An electronic wiring harness performance detection method and subsystem

Abstract

The present application relates to the technical field of electronic harness detection, and particularly relates to an electronic harness performance detection method and a subsystem. Timing data of harness temperature and performance parameters of the electronic harness under a full temperature range is acquired; a harness temperature performance curve is obtained based on timing data mapping processing, and the dynamic influence law of temperature on performance is quantified; the influence of environmental temperature on the performance of the electronic harness is accurately identified by combining the performance parameter fluctuation characteristics and the environmental temperature value characteristics, and the environmental temperature influence weight is determined; at a key preset temperature (such as a standard working temperature), the qualification rate is calculated by comparing the performance parameter data with the reference range, and the local compliance is judged; finally, the performance stability (global) under multiple environmental temperatures and the key temperature qualification rate (local) are fused to form a two-dimensional evaluation system of "global stability + local compliance", which not only reflects the overall environmental adaptability of the harness, but also clearly shows the actual qualified state under the key temperature, and improves the credibility and practicability of the detection result.

Description

Technical Field

[0001] This invention relates to the field of electronic wire harness testing technology, and specifically to an electronic wire harness performance testing method and subsystem. Background Technology

[0002] In manufacturing, electronic wire harnesses serve as the core carrier for signal and power transmission between internal components of electronic devices, and their performance directly determines the stability, safety, and lifespan of the system. Especially in high-end manufacturing sectors such as automotive, electronics, and aerospace, the application scenarios for electronic wire harnesses are complex and demanding, making performance testing even more crucial.

[0003] The core of wire harness testing is to ensure the safety and reliability of electrical systems. Current technologies typically compare the test values ​​of various performance parameters of electronic wire harnesses with preset reference ranges to evaluate their performance. However, in actual electronic wire harness applications, ambient temperature is often not constant. Therefore, fluctuations in ambient temperature can affect the material properties of the wire harness and also influence its temperature distribution through heat conduction. Thus, if the impact of ambient temperature is not analyzed during performance testing of electronic wire harnesses, and the test values ​​of performance parameters are directly judged, the reliability of the final performance test results will be low. Summary of the Invention

[0004] To address the issue that in practical electronic wire harness applications, ambient temperatures are often not constant, and these fluctuations can affect the material properties of the wire harness and influence its temperature distribution through heat conduction. Therefore, if the impact of ambient temperature is not analyzed during performance testing of electronic wire harnesses, and performance parameters are directly judged, the reliability of the final performance test results will be low. The present invention aims to provide an electronic wire harness performance testing method and subsystem, the specific technical solution of which is as follows:

[0005] A method for testing the performance of an electronic wire harness, comprising:

[0006] During the performance testing of the electronic wire harness, the ambient temperature was changed, and the wire harness temperature timing data and various performance parameter timing data of the electronic wire harness at each ambient temperature were acquired.

[0007] At each ambient temperature, the time-series data of the wire harness temperature and the time-series data of each performance parameter are mapped to obtain the wire harness temperature performance curve. At all ambient temperatures, the differences between the wire harness temperature performance curves corresponding to the same performance parameter are analyzed and compared. The fluctuation of the data values ​​in the time-series data of each performance parameter is combined with the numerical characteristics of the ambient temperature to obtain the influence weight of each ambient temperature on the electronic wire harness.

[0008] Under all ambient temperatures, the fluctuation trend of the performance parameter time series data and the difference characteristics between data values ​​are adjusted by using the influence weight corresponding to the ambient temperature to determine the performance index of the electronic wire harness; under the preset ambient temperature, the difference between the data values ​​in the performance parameter time series data and the preset reference range is compared, and the pass rate of the electronic wire harness is determined by combining the influence weight corresponding to the preset ambient temperature.

[0009] Performance evaluation is conducted based on the performance indicators and pass rate of electronic wire harnesses.

[0010] Furthermore, the method for obtaining the temperature performance curve of the wiring harness includes:

[0011] At each ambient temperature, a two-dimensional space is constructed with the harness temperature as the horizontal axis and each performance parameter as the vertical axis. The temperature values ​​of the harness at all times and the data values ​​of each performance parameter are mapped into the two-dimensional space, and the least squares method is used to fit curves to all data points to obtain the harness temperature performance curve corresponding to each performance parameter.

[0012] Furthermore, the method for obtaining the influence weights includes:

[0013] At each ambient temperature, the fluctuation of the data value in the time series data of each performance parameter is analyzed, and combined with the numerical characteristics of the ambient temperature, the first influence coefficient of each performance parameter at each ambient temperature is obtained.

[0014] Under all ambient temperatures, the differences between the wire harness temperature performance curves corresponding to the same performance parameter are analyzed and compared to obtain the second influence coefficient of each performance parameter under each wire harness temperature.

[0015] At each ambient temperature, in the wire harness temperature performance curve corresponding to each performance parameter, the normalized value of the product of the second influence coefficient and the first influence coefficient of each performance parameter at each wire harness temperature is used as the influence factor of each performance parameter at each wire harness temperature.

[0016] In all wire harness temperature performance curves at each ambient temperature, the mean value of the influencing factors at all wire harness temperatures is used as the weight of the influence of each ambient temperature on the electronic wire harness.

[0017] Furthermore, the method for obtaining the first influence coefficient includes:

[0018] At each ambient temperature, the variance of all data values ​​in the time series data of each performance parameter is negatively correlated and mapped to the value, which is then used as the confidence factor.

[0019] The normalized value of the difference between each ambient temperature and the preset ambient temperature is used as the temperature deviation factor.

[0020] The normalized value of the product of the temperature deviation factor corresponding to each ambient temperature and the confidence factor corresponding to each performance parameter at each ambient temperature is used as the first influence coefficient.

[0021] Furthermore, the method for obtaining the second influence coefficient includes:

[0022] For each performance parameter, in the wire harness temperature performance curves corresponding to all ambient temperatures, the data values ​​at the same wire harness temperature are taken as a set of target values;

[0023] Using ambient temperature as the x-axis and performance parameters as the y-axis, a linear fit is performed on each set of target values ​​using the least squares method. The absolute value of the slope of the fitted line is then normalized and used as the second influence coefficient for each performance parameter at each harness temperature.

[0024] Furthermore, the method for obtaining the performance indicators includes:

[0025] Under all ambient temperatures, the fluctuation characteristics of the data values ​​in the time series data of each performance parameter are quantified and the trend of fluctuation characteristics with ambient temperature is analyzed. Combined with the influence weight of ambient temperature, the first performance factor of the electronic wire bundle is obtained.

[0026] At each ambient temperature, in the time series data of the performance parameters corresponding to each performance parameter, the absolute value of the difference between each two adjacent data values ​​is calculated as the data deviation coefficient. The sum of all data deviation coefficients in the time series data of the performance parameters corresponding to each performance parameter is used as the data deviation parameter.

[0027] The sum of the data deviation parameters corresponding to all performance parameters, multiplied by the influence weight corresponding to each ambient temperature, is normalized and used as the performance fluctuation characteristic value of the electronic wire bundle at each ambient temperature.

[0028] Under all ambient temperatures, the ambient temperature corresponding to the performance fluctuation characteristic value that is less than the preset fluctuation threshold is taken as the target temperature value. Among all target temperature values, the difference between the maximum and minimum values ​​is taken as the second performance factor of the electronic wire harness.

[0029] The normalized value of the product of the first performance factor and the second performance factor of the electronic wire harness is used as the performance index of the electronic wire harness.

[0030] Furthermore, the method for obtaining the first performance factor includes:

[0031] At each ambient temperature, in the time series data of the performance parameters corresponding to each performance parameter, the variance of all data values ​​is used as the fluctuation factor, and the sum of the fluctuation factors corresponding to all performance parameters is normalized and used as the performance fluctuation index of the electronic wire bundle at each ambient temperature.

[0032] Using ambient temperature as the horizontal axis and the performance fluctuation index of the electronic wire bundle as the vertical axis, curve fitting is performed on the performance fluctuation index of the electronic wire bundle under all ambient temperatures to obtain the fluctuation curve.

[0033] The first performance factor of the electronic wire bundle is obtained by multiplying the sum of the absolute values ​​of the slope values ​​at all data points on the fluctuation curve with the influence weight, and then performing negative correlation mapping and normalization on the resulting product.

[0034] Furthermore, the method for obtaining the pass rate includes:

[0035] Under a preset ambient temperature, in the time series data of the performance parameters for each performance parameter, the number of all data values ​​within the preset reference range corresponding to each performance parameter is counted as a quantity factor, and the ratio of the quantity factor to the total number of data values ​​is used as the pass factor for each performance parameter.

[0036] The value obtained by negatively mapping the influence weight corresponding to the preset ambient temperature is multiplied by the mean of the pass factor of all performance parameters under the preset ambient temperature, and the result is used as the pass rate of the electronic wire harness.

[0037] Furthermore, the performance evaluation based on the performance indicators and pass rate of the electronic wire harness includes:

[0038] When the performance indicators of the electronic wire harness are greater than or equal to the preset performance threshold, and the pass rate is greater than or equal to the preset pass threshold, the performance evaluation of the electronic wire harness is considered qualified; otherwise, the performance evaluation of the electronic wire harness is considered unqualified.

[0039] An electronic wire harness performance testing subsystem includes a processor and a memory. The memory stores at least one instruction, at least one program, code set, or instruction set. When the processor loads and executes the at least one instruction, at least one program, code set, or instruction set, it implements the steps of the electronic wire harness performance testing method.

[0040] The present invention has the following beneficial effects:

[0041] By varying the ambient temperature, the system covers multiple temperature scenarios that wire harnesses may encounter in actual use (such as high temperature, low temperature, and temperature fluctuations), acquiring time-series data on wire harness temperature and performance parameters across the entire temperature range, thus improving the scenario coverage and realism of the testing. Through mapping and processing of the time-series data, a direct correlation model between wire harness temperature and performance parameters (wire harness temperature-performance curve) is established, quantifying the dynamic law of wire harness temperature on performance and providing a precise quantitative basis for subsequent adjustments to ambient temperature interference. The differences in the same performance parameter curves under different ambient temperatures are analyzed. Combining the fluctuation characteristics of performance parameter time-series data and the numerical characteristics of ambient temperature, the influence of ambient temperature on performance parameters is accurately identified and calculated, obtaining the influence weight of ambient temperature on the electronic wire harness. In subsequent processes, the fluctuation trends and data difference characteristics of performance parameter time-series data under multiple ambient temperatures are integrated, and the influence weight corresponding to ambient temperature is used to adjust them, thereby comprehensively evaluating the performance stability of the wire harness under different temperature scenarios, forming more objective and multi-dimensional performance indicators, which helps to verify the environmental adaptability of the electronic wire harness. Under key preset ambient temperatures (such as standard operating temperatures), the data values ​​in the performance parameter time-series data are compared with preset reference ranges to calculate the pass rate of the electronic wiring harness, accurately determining whether the harness meets performance requirements at that ambient temperature. Finally, by combining performance indicators (stability under multiple ambient temperatures) and the pass rate (compliance at key temperatures), a two-dimensional evaluation system of "global stability + local compliance" is formed. This system reflects both the overall performance level of the wiring harness under different ambient temperature scenarios and clarifies its actual compliance status at key operating temperatures, making the performance evaluation more aligned with actual application needs and increasing the reliability of the test results. Attached Figure Description

[0042] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0043] Figure 1 This is a flowchart of an electronic wire harness performance testing method provided in one embodiment of the present invention;

[0044] Figure 2 This is a schematic diagram of the wire harness temperature performance curve provided in one embodiment of the present invention;

[0045] Figure 3 A flowchart illustrating a method for obtaining influence weights according to an embodiment of the present invention;

[0046] Figure 4A flowchart illustrating a method for obtaining performance indicators according to an embodiment of the present invention;

[0047] Figure 5 This is a system block diagram of an electronic wire harness performance testing subsystem provided in one embodiment of the present invention;

[0048] Figure 6 This is a schematic diagram of the system structure of an electronic wire harness performance testing subsystem provided in one embodiment of the present invention. Detailed Implementation

[0049] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of an electronic wire harness performance testing method and subsystem proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0050] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0051] The following description, in conjunction with the accompanying drawings, details a specific scheme for an electronic wire harness performance testing method and subsystem provided by the present invention.

[0052] Please see Figure 1 The diagram illustrates a flowchart of an electronic wire harness performance testing method according to an embodiment of the present invention, which includes the following steps:

[0053] Step S1: During the performance testing of the electronic wire harness, the ambient temperature is changed, and the wire harness temperature timing data and various performance parameter timing data of the electronic wire harness at each ambient temperature are obtained.

[0054] The core of electronic wire harness testing is to ensure the safety and reliability of electrical systems. Tests typically cover electrical and mechanical performance. Key electrical tests generally include continuity, insulation, and withstand voltage tests, while tensile and bending tests in mechanical performance testing are particularly important for applications in fields such as new energy vehicles.

[0055] Meanwhile, when electronic wiring harnesses are used in automobiles or other fields, the temperature of the working environment often changes and fluctuates. When the ambient temperature changes, the temperature of the wiring harness will also change, which will have a certain impact on the material properties of the wiring harness. Therefore, when conducting subsequent performance evaluation, it is necessary to analyze the impact of changes in ambient temperature on the performance parameters of electronic wiring harnesses, such as the stability of performance parameters after environmental changes and the retention of performance parameters under certain environmental changes. In other words, it is also necessary to test the environmental temperature adaptability of electronic wiring harnesses.

[0056] Therefore, in this embodiment of the invention, the ambient temperature is changed during the performance testing of the electronic wire harness, and the wire harness temperature and various performance parameter time-series data of the electronic wire harness at each ambient temperature are acquired. Specifically, the types of performance parameters in this embodiment of the invention include insulation voltage, insulation resistance, conductor resistance, current, breaking strength, bending strength, etc. Insulation voltage, insulation resistance, conductor resistance, and current are mainly used to test the conductivity of the electronic wire harness, and can be tested using a multimeter or continuity tester; breaking strength and bending strength are mainly used to test the mechanical properties of the electronic wire harness, and can be tested and acquired using a tensile tester and a bending tester; the wire harness temperature can be acquired by a temperature sensor. The acquisition frequency of the wire harness temperature time-series data and the performance parameter time-series data is set to once per second, with a length of half an hour, and is acquired synchronously. That is, the ambient temperature can be set to change once every 10 minutes, with a wire harness temperature value and multiple performance parameter values ​​at each moment; the range of ambient temperature change in this embodiment of the invention should include low temperature to high temperature, so it can be set to -40 degrees Celsius to 60 degrees Celsius, with an ambient temperature change step of 1 degree Celsius.

[0057] It should be noted that the range of changes in ambient temperature, the step size of changes, the collection frequency, length, and types of various time-series data can all be adjusted according to the needs of the implementation scenario, and no restrictions are imposed here.

[0058] Step S2: At each ambient temperature, the time series data of the wire harness temperature and the time series data of each performance parameter are mapped to obtain the wire harness temperature performance curve; at all ambient temperatures, the differences between the wire harness temperature performance curves corresponding to the same performance parameter are analyzed and compared, and the fluctuation of the data value in the time series data of each performance parameter is combined with the numerical characteristics of the ambient temperature to obtain the influence weight of each ambient temperature on the electronic wire harness.

[0059] Under normal ambient temperature conditions, the fluctuations of various performance parameters of electronic wire harnesses should exhibit better consistency. However, due to changes in ambient temperature, the performance parameters of electronic wire harnesses will fluctuate to some extent. Furthermore, when performing temperature effect analysis, there are two sources of temperature: one is the heat generated by the load during wire harness testing, and the other is the temperature information in the external environment. The impact of these two types of temperature on wire harness performance indicators is different. Therefore, in this embodiment, the wire harness temperature time series data and the time series data of each performance parameter are first mapped at each ambient temperature to obtain the wire harness temperature performance curve. Further, the impact of changes in ambient temperature on performance parameters is analyzed, mainly focusing on the stability and maintenance of performance parameters under changes in ambient temperature.

[0060] Preferably, in one embodiment of the present invention, the method for obtaining the temperature performance curve of the wire harness includes:

[0061] Since the temperature time-series data and various performance parameter time-series data of the electronic wire harness are collected synchronously, the wire harness temperature and each performance parameter at each moment can form a binary tuple of the form (x, y), where x can represent the temperature value of the wire harness and y can represent the data value of each performance parameter. Therefore, at each ambient temperature, the wire harness temperature is used as the horizontal axis and each performance parameter is used as the vertical axis to construct a two-dimensional space.

[0062] The temperature values ​​of the wire harness at all times and the data values ​​of each performance parameter are mapped to a two-dimensional space, and the least squares method is used to fit curves to all data points, thus obtaining the wire harness temperature performance curve corresponding to each performance parameter. The wire harness temperature performance curve reflects the change of each performance parameter of the electronic wire harness with the wire harness temperature. Here, only the performance parameters of insulation resistance, conductor resistance, and breaking strength are used as examples. The wire harness temperature performance curves of other performance parameters are not explained. Among them, insulation resistance and breaking strength decrease with increasing wire harness temperature, while conductor resistance increases with increasing wire harness temperature; please refer to [link to relevant documentation]. Figure 2 The diagram shows a schematic of the temperature performance curves of three wire harnesses in one embodiment of the present invention.

[0063] It should be noted that the least squares method is a well-known technique, and the process of obtaining the fitted curve will not be described in detail here.

[0064] At this point, the wire harness temperature performance curve corresponding to each performance parameter can be obtained at each ambient temperature.

[0065] Variations in ambient temperature can impact the performance of electronic wiring harnesses. Therefore, to assess the environmental temperature adaptability of electronic wiring harnesses, we can analyze the differences between the temperature performance curves of the harness under various ambient temperatures and for all performance parameters, as well as the fluctuations in the time-series data of each performance parameter and the numerical characteristics of the ambient temperature. This analysis yields the influence weight of each ambient temperature on the electronic wiring harness. The influence weight reflects the potential impact of ambient temperature on the electronic wiring harness in actual application scenarios, helping to more accurately reflect the performance essence of the electronic wiring harness in real-world applications and significantly improving the reliability of subsequent test results.

[0066] Preferably, in one embodiment of the present invention, the method for obtaining the influence weight includes:

[0067] Please see Figure 3 The diagram illustrates a method flowchart for obtaining the influence weight in one embodiment of the present invention. The method includes the following steps:

[0068] Step S201: Under each ambient temperature, analyze the fluctuation of the data value in the time series data of each performance parameter, and combine it with the numerical characteristics of the ambient temperature to obtain the first influence coefficient of each performance parameter under each ambient temperature.

[0069] At each ambient temperature, the variance of all data values ​​in the time-series data of each performance parameter is calculated. A larger variance indicates a worse convergence of the current performance parameter, resulting in lower effectiveness when applying temperature compensation. Therefore, the variance is negatively correlated and mapped to a confidence factor. A larger confidence factor indicates better stability of the performance parameter and higher reference value. This negative correlation mapping can be performed using the formula... ,in, Let x represent an exponential function with the natural constant e as the base, and let x represent the independent variable.

[0070] Then, the normalized value of the difference between each ambient temperature and the preset ambient temperature is used as a temperature deviation factor. The larger the temperature deviation factor, the greater the deviation between the current ambient temperature and the preset ambient temperature (in this embodiment of the invention, the ambient temperature at which the electronic wire harness is most suitable for operation, which can be set to 25 degrees Celsius), and the greater the impact of ambient temperature changes on the electronic wire harness. Since the difference between the ambient temperature and the preset ambient temperature may be positive or negative, a normalization method can be used when normalizing this difference. function.

[0071] Finally, the normalized value of the product of the temperature deviation factor corresponding to each ambient temperature and the confidence factor corresponding to each performance parameter at each ambient temperature is used as the first influence coefficient. The larger the first influence coefficient, the greater the influence of the ambient temperature on the performance parameters of the electronic wire bundle, and the higher the reliability. Normalization is a technique well known to those skilled in the art. The normalization function can be linear normalization or standard normalization, etc., and the specific normalization method is not limited here.

[0072] Step S202: Under all ambient temperatures, analyze and compare the differences between the wire harness temperature performance curves corresponding to the same performance parameter, and obtain the second influence coefficient of each performance parameter under each wire harness temperature.

[0073] Each performance parameter has a wire harness temperature performance curve under all ambient temperatures. The performance change pattern of the electronic wire harness may be different under different ambient temperatures. Therefore, in this embodiment of the invention, the influence of ambient temperature on the performance of the electronic wire harness is quantified by comparing the wire harness temperature performance curves laterally and then analyzing the trend of data change, thereby obtaining the second influence coefficient.

[0074] For each performance parameter, in the wire harness temperature performance curves corresponding to all ambient temperatures, the data values ​​at the same wire harness temperature are taken as a set of target values. At this time, the variation characteristics of each set of target values ​​can reflect the influence of different ambient temperatures on the data values ​​of the performance parameters under the same wire harness temperature.

[0075] Then, using ambient temperature as the x-axis and performance parameters as the y-axis, a linear fit is performed on each set of target values ​​using the least squares method to obtain a fitted line. If ambient temperature has no effect on performance parameters, then the slope of the fitted line should be 0, assuming a consistent wire harness temperature. If it is not 0, it indicates that ambient temperature affects the performance of the electronic wire harness, and the greater the effect, the greater the difference between the slope value and 0. Therefore, the normalized absolute value of the slope of the obtained fitted line is used as the second influence coefficient for each performance parameter at each wire harness temperature. The larger the second influence coefficient, the greater the impact of ambient temperature on the performance of the electronic wire harness. Normalization is a technique well-known to those skilled in the art, and the normalization function can be linear normalization or standard normalization, etc. The specific normalization method is not limited here.

[0076] Step S203: Combine the first influence coefficient corresponding to each performance parameter of the electronic wire bundle at each ambient temperature with the second influence coefficient corresponding to each performance parameter at all ambient temperatures to obtain the influence weight of each ambient temperature on the electronic wire bundle.

[0077] Based on the aforementioned steps, we can obtain the first influence coefficient of each ambient temperature on each performance parameter and the second influence coefficient of the ambient temperature on each performance parameter at each wire harness temperature. In this step, we can perform a fusion analysis on these two coefficients.

[0078] At each ambient temperature, in the wire harness temperature performance curve corresponding to each performance parameter, the normalized value of the product of the second influence coefficient and the first influence coefficient of each performance parameter at each wire harness temperature is used as the influence factor of each performance parameter at each wire harness temperature. The larger the influence factor, the greater the influence of ambient temperature on that performance parameter of the electronic wire harness at that ambient temperature and wire harness temperature. Normalization is a technique well known to those skilled in the art, and the choice of normalization function can be linear normalization or standard normalization, etc. The specific normalization method is not limited here.

[0079] Finally, in all the wire harness temperature performance curves at each ambient temperature, the average value of the influence factors at all wire harness temperatures is taken as the influence weight of each ambient temperature on the electronic wire harness. The larger the influence weight, the more significant the influence of the change in ambient temperature on the performance of the electronic wire harness.

[0080] To facilitate understanding, the process of obtaining the influence weights is illustrated below: Based on the aforementioned steps, the wire harness temperature performance curves corresponding to each performance parameter of the electronic wire harness at each ambient temperature (e.g., ambient temperatures of 24 degrees Celsius, 25 degrees Celsius, and 26 degrees Celsius) can be obtained, reflecting the change of performance parameters with wire harness temperature; firstly, the variance of all data in each wire harness temperature performance curve of the electronic wire harness at each ambient temperature (e.g., 26 degrees Celsius) is analyzed and combined with the difference between that ambient temperature and 25 degrees Celsius to obtain the first influence coefficient (the specific process is recorded in step S201); furthermore, the influence coefficients are calculated based on the changes in the wire harness temperature performance curves of each performance parameter at different ambient temperatures. In the wire harness temperature performance curve, data values ​​under the same wire harness temperature are used as a set of target values. For example, if the same wire harness temperature is selected as 20 degrees Celsius, then there are three target values ​​with the same wire harness temperature of 20 degrees Celsius, but the ambient temperatures are 24 degrees Celsius, 25 degrees Celsius, and 26 degrees Celsius, respectively. Keeping the wire harness temperature constant, the influence of ambient temperature on performance parameters is analyzed based on the change characteristics of the target values, thereby obtaining the second influence coefficient (the specific process is recorded in step S202). Finally, the first influence coefficient and the second influence coefficient are combined to obtain the influence weight of each ambient temperature on the electronic wire harness (the specific process is recorded in step S203).

[0081] Step S3: Under all ambient temperatures, adjust the fluctuation trend of the performance parameter time series data and the difference characteristics between data values ​​using the influence weight corresponding to the ambient temperature to determine the performance indicators of the electronic wire harness; Under the preset ambient temperature, compare the differences between the data values ​​in the performance parameter time series data and the preset reference range, and combine the influence weight corresponding to the preset ambient temperature to determine the pass rate of the electronic wire harness.

[0082] Based on the operations described above, the influence weight of each ambient temperature on the electronic wire harness can be obtained. In this step, the influence weight can be used to adjust the fluctuation trend and the difference characteristics between data values ​​in the performance parameter time series data. This is used to quantify the adaptability of the electronic wire harness to changes in ambient temperature, thereby determining the performance indicators of the electronic wire harness. At the same time, under normal circumstances, the preset reference range of performance parameters is used to determine whether the performance parameters of the electronic wire harness are qualified. If the ambient temperature change has a significant impact on the electronic wire harness, the qualification status also needs to be appropriately corrected. Therefore, under the preset ambient temperature, when comparing the differences between the data values ​​in the performance parameter time series data and the preset reference range, the influence weight corresponding to the preset ambient temperature is used to correct the difference, thereby determining the pass rate of the electronic wire harness.

[0083] First, the performance indicators of the electronic wire bundle are calculated. Preferably, in one embodiment of the present invention, the method for obtaining the performance indicators includes:

[0084] Please see Figure 4 The diagram illustrates a method flowchart for obtaining performance indicators according to an embodiment of the present invention, which includes the following steps:

[0085] Step S301: Under all ambient temperatures, quantify the fluctuation characteristics of the data values ​​in the time series data of each performance parameter and analyze the trend of the fluctuation characteristics with ambient temperature. Combine the influence weight of ambient temperature to obtain the first performance factor of the electronic wire harness.

[0086] If the performance of the electronic wire bundle is good, then the stability of its performance parameter data values ​​should also be good. Therefore, at each ambient temperature, the variance of all data values ​​in the time series data corresponding to each performance parameter is calculated and used as a fluctuation factor. The larger the fluctuation factor, the more significant the fluctuation of the data value in the time series data corresponding to that performance parameter, and thus the worse the stability. The sum of the fluctuation factors corresponding to all performance parameters is normalized and used as the performance fluctuation index of the electronic wire bundle at each ambient temperature. Based on the aforementioned analysis, it can be seen that the larger the performance fluctuation index, the worse the performance stability of the electronic wire bundle at that ambient temperature. Normalization is a technique well-known to those skilled in the art. The choice of normalization function can be linear normalization or standard normalization, etc., and the specific normalization method is not limited here.

[0087] Next, we can analyze the stability of the performance parameters under changes in ambient temperature: using ambient temperature as the horizontal axis and the performance fluctuation index of the electronic wire bundle as the vertical axis, we can perform curve fitting on the performance fluctuation index of the electronic wire bundle under all ambient temperatures to obtain the fluctuation curve. The fluctuation curve can reflect the changing trend of the performance of the electronic wire bundle with changes in ambient temperature.

[0088] The slope value at each data point on the fluctuation curve is obtained. The larger the absolute value of the slope value, the more significant the fluctuation in the performance index of the electronic wire bundle with changes in ambient temperature, and thus the worse the stability. The larger the influence weight corresponding to ambient temperature obtained in step S2, the greater the impact of ambient temperature changes on the performance of the electronic wire bundle. Therefore, the sum of the absolute values ​​of the slope values ​​at all data points on the fluctuation curve is multiplied by the influence weight. The larger the product, the worse the adaptability of the electronic wire bundle to changes in ambient temperature, which is considered poorer performance. Therefore, the resulting product is negatively correlated and normalized to correct the logical relationship, thus obtaining the first performance factor of the electronic wire bundle. The larger the first performance factor, the better the performance of the electronic wire bundle. The negative correlation mapping and normalization here can be performed using the formula... ,in, Let x represent an exponential function with the natural constant e as the base, and let x represent the independent variable.

[0089] Step S302: Under all ambient temperatures, analyze the differences between data values ​​in the time series data of performance parameters, and adjust them using the influence weight of ambient temperature to obtain the second performance factor of the electronic wire bundle.

[0090] At each ambient temperature, in the time-series data of each performance parameter, the absolute value of the difference between any two adjacent data values ​​is calculated as the data deviation coefficient. The larger the data deviation coefficient, the more drastic the fluctuation of the performance parameter in a short period of time, and the worse the local consistency. The sum of all data deviation coefficients in the time-series data of each performance parameter is taken as the data deviation parameter. The larger the data deviation parameter, the worse the overall consistency of the data represented by the time-series data of a certain performance parameter, and thus the worse the performance of the electronic wire bundle at that ambient temperature. The larger the influence weight of the ambient temperature, the greater its influence on the performance of the electronic wire bundle. Therefore, both the data deviation parameter and the influence weight are positively correlated with the performance instability of the electronic wire bundle. Thus, the product of the sum of the data deviation parameters of all performance parameters at each ambient temperature and the influence weight of each ambient temperature is normalized and taken as the performance fluctuation characteristic value of the electronic wire bundle at each ambient temperature. The larger the performance fluctuation characteristic value, the worse the performance stability of the electronic wire bundle at that ambient temperature. Normalization is a technique well-known to those skilled in the art. The normalization function can be linear normalization or standard normalization, etc. The specific normalization method is not limited here.

[0091] Under all ambient temperatures, the ambient temperature corresponding to the performance fluctuation characteristic value that is less than the preset fluctuation threshold is taken as the target temperature value. The target temperature value is considered to be the ambient temperature that maintains the performance stability of the electronic wire bundle well. If the difference between the target temperature values ​​is greater, it means that the electronic wire bundle can maintain a better performance stability under larger ambient temperature changes, and the performance of the electronic wire bundle is better. Therefore, among all target temperature values, the difference between the maximum and minimum values ​​is taken as the second performance factor of the electronic wire bundle. The larger the second performance factor, the better the performance stability of the electronic wire bundle under larger ambient temperature differences, and therefore the better the performance.

[0092] It should be noted that in this embodiment of the invention, the preset fluctuation threshold is set to 0.4. The specific value can be adjusted according to the implementation scenario and is not limited here.

[0093] Step S303: Combine the first performance factor and the second performance factor of the electronic wire harness to calculate the performance index of the electronic wire harness.

[0094] Based on the analysis in steps S301 and S302, it is known that both the first performance factor and the second performance factor of the electronic wire bundle are positively correlated with the performance of the electronic wire bundle, mainly referring to its environmental temperature adaptability. Therefore, the normalized value of the product of the first performance factor and the second performance factor of the electronic wire bundle is used as the performance index of the electronic wire bundle. The larger the performance index, the more stable the electronic wire bundle can maintain its state under changes in environmental temperature. Normalization is a technique well known to those skilled in the art. The normalization function can be linear normalization or standard normalization, etc., and the specific normalization method is not limited here.

[0095] After obtaining the performance indicators of the electronic wire harness, it is also necessary to analyze the conformity of the specific data values ​​of the performance parameters of the electronic wire harness at the key temperature. Specifically, at a preset ambient temperature (in this embodiment of the invention, the ambient temperature at which the electronic wire harness is most suitable for operation, which can be set to 25 degrees Celsius), the difference between the data values ​​of the performance parameters and the preset reference range can be compared, and the influence weight corresponding to the preset ambient temperature can be combined to obtain the test pass rate of the electronic wire harness.

[0096] Preferably, in one embodiment of the present invention, the method for obtaining the pass rate includes:

[0097] Under a preset ambient temperature, in the time series data of each performance parameter, the number of all data values ​​within the preset reference range corresponding to that performance parameter is counted as a quantity factor. The quantity factor reflects the absolute number of qualified data values ​​of the electronic wire bundle in the performance parameters under the preset ambient temperature. The ratio of the quantity factor to the total number of data values ​​is used as the qualification factor for each performance parameter. The larger the qualification factor, the greater the probability that the data value of the performance parameter meets the preset reference range, and the better the performance.

[0098] Given that ambient temperature has a certain impact on the performance of electronic wire harnesses, this impact is quantified by weighting. A larger weight indicates a greater degree of influence, thus requiring a corresponding reduction in the pass rate. Therefore, the negative correlation mapping of the impact weight corresponding to the preset ambient temperature is multiplied by the mean of the pass factors for all performance parameters of the electronic wire harness at the preset ambient temperature. This multiplication is used as the pass rate of the electronic wire harness. A higher pass rate indicates better performance of the electronic wire harness at the preset ambient temperature. This negative correlation mapping can be achieved using the formula... , where z represents the independent variable.

[0099] It should be noted that, in the embodiments of the present invention, the preset reference range of various performance parameters can be determined and adjusted according to the implementation scenario. For example, if the preset reference range of the breaking strength of the electronic wire bundle is greater than or equal to 100N, then if the breaking strength at a certain moment is 80N, then the data value of the performance parameter at that moment is unqualified.

[0100] Step S4: Conduct performance evaluation based on the performance indicators and pass rate of the electronic wire harness.

[0101] Based on the aforementioned steps, two indicators describing the performance of the electronic wire harness can be obtained: performance index and inspection pass rate. In this step, the performance of the electronic wire harness can be evaluated based on these two indicators.

[0102] Preferably, in one embodiment of the present invention, performance evaluation based on the performance indicators and pass rate of the electronic wire harness includes:

[0103] Based on the analysis in step S3, it can be seen that the higher the performance index of the electronic wire harness, the more stable the electronic wire harness can remain under the condition of changes in ambient temperature; the higher the pass rate of the electronic wire harness, the better the performance of the electronic wire harness under the preset ambient temperature.

[0104] Therefore, when the performance indicators of the electronic wire harness are greater than or equal to the preset performance threshold, and the pass rate is greater than or equal to the preset pass threshold, the performance evaluation of the electronic wire harness is considered qualified; otherwise, the performance evaluation of the electronic wire harness is considered unqualified, and staff need to be notified to make process adjustments, etc.

[0105] It should be noted that in this embodiment of the present invention, the preset performance threshold is 0.7 and the preset qualified threshold is 0.75. The specific values ​​can be adjusted according to the implementation scenario and are not limited here.

[0106] This invention also provides an electronic wire harness performance testing subsystem; please refer to [link / reference]. Figure 5 The diagram shows a system block diagram, including a data acquisition module 401 for implementing step S1 in the above method embodiment; an impact analysis module 402 for implementing step S2 in the above method embodiment; an evaluation index acquisition module 403 for implementing step S3 in the above method embodiment; and a performance evaluation module 404 for implementing step S4 in the above method embodiment.

[0107] It should be noted that the subsystems provided in the above embodiments are only illustrative examples of the division of the above functional modules. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the computer device can be divided into different functional modules to complete all or part of the functions described above. In addition, the electronic wire harness performance testing subsystem and the electronic wire harness performance testing method embodiment provided in the above embodiments belong to the same concept, and their specific implementation process can be found in the method embodiment, which will not be repeated here.

[0108] Please see Figure 6 This diagram illustrates a system structure of an electronic wire harness performance testing subsystem according to an embodiment of the present invention. The subsystem includes a processor 500, a memory 501, a bus 502, and a communication interface 503. The processor 500, communication interface 503, and memory 501 are connected via the bus 502. The memory 501 may contain a high-speed random access memory. The bus 502 may be an ISA bus, PCI bus, or EISA bus, etc. The processor 500 may be an integrated circuit chip with signal processing capabilities. The memory 501 stores at least one instruction, at least one program, code set, or instruction set. When the processor loads and executes the at least one instruction, at least one program, code set, or instruction set, it implements the steps in an electronic wire harness performance evaluation method.

[0109] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0110] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

Claims

1. A method of electronic harness performance detection, characterized by, The method comprises: changing the environmental temperature during performance detection of the electronic harness, and acquiring harness temperature time series data and various performance parameter time series data of the electronic harness at each environmental temperature; mapping the harness temperature time series data and each performance parameter time series data at each environmental temperature, so as to obtain a harness temperature performance curve; analyzing and comparing the differences between the harness temperature performance curves corresponding to the same performance parameter at all environmental temperatures, and combining the fluctuation of the data values in each performance parameter time series data with the numerical characteristics of the environmental temperature, so as to obtain the influence weight of each environmental temperature on the electronic harness; adjusting the fluctuation trend and difference characteristics of the performance parameter time series data by using the influence weight corresponding to the environmental temperature at all environmental temperatures, so as to determine the performance index of the electronic harness; comparing the differences between the data values in the performance parameter time series data and the preset reference range at the preset environmental temperature, and combining the influence weight corresponding to the preset environmental temperature, so as to determine the detection qualified rate of the electronic harness; performing performance evaluation based on the performance index and the detection qualified rate of the electronic harness; The method for obtaining the performance index comprises: quantifying the fluctuation characteristics of the data values in each performance parameter time series data and analyzing the change trend of the fluctuation characteristics with the environmental temperature at all environmental temperatures, and combining the influence weight of the environmental temperature, so as to obtain a first performance factor of the electronic harness; at each environmental temperature, calculating the absolute value of the difference between each adjacent two data values in the performance parameter time series data corresponding to each performance parameter as a data deviation coefficient, and taking the sum of all data deviation coefficients in the performance parameter time series data corresponding to each performance parameter as a data deviation parameter; taking the product of the sum of all data deviation parameters corresponding to all performance parameters and the influence weight corresponding to each environmental temperature after normalization as a performance fluctuation characteristic value of the electronic harness at each environmental temperature; at all environmental temperatures, taking the environmental temperature corresponding to the performance fluctuation characteristic value less than the preset fluctuation threshold as a target temperature value, and taking the difference between the maximum value and the minimum value among all target temperature values as a second performance factor of the electronic harness; taking the product of the first performance factor and the second performance factor of the electronic harness after normalization as the performance index of the electronic harness.

2. The method of claim 1, wherein, The method for obtaining the harness temperature performance curve comprises: at each environmental temperature, taking the harness temperature as the abscissa and each performance parameter as the ordinate to construct a two-dimensional space, mapping the temperature value of the harness temperature and the data value of each performance parameter at all times into the two-dimensional space, and using the least square method to perform curve fitting on all data points, so as to obtain the harness temperature performance curve corresponding to each performance parameter.

3. The method of claim 1, wherein the step of detecting the performance of the electronic beam comprises the step of: The method for obtaining the influence weight comprises: at each environmental temperature, analyzing the fluctuation of the data values in each performance parameter time series data, and combining the numerical characteristics of the environmental temperature, so as to obtain a first influence coefficient of each performance parameter at each environmental temperature; All ambient temperatures, analyze and compare the differences between the corresponding wire harness temperature performance curves of the same performance parameters, and obtain the second influence coefficient of each performance parameter at each wire harness temperature; At each ambient temperature, in the wire harness temperature performance curve corresponding to each performance parameter, the product of the second influence coefficient of each performance parameter at each wire harness temperature and the first influence coefficient of each performance parameter is normalized as the influence factor of each performance parameter at each wire harness temperature. In all wire harness temperature performance curves at each ambient temperature, the average of the influence factors at all wire harness temperatures is taken as the influence weight of each ambient temperature on the electron beam.

4. The method of claim 3, wherein the step of detecting the performance of the electronic beam comprises the step of: The method for obtaining the first influence coefficient comprises: At each ambient temperature, in the performance parameter time series data of each performance parameter, the value obtained by negatively correlating the variance of all data values is taken as the confidence factor; The value obtained by normalizing the difference between each ambient temperature and the preset ambient temperature is taken as the temperature deviation factor; The product of the temperature deviation factor corresponding to each ambient temperature and the confidence factor corresponding to each performance parameter at each ambient temperature is normalized as the first influence coefficient.

5. The method of claim 3, wherein the step of detecting the performance of the electronic beam comprises the step of: The method for obtaining the second influence coefficient comprises: At each performance parameter, in the wire harness temperature performance curves corresponding to all ambient temperatures, the data value at the same wire harness temperature is taken as a group of target values; The ambient temperature is taken as the horizontal coordinate, the performance parameter is taken as the vertical coordinate, the least square method is used to linearly fit each group of target values, and the absolute value of the slope value of the obtained fitting straight line is normalized as the second influence coefficient of each performance parameter at each wire harness temperature.

6. The method of claim 1, wherein, The method for obtaining the first performance factor comprises: At each ambient temperature, in the performance parameter time series data corresponding to each performance parameter, the variance of all data values is taken as the fluctuation factor, and the sum of the fluctuation factors corresponding to all performance parameters is normalized as the performance fluctuation index of the electron beam at each ambient temperature; The ambient temperature is taken as the horizontal coordinate, and the performance fluctuation index of the electron beam is taken as the vertical coordinate, so as to perform curve fitting on the performance fluctuation index of the electron beam at all ambient temperatures to obtain a fluctuation curve; The absolute value of the slope value of all data points on the fluctuation curve is added, multiplied by the influence weight, and the obtained product is negatively correlated and normalized to obtain the first performance factor of the electron beam.

7. The method of claim 1, wherein the step of detecting the performance of the electronic beam further comprises the step of: The method for obtaining the detection qualified rate comprises: ​ At the preset ambient temperature, in the performance parameter time series data of each performance parameter, the number of data values within the preset reference range corresponding to each performance parameter is counted as the number factor, and the ratio of the number factor to the total number of data values is taken as the qualified factor of each performance parameter; The value obtained by negatively correlating the influence weight corresponding to the preset ambient temperature is multiplied by the average of the qualified factors of all performance parameters at the preset ambient temperature, as the detection qualified rate of the electron beam.

8. The method of claim 1, wherein the step of detecting the performance of the electronic beam further comprises the step of: The performance evaluation based on the performance index and the detection qualified rate of the electron beam comprises: ​ When the performance index of the electronic beam is greater than or equal to the preset performance threshold value, and the detection qualified rate is greater than or equal to the preset qualified threshold value, it is considered that the performance evaluation of the electronic beam is qualified; otherwise, it is considered that the performance evaluation of the electronic beam is unqualified.

9. An electronic harness performance detection subsystem, characterized by, The electronic beam performance detection method comprises the following steps: acquiring a performance index of an electronic beam; acquiring a detection qualified rate of the electronic beam; and determining whether the performance evaluation of the electronic beam is qualified or unqualified according to the performance index and the detection qualified rate. The electronic beam performance detection method comprises the following steps: acquiring a performance index of an electronic beam; acquiring a detection qualified rate of the electronic beam; and determining whether the performance evaluation of the electronic beam is qualified or unqualified according to the performance index and the detection qualified rate.

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