A tensile strength detection system for metal wire and its detection method

Abstract

The present invention discloses a tensile strength detection system for metal wire and its detection method, which relates to the technical field of material testing. The system realizes the acquisition of the tensile strength data of steel wire through the data acquisition module, and transmits the acquired 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 the time series database. The wire strength analysis module outputs the accurate transient stress coefficient Y(t), stress-temperature correction coefficient Y T (t) and stress-vibration correction coefficient Y a (t), laying a foundation for further evaluation. The wire strength evaluation module outputs the comprehensive stress value Y final (t). By comparing this comprehensive stress value Y final (t) with the set stress threshold L1, the actual tensile strength state of the steel wire can be accurately evaluated.

Description

Technical Field

[0001] The present invention relates to the technical field of metal wire testing, and specifically to a tensile strength detection system for metal wires and its detection method. Background Technique

[0002] Since wire rods are delivered in coils, they are also called wire bars. Wire rods have other shapes besides circular cross-sections. Wire rods are generally made of ordinary carbon steel and high-quality carbon steel. Wire rods are the ones with the smallest cross-sectional dimensions among hot-rolled steel sections. Their diameters vary due to demand and production technology levels and are inconsistent. According to different rolling mills, they can be divided into high-speed wire rods (high wire) and ordinary wire rods (ordinary wire); in the tensile testing of wire rods, the metal wire tensile strength detection system often belongs to the field of material testing and analysis. This field mainly involves testing and evaluating the mechanical properties of metal materials; specifically, the tensile strength test is a key detection item in material mechanics. It evaluates the load-bearing capacity of metal wires under the action of tensile force and the maximum stress they can withstand before fracture; and steel wire rods, as one of the metal wires, are widely used in fields such as bridges, buildings, and mechanical equipment. The accurate detection of their tensile strength is crucial for ensuring the safety and reliability of these structures.

[0003] Currently, the existing steel wire rod tensile strength detection devices have certain limitations in data monitoring and analysis. Especially when dealing with complex working conditions, in the face of the transient fluctuations of the stress value of the wire rod caused by external factors such as temperature changes and vibration frequencies, the existing detection devices usually only focus on a single index of tensile force, thus ignoring the dynamic influence of environmental factors and stress fluctuations on the wire rod strength, resulting in the inability to accurately ensure the tensile strength of metal wires. In addition, the traditional detection systems also lack sufficient real-time performance and flexibility in data processing and analysis and cannot provide accurate early warning information in a timely manner, which may lead to potential safety hazards during the operation process.

[0004] For example: The Chinese utility model patent with the publication number CN219161806U and the name "A Metal Wire Tensile Strength Detection Device", when solving the problem of "the current tensile strength detection device excessively squeezes or bends the wire rod, resulting in deformation at both ends, and the two ends of the wire rod are relatively weak, resulting in the detected tensile strength being unequal to the true tensile strength", prevents the deformation of both ends of the wire rod by setting an arc-shaped depression and an elastic layer at the fixed block, reducing the error of being easily broken due to the deformation of both ends of the wire rod, and further reducing the occurrence of the situation of being easily broken due to the deformation of both ends of the wire rod. At the same time, it can prevent the object to be detected from falling off and is convenient for a large number of detections; however, this technical solution still cannot directly detect the problem of transient fluctuations in the stress value of the wire rod caused by external factors such as temperature changes and vibration frequencies, and it also cannot monitor and alarm the wire rod during the test process in real time and flexibly.

[0005] Therefore, how to intelligently test the tensile strength of metal wire is a technical problem that technicians need to solve at present. Summary of the Invention

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

[0007] To achieve the above object, 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 visualization warning module;

[0008] When the data acquisition module conducts a tensile strength test on the steel wire, a sensor group is installed on the steel wire to collect the tensile strength data of the steel wire in real time, and the tensile strength data is transmitted to the data processing module;

[0009] The data processing module is used to receive the tensile strength data in real time, preprocess the tensile strength data, obtain a wire strength data set, extract features from the wire strength data set to obtain a wire strength feature set, and then store the wire strength data set 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 set 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 the stress-vibration correction coefficient Y a (t);

[0011] The wire strength evaluation module is used to combine the obtained transient stress coefficient Y(t), the stress-temperature correction coefficient Y T (t), and the stress-vibration correction coefficient Y a (t) with the wire strength feature set for comprehensive calculation to obtain a comprehensive stress value Y final (t), preset a stress threshold L1, compare and evaluate it with the obtained comprehensive stress value Y final (t), and output a warning message;

[0012] The visualization warning module is used to construct a user-friendly interface, receive the warning message in real time for storage and recording, and analyze the warning message to generate a visualization 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 a sensor group at both ends and the midline position of the steel wire rod when testing the tensile strength of the steel wire rod, and to collect the tensile strength data of the steel wire rod 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 includes strain force ε, tensile force F, temperature T and dynamic load acceleration a;

[0017] The transmission unit transmits the collected tensile strength data to the data processing module through 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 rod strength data group, mark the wire rod strength data group with a timestamp, and then perform correlation calculation on the processed tensile strength data to obtain the wire rod strength data group;

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

[0021] The transient strain rate Estimate the strain rate from discrete data points by using numerical differentiation method, and the specific calculation formula is: In the formula, d is differentiation and dt is time differentiation;

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

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

[0024] Preferably, the feature extraction unit is used to construct a collection of feature extraction algorithms Extract the wire strength data and input it into the feature extraction algorithm set to perform feature extraction and output the wire strength feature set, where the wire strength feature set includes the non-linear stress-strain relationship the temperature-stress coupling effect η(T(t)), the high-frequency correction κ(w, t) of the vibration influence, and the time-delay correction δ delay (t);

[0025] The non-linear stress-strain relationship the temperature-stress coupling effect η(T(t)), the high-frequency correction κ(w, t) of the vibration influence, and the time-delay correction δ delay (t) is calculated through the following feature extraction algorithm set to obtain;

[0026]

[0027] In the formula, a1 represents the first non-linear coefficient, a2 represents the second non-linear coefficient, considering the non-linear 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 influence 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 represents the second time correction coefficient, considering the time-delay effect of the system response, t represents time, e represents the exponential function, cos represents the cosine function, w represents the vibration frequency;

[0028] The data storage unit constructs a time-series database using InfluxDB, records the tensile strength data according to the implementation sequence, then combines the obtained wire data with the wire strength feature set, stores it in real time, and sets up an API application program interface to be integrated and connected with the wire strength analysis module, the wire strength evaluation module, and the visualization 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 an algorithm formula for the transient strain-stress relationship, and 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 through the following algorithm formula for the transient strain-stress relationship;

[0032]

[0033] In the formula, Y(t) represents the transient stress coefficient of the steel wire at time t, and 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 further calculate and obtain the stress temperature correction coefficient Y in combination with the transient stress coefficient Y(t) of the steel wire at time t. T (t);

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

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

[0037] In the formula, Y T (t) represents the stress temperature correction coefficient at time t, δ T represents the dynamic temperature correction coefficient, θ represents the temperature influence attenuation coefficient, and the meaning of the formula is to correct the stress value through temperature so that the stress calculation is more in line with the temperature change in the actual operating environment.

[0038] Preferably, the vibration frequency correction unit extracts the wire data group in the time series database in real time by constructing a vibration frequency influence algorithm formula, and further calculates and obtains the stress vibration correction coefficient Y in combination with the stress temperature correction coefficient Y T (t) at time t. a (t);

[0039] The stress vibration correction coefficient Y a is calculated and obtained through the following vibration frequency influence algorithm formula;

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

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

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

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

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

[0045]

[0046] In the formula, ζ represents the strain correction coefficient, and 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 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) for comparative evaluation and analysis to analyze the tensile strength of the steel wire. The specific evaluation content is as follows;

[0048] When the comprehensive stress value Y final (t) > stress threshold L1, mark that the tension borne by the steel wire is overloaded, and generate the first evaluation result at this time;

[0049] When the comprehensive stress value Y final (t) = stress threshold L1, mark that the tension borne by the steel wire is abnormal, and generate the second evaluation result at this time;

[0050] When the comprehensive stress value Y final (t) < stress threshold L1, mark that the tension borne by the steel wire is normal, and generate the third evaluation result at this time.

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

[0052] The visual interaction unit is used to construct a visual user-friendly interface, set the tensile strength chart and interactive dashboard using Tableau, and integrate and connect with the wire strength analysis module and the wire strength evaluation module to receive the obtained transient stress coefficient Y(t), stress temperature correction coefficient Y T (t), stress vibration correction coefficient Y a (t) and comprehensive stress value Y final (t) for visual interaction;

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

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

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

[0056] When the third evaluation result is received, no instruction is sent and the tensile force is continuously applied.

[0057] The second aspect of this application provides a method for detecting the tensile strength of metal wire, including the following steps:

[0058] S1. When testing the tensile strength of the steel wire, install a sensor group on the steel wire to collect the tensile strength data of the steel wire in real time, and transmit the tensile strength data to the data processing module;

[0059] S2. Receive the tensile strength data in real time. After preprocessing the tensile strength data, obtain a wire strength data set, extract features from the wire strength data set to obtain a wire strength feature set, and then store the wire strength data set and the wire strength feature set in the time series database;

[0060] S3. Build a strength analysis algorithm model, input the extracted wire strength data set into the strength analysis algorithm model, and calculate to output the transient stress coefficient Y(t), the stress-temperature correction coefficient Y T (t) and the stress-vibration correction coefficient Y a (t);

[0061] S4. Combine the obtained transient stress coefficient Y(t), the stress-temperature correction coefficient Y T (t) and the stress-vibration correction coefficient Y a (t), and then perform comprehensive calculation with the wire strength feature set to obtain the comprehensive stress value Y final (t), preset the stress threshold L1, compare and evaluate it with the obtained comprehensive stress value Y final (t), and output a warning message;

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

[0063] The present invention provides a system and a method for detecting the tensile strength of metal wire. It has the following

[0064] Beneficial effects:

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

[0066] (2) This 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 (t), and stress-vibration correction coefficient Y a (t) in real time, and combine them with the wire rod strength feature set to finally calculate the comprehensive stress value Y final (t). The calculation of the comprehensive stress value Y final (t) fully considers complex factors such as non-linear stress-strain relationship, temperature-stress coupling effect, and vibration influence, enabling the system to accurately evaluate the tensile strength of the steel wire rod under various complex environmental conditions. This algorithm mechanism of multi-factor dynamic correction effectively improves the system's adaptability to complex working condition changes, ensuring the high accuracy and high reliability of the evaluation results.

[0067] (3) Through the built-in visualization warning module of this system, a user-friendly interactive interface is constructed using Tableau, which can display the dynamic changes of the transient stress coefficient Y(t), stress-temperature correction coefficient Y T (t), stress-vibration correction coefficient Y a (t), and comprehensive stress value Y final (t) in real time. The warning module comprehensively analyzes the evaluation results. When the comprehensive stress value Y final (t) exceeds the set stress threshold L1, the system will automatically generate a warning message and send an instruction to the tensile testing machine to stop running or reduce the tensile force, preventing accidents such as the fracture of the steel wire rod. When the comprehensive stress value is normal, the system will not issue a stop instruction to ensure the continuity of operation. This intelligent warning mechanism not only improves the safety of tensile strength detection of the steel wire rod, but also provides timely risk feedback to the operator, greatly reducing the safety hazards caused by overloading of the tensile force and effectively extending the service life of the steel wire rod. Description of the Drawings

[0068] Figure 1Schematic flow diagram of a tensile strength detection system for a metal wire according to the present invention;

[0069] Figure 2 Schematic diagram of the steps of a method for detecting the tensile strength of a metal wire according to the present invention. Specific embodiments

[0070] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0071] Embodiment 1

[0072] Please refer to Figure 1 , the present invention provides a tensile strength detection system for metal wires. To achieve the above objectives, the present invention is realized 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 visualization warning module;

[0073] When the data acquisition module performs a tensile strength test on a steel wire, a sensor group is installed on the steel wire to collect the tensile strength data of the steel wire in real time, and the tensile strength data is transmitted to the data processing module;

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

[0075] The wire strength analysis module is used to construct a strength analysis algorithm model, input the extracted wire strength data set 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 the stress-vibration correction coefficient Y a (t);

[0076] The wire strength evaluation module is used to combine the obtained transient stress coefficient Y(t), the stress-temperature correction coefficient Y T (t), and the stress-vibration correction coefficient Y a (t), and then perform a comprehensive calculation with the wire strength feature set to obtain a comprehensive stress value Y final (t), and preset a stress threshold L1 and compare and evaluate it with the obtained comprehensive stress value Y final (t), and output a warning message;

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

[0078] In this embodiment, the system realizes the real-time and high-precision acquisition of the tensile strength of steel wire rods through the data acquisition module, and transmits the acquired tensile strength data to the data processing module through LoRa wireless communication technology. The data processing module then preprocesses and extracts features from these data, and stores the processed data in the time series database for subsequent analysis and evaluation calls. The wire rod 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 coefficient Y a (t), laying a foundation for further evaluation. Through the wire rod strength evaluation module, the system further comprehensively calculates various coefficients generated by the analysis module with the wire rod strength feature set to obtain the comprehensive stress value Y final (t). By comparing this comprehensive stress value Y final (t) with the set stress threshold L1, the actual tensile strength state of the steel wire rod can be accurately evaluated. When it is found that the stress borne by the steel wire rod exceeds the set stress threshold L1, the system will generate a warning message and take corresponding control measures in time, such as stopping the operation of the tensile machine or reducing the tension, thereby effectively preventing accidents. This evaluation mechanism ensures the accurate grasp of the state of the steel wire rod by the system, making the steel wire rod always within the safe and controllable range during use, greatly improving the operation safety and the service life of the equipment.

[0079] Embodiment 2

[0080] This embodiment is an explanatory description based on Embodiment 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 a sensor group at both ends and the midline position of the steel wire rod when testing the tensile strength of the steel wire rod, and collect the tensile strength data of the steel wire rod in real time;

[0082] The sensor group includes a strain gauge, a temperature sensor, an accelerometer, and a displacement sensor;

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

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

[0085] In this embodiment, the data acquisition module realizes multi-dimensional and real-time monitoring of the tensile strength by installing the sensor group at key positions of the steel wire rod. This way of multi-sensor collaborative work 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 nature and transmission efficiency of the data. This module has significantly improved in terms of the accuracy of data collection and the real-time nature of transmission. Traditional methods often rely on a single sensor or wired transmission, which may lead to data loss or transmission delay. However, this system monitors simultaneously through multiple sensors, ensuring the comprehensiveness of the data, and overcomes the distance limitation through wireless transmission, improving the flexibility and response speed of the system. Finally, this data acquisition module provides high-quality basic data for subsequent data processing, analysis, and evaluation, significantly improving the overall effect and reliability of the tensile strength detection.

[0086] Embodiment 3

[0087] This embodiment is an explanatory description based on Embodiment 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, perform outlier removal, noise removal, and normalization processing on the tensile strength, perform time-domain conversion on the wire rod strength data group, label the wire rod strength data group with a timestamp, and then perform correlation calculation on the processed tensile strength data to obtain the wire rod strength data group;

[0089] The wire rod strength data group includes the transient strain rate dynamic temperature correction coefficient δ T (t), vibration frequency stress influence coefficient γ(t), and tensile force F(t) at time t;

[0090] The transient strain rate Estimate the strain rate from discrete data points by using the numerical differentiation method. The specific calculation formula is: In the formula, d is the differential, and dt is the time differential;

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

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

[0093] The feature extraction unit is only used to construct a collection of feature extraction algorithms Extract the wire strength data and input it into the collection of feature extraction algorithms For feature extraction, the wire strength feature set is output. The wire strength feature set includes the non-linear stress-strain relationship The temperature stress coupling effect η(T(t)), the high-frequency correction κ(w, t) affected by vibration, and the time delay correction δ delay (t);

[0094] Non-linear stress-strain relationship The temperature stress coupling effect η(T(t)), the high-frequency correction κ(w, t) affected by vibration, and the time delay correction δ delay (t) is obtained through the following collection of feature extraction algorithms Calculated and obtained;

[0095]

[0096] In the formula, a1 represents the first non-linear coefficient, a2 represents the second non-linear coefficient, considering the non-linear 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 vibration, δ d Represents the first time delay correction coefficient, λ d Represents the second time correction coefficient, considering the time delay effect of the system response, t represents time, e represents the exponential function, cos represents the cosine function, w represents the vibration frequency;

[0097] The data storage unit constructs a time series database using InfluxDB, records the tensile strength data according to the implementation sequence, then combines the obtained wire data with the wire strength feature set for real-time storage, and sets up an API application program interface to be integrated and connected with the wire strength analysis module, the wire strength evaluation module, and the visualization 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 through steps such as 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 then uses a collection of feature extraction algorithms to deeply analyze the processed data and extract a wire strength feature set, thus 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 the extracted feature set in real time, but also achieve seamless connection with other modules through the API interface to ensure the smooth flow of data throughout the system.

[0099] Embodiment 4

[0100] This embodiment is an explanatory description carried out in Embodiment 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 an algorithm formula for the transient strain-stress relationship, and extract the wire data group in the time-series database in real time for calculation to obtain the transient stress coefficient Y(t);

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

[0103]

[0104] In the formula, Y(t) represents the transient stress coefficient of the steel wire at time t, and 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 it with 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);

[0106] The stress temperature correction coefficient Y T (t) is calculated and obtained through the following dynamic temperature correction algorithm formula;

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

[0108] In the formula, Y T (t) represents the stress temperature correction coefficient at time t, and δ T represents the dynamic temperature correction coefficient, and θ represents the temperature influence attenuation coefficient. The meaning of the formula is to make the stress calculation more in line with the temperature change in the actual operating environment by correcting the stress value with temperature.

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

[0110] The stress vibration correction coefficient Y a is calculated and obtained through the following vibration frequency influence algorithm formula;

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

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

[0113] In this embodiment, the system enables the system to calculate and obtain the transient stress coefficient Y(t) of the steel wire at different time points in real time through the transient strain stress relationship algorithm constructed by the transient stress analysis unit, so as to dynamically reflect the instant state of the wire under stress changes. The dynamic temperature correction unit further generates the stress temperature correction coefficient Y T (t) by combining the transient stress coefficient Y(t) and the temperature change data, effectively correcting the stress value to make it more in line with the temperature fluctuation in the actual operating environment. The vibration frequency correction unit then corrects the stress value under the vibration environment in real time by introducing the vibration frequency influence algorithm to obtain the stress vibration correction coefficient Y a (t), thus ensuring the accuracy of the wire strength analysis, even under complex vibration conditions. By introducing the multi-algorithm, this module significantly improves the accuracy and real-time performance of the stress analysis of the steel wire. Traditional methods often ignore the dynamic effects of temperature and vibration, while this system solves this problem through the 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 in the calculation process, ensuring the efficiency and accuracy of the stress analysis. These improvements effectively enhance the adaptability and analysis depth of the system in complex environments, and finally provide a more reliable basis for the strength evaluation and early warning of the wire.

[0114] Embodiment 5

[0115] This embodiment is explained in Embodiment 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), stress-temperature correction coefficient Y T (t), and stress-vibration correction coefficient Y a (t) obtained in real time, and then extract the wire strength feature set from the time series database for combined calculation to obtain the comprehensive stress value Y final (t);

[0117] The comprehensive stress value Y final (t) is obtained through the following algorithm formula;

[0118]

[0119] In the formula, ζ represents the strain correction coefficient, and Y final (t) represents the comprehensive stress value of the steel wire at time t;

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

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

[0122] When the comprehensive stress value Y final (t) = stress threshold L1, it is marked that the tension borne by the steel wire is abnormal, and the second evaluation result is generated at this time;

[0123] When the comprehensive stress value Y final (t) < stress threshold L1, it is marked that the tension borne by the steel wire is normal, and the third evaluation result is generated at this time.

[0124] In this embodiment, the system accurately calculates the comprehensive stress value Y T (t) by the comprehensive analysis unit extracting the transient stress coefficient Y(t), stress-temperature correction coefficient Y a (t), and stress-vibration correction coefficient Y final (t) in real time and combining the wire strength feature set, so as to comprehensively reflect the actual stress situation of the wire under the action of various stress factors. The tensile strength evaluation unit then compares Y final(t) is compared with a preset stress threshold L1 to quickly evaluate the tensile strength state of the steel wire rod, provide a clear evaluation result, and mark whether there is overload or abnormality in the stress condition of the wire rod. And this module effectively solves this deficiency by introducing multiple correction factors. In addition, the real-time calculation and evaluation function of the system greatly improves the evaluation efficiency, can quickly respond to the change of wire strength, and generate evaluation results and warning information in a timely manner. These improvements significantly enhance the reliability and safety of the system in practical applications, ensuring the safe use of the wire rod in complex environments.

[0125] Embodiment 6

[0126] This embodiment is an explanatory description based on Embodiment 5. Please refer to Figure 1 , specifically: The visual warning module includes a visual interaction unit and a warning unit;

[0127] The visual interaction unit is used to construct a visual user-friendly interface, set up a tensile strength chart and an interactive dashboard using Tableau, and is integrally connected with the wire strength analysis module and the wire strength evaluation module to receive in real time the obtained transient stress coefficient Y(t), stress temperature correction coefficient Y T (t), stress vibration correction coefficient Y a (t) and comprehensive stress value Y final (t) for visual interaction;

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

[0129] When the first evaluation result is received, send a first instruction to the tensile testing machine to stop running, and generate a first-level warning message indicating that the steel wire rod will break if the tensile force is applied again;

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

[0131] When the third evaluation result is received, no instruction is sent and the tensile force is continuously applied.

[0132] In this embodiment, the visual interaction unit uses the user-friendly interface constructed by Tableau to display the transient stress coefficient Y(t), stress temperature correction coefficient Y T (t), stress vibration correction coefficient Y a (t) and the comprehensive stress value Y final(t) is presented in the form of intuitive charts and dashboards, enhancing the user's understanding and control of the stress state of wire rods. The warning unit automatically generates 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 testing machine, to ensure that the steel wire rod does not continue to work under overload conditions, thus avoiding potential fracture risks. This module significantly improves the level of intelligence and automation of the operation. Traditional systems usually require manual intervention to analyze data and make decisions, while this module greatly reduces the complexity of manual operations through automated real-time analysis and visual display, and at the same time improves the response speed. In the face of emergencies, the system can respond in a timely manner to prevent accidents from occurring. In addition, through the interactive interface of Tableau, users can more conveniently customize monitoring views and warning conditions, significantly enhancing 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 rods.

[0133] Example 7

[0134] Please refer to Figure 1 and Figure 2 , a method for detecting the tensile strength of metal wire rods, comprising the following steps:

[0135] S1. When testing the tensile strength of a steel wire rod, install a sensor group on the steel wire rod to collect the tensile strength data of the steel wire rod in real time, and transmit the tensile strength data to a data processing module;

[0136] S2. Receive the tensile strength data in real time, preprocess the tensile strength data to obtain a wire rod strength data set, extract features from the wire rod strength data set to obtain a wire rod strength feature set, and then store the wire rod strength data set and the wire rod strength feature set in a time series database;

[0137] S3. Build a strength analysis algorithm model, input the extracted wire rod strength data set into the strength analysis algorithm model for calculation, and output the transient stress coefficient Y(t), the stress-temperature correction coefficient Y T (t) and the stress-vibration correction coefficient Y a (t);

[0138] S4. Combine the obtained transient stress coefficient Y(t), the stress-temperature correction coefficient Y T (t) and the stress-vibration correction coefficient Y a (t) with the wire rod strength feature set for comprehensive calculation to obtain a comprehensive stress value Y final (t), preset a stress threshold L1, compare and evaluate it with the obtained comprehensive stress value Y final (t), and output a warning message;

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

[0140] Although the embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the present 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 when testing the tensile strength of the steel wire to collect the tensile strength data of the steel wire 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, and mark timestamps on the tensile strength data, 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 The extracted wire strength data set is input into the feature extraction algorithm collection The wire strength feature set is outputted by extracting features, and 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 construct a time series database by using InfluxDB, record the tensile strength data according to the implementation sequence, and then store the acquired wire strength data group and wire strength feature set in real time, and set 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; 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 Calculate acquisition; 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 strength 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 strength 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 strength 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 sine 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 (t)> stress threshold L1, marking the tensile overload of the steel wire and generating a first evaluation result; 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 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; 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 tension.

10. A method for detecting the tensile strength of a metal wire, 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 performing feature extraction on 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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