force characteristic conditions of the simulated application point, and then adaptively selects different application settings based on the use of the influence threshold. By using span adjustment detection, the force change process of the composite spring in actual work can be simulated, and its performance can be evaluated more comprehensively; by using constant threshold detection, the load-bearing capacity of the composite spring can be determined quickly and directly, which is beneficial to improving detection efficiency and detection accuracy.

[0037] Furthermore, in the present invention, the deformation coefficient and the detection abnormality are used to effectively reflect the defect state, and then different non-destructive testing methods are adaptively selected according to the deformation coefficient and the relaxation and displacement coefficient, so that the selection of non-destructive testing methods is more in line with the actual application scenario. The method of setting non-destructive testing points in an associated manner can focus on key parts according to the characteristics and distribution patterns of the defects. The method of evenly setting non-destructive testing points can avoid overly intensive and time-consuming testing of the entire spring while ensuring comprehensive testing.

[0038] Furthermore, the present invention effectively reflects the correlation degree of the detection results of each detection point and the degree of internal defects through the detection point correlation degree and the instability threshold, and then adaptively selects different adjustment methods according to the detection point correlation degree and the instability threshold, so that the selection of the adjustment method is more in line with the actual application scenario, thereby improving the production quality of the composite spring. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 This is a module connection diagram of the intelligent detection system for the integrally stamped composite spring of the present invention;

[0040] Figure 2 This is a flow chart of the present invention for determining a processing method according to a composite spring state;

[0041] Figure 3 This is a flow chart of the present invention for determining a simulation method based on the complexity of the working condition and the multi-directional uniformity;

[0042] Figure 4 Schematic diagram of the intelligent detection method of the integrally stamped composite spring of the present invention. DETAILED DESCRIPTION

[0043] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are merely used to explain the present invention and are not intended to limit the present invention.

[0044] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0045] It should be noted that, in the description of the present invention, terms such as "up", "down", "left", "right", "inside", and "outside" indicating directions or positional relationships are based on the directions or positional relationships shown in the accompanying drawings. This is only for the convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it cannot be understood as a limitation on the present invention.

[0046] Furthermore, it should be noted that, in the description of the present invention, unless otherwise expressly specified or limited, the terms "mounted," "connected," and "connected" should be understood in a broad sense. For example, they may refer to fixed connections, detachable connections, or integral connections; mechanical connections or electrical connections; direct connections or indirect connections through an intermediate medium; and internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on specific circumstances.

[0047] See also Figures 1 to 3 As shown, the present invention provides an intelligent detection system for an integrally stamped composite spring, comprising:

[0048] Data acquisition module, used to obtain operation monitoring data;

[0049] A primary inspection module, used to perform a primary inspection on the composite spring to obtain inspection data;

[0050] a processing and analysis module connected to the primary detection module, configured to determine a state of the composite spring based on a degree of abnormality and an abnormality correlation, and to determine a processing method, based on the composite spring state, as secondary detection and analysis or adjustment of the fiber winding angle;

[0051] a secondary detection module, connected to the data acquisition module and the processing and analysis module, respectively, for determining a simulation method according to the complexity of the working condition and the multi-directional uniformity, and determining an application setting method according to a usage impact threshold, in the secondary detection and analysis;

[0052] The simulation mode is to determine the simulation application point according to the distance coefficient and the action similarity or to determine the application simulation mode according to the feature point category, the application simulation mode is interval application or continuous application, and the application setting mode is span adjustment detection or constant threshold detection;

[0053] A nondestructive testing module is connected to the secondary testing module and is used to determine, under preset testing conditions, whether the nondestructive testing method is to set nondestructive testing points in an associated manner or to set nondestructive testing points evenly according to the deformation coefficient and the relaxation and dislocation coefficient, and to determine, according to the correlation degree of the testing points and the instability threshold, whether the adjustment method is to adjust the gradient reference value or to perform local strengthening according to the defect coefficient.

[0054] The application scenario of the present invention is the quality inspection of composite springs. In the present invention, several historical records are correspondingly provided. Any historical record records the detection abnormality, abnormal correlation, working condition complexity, multi-directional uniformity, distance coefficient and action similarity, etc. in the historical process of at least one quality inspection of the composite spring, and each historical record corresponds to a qualified mark. The qualified mark records whether the quality inspection process of the composite spring meets the user's requirements. The qualified mark can be recorded manually. It can be understood that the user can determine whether the quality inspection process of the composite spring meets the requirements based on self-set indicators. The self-set indicators can be but are not limited to the detection accuracy, which will not be elaborated here. Among them, the detection accuracy=the number of composite springs with accurate detection results / the total amount of composite springs tested;

[0055] The production process of the composite spring of the present invention includes:

[0056] Winding: The glass fiber is pulled into the glue pool through a guide plate, and the excess glue is scraped off and then twisted to form the inner core and the middle layer. The glass fiber is pulled into the glue pool by a high-precision guide plate with a tension of 5N. The glue pool is filled with epoxy resin glue with a viscosity of 500cPs. The temperature is controlled at 25±2℃ to maintain the stability of the glue. The fiber is dipped into the glue for 2 seconds. A double-roller scraping system is used to scrape off the excess glue. The fiber passes through a twister with a rotation speed of 500-2000rpm to form an inner core with 3 fiber winding layers. The fiber pulling speed is linked to the mold rotation speed to control the fiber angle at 45°.

[0057] Wrapping fixed layer: PE film, PET film, etc. are used as the inner fixed layer to wrap around the inner core to form a uniform winding layer. Fluorine rubber hose, PO hose, etc. are used as the outer support layer and embedded in the wrapped spring wire.

[0058] Heating and curing: Place the mold in a constant temperature box, set the initial heating temperature at 25°C, increase the temperature evenly to the final heating temperature, the heating time is 50 minutes, the final heating temperature is 150°C, and heat at the final heating temperature for 25 minutes for heating and curing.

[0059] The present invention is provided with a target coefficient and a related threshold value, and the corresponding relationship between the target coefficient and the related threshold value is expressed by a weight formula, and the weight formula is: target coefficient = weight coefficient × related threshold value. Specifically, the present invention records the reduction value of the fiber winding angle, the duration of the application cycle corresponding to a type of feature point, the value of w, the selection interval, the reduction value of the gradient reference value, and the increase value of the fiber winding layer number of the enhanced section as the target coefficient, and records the abnormal coefficient, the feature evaluation threshold value corresponding to a type of feature point, the length of the spiral line, the total number of points to be selected, the comprehensive evaluation coefficient, and the enhanced threshold value as the related threshold value. It can be understood that the target coefficients all have corresponding related relationships. Threshold, for example, the reduction value of the fiber winding angle is positively correlated with the abnormality coefficient, and the positive correlation between the reduction value of the fiber winding angle and the abnormality coefficient is expressed by a weight formula, and the value of the weight coefficient can be determined according to the user's historical experience based on the degree of influence of the abnormality coefficient on the reduction value of the fiber winding angle, and the value of the weight coefficient can be optimized based on the historical records of the quality inspection process of multiple composite springs combined with a multi-layer perceptron. The use of a multi-layer perceptron to optimize the value of the weight coefficient is content that is easy for technical personnel in this field to understand, and will not be elaborated on. The value principles of the weight coefficients corresponding to other target coefficients and related thresholds are the same, and will not be elaborated on here.

[0060] A single test is performed on composite springs, including:

[0061] For a single composite spring, the composite spring is placed in a target container with its central axis perpendicular to the ground. A pressure sensor is provided at the center of the bottom of the target container, and a displacement sensor is provided at any position on the top of the composite spring. The pressure head of the pressure device is controlled to apply a constant force to compress the composite spring at the center of the top of the composite spring, and the pressure value detected by the pressure sensor and the displacement amount detected by the displacement sensor are continuously recorded. When the height of the composite spring is one-third of the standard height, the compression is stopped and test data is obtained; the test data is the continuously recorded pressure value detected by the pressure sensor and the displacement amount detected by the displacement sensor;

[0062] The standard height is the length of the composite spring when it is placed in the target container and is not subject to external forces.

[0063] The target container is in the shape of a cylinder with openings at the top and bottom, and one opening is placed close to the ground. The diameter and height of the target container are set according to actual user needs. It needs to be ensured that the target container can accommodate the composite spring and that the center position of the bottom of the composite spring coincides with the center position of the target container when the composite spring is placed in the target container; the center position of the bottom of the target container is the center of the circle of the bottom of the target container, and the center position of the top of the composite spring is the center of the circle of the top of the composite spring when the composite spring is placed in the target container and the central axis of the composite spring is perpendicular to the ground.

[0064] The constant force can be set according to the quality requirements of the composite spring during the production process. In the present invention, the direction of the constant force is perpendicular to the ground and downward. A constant force value is provided, and the magnitude of the constant force is 50 Newtons.

[0065] The characteristic curve has the displacement detected by the displacement sensor as the x-axis and the pressure value detected by the pressure sensor as the y-axis. The specific characteristics of the characteristic curve are as follows: when x = 0, that is, when the composite spring is not compressed, the intersection of the curve and the y-axis is the pressure value of the pressure sensor when the composite spring is not compressed; as the displacement x continues to increase, the pressure value y also gradually increases until it reaches the maximum pressure value;

[0066] The preset detection condition is that the secondary anomaly coefficient is greater than the preset secondary anomaly coefficient.

[0067] Specifically, when the composite spring state has a detection abnormality greater than or equal to a preset detection abnormality and an abnormality correlation greater than or equal to a preset abnormality correlation, the processing and analysis module determines that the processing method is to reduce the fiber winding angle;

[0068] The reduction value of the fiber winding angle is positively correlated with the abnormal coefficient.

[0069] The composite springs with qualified test results in the historical records are recorded as qualified springs;

[0070] Divide the horizontal axis corresponding to the curve in the characteristic curve into n equal parts. The greater the user's demand for detection accuracy, the larger the value of n. Provide a value of n, n is 15;

[0071] The composite spring being tested is recorded as a target composite spring;

[0072] The detection abnormality degree is the average value of the sub-abnormality degrees corresponding to each equally divided point in the characteristic curve of the target composite spring. The sub-abnormality degree corresponding to a single equally divided point = the average value of the pressure values corresponding to the equally divided point in the characteristic curves of all qualified springs - the pressure value corresponding to the equally divided point in the characteristic curve of the target composite spring;

[0073] Abnormal correlation degree = 1 / (the maximum value of the correlation coefficients between the characteristic curve of the target composite spring and the characteristic curves of each qualified spring + 1);

[0074] The calculation formula for the correlation coefficient r corresponding to any two characteristic curves is:

[0075]

[0076] Where n is the number of equal points in a single characteristic curve; and are the pressure values corresponding to the i-th equally divided point in the two characteristic curves, for The average value of the pressure values corresponding to each equally divided point in the corresponding characteristic curve, for The average value of the pressure values corresponding to each equally divided point in the corresponding characteristic curve, i = 1, 2, 3, ..., n;

[0077] The values of the preset detection abnormality and the preset abnormality correlation can be determined by the user according to the actual application scenario. The greater the user's demand for improving the processing quality of the composite spring, the smaller the values of the preset detection abnormality and the preset abnormality correlation. A method for determining the values of the preset detection abnormality and the preset abnormality correlation is provided. The historical records of the user's reduction adjustment for the material ratio are detected, and the average values of the detection abnormality and the average values of the abnormality correlation corresponding to the historical records that can meet the user's needs are recorded as the preset detection abnormality and the preset abnormality correlation, respectively.

[0078] The fiber winding angle θ is the angle between the glass fiber direction and the spring axis, θ=arctan(π×D×Ω / v), D is the diameter of the composite spring, Ω is the mold rotation speed, and v is the fiber pulling speed.

[0079] It should be noted that the diameter of the composite spring is 0.02 m. When the fiber winding angle is reduced, D remains unchanged, and only Ω or v is adjusted. There is no restriction on the specific adjustment parameters as long as they can meet user needs. The initial mold rotation speed is 10 rad / s, and the initial fiber pulling speed is 1 m / s.

[0080] Abnormality coefficient = detection abnormality degree / preset detection abnormality degree + abnormality correlation degree / preset abnormality correlation degree.

[0081] Specifically, when the composite spring state has a detection abnormality degree less than a preset detection abnormality degree or an abnormality correlation degree less than a preset abnormality correlation degree, the processing and analysis module determines that the processing method is secondary detection and analysis.

[0082] Specifically, when the working condition complexity is less than the preset working condition complexity and the multidirectional uniformity is greater than or equal to the preset multidirectional uniformity, the secondary detection module determines the simulation method to determine the simulation application point according to the distance coefficient and the action similarity.

[0083] Among them, the present invention includes several operation monitoring data, a single operation monitoring data is a sub-monitoring data corresponding to each characteristic point of a single composite spring, the sub-monitoring data is the force value of a single characteristic point monitored in real time during the actual use of the composite spring as the use time increases, the number and position of the characteristic points corresponding to each composite spring are the same, the characteristic point is the position where the force sensor is installed in the composite spring, and the force value of the characteristic point is monitored by the force sensor. The user can install the force sensor at the fixed end and the loading end of the composite spring according to actual needs. The fixed end is the part of the composite spring that is fixed during installation and use, and the loading end is the part of the composite spring that is subjected to external force;

[0084] Working condition complexity = characteristic point reference value × characteristic point distribution coefficient, where the characteristic point reference value is the number of characteristic points in a single composite spring, and the characteristic point distribution coefficient is the average value of the distance reference values corresponding to each characteristic point. The distance reference value corresponding to a single characteristic point is the average value of the shortest distance from the characteristic point to all other characteristic points outside the characteristic point.

[0085] The multidirectional uniformity is the average of the sub-uniformities corresponding to each operation monitoring data. The sub-uniformity corresponding to a single operation monitoring data is 1 / (the standard deviation of the multi-point differences corresponding to each time point + 1). The multi-point difference corresponding to a single time point in a single operation monitoring data is the standard deviation of the force values corresponding to each feature point in the operation monitoring data at that time point. The time point is set by the user. A time point setting method is provided. The starting time of a single operation monitoring data is used as the starting point, and an interval point is set every 5 seconds in chronological order. The starting point and each interval point are recorded as time points.

[0086] The values of the preset working condition complexity and the preset multi-directional uniformity can be determined by the user according to the actual application scenario. The greater the user's demand for improving the simulation accuracy, the smaller the values of the preset working condition complexity and the preset multi-directional uniformity. A value of the preset working condition complexity and the preset multi-directional uniformity is provided, and the historical records of the user determining the simulation application point according to the distance coefficient and the action similarity are detected. The average value of the working condition complexity and the average value of the multi-directional uniformity corresponding to the historical records that can meet the user's needs are recorded as the preset working condition complexity and the preset multi-directional uniformity, respectively;

[0087] Determining the simulation application point according to the distance coefficient and the action similarity includes: performing association analysis on each feature point, when performing association analysis on a single feature point, recording the feature point as a target feature point, recording other feature points other than the feature point that are not recorded in the association combination as reference feature points, recording the reference feature points and the target feature points whose distance coefficients to the target feature point are less than a preset distance coefficient and whose action similarity is greater than a preset action similarity as an association combination, and continuing to perform association analysis on the feature points that are not recorded in the association combination until all feature points are recorded in the association combination, then stopping the association analysis; and taking any feature point in each association combination as a simulation application point, and each association combination corresponds to a simulation application point;

[0088] The distance coefficient corresponding to any two feature points is the shortest distance between the two feature points.

[0089] The action similarity between any two feature points = the number of time points with the same force value in the sub-monitoring data corresponding to the two feature points / the number of time points in a single sub-monitoring data;

[0090] The values of the preset distance coefficient and the preset action similarity can be determined by the user according to the actual application scenario. The greater the user's demand for improving the simulation accuracy, the smaller the value of the preset distance coefficient and the larger the value of the preset action similarity. A value of the preset distance coefficient and the preset action similarity is provided, and the average value of the reference distance coefficient and the average value of the reference action similarity corresponding to each historical record that can meet the user's needs are extracted and recorded as the preset distance coefficient and the preset action similarity respectively;

[0091] The reference distance coefficient is the distance coefficient corresponding to any two feature points in a single association combination of a single historical record, and the reference action similarity is the action similarity corresponding to any two feature points in a single association combination of a single historical record.

[0092] Specifically, when the working condition complexity is greater than or equal to the preset working condition complexity or the multidirectional uniformity is less than the preset multidirectional uniformity, the secondary detection module determines that the simulation mode is to be applied according to the feature point category;

[0093] If the characteristic point type is a characteristic point whose action duration coefficient is less than the preset action duration coefficient or whose change response value is greater than or equal to the preset change response value, the application simulation mode is interval application;

[0094] If the feature point category is a second-category feature point whose action duration coefficient is greater than or equal to the preset action duration coefficient and whose change response value is less than the preset change response value, the application simulation mode is continuous application.

[0095] The action duration coefficient corresponding to a single feature point is the average value of the sub-duration coefficients corresponding to each operation monitoring data. The sub-duration coefficient corresponding to a single operation monitoring data = the number of time points in the operation monitoring data at which the force value corresponding to the feature point is not 0 / the total number of time points in the operation monitoring data;

[0096] The change response value is the standard deviation of the force values corresponding to each time point of the feature point in the operation monitoring data;

[0097] During continuous application, each of the second-category feature points is used as a simulation application point within the detection time;

[0098] In the interval application, a type of feature point is used as a simulation application point within the feature time corresponding to the type of feature point;

[0099] The characteristic time corresponding to a single type of feature point is the time range that coincides with the characteristic time in the (2n+1)th application cycle, where n is 0, 1, 2, ..., n0, and n0 is the smallest integer greater than or equal to n1, and n1 = detection time / the duration of a single application cycle corresponding to the type of feature point. The user can determine the duration of the detection time based on actual detection requirements. A detection time value of 1 hour is provided.

[0100] In the present invention, each type of feature point is provided with a continuous cycle of application within the detection time. The duration of the application cycle corresponding to a single type of feature point is negatively correlated with the feature evaluation threshold corresponding to the type of feature point. The feature evaluation threshold corresponding to a single type of feature point = change response value / preset change response value - action duration coefficient / preset action duration coefficient.

[0101] The values of the preset action duration coefficient and the preset change response value can be determined by the user according to the actual application scenario. The greater the user's demand for improving the simulation accuracy, the smaller the value of the preset action duration coefficient and the larger the value of the preset change response value. A method for determining the values of the preset action duration coefficient and the preset change response value is provided. The historical records of interval application are detected, and the average value of the action duration coefficient and the average value of the change response value corresponding to the historical records that can meet the user's needs are recorded as the preset action duration coefficient and the preset change response value, respectively.

[0102] Specifically, the secondary detection module determines the application setting mode according to the usage impact threshold, including:

[0103] If the usage impact threshold is greater than or equal to the preset usage impact threshold, the setting mode applied is span adjustment detection;

[0104] If the usage impact threshold is less than the preset usage impact threshold, the setting mode applied is constant threshold detection.

[0105] The usage impact threshold corresponding to a single simulation application point is the average value of the sub-impact thresholds corresponding to each operation monitoring data of the simulation application point;

[0106] The sub-impact threshold corresponding to a single simulation application point in a single operation monitoring data = maximum duration ratio / preset maximum duration ratio + maximum force value / preset maximum force value;

[0107] Maximum duration ratio = the number of time points with maximum stress value in the sub-monitoring data corresponding to a single simulation application point / the total number of time points in the sub-monitoring data corresponding to a single simulation application point;

[0108] The maximum force value is the maximum value among the force values corresponding to each time point in the sub-monitoring data corresponding to a single simulation application point;

[0109] The value of the preset usage impact threshold can be determined by the user based on the actual application scenario. The larger the value of the preset usage impact threshold, the greater the user's need for constant threshold detection. A value of the preset usage impact threshold is provided, and the user's history of constant threshold detection is detected. The average value of the usage impact threshold corresponding to the historical records that can meet the user's needs is recorded as the preset usage impact threshold;

[0110] The values of the preset maximum duration ratio and the preset maximum force value can be determined by the user according to the actual application scenario. The larger the values of the preset maximum duration ratio and the preset maximum force value, the greater the user's need for constant threshold detection. Through a method for determining the values of the preset maximum duration ratio and the preset maximum force value, the average value of the maximum duration ratio and the average value of the maximum force value corresponding to the historical records that can meet the user's needs are recorded as the values of the preset maximum duration ratio and the preset maximum force value respectively;

[0111] In the span adjustment test, for a single simulated application point, the applied force at the simulated application point is increased from the initial force value to the maximum force value at a standard increase rate, and the force value remains unchanged when it reaches the maximum force value;

[0112] It should be noted that in the interval application, the application period of the applied force is recorded as the analysis period. For a single analysis period, the analysis period is recorded as the target period, and the analysis period adjacent to and after the target period is recorded as the adjacent period. The applied force at the start time of the adjacent period is the same as the applied force at the end time of the target period.

[0113] Constant threshold detection: for a single simulated application point, the applied force of the simulated application point is set to the maximum force value corresponding to the simulated application point, and the force value remains unchanged.

[0114] It is understandable that due to the different stress characteristics of different simulation application points, the corresponding detection requirements will also vary. For some application points with large forces or long durations, a more detailed detection process may be required to accurately evaluate their performance and impact. Span adjustment detection can provide more detailed detection results and is suitable for these situations; for application points with relatively small forces or short durations, constant threshold detection can complete the detection task quickly and efficiently to meet the corresponding needs.

[0115] The direction of the applied force corresponding to each simulated application point is parallel to the central axis of the target composite spring and the direction of the applied force at each simulated application point is the same;

[0116] A method for setting an initial force value and a standard increase rate is provided, wherein the initial force value is 0 N and the standard increase rate is 10 N / min; when applying force at each simulated application point of the composite spring, the force is applied by an electric push rod, which is easy for those skilled in the art to understand and will not be described in detail.

[0117] Secondary abnormal coefficient = deformation coefficient / preset deformation coefficient + relaxation dislocation coefficient / preset relaxation dislocation coefficient;

[0118] The value of the preset secondary abnormality coefficient can be determined by the user according to the actual application scenario. The greater the user's demand for improving the detection accuracy, the smaller the value of the preset secondary abnormality coefficient is. A value of the preset secondary abnormality coefficient is provided, and the historical records of the composite spring being judged as qualified are detected. The maximum value of the secondary abnormality coefficient corresponding to the historical records that can meet the user's needs is recorded as the preset secondary abnormality coefficient.

[0119] It should be noted that if the secondary abnormality coefficient is less than or equal to the preset abnormality influence coefficient, the test result of the target composite spring is determined to be qualified.

[0120] Specifically, the nondestructive testing module determines the nondestructive testing method according to the deformation coefficient and the relaxation dislocation coefficient, including:

[0121] If the deformation coefficient is greater than or equal to the preset deformation coefficient or the relaxation displacement coefficient is greater than or equal to the preset relaxation displacement coefficient, the non-destructive testing method is to set the non-destructive testing point in association;

[0122] If the deformation coefficient is less than the preset deformation coefficient and the relaxation displacement coefficient is less than the preset relaxation displacement coefficient, the nondestructive testing method is to evenly set the nondestructive testing points.

[0123] The helical wire of the composite spring is divided into w equal parts, the value of w being positively correlated with the length of the helical wire, and a displacement sensor is set at each equal dividing point. The helical wire of the composite spring is wound around the central axis of the composite spring to form a continuous helical line;

[0124] The deformation coefficient is the maximum value of the maximum displacements corresponding to each equally divided point, and the maximum displacement corresponding to a single equally divided point is the maximum value of the displacements corresponding to each reference time point during the monitoring time;

[0125] The relaxation dislocation coefficient is the average value of the relaxation reference values corresponding to each reference time point. The relaxation reference value corresponding to a single reference time point is the standard deviation of the displacement corresponding to each equally divided point at that reference time point.

[0126] The reference time point is set by the user. A method for setting the reference time point is provided. The starting moment of the detection time is set as the first starting point, and a first interval point is set every 10 seconds in chronological order. The first starting point and each first interval point are recorded as reference time points.

[0127] The values of the preset deformation coefficient and the preset relaxation dislocation coefficient can be determined by the user according to the actual application scenario. The smaller the values of the preset deformation coefficient and the preset relaxation dislocation coefficient, the greater the user's need to associate and set non-destructive testing points. A value of the preset deformation coefficient and the preset relaxation dislocation coefficient is provided, and the historical records of the user's association and setting of non-destructive testing points are detected. The average value of the deformation coefficient and the average value of the relaxation dislocation coefficient corresponding to the historical records that can meet the user's needs are recorded as the preset deformation coefficient and the preset relaxation dislocation coefficient respectively;

[0128] The points where the helical line of the composite spring is divided into w equal parts are recorded as points to be selected;

[0129] The non-destructive testing point is set in association, including: performing association testing on each to-be-selected point, when performing association testing on a single to-be-selected point, recording the to-be-selected point as a target to-be-selected point, recording other to-be-selected points other than the target to-be-selected point that are not recorded in the to-be-selected point combination as reference to-be-selected points, recording the reference to-be-selected points and the target to-be-selected point whose matching reference values with the target to-be-selected point are greater than a preset matching reference value into a to-be-selected point combination, and continuing to perform association testing on the to-be-selected points that are not recorded in the to-be-selected point combination until all to-be-selected points are recorded in the to-be-selected point combination; and selecting any to-be-selected point in each to-be-selected point combination as a non-destructive testing point, so that there is a non-destructive testing point in each to-be-selected point combination;

[0130] Evenly setting the non-destructive testing points includes: starting from the first to-be-selected point located on either side of the spiral line, performing interval selection on each to-be-selected point, recording each selected to-be-selected point as a non-destructive testing point, the selection interval being the number of to-be-selected points between two adjacent non-destructive testing points, and the selection interval being positively correlated with the total number of to-be-selected points;

[0131] The matching reference value corresponding to any two points to be selected = 1-(the absolute value of the difference between the evaluation coefficients corresponding to the two points to be selected / the larger value of the evaluation coefficients corresponding to the two points to be selected). The evaluation coefficient of a single point to be selected = the average displacement corresponding to the single point to be selected at each reference time point / the standard deviation of the displacement corresponding to the single point to be selected at each reference time point; Preset matching reference value; The value of the preset matching reference value can be determined by the user according to the actual application scenario. The greater the user's demand for improving detection accuracy, the larger the value of the preset matching reference value. A preset matching reference value is provided, and the preset matching reference value is 80%;

[0132] The nondestructive testing is performed on each nondestructive testing point, including: emitting 5 MHz high-frequency ultrasonic waves into the interior of the target composite spring in a direction perpendicular to the central axis of the spring through a probe at the nondestructive monitoring point.

[0133] Specifically, the nondestructive testing module determines that the adjustment method is to reduce the gradient reference value when the detection point correlation degree is greater than or equal to the preset detection point correlation degree and the instability threshold is greater than or equal to the preset instability threshold;

[0134] The reduction value of the gradient reference value is positively correlated with the comprehensive evaluation coefficient.

[0135] Among them, the correlation degree of the test points = 1 / (the standard deviation of the defect coefficients corresponding to each non-destructive test point + 1), and the defect coefficient corresponding to a single non-destructive test point = the echo amplitude corresponding to the non-destructive test point / the average value of the echo amplitudes corresponding to each non-destructive test point + the echo time corresponding to the non-destructive test point / the average value of the echo times corresponding to each non-destructive test point;

[0136] The echo amplitude corresponding to a single nondestructive testing point is the signal strength captured by the receiving probe after the ultrasonic transmitting probe transmits the ultrasonic wave at the nondestructive testing point and reflects it at the defect. The unit is dB. The echo time corresponding to a single nondestructive testing point is the total time required for the ultrasonic wave to travel from the transmitting probe to the defect and then return to the receiving probe after the ultrasonic transmitting probe transmits the ultrasonic wave at the nondestructive testing point.

[0137] The instability threshold is the average value of the echo amplitude corresponding to each nondestructive testing point;

[0138] The values of the preset detection point correlation degree and the preset instability threshold can be determined by the user according to the actual application scenario. The smaller the values of the preset detection point correlation degree and the preset instability threshold, the greater the user's demand for increasing the gradient reference value. The values of the preset detection point correlation degree and the preset instability threshold are provided, and the historical records of the user's increasing adjustment of the gradient reference value are detected. The average value of the detection point correlation degrees corresponding to the historical records that can meet the user's needs is recorded as the preset detection point correlation degree, and the average value of the instability threshold values corresponding to the historical records that can meet the user's needs is recorded as the preset instability threshold.

[0139] Comprehensive evaluation coefficient = detection point correlation / preset detection point correlation + instability threshold / preset instability threshold;

[0140] Gradient reference value = (final heating temperature - initial heating temperature) / heating time. It should be noted that when the gradient reference value is reduced, the final heating temperature and the initial heating temperature remain unchanged, and only the heating time is adjusted.

[0141] Specifically, when the detection point correlation degree is less than a preset detection point correlation degree or the instability threshold is less than a preset instability threshold, the nondestructive testing module determines that the adjustment method is to perform local strengthening according to the defect coefficient.

[0142] The local strengthening according to the defect coefficient includes: recording non-destructive detection points with defect coefficients greater than a preset defect coefficient as unstable points, recording each unstable point and each to-be-selected point in the combination of to-be-selected points corresponding to each unstable point as a to-be-strengthened point, recording the smallest spiral line section that can contain each to-be-strengthened point as a strengthening section, and increasing the number of fiber winding layers of the strengthening section. The increase in the number of fiber winding layers of the strengthening section is positively correlated with the strengthening threshold; the strengthening threshold is the maximum value of the defect coefficients corresponding to each unstable point;

[0143] The value of the preset defect coefficient can be determined by the user according to the actual application scenario. The greater the user's demand for improving the preparation accuracy, the smaller the value of the preset defect coefficient. The historical records of the user performing local reinforcement based on the defect coefficient are detected, and the average value of the defect coefficients corresponding to each instability point in the historical records that can meet the user's needs is recorded as the preset defect coefficient.

[0144] See also Figure 4 As shown, it is a schematic diagram of the intelligent detection method of the integrally stamped composite spring of the present invention. The present invention also provides an intelligent detection method of the integrally stamped composite spring, comprising:

[0145] Acquire operation monitoring data and perform a test on the composite spring to obtain test data;

[0146] Determine the composite spring status based on the abnormality degree and abnormality correlation, and determine the treatment method based on the composite spring status, such as secondary detection and analysis or adjustment of the fiber winding angle;

[0147] In the secondary detection analysis, the simulation method is determined according to the complexity of the working conditions and the degree of multi-directional uniformity, and the application setting method is determined according to the use impact threshold;

[0148] The simulation mode is to determine the simulation application point according to the distance coefficient and the action similarity or to determine the application simulation mode according to the feature point category, the application simulation mode is interval application or continuous application, and the application setting mode is span adjustment detection or constant threshold detection;

[0149] Under the preset detection conditions, the non-destructive testing method is determined as associated setting of non-destructive testing points or uniform setting of non-destructive testing points according to the deformation coefficient and the relaxation dislocation coefficient, and the adjustment method is determined as adjustment based on the gradient reference value or local strengthening based on the defect coefficient according to the correlation degree of the detection points and the instability threshold.

[0150] Thus far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art may make equivalent changes or substitutions to the relevant technical features, and the technical solutions after such changes or substitutions will fall within the scope of protection of the present invention.

[0151] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that the present invention is susceptible to various modifications and variations. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention are intended to be within the scope of protection of the present invention.

Claims

1. An intelligent detection system for integrally stamped composite springs, characterized in that: include: Data acquisition module, used to obtain operation monitoring data; A primary inspection module, used to perform a primary inspection on the composite spring to obtain inspection data; a processing and analysis module connected to the primary detection module, configured to determine a state of the composite spring based on a degree of abnormality and an abnormality correlation, and to determine a processing method, based on the composite spring state, as secondary detection and analysis or adjustment of the fiber winding angle; a secondary detection module, connected to the data acquisition module and the processing and analysis module, respectively, for determining a simulation method according to the complexity of the working condition and the multi-directional uniformity, and determining an application setting method according to a usage impact threshold, in the secondary detection and analysis; The simulation mode is to determine the simulation application point according to the distance coefficient and the action similarity or to determine the application simulation mode according to the feature point category, the application simulation mode is interval application or continuous application, and the application setting mode is span adjustment detection or constant threshold detection; a nondestructive testing module connected to the secondary testing module, configured to determine, under preset testing conditions, based on the deformation coefficient and the relaxation and dislocation coefficient, whether the nondestructive testing method is to set nondestructive testing points in an associated manner or to set nondestructive testing points uniformly, and to determine, based on the correlation degree of the testing points and the instability threshold, whether the adjustment method is to adjust the gradient reference value or to perform local strengthening based on the defect coefficient; The detection abnormality degree is the average value of the sub-abnormality degrees corresponding to each equally divided point in the characteristic curve of the target composite spring. The sub-abnormality degree corresponding to a single equally divided point = the average value of the pressure values corresponding to the equally divided point in the characteristic curves of all qualified springs - the pressure value corresponding to the equally divided point in the characteristic curve of the target composite spring; Abnormal correlation degree = 1 / (the maximum value of the correlation coefficients between the characteristic curve of the target composite spring and the characteristic curves of each qualified spring + 1); Working condition complexity = characteristic point reference value × characteristic point distribution coefficient, where the characteristic point reference value is the number of characteristic points in a single composite spring, and the characteristic point distribution coefficient is the average value of the distance reference values corresponding to each characteristic point. The distance reference value corresponding to a single characteristic point is the average value of the shortest distance from the characteristic point to all other characteristic points outside the characteristic point. The multidirectional uniformity is the average of the sub-uniformities corresponding to each operation monitoring data. The sub-uniformity corresponding to a single operation monitoring data = 1 / (the standard deviation of the multi-point difference corresponding to each time point + 1). The multi-point difference corresponding to a single time point in a single operation monitoring data is the standard deviation of the force value corresponding to each feature point in the operation monitoring data at that time point. The distance coefficient corresponding to any two feature points is the shortest distance between the two feature points; The action similarity between any two feature points = the number of time points with the same force value in the sub-monitoring data corresponding to the two feature points / the number of time points in a single sub-monitoring data; The deformation coefficient is the maximum value of the maximum displacements corresponding to each equally divided point, and the maximum displacement corresponding to a single equally divided point is the maximum value of the displacements corresponding to each reference time point during the monitoring time; The relaxation dislocation coefficient is the average value of the relaxation reference values corresponding to each reference time point. The relaxation reference value corresponding to a single reference time point is the standard deviation of the displacement corresponding to each equally divided point at that reference time point. Correlation degree of inspection points = 1 / (standard deviation of defect coefficients corresponding to each nondestructive inspection point + 1); The defect coefficient corresponding to a single nondestructive testing point = the echo amplitude corresponding to the nondestructive testing point / the average of the echo amplitudes corresponding to all nondestructive testing points + the echo time corresponding to the nondestructive testing point / the average of the echo times corresponding to all nondestructive testing points. The echo amplitude corresponding to a single nondestructive testing point is the signal strength (in dB) captured by the receiving probe after the ultrasonic transmitting probe transmits the ultrasonic wave at the nondestructive testing point and reflects it at the defect. The echo time corresponding to a single nondestructive testing point is the total time required for the ultrasonic wave to travel from the transmitting probe to the defect and then return to the receiving probe after the ultrasonic transmitting probe transmits the ultrasonic wave at the nondestructive testing point. The instability threshold is the average value of the echo amplitude corresponding to each nondestructive testing point; Gradient reference value = (final heating temperature - initial heating temperature) / heating time.

2. The intelligent detection system for integrally stamped composite springs according to claim 1, characterized in that: The processing and analysis module determines that the processing method is to reduce the fiber winding angle when the composite spring state has a detection abnormality greater than or equal to a preset detection abnormality and an abnormality correlation greater than or equal to a preset abnormality correlation; The reduction value of the fiber winding angle is positively correlated with the abnormal coefficient.

3. The intelligent detection system for integrally stamped composite springs according to claim 2, characterized in that: The processing and analysis module determines that the processing method is secondary detection and analysis when the composite spring state has a detection abnormality degree less than a preset detection abnormality degree or an abnormality correlation degree less than a preset abnormality correlation degree.

4. The intelligent detection system for integrally stamped composite springs according to claim 3, characterized in that: When the working condition complexity is less than the preset working condition complexity and the multidirectional uniformity is greater than or equal to the preset multidirectional uniformity, the secondary detection module determines that the simulation method is to determine the simulation application point according to the distance coefficient and the action similarity.

5. The intelligent detection system for integrally stamped composite springs according to claim 4, characterized in that: The secondary detection module determines that the simulation mode is to be applied according to the feature point category when the working condition complexity is greater than or equal to the preset working condition complexity or the multi-directional uniformity is less than the preset multi-directional uniformity; If the characteristic point type is a characteristic point whose action duration coefficient is less than the preset action duration coefficient or whose change response value is greater than or equal to the preset change response value, the application simulation mode is interval application; If the feature point category is a second-category feature point whose action duration coefficient is greater than or equal to the preset action duration coefficient and whose change response value is less than the preset change response value, the application simulation mode is continuous application.

6. The intelligent detection system for integrally stamped composite springs according to claim 5, characterized in that: The secondary detection module determines the application setting mode according to the use impact threshold, including: If the usage impact threshold is greater than or equal to the preset usage impact threshold, the setting mode applied is span adjustment detection; If the usage impact threshold is less than the preset usage impact threshold, the setting mode applied is constant threshold detection.

7. The intelligent detection system for integrally stamped composite springs according to claim 6, characterized in that: The nondestructive testing module determines the nondestructive testing method according to the deformation coefficient and the relaxation dislocation coefficient, including: If the deformation coefficient is greater than or equal to the preset deformation coefficient or the relaxation displacement coefficient is greater than or equal to the preset relaxation displacement coefficient, the non-destructive testing method is to set the non-destructive testing point in association; If the deformation coefficient is less than the preset deformation coefficient and the relaxation displacement coefficient is less than the preset relaxation displacement coefficient, the nondestructive testing method is to evenly set the nondestructive testing points.

8. The intelligent detection system for the integrally stamped composite spring according to claim 7, characterized in that: The nondestructive testing module determines that the adjustment method is to reduce the gradient reference value when the detection point correlation degree is greater than or equal to the preset detection point correlation degree and the instability threshold is greater than or equal to the preset instability threshold; The reduction value of the gradient reference value is positively correlated with the comprehensive evaluation coefficient; Comprehensive evaluation coefficient = detection point correlation / preset detection point correlation + instability threshold / preset instability threshold.

9. The intelligent detection system for the integrally stamped composite spring according to claim 8, characterized in that: The nondestructive testing module determines that the adjustment method is to perform local strengthening according to the defect coefficient when the detection point correlation degree is less than the preset detection point correlation degree or the instability threshold is less than the preset instability threshold.

10. A detection method using an intelligent detection system for an integrally stamped composite spring according to any one of claims 1 to 9, characterized in that: include: Acquire operation monitoring data and perform a test on the composite spring to obtain test data; Determine the composite spring status based on the abnormality degree and abnormality correlation, and determine the treatment method based on the composite spring status, such as secondary detection and analysis or adjustment of the fiber winding angle; In the secondary detection analysis, the simulation method is determined according to the complexity of the working conditions and the degree of multi-directional uniformity, and the application setting method is determined according to the use impact threshold; The simulation mode is to determine the simulation application point according to the distance coefficient and the action similarity or to determine the application simulation mode according to the feature point category, the application simulation mode is interval application or continuous application, and the application setting mode is span adjustment detection or constant threshold detection; Under the preset detection conditions, the non-destructive testing method is determined as associated setting of non-destructive testing points or uniform setting of non-destructive testing points according to the deformation coefficient and the relaxation dislocation coefficient, and the adjustment method is determined as adjustment based on the gradient reference value or local strengthening based on the defect coefficient according to the correlation degree of the detection points and the instability threshold.

Images