Metal wire tensile strength detection system and detection method thereof

Abstract

The invention discloses a metal wire tensile strength detection system and a detection method thereof, and relates to the technical field of material testing, the system realizes acquisition of steel wire tensile strength data through a data acquisition module, and transmits the acquired tensile strength data to a data processing module through a LoRa wireless communication technology. The data processing module carries out preprocessing and feature extraction on the data and stores the processed data in a time sequence database. The wire rod strength analysis module outputs an accurate transient stress coefficient Y (t), a stress temperature correction coefficient YT (t) and a stress vibration correction coefficient Ya (t), and a foundation is laid for further evaluation. And a comprehensive stress value Yfinal (t) is output through the wire rod strength evaluation module. The comprehensive stress value Yfinal (t) is compared with a set stress threshold value L1, and the actual tensile strength state of the steel wire rod can be accurately evaluated.

Description

Technical Field

[0001] The present invention relates to the technical field of metal wire testing, and in particular to a metal wire tensile strength testing system and a testing method thereof. Background Art

[0002] Wire rod is also called wire rod because it is delivered in coils. Wire rod has other shapes besides circular cross section. Wire rod is generally made of ordinary carbon steel and high-quality carbon steel. Wire rod is the smallest cross-section size among hot-rolled steel sections. Its diameter varies due to different demand conditions and production technology levels. It can be divided into high-speed wire rod (high-speed wire) and ordinary wire rod (ordinary wire) according to different rolling mills. In the tensile test of wire rod, its metal wire tensile strength test system often belongs to the field of material testing and analysis, which mainly involves testing and evaluating the mechanical properties of metal materials. Specifically, tensile strength test is a key test item in material mechanics, which evaluates the bearing capacity of metal wire rod under tension and the maximum stress it can withstand before breaking. Steel wire rod, as one of the metal wire rods, is widely used in bridges, buildings, mechanical equipment and other fields. Accurate detection of its tensile strength is crucial to ensure the safety and reliability of these structures.

[0003] At present, the current steel wire tensile strength detection devices have certain limitations in data monitoring and analysis. Especially when dealing with complex working conditions, facing the transient fluctuations of wire stress values ​​due to external factors such as temperature changes and vibration frequency, the existing detection devices can usually only focus on a single indicator of tension, thereby ignoring the dynamic effects of environmental factors and stress fluctuations on wire strength, resulting in the inability to accurately ensure the tensile strength of metal wires. In addition, traditional detection systems also lack sufficient real-time and flexibility in data processing and analysis, and cannot provide accurate early warning information in a timely manner, which may lead to safety hazards during operation.

[0004] For example, the Chinese utility model patent with publication number CN219161806U and name “A metal wire tensile strength detection device” solves the problem that “the current tensile strength detection device over-extrudes the wire or bends the wire to cause deformation at both ends, and the deformation at both ends of the wire is relatively weak, resulting in the detected tensile strength being not equal to the actual tensile strength”. By setting an arc-shaped depression and an elastic layer at the fixed block, the deformation of the wire ends is prevented, and the error of easy breaking due to deformation at both ends of the wire is reduced, thereby reducing the situation of easy breaking due to deformation at both ends of the wire. At the same time, it can prevent the object being detected from falling off, facilitating large-scale detection. However, this technical solution still cannot directly detect the problem of transient fluctuations in the stress value of the wire due to external factors such as temperature changes and vibration frequency, and cannot monitor and alarm the wire during the test in a real-time and flexible manner.

[0005] Therefore, how to intelligently test the tensile strength of metal wires is a technical problem that technicians currently need to solve. Summary of the invention

[0006] In view of the deficiencies in the prior art, the present invention provides a metal wire tensile strength detection system and a detection method thereof, which solve the problems mentioned in the background technology.

[0007] To achieve the above objectives, the first aspect of the present application provides a metal wire tensile strength detection system, including: a data acquisition module, a data processing module, a wire strength analysis module, a wire strength evaluation module and a visual early warning module;

[0008] The data acquisition module installs a sensor group on the steel wire during the tensile strength test of the steel wire, collects the tensile strength data of the steel wire in real time, and transmits the tensile strength data to the data processing module;

[0009] The data processing module is used to receive the tensile strength data in real time, and after preprocessing the tensile strength data, obtain the wire strength data group, perform feature extraction on the wire strength data group to obtain the wire strength feature set, and then store the wire strength data group and the wire strength feature set in a time series database;

[0010] The wire strength analysis module is used to construct a strength analysis algorithm model, input the extracted wire strength data group into the strength analysis algorithm model, and calculate and output the transient stress coefficient Y(t), the stress temperature correction coefficient Y T (t) and stress vibration correction factor Y a (t);

[0011] The wire strength evaluation module is used to obtain the transient stress coefficient Y(t), the stress temperature correction coefficient Y T (t) and stress vibration correction factor Y a (t), and then perform comprehensive calculation with the wire strength characteristic set to obtain the comprehensive stress value Y final (t), and preset the stress threshold L1 and the obtained comprehensive stress value Y final (t) Compare and evaluate, and output warning information;

[0012] The visual warning module is used to build a user-friendly interface, receive warning information in real time for storage and recording, analyze the warning information, and generate visual data display and alarm settings.

[0013] Preferably, the data acquisition module includes an acquisition unit and a transmission unit;

[0014] The acquisition unit is used to install sensor groups at both ends and the midline of the steel wire when testing the tensile strength of the steel wire to collect the tensile strength data of the steel wire in real time;

[0015] The sensor group includes a strain gauge, a temperature sensor, an accelerometer and a displacement sensor;

[0016] The tensile strength data include strain ε, tension F, temperature T and dynamic load acceleration a;

[0017] The transmission unit transmits the collected tensile strength data to the data processing module through the LoRa wireless communication technology.

[0018] Preferably, the data processing module includes a processing unit, a feature extraction unit and a data storage unit;

[0019] The processing unit is used to receive the collected tensile strength data in real time, remove outliers, noise and normalize the tensile strength, perform time domain conversion on the wire strength data group, mark the wire strength data group with a timestamp, and then obtain the wire strength data group by performing correlation calculation on the processed tensile strength data;

[0020] The wire strength data set includes transient strain rate Dynamic temperature correction coefficient δ T (t), vibration frequency stress influence coefficient γ(t) and tension F(t) at time t;

[0021] The transient strain rate The strain rate is estimated from discrete data points using numerical differentiation methods, as follows: Where d is the differential, dt is the time differential;

[0022] The dynamic temperature correction coefficient δ T (t) is obtained by fitting the stress-strain data of steel wire at different temperatures. The specific calculation formula is: Where σ(T) is the stress at temperature T, and σ(T0) represents the stress at reference temperature T0;

[0023] The vibration frequency stress influence coefficient γ(t) is obtained by measuring the vibration acceleration of the steel wire with an accelerometer, determining the dynamic load acceleration a, calculating the acceleration amplitude △a, and then calculating the stress change Δσ caused by the vibration. The specific calculation formula is:

[0024] Preferably, the feature extraction unit is used to construct a feature extraction algorithm collection Extract wire strength data and input it into the feature extraction algorithm collection In the process, feature extraction is performed to output a wire strength feature set, wherein the wire strength feature set includes a nonlinear stress-strain relationship Temperature-stress coupling effect η(T(t)), high-frequency correction κ(w, t) for vibration effects, and time delay correction δ delay (t);

[0025] The nonlinear stress-strain relationship Temperature-stress coupling effect η(T(t)), high-frequency correction κ(w, t) for vibration effects, and time delay correction δ delay (t) Through the following feature extraction algorithm collection Calculate acquisition;

[0026]

[0027] In the formula, a1 represents the first nonlinear coefficient, a2 represents the second nonlinear coefficient, considering the nonlinear behavior of the steel wire under different strains, β1 represents the first temperature coupling coefficient, β2 represents the second temperature coupling coefficient, considering the dynamic correction effect of temperature on stress, δ f represents the vibration frequency correction coefficient, v represents the high-frequency component of the vibration, δ d represents the first time delay correction coefficient, λ d It represents the second time correction coefficient, taking into account the time delay effect of system response, t represents time, e represents exponential function, cos represents cosine function, and w represents vibration frequency;

[0028] The data storage unit uses InfluxDB to build a time series database, records the tensile strength data according to the implementation sequence, combines the acquired wire data with a wire strength feature set, stores it in real time, and sets an API application program interface to be integrated with the wire strength analysis module, the wire strength evaluation module and the visual early warning module.

[0029] Preferably, the wire strength analysis module includes a transient stress analysis unit, a dynamic temperature correction unit and a vibration frequency correction unit;

[0030] The transient stress analysis unit is used to construct a transient strain-stress relationship algorithm formula, and to extract the wire data group in the time series database in real time to calculate and obtain the transient stress coefficient Y(t);

[0031] The transient stress coefficient Y(t) is calculated by the following transient strain-stress relationship algorithm formula;

[0032]

[0033] Where, Y(t) represents the transient stress coefficient of the steel wire at time t, E(t) represents the elastic modulus of the steel wire at time t, represents the transient strain rate at time t, ΔT(t) represents the temperature change at time t, and λ represents the temperature correction coefficient.

[0034] Preferably, the dynamic temperature correction unit is used to construct a dynamic temperature correction algorithm formula, extract the wire data group in the time series database in real time, and combine the transient stress coefficient Y(t) of the steel wire at time t to further calculate and obtain the stress temperature correction coefficient Y T (t);

[0035] The stress temperature correction factor Y T (t) is calculated and obtained by the following dynamic temperature correction algorithm formula;

[0036] Y T (t) = Y (t) × (1 + δ T ·e -θ·T(t) );

[0037] Where Y T (t) represents the stress temperature correction coefficient at time t, δ T It represents the dynamic temperature correction coefficient, θ represents the temperature influence attenuation coefficient. The significance of the formula is that by correcting the stress value through temperature, the stress calculation can be more consistent with the temperature changes in the actual operating environment.

[0038] Preferably, the vibration frequency correction unit constructs a vibration frequency influence algorithm formula, extracts the wire data group in the time series database in real time, and combines the stress temperature correction coefficient Y at time t T (t), further calculate to obtain the stress vibration correction coefficient Y a (t);

[0039] The stress vibration correction factor Y a Obtained through the following vibration frequency influence algorithm formula calculation;

[0040] Y a (t) = Y T (t)×(1+γ·sin(w·t));

[0041] In the formula, sin represents the cosine function. The significance of the formula is to correct the stress value of the steel wire in a vibration environment.

[0042] Preferably, the wire strength assessment module includes a comprehensive analysis unit and a tensile strength assessment unit;

[0043] The comprehensive analysis unit is used to extract the obtained transient stress coefficient Y(t), stress temperature correction coefficient YT (t) and stress vibration correction factor Y a (t), and then extract the wire strength feature set from the time series database and perform combined calculation to obtain the comprehensive stress value Y final (t);

[0044] The comprehensive stress value Y final (t) is calculated and obtained by the following algorithm formula;

[0045]

[0046] Where ζ represents the strain correction factor, Y final (t) represents the comprehensive stress value of the steel wire at time t;

[0047] The tensile strength evaluation unit is used to preset a stress threshold L1 based on the standard tensile strength stress value of the steel wire, and then compare it with the obtained comprehensive stress value Y final (t) Conduct comparative evaluation and analysis to analyze the tensile strength of the steel wire rod. The specific evaluation contents are as follows;

[0048] When the comprehensive stress value Y final When (t)>stress threshold L1, the steel wire is marked as overloaded by tension, and the first evaluation result is generated;

[0049] When the comprehensive stress value Y final When (t) = stress threshold L1, the steel wire is marked to be subjected to abnormal tension, and a second evaluation result is generated;

[0050] When the comprehensive stress value Y final When (t) is less than the stress threshold L1, the steel wire is marked to withstand the tension normally, and the third evaluation result is generated.

[0051] Preferably, the visual warning module includes a visual interaction unit and a warning unit;

[0052] The visualization interaction unit is used to construct a visual user-friendly interface, use Tableau to set up a tensile strength chart and an interactive dashboard, and integrate with the wire strength analysis module and the wire strength evaluation module to receive the acquired transient stress coefficient Y(t) and stress temperature correction coefficient Y in real time. T (t), stress vibration correction factor Y a (t) and the comprehensive stress value Y final (t), conduct visual interaction;

[0053] The early warning unit is used to receive the assessment in real time, and generate early warning information by analyzing the received assessment results, and display it on a visual user-friendly interface for response. The specific analysis and early warning information are as follows;

[0054] When the first evaluation result is received, a first instruction is sent to the tensile testing machine to stop the operation, and a first-level warning message is generated, indicating that the steel wire will break if tension is applied again;

[0055] When the second evaluation result is received, a second instruction is sent to the tensile testing machine to reduce the tensile force by 50%, and a second-level warning message is generated, indicating that the steel wire exceeds the normal tensile strength value;

[0056] When the third evaluation result is received, there is no need to send an instruction to continue applying the tension.

[0057] A second aspect of the present application provides a method for detecting the tensile strength of a metal wire, comprising the following steps:

[0058] S1. When the steel wire is subjected to a tensile strength test, a sensor group is installed on the steel wire to collect tensile strength data of the steel wire in real time, and the tensile strength data is transmitted to a data processing module;

[0059] S2, receiving tensile strength data in real time, and obtaining a wire strength data group after preprocessing the tensile strength data, and extracting features from the wire strength data group to obtain a wire strength feature set, and then storing the wire strength data group and the wire strength feature set in a time series database;

[0060] S3, construct a strength analysis algorithm model, input the extracted wire strength data group into the strength analysis algorithm model, calculate and output the transient stress coefficient Y(t), stress temperature correction coefficient Y T (t) and stress vibration correction factor Y a (t);

[0061] S4. The obtained transient stress coefficient Y(t) and stress temperature correction coefficient Y T (t) and stress vibration correction factor Y a (t), and then perform comprehensive calculation with the wire strength characteristic set to obtain the comprehensive stress value Y final (t), and preset the stress threshold L1 and the obtained comprehensive stress value Y final (t) Compare and evaluate, and output warning information;

[0062] S5. Build a user-friendly interface and set up a database system to receive warning information in real time for storage and recording, analyze the warning information, and generate visual data display and alarm settings.

[0063] The present invention provides a metal wire tensile strength detection system and detection method.

[0064] Beneficial effects:

[0065] (1) The system can collect tensile strength data in real time and accurately by installing strain gauges, temperature sensors, accelerometers and displacement sensors at both ends and the midline of the steel wire. The data acquisition module uses LoRa wireless communication technology to transmit these data to the data processing module to ensure the stability and real-time performance of data transmission. The data processing module removes outliers, noise and normalizes these data, and then performs time domain conversion and feature extraction to generate a wire strength feature set. Through in-depth mining of tensile strength data and extraction of multi-dimensional features, the system can more accurately reflect the mechanical properties of steel wire under different working conditions, improving the system's data processing capabilities and analysis depth.

[0066] (2) The system constructs algorithm models such as transient strain-stress relationship, dynamic temperature correction, and vibration frequency correction. These models calculate the transient stress coefficient Y(t), stress temperature correction coefficient Y(t) in real time. T (t) and stress vibration correction factor Y a (t), and combine it with the wire strength feature set to finally calculate the comprehensive stress value Y final (t). Comprehensive stress value Y final The calculation of (t) fully considers complex factors such as nonlinear stress-strain relationship, temperature-stress coupling effect, and vibration influence, so that the system can accurately evaluate the tensile strength of steel wire under a variety of complex environmental conditions. This multi-factor dynamic correction algorithm mechanism effectively improves the system's adaptability to complex working conditions and ensures high accuracy and reliability of the evaluation results.

[0067] (3) The system uses the built-in visual warning module and Tableau to build a user-friendly interactive interface, which can display the transient stress coefficient Y(t), stress temperature correction coefficient Y(t) and other parameters in real time. T (t), stress vibration correction factor Y a (t) and the comprehensive stress value Y final (t) dynamic changes. The early warning module comprehensively analyzes the evaluation results. When the comprehensive stress value Y final (t) When the stress threshold L1 is exceeded, the system will automatically generate a warning message and send a command to the tensile testing machine to stop operation or reduce tension to prevent accidents such as wire breakage. When the comprehensive stress value is normal, the system will not issue a stop command to ensure the continuity of operation. This intelligent warning mechanism not only improves the safety of steel wire tensile strength testing, but also provides operators with timely risk feedback, greatly reducing safety hazards caused by tensile overload and effectively extending the service life of steel wire. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] Figure 1This is a schematic diagram of the process of a metal wire tensile strength detection system of the present invention;

[0069] Figure 2 The present invention is a schematic diagram of the steps of a method for detecting the tensile strength of a metal wire. DETAILED DESCRIPTION

[0070] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0071] Example 1

[0072] See also Figure 1 , the present invention provides a metal wire tensile strength detection system. To achieve the above purpose, the present invention is implemented through the following technical solutions: including a data acquisition module, a data processing module, a wire strength analysis module, a wire strength evaluation module and a visual early warning module;

[0073] The data acquisition module installs a sensor group on the steel wire during the tensile strength test of the steel wire to collect the tensile strength data of the steel wire in real time, and transmits the tensile strength data to the data processing module;

[0074] The data processing module is used to receive the tensile strength data in real time, and after preprocessing the tensile strength data, obtain the wire strength data group, extract the features of the wire strength data group to obtain the wire strength feature set, and then store the wire strength data group and the wire strength feature set in the time series database;

[0075] The wire strength analysis module is used to build a strength analysis algorithm model, input the extracted wire strength data group into the strength analysis algorithm model, and calculate and output the transient stress coefficient Y(t) and stress temperature correction coefficient Y T (t) and stress vibration correction factor Y a (t);

[0076] The wire strength assessment module is used to convert the obtained transient stress coefficient Y(t), stress temperature correction coefficient Y T (t) and stress vibration correction factor Y a (t), and then perform comprehensive calculation with the wire strength characteristic set to obtain the comprehensive stress value Y final (t), and preset the stress threshold L1 and the obtained comprehensive stress value Y final (t) Compare and evaluate, and output warning information;

[0077] The visual warning module is used to build a user-friendly interface, receive warning information in real time for storage and recording, analyze the warning information, and generate visual data display and alarm settings.

[0078] In this embodiment, the system realizes real-time and high-precision acquisition of the tensile strength of steel wires through the data acquisition module, and transmits the collected tensile strength data to the data processing module through LoRa wireless communication technology. The data processing module preprocesses and extracts features from these data, and stores the processed data in a time series database for subsequent analysis and evaluation. The wire strength analysis module constructs a strength analysis algorithm model and outputs accurate transient stress coefficient Y(t), stress temperature correction coefficient Y T (t) and stress vibration correction factor Y a (t), laying the foundation for further evaluation. Through the wire strength evaluation module, the system further comprehensively calculates the various coefficients generated by the analysis module and the wire strength feature set to obtain the comprehensive stress value Y final (t). This comprehensive stress value Y final (t) is compared with the set stress threshold L1, which can accurately evaluate the actual tensile strength state of the steel wire. When it is found that the stress on the steel wire exceeds the set stress threshold L1, the system will generate an early warning message and take corresponding control measures in time, such as stopping the operation of the tensile machine or reducing the tension, so as to effectively prevent accidents. This evaluation mechanism ensures that the system accurately grasps the state of the steel wire, so that the steel wire is always within a safe and controllable range during use, greatly improving operational safety and equipment service life.

[0079] Example 2

[0080] This embodiment is explained in Example 1, please refer to Figure 1 ,Specifically: the data acquisition module includes an acquisition unit and a transmission unit;

[0081] The acquisition unit is used to install sensor groups at both ends and the midline of the steel wire when testing the tensile strength of the steel wire to collect the tensile strength data of the steel wire in real time;

[0082] The sensor set includes strain gauges, temperature sensors, accelerometers, and displacement sensors;

[0083] The tensile strength data include strain ε, tension F, temperature T and dynamic load acceleration a;

[0084] The transmission unit transmits the collected tensile strength data to the data processing module through the LoRa wireless communication technology.

[0085] In this embodiment, the data acquisition module realizes multi-dimensional and real-time monitoring of tensile strength by installing the sensor group at the key position of the steel wire. This multi-sensor collaborative working mode greatly improves the accuracy and comprehensiveness of the data. In addition, through the application of LoRa wireless communication technology, the collected tensile strength data can be transmitted to the data processing module in a timely and stable manner, ensuring the real-time and transmission efficiency of the data. The module has significantly improved the accuracy of collected data and the real-time transmission. Traditional methods often rely on a single sensor or wired transmission, which may result in data loss or transmission delay. The system monitors through multiple sensors at the same time, ensuring the comprehensiveness of the data, and overcomes the distance limitation through wireless transmission, improving the flexibility and response speed of the system. Finally, the data acquisition module provides high-quality basic data for subsequent data processing, analysis and evaluation, significantly improving the overall effect and reliability of tensile strength detection.

[0086] Example 3

[0087] This embodiment is explained in Example 2. Please refer to Figure 1 ,Specifically: the data processing module includes a processing unit, a feature extraction unit and a data storage unit;

[0088] The processing unit is used to receive the collected tensile strength data in real time, remove outliers, noise and normalize the tensile strength, perform time domain conversion on the wire strength data group, mark the wire strength data group with a timestamp, and then obtain the wire strength data group by performing correlation calculation on the processed tensile strength data;

[0089] Wire strength data set including transient strain rate Dynamic temperature correction coefficient δ T (t), vibration frequency stress influence coefficient γ(t) and tension F(t) at time t;

[0090] Transient strain rate The strain rate is estimated from discrete data points using numerical differentiation methods, as follows: Where d is the differential, dt is the time differential;

[0091] Dynamic temperature correction coefficient δ T (t) is obtained by fitting the stress-strain data of steel wire at different temperatures. The specific calculation formula is: Where σ(T) is the stress at temperature T, and σ(T0) represents the stress at reference temperature T0;

[0092] The vibration frequency stress influence coefficient γ(t) is obtained by measuring the vibration acceleration of the steel wire with an accelerometer, determining the dynamic load acceleration a, calculating the acceleration amplitude △a, and then calculating it with the stress change Δσ caused by vibration. The specific calculation formula is:

[0093] Feature extraction sheet is used to build a collection of feature extraction algorithms Extract wire strength data and input it into the feature extraction algorithm collection In the process, feature extraction is performed and the wire strength feature set is output. The wire strength feature set includes the nonlinear stress-strain relationship Temperature-stress coupling effect η(T(t)), high-frequency correction κ(w, t) for vibration effects, and time delay correction δ delay (t);

[0094] Nonlinear stress-strain relationship Temperature-stress coupling effect η(T(t)), high-frequency correction κ(w, t) for vibration effects, and time delay correction δ delay (t) Through the following feature extraction algorithm collection Calculate acquisition;

[0095]

[0096] In the formula, a1 represents the first nonlinear coefficient, a2 represents the second nonlinear coefficient, considering the nonlinear behavior of the steel wire under different strains, β1 represents the first temperature coupling coefficient, β2 represents the second temperature coupling coefficient, considering the dynamic correction effect of temperature on stress, δ f represents the vibration frequency correction coefficient, v represents the high-frequency component of the vibration, δ d represents the first time delay correction coefficient, λ d It represents the second time correction coefficient, taking into account the time delay effect of system response, t represents time, e represents exponential function, cos represents cosine function, and w represents vibration frequency;

[0097] The data storage unit uses InfluxDB to build a time series database, records the tensile strength data according to the implementation sequence, and then combines the acquired wire data with the wire strength feature set for real-time storage, and sets an API application interface to integrate with the wire strength analysis module, wire strength assessment module and visual early warning module.

[0098] In this embodiment, the system can not only receive the collected tensile strength data in real time through the processing unit, but also ensure the accuracy and consistency of the data by removing outliers, noise and normalization. Through time domain conversion and timestamp annotation, the module further optimizes the timing characteristics of the data, providing an accurate basis for subsequent analysis. The feature extraction unit uses a collection of feature extraction algorithms to perform in-depth analysis on the processed data and extract the wire strength feature set, thereby providing important parameter support for the strength analysis and evaluation of the system. Finally, the data storage unit uses InfluxDB to build an efficient time series database, which can not only store the processed data and extracted feature sets in real time, but also achieve seamless connection with other modules through the API interface to ensure the smooth flow of data in the entire system.

[0099] Example 4

[0100] This embodiment is explained in Example 3, please refer to Figure 1 ,Specifically: the wire strength analysis module includes a transient stress analysis unit, a dynamic temperature correction unit, and a vibration frequency correction unit;

[0101] The transient stress analysis unit is used to construct the transient strain-stress relationship algorithm formula, and to extract the wire data group in the time series database in real time to calculate and obtain the transient stress coefficient Y(t);

[0102] The transient stress coefficient Y(t) is calculated by the following transient strain-stress relationship algorithm formula;

[0103]

[0104] Where, Y(t) represents the transient stress coefficient of the steel wire at time t, E(t) represents the elastic modulus of the steel wire at time t, represents the transient strain rate at time t, ΔT(t) represents the temperature change at time t, and λ represents the temperature correction coefficient.

[0105] The dynamic temperature correction unit is used to construct a dynamic temperature correction algorithm formula, extract the wire data group in the time series database in real time, and combine the transient stress coefficient Y(t) of the steel wire at time t to further calculate the stress temperature correction coefficient Y T (t);

[0106] Stress temperature correction factor Y T (t) is calculated and obtained by the following dynamic temperature correction algorithm formula;

[0107] Y T (t) = Y (t) × (1 + δ T ·e -θ·T(t) );

[0108] Where Y T (t) represents the stress temperature correction coefficient at time t, δ T It represents the dynamic temperature correction coefficient, θ represents the temperature influence attenuation coefficient. The significance of the formula is that by correcting the stress value through temperature, the stress calculation can be more consistent with the temperature changes in the actual operating environment.

[0109] The vibration frequency correction unit constructs the vibration frequency influence algorithm formula, extracts the wire data group in the time series database in real time, and combines the stress temperature correction coefficient Y at time t T (t), further calculate to obtain the stress vibration correction coefficient Y a (t);

[0110] Stress vibration correction factor Y a Obtained through the following vibration frequency influence algorithm formula calculation;

[0111] Y a (t) = Y T (t)×(1+γ·sin(w·t));

[0112] In the formula, sin represents the cosine function. The significance of the formula is to correct the stress value of the steel wire in a vibration environment.

[0113] In this embodiment, the system uses the transient strain-stress relationship algorithm constructed by the transient stress analysis unit to enable the system to calculate and obtain the transient stress coefficient Y(t) of the steel wire at different time points in real time, thereby dynamically reflecting the instantaneous state of the wire under stress changes. The dynamic temperature correction unit further generates the stress temperature correction coefficient Y by combining the transient stress coefficient Y(t) and the temperature change data. T (t), effectively correcting the stress value to make it more consistent with the temperature fluctuation in the actual operating environment. The vibration frequency correction unit introduces the vibration frequency influence algorithm to correct the stress value in the vibration environment in real time and obtain the stress vibration correction coefficient Y a (t), thereby ensuring the accuracy of wire strength analysis even under complex vibration conditions. This module significantly improves the accuracy and real-time performance of steel wire stress analysis through the introduction of multivariate algorithms. Traditional methods often ignore the dynamic effects of temperature and vibration, but this system solves this problem through precise calculation of temperature correction and vibration correction, making the analysis results closer to the actual application environment. In addition, the system introduces a mechanism of dynamic data extraction and real-time correction during the calculation process to ensure the efficiency and accuracy of stress analysis. These improvements effectively improve the system's adaptability and analysis depth in complex environments, and ultimately provide a more reliable basis for wire strength assessment and early warning.

[0114] Example 5

[0115] This embodiment is explained in Example 4. Please refer to Figure 1 ,Specifically: the wire strength evaluation module includes a comprehensive analysis unit and a tensile strength evaluation unit;

[0116] The comprehensive analysis unit is used to extract the transient stress coefficient Y(t) and stress temperature correction coefficient Y in real time. T (t) and stress vibration correction factor Y a (t), and then extract the wire strength feature set from the time series database and perform combined calculation to obtain the comprehensive stress value Y final (t);

[0117] Comprehensive stress value Y final (t) is calculated and obtained by the following algorithm formula;

[0118]

[0119] Where ζ represents the strain correction factor, Y final (t) represents the comprehensive stress value of the steel wire at time t;

[0120] The tensile strength evaluation unit is used to preset the stress threshold L1 based on the standard tensile strength stress value of the steel wire, and then compare it with the obtained comprehensive stress value Y final (t) Conduct comparative evaluation and analysis to analyze the tensile strength of the steel wire rod. The specific evaluation contents are as follows;

[0121] When the comprehensive stress value Y final When (t)>stress threshold L1, the steel wire is marked as overloaded by tension, and the first evaluation result is generated;

[0122] When the comprehensive stress value Y final When (t) = stress threshold L1, the steel wire is marked to be subjected to abnormal tension, and a second evaluation result is generated;

[0123] When the comprehensive stress value Y final When (t) is less than the stress threshold L1, the steel wire is marked to withstand the tension normally, and the third evaluation result is generated.

[0124] In this embodiment, the system extracts the transient stress coefficient Y(t), the stress temperature correction coefficient Y(t) and the stress temperature correction coefficient Y(t) in real time through the comprehensive analysis unit. T (t) and stress vibration correction factor Y a (t), combined with the wire strength characteristic set, the comprehensive stress value Y is accurately calculated final (t), thus fully reflecting the actual stress of the wire under various stress factors. The tensile strength evaluation unit will final(t) is compared with the preset stress threshold L1 to quickly evaluate the tensile strength state of the steel wire, provide clear evaluation results, and mark whether the wire is overloaded or abnormal. This module effectively solves this problem by introducing multiple correction coefficients. In addition, the real-time calculation and evaluation functions of the system greatly improve the evaluation efficiency, can quickly respond to changes in wire strength, and generate evaluation results and early warning information in a timely manner. These improvements significantly enhance the reliability and safety of the system in practical applications and ensure the safe use of wires in complex environments.

[0125] Example 6

[0126] This embodiment is explained in Example 5. Please refer to Figure 1 ,Specifically: the visual warning module includes a visual interaction unit and a warning unit;

[0127] The visualization interaction unit is used to build a visual user-friendly interface, use Tableau to set up tensile strength charts and interactive dashboards, and integrate with the wire strength analysis module and the wire strength evaluation module to receive the acquired transient stress coefficient Y(t) and stress temperature correction coefficient Y in real time. T (t), stress vibration correction factor Y a (t) and the comprehensive stress value Y final (t), conduct visual interaction;

[0128] The early warning unit is used to receive the assessment in real time, and generate early warning information by analyzing the received assessment results, and display it on a visual user-friendly interface for response. The specific analysis and early warning information are as follows;

[0129] When the first evaluation result is received, a first instruction is sent to the tensile testing machine to stop the operation, and a first-level warning message is generated, indicating that the steel wire will break if tension is applied again;

[0130] When the second evaluation result is received, a second instruction is sent to the tensile testing machine to reduce the tensile force by 50%, and a second-level warning message is generated, indicating that the steel wire exceeds the normal tensile strength value;

[0131] When the third evaluation result is received, there is no need to send an instruction to continue applying the tension.

[0132] In this embodiment, the visualization interaction unit uses a user-friendly interface built by Tableau to convert the transient stress coefficient Y(t), the stress temperature correction coefficient Y T (t), stress vibration correction factor Y a (t) and the comprehensive stress value Y final(t) is displayed in the form of intuitive charts and dashboards, which enhances the user's understanding and control of the stress state of the wire. The early warning unit automatically generates early warning information through real-time analysis of the evaluation results, and takes corresponding control measures, such as stopping or adjusting the operation of the tensile machine to ensure that the steel wire does not continue to work under overload, thereby avoiding potential breakage risks. This module significantly improves the intelligence and automation level of operation. Traditional systems usually require manual intervention to analyze data and make decisions, while this module greatly reduces the complexity of manual operation and improves the response speed through automated real-time analysis and visual display. In the face of emergencies, the system can respond in time to prevent accidents. In addition, through Tableau's interactive interface, users can more conveniently customize monitoring views and early warning conditions, which significantly enhances the flexibility and adaptability of the system. These improvements not only improve the safety and efficiency of the system, but also provide a more reliable and intelligent solution for the tensile strength test of steel wire.

[0133] Example 7

[0134] See also Figure 1 and Figure 2 , a method for detecting the tensile strength of a metal wire, comprising the following steps:

[0135] S1. When the steel wire is subjected to a tensile strength test, a sensor group is installed on the steel wire to collect tensile strength data of the steel wire in real time, and the tensile strength data is transmitted to a data processing module;

[0136] S2, receiving tensile strength data in real time, and obtaining a wire strength data group after preprocessing the tensile strength data, and extracting features from the wire strength data group to obtain a wire strength feature set, and then storing the wire strength data group and the wire strength feature set in a time series database;

[0137] S3, construct a strength analysis algorithm model, input the extracted wire strength data group into the strength analysis algorithm model, calculate and output the transient stress coefficient Y(t), stress temperature correction coefficient Y T (t) and stress vibration correction factor Y a (t);

[0138] S4. The obtained transient stress coefficient Y(t) and stress temperature correction coefficient Y T (t) and stress vibration correction factor Y a (t), and then perform comprehensive calculation with the wire strength characteristic set to obtain the comprehensive stress value Y final (t), and preset the stress threshold L1 and the obtained comprehensive stress value Y final (t) Compare and evaluate, and output warning information;

[0139] S5. Build a user-friendly interface and set up a database system to receive warning information in real time for storage and recording, analyze the warning information, and generate visual data display and alarm settings.

[0140] While the embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that many changes, modifications, substitutions and variations can be made to the embodiments without departing from the principles and spirit of the invention.

Claims

1. A metal wire tensile strength detection system, characterized in that: It includes data acquisition module, data processing module, wire strength analysis module, wire strength assessment module and visual early warning module; The data acquisition module is used to collect the tensile strength data of the steel wire in real time during the tensile strength test of the steel wire, and transmit the tensile strength data to the data processing module; The data processing module is used to receive the tensile strength data in real time, pre-process the tensile strength data to obtain a wire strength data group, and extract features from the wire strength data group to obtain a wire strength feature set, and then store the wire strength data group and the wire strength feature set in a time series database; The wire strength analysis module is used to construct a strength analysis algorithm model, input the wire strength data set into the strength analysis algorithm model, and calculate the output transient stress coefficient Y(t), stress temperature correction coefficient Y T (t) and stress vibration correction factor Y a (t); The wire strength evaluation module is used to convert the transient stress coefficient Y(t), the stress temperature correction coefficient Y T (t) and the stress vibration correction factor Y a (t), and the wire strength characteristic set is comprehensively calculated to obtain the comprehensive stress value Y final (t), and preset the stress threshold L1 and the comprehensive stress value Y final (t) Compare and evaluate, and output warning information; The visual warning module is used to build a user-friendly interface, receive the warning information in real time and store and record it, analyze the warning information, and generate visual data display and alarm settings.

2. A metal wire tensile strength detection system according to claim 1, characterized in that: The data acquisition module includes an acquisition unit and a transmission unit; The acquisition unit is used to install sensor groups at both ends and the midline of the steel wire rope when testing the tensile strength of the steel wire rope, so as to collect the tensile strength data of the steel wire rope in real time; The sensor group includes a strain gauge, a temperature sensor, an accelerometer and a displacement sensor; The tensile strength data include strain ε, tension F, temperature T and dynamic load acceleration a; The transmission unit transmits the collected tensile strength data to the data processing module through the LoRa wireless communication technology.

3. A metal wire tensile strength detection system according to claim 1, characterized in that: The data processing module includes a processing unit, a feature extraction unit and a data storage unit; The processing unit is used to receive the collected tensile strength data in real time, remove outliers, noise and normalize the tensile strength data, perform time domain conversion on the wire strength data group, mark the wire strength data group with a timestamp, and then obtain the wire strength data group by performing correlation calculation on the processed tensile strength data; The wire strength data set includes transient strain rate Dynamic temperature correction coefficient δ T (t), vibration frequency stress influence coefficient γ(t) and tension F(t) at time t; wherein the transient strain rate The strain rate is estimated from discrete data points using numerical differentiation methods, as follows: Where d is the differential, dt is the time differential; the dynamic temperature correction coefficient δ T (t) is obtained by fitting the stress-strain data of steel wire at different temperatures. The specific calculation formula is: Wherein σ(T) is the stress at temperature T, σ(T0) represents the stress at reference temperature T0; the vibration frequency stress influence coefficient γ(t) is obtained by measuring the vibration acceleration of the steel wire with an accelerometer, determining the dynamic load acceleration a, calculating the acceleration amplitude △a, and then calculating the stress change Δσ caused by vibration. The specific calculation formula is:

4. A metal wire tensile strength detection system according to claim 3, characterized in that: The feature extraction unit is used to construct a feature extraction algorithm collection ( η(T(t)),κ(w,t),δ delay (t)), and input the extracted wire strength data into the feature extraction algorithm collection ( η(T(t)),κ(w,t),δ delay (t)) to extract features and output a wire strength feature set, wherein the wire strength feature set includes a nonlinear stress-strain relationship Temperature-stress coupling effect η(T(t)), high-frequency correction κ(w, t) for vibration effects, and time delay correction δ delay (t); The data storage unit is used to build a time series database by using InfluxDB, record the tensile strength data according to the implementation sequence, and then combine the acquired wire data with the wire strength feature set for real-time storage, and set an API application program interface to be integrated with the wire strength analysis module, the wire strength evaluation module and the visual warning module; Among them, the nonlinear stress-strain relationship Temperature-stress coupling effect η(T(t)), high-frequency correction κ(w, t) for vibration effects, and time delay correction δ delay (t) Through the following feature extraction algorithm collection ( η(T(t)),κ(w,t),δ delay (t)) Calculate and obtain; Where a1 represents the first nonlinear coefficient, a2 represents the second nonlinear coefficient, β1 represents the first temperature coupling coefficient, β2 represents the second temperature coupling coefficient, δ f represents the vibration frequency correction coefficient, v represents the high-frequency component of the vibration, δ d represents the first time delay correction coefficient, λ d represents the second time correction coefficient, t represents time, e represents exponential function, cos represents cosine function, and w represents vibration frequency.

5. A metal wire tensile strength detection system according to claim 1, characterized in that: The wire strength analysis module includes a transient stress analysis unit, a dynamic temperature correction unit and a vibration frequency correction unit; The transient stress analysis unit is used to construct a transient strain-stress relationship algorithm formula, and to extract the wire data group in the time series database in real time to calculate and obtain the transient stress coefficient Y(t); The transient stress coefficient Y(t) is calculated by the following transient strain-stress relationship algorithm formula; Where, Y(t) represents the transient stress coefficient of the steel wire at time t, E(t) represents the elastic modulus of the steel wire at time t, represents the transient strain rate at time t, ΔT(t) represents the temperature change at time t, and λ represents the temperature correction coefficient.

6. A metal wire tensile strength detection system according to claim 5, characterized in that: The dynamic temperature correction unit is used to construct a dynamic temperature correction algorithm formula, extract the wire data group in the time series database in real time, and combine the transient stress coefficient Y(t) of the steel wire at time t to calculate the stress temperature correction coefficient Y T (t); The stress temperature correction factor Y T (t) is calculated and obtained by the following dynamic temperature correction algorithm formula; Y T (t)=Y(t)×(1+δ T ·e -θ·T(t) ); Where Y T (t) represents the stress temperature correction coefficient at time t, δ T represents the dynamic temperature correction coefficient, and θ represents the temperature influence attenuation coefficient.

7. A metal wire tensile strength detection system according to claim 5, characterized in that: The vibration frequency correction unit is used to construct a vibration frequency influence algorithm formula, extract the wire data group in the time series database in real time, and combine the stress temperature correction coefficient Y at time t T (t) is calculated to obtain the stress vibration correction coefficient Y a (t); The stress vibration correction factor Y a Obtained through the following vibration frequency influence algorithm formula calculation; Y a (t)=Y T (t)×(1+γ·sin(w·t)); In the formula, sin represents the cosine function. The significance of the formula is to correct the stress value of the steel wire in a vibration environment.

8. A metal wire tensile strength detection system according to claim 1, characterized in that: The wire strength assessment module includes a comprehensive analysis unit and a tensile strength assessment unit; The comprehensive analysis unit is used to extract the obtained transient stress coefficient Y(t), stress temperature correction coefficient Y T (t) and stress vibration correction factor Y a (t), and then extract the wire strength feature set from the time series database and perform combined calculation to obtain the comprehensive stress value Y final (t); The comprehensive stress value Y final (t) is calculated and obtained by the following algorithm formula; Where ζ represents the strain correction factor, Y final (t) represents the comprehensive stress value of the steel wire at time t; The tensile strength evaluation unit is used to preset a stress threshold L1 based on the standard tensile strength stress value of the steel wire, and then compare it with the obtained comprehensive stress value Y final (t) Conduct comparative evaluation and analysis to analyze the tensile strength of the steel wire rod. The specific evaluation contents are as follows; When the comprehensive stress value Y final When (t)>stress threshold L1, the tensile force borne by the steel wire is marked as overloaded, and a first evaluation result is generated; When the comprehensive stress value Y final When (t) = stress threshold L1, the steel wire is marked as abnormally stressed and a second evaluation result is generated; When the comprehensive stress value Y final When (t) < stress threshold L1, it is marked that the steel wire can withstand the tension normally, and a third evaluation result is generated.

9. A metal wire tensile strength detection system according to claim 1, characterized in that: The visual warning module includes a visual interaction unit and a warning unit; The visualization interaction unit is used to construct a visual user-friendly interface, use Tableau to set up a tensile strength chart and an interactive dashboard, and integrate with the wire strength analysis module and the wire strength evaluation module to receive the acquired transient stress coefficient Y(t) and stress temperature correction coefficient Y in real time. T (t), stress vibration correction factor Y a (t) and the comprehensive stress value Y final (t), conduct visual interaction; The early warning unit is used to receive the assessment in real time, and generate early warning information by analyzing the received assessment results, and display it on a visual user-friendly interface for response. The specific analysis and early warning information are as follows; When the first evaluation result is received, a first instruction is sent to the tensile machine to stop the operation, and a first-level warning message is generated, indicating that the steel wire will break if tension is applied again; When the second evaluation result is received, a second instruction is sent to the tensile testing machine to reduce the tensile force by 50%, and a second-level warning message is generated, indicating that the steel wire exceeds the normal tensile strength value; When the third evaluation result is received, there is no need to send an instruction to continue applying the pulling force.

10. A metal wire tensile strength detection method, applied to a metal wire tensile strength detection system according to any one of claims 1 to 9, characterized in that: The following steps are involved: S1. When the steel wire is subjected to a tensile strength test, a sensor group is installed on the steel wire to collect tensile strength data of the steel wire in real time, and the tensile strength data is transmitted to a data processing module; S2, receiving tensile strength data in real time, and obtaining a wire strength data group after preprocessing the tensile strength data, and extracting features from the wire strength data group to obtain a wire strength feature set, and then storing the wire strength data group and the wire strength feature set in a time series database; S3, construct a strength analysis algorithm model, input the extracted wire strength data group into the strength analysis algorithm model, calculate and output the transient stress coefficient Y(t), stress temperature correction coefficient Y T (t) and stress vibration correction factor Y a (t); S4. The obtained transient stress coefficient Y(t) and stress temperature correction coefficient Y T (t) and stress vibration correction factor Y a (t), and then perform comprehensive calculation with the wire strength characteristic set to obtain the comprehensive stress value Y final (t), and preset the stress threshold L1 and the obtained comprehensive stress value Y final (t) Compare and evaluate, and output warning information; S5. Build a user-friendly interface and set up a database system to receive warning information in real time for storage and recording, analyze the warning information, and generate visual data display and alarm settings.

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