A wire harness breakage early warning and positioning method and system based on multi-sensor fusion

Abstract

The application relates to the technical field of electrical system health monitoring, and provides a wire harness fracture early warning and positioning method and system based on multi-sensor fusion. The method comprises the following steps: collecting the current value of a wire harness in real time through a current sensor; when it is detected that the current change rate is greater than a change threshold value and the difference between the current and a reference current value exceeds a preset threshold value, triggering early warning and starting tension detection; collecting the tension data of the wire harness through a tension sensor arranged at the inlet and outlet of a wire harness drag chain; calculating the variance of the tension data, and if the variance exceeds a first threshold value, starting strain detection; detecting the strain change of the wire harness through a distributed resistance strain sensor, and converting the strain change into an electric signal through a bridge circuit; uploading the collected data to the cloud, comparing through a historical fault model, calculating a real-time fracture probability, and triggering graded early warning. The accuracy and reliability of wire harness fracture early warning and positioning are improved.

Description

Technical Field

[0001] This application relates to the field of electrical system health monitoring technology, specifically a method and system for early warning and location of wire harness breakage based on multi-sensor fusion. Background Technology

[0002] In industrial production, cutting machines, as crucial processing equipment, directly impact production efficiency and product quality through their operational stability and reliability. Similarly, wire harnesses, as core components of electrical systems, bear the vital responsibility of transmitting electrical energy and signals; their health plays a decisive role in the stable operation of the entire electrical system.

[0003] However, in actual cutting machine operations, wire harnesses face complex and variable working environments and numerous potential risk factors. Vibrations generated during the cutting process, frequent mechanical movements, and possible external collisions can all cause varying degrees of damage to the wire harness. Among these, wire harness breakage is a relatively common and serious type of failure. Once a wire harness breaks, it can not only lead to partial or complete equipment failure, preventing normal cutting operations and causing production interruptions and reduced efficiency, but it can also cause safety issues such as electrical short circuits and sparks.

[0004] Currently, real-time status monitoring and fault diagnosis of wiring harnesses generally rely on a single type of sensor. The information acquired by a single sensor is often limited, making it difficult to comprehensively and accurately reflect the actual condition of the wiring harness, and prone to misjudgment or omission. In addition, when a potential fault is detected in the wiring harness, it is impossible to quickly and accurately determine the specific location of the fault, which brings great difficulties to maintenance work, prolongs equipment downtime, and increases maintenance costs. Summary of the Invention

[0005] To address the aforementioned problems, this invention provides a method and system for early warning and location of wire harness breakage based on multi-sensor fusion.

[0006] In a first aspect, the present invention provides a method for early warning and location of wire harness breakage based on multi-sensor fusion, comprising the following steps: S1. The current value of the wire harness is collected in real time by the current sensor. When the current change rate is detected to be greater than the change threshold and the difference between the current and the reference current value exceeds the preset threshold, an early warning is triggered and the tension detection is started. S2. By deploying tension sensors at the inlet and outlet of the cable chain, the tension data of the cable harness is collected; the variance of the tension data is calculated, and if the variance exceeds the first threshold, strain detection is initiated. S3. The strain change of the wire harness is detected by a distributed resistance strain gauge sensor and the strain change is converted into an electrical signal; S4. Based on the collected signals, perform early warning and location of wire harness breakage.

[0007] Real-time acquisition of current, tension, and strain data of the wiring harness can promptly detect abnormal conditions and trigger early warnings, effectively preventing equipment failures and safety accidents caused by harness breakage.

[0008] As a preferred embodiment of the technical solution of the present invention, S1 specifically includes: S11. The current signal of the wire harness is collected in real time by a current sensor, and the reference current value is recorded during the equipment startup phase. S12. Calculate the rate of change of current in real time. If the following conditions are met simultaneously, the current is judged to be abnormal: The rate of change of current exceeds the preset dynamic change threshold; The deviation between the current value and the reference current value exceeds the preset static difference threshold; S13. When the current is abnormal, a warning signal is sent to the host computer and the tension sensor is triggered to start detection.

[0009] As long as the current and tensile force data do not exceed the corresponding thresholds, the current detection status is maintained and the data is periodically uploaded to the cloud. This design avoids unnecessary frequent detection and data processing, reduces system resource consumption and energy consumption, while ensuring continuous monitoring of the harness status under normal conditions. Cloud data storage provides data support for subsequent analysis, improving the system's operating efficiency and economy while ensuring the effectiveness of monitoring.

[0010] As a preferred embodiment of the technical solution of the present invention, in S1, the step of recording the reference current value during the device startup phase includes: During the first m seconds of device startup, the current value is recorded once per second to obtain m startup transient reference values; After the equipment is running stably, the current value is recorded continuously m times and the average value is taken to generate a steady-state reference value. The m transient reference values ​​and 1 steady-state reference value are used together as the reference current value set for current anomaly determination.

[0011] Recording the baseline current value during equipment startup provides an accurate reference standard for subsequent current anomaly detection. Real-time calculation of the current change rate, combined with dynamic change thresholds and static difference thresholds, improves the accuracy of current anomaly detection and reduces the possibility of false positives. When a current anomaly is detected, a warning signal is promptly sent to the host computer, triggering the tension sensor for detection. This enables rapid response to potential wiring harness problems, buying time for subsequent troubleshooting and improving the real-time performance and reliability of the entire monitoring system.

[0012] As a preferred embodiment of the technical solution of the present invention, in S2, the tension sensor is arranged as follows: A set of tension sensors is installed at each of the inlet and outlet of the cable chain, with the number of sensors in each set matching the number of wire harnesses. Each wire bundle is secured by a comb and comes into contact with a corresponding tension sensor.

[0013] This arrangement allows for accurate measurement of the tensile force borne by each wire harness, ensuring the accuracy and specificity of the tensile force data. By monitoring the tensile force of each wire harness individually, abnormal stress conditions in individual harnesses can be detected in a timely manner, providing more precise data support for subsequent assessments of whether the harnesses are at risk of breakage. This helps improve the sensitivity and accuracy of the entire wire harness monitoring system.

[0014] As a preferred embodiment of the technical solution of the present invention, the distributed resistance strain gauge sensor includes a strain gauge and a bridge circuit, and S3 specifically includes: S31. The strain change of the wire harness is detected by strain gauges, wherein the strain gauges are distributed and arranged below the wire harness in the wire groove and are in contact with the wire harness through the wire harness strip; S32. Use a bridge circuit to convert the resistance change of the strain gauge into a voltage signal.

[0015] Distributed resistance strain gauge sensors are arranged below the wire harness inside the wire trough and contact the wire harness through the wire harness strap, which can accurately detect the strain changes of the wire harness.

[0016] As a preferred embodiment of the technical solution of the present invention, the steps of performing wire harness breakage early warning and location based on the collected signals include: S41a. Process the voltage signal to obtain the resistance change; S42a. Compare the resistance changes of each strain gauge, locate the strain gauge with the largest resistance change, determine the fracture location, and output fracture warning information; the specific method for locating the fracture location is as follows: Calculate the resistance change ΔR of each strain gauge; Calculate the average value B of the resistance changes of all strain gauges; Compare the difference between each resistance change ΔR and the average value B. The location of the strain gauge with the largest difference is the fracture location.

[0017] This positioning method is simple and effective, quickly and accurately locating the strain gauge with the largest resistance change, i.e., the fracture location. This method is unaffected by the complex structure of the wire harness or environmental factors, exhibiting high reliability and accuracy. It provides strong support for the timely handling of wire harness fracture faults, ensuring the normal operation of the cutting machine.

[0018] As a preferred embodiment of the technical solution of the present invention, the steps of performing wire harness breakage early warning and location based on the collected signals include: S41b: Compress the feature data collected by the current sensor, tension sensor and resistance strain gauge sensor and upload it to the cloud database; S42b: Retrieve historical fault models from the cloud database. The historical fault models are based on features and statistical patterns extracted from past fault data. S43b. Compare the uploaded current feature data with the historical fault model, and calculate the similarity between the current data and the historical fault features; S44b: Using the Bayesian variable point detection algorithm combined with the comparison results, calculate the risk function value, and trigger different levels of early warning signals based on the magnitude of the risk function value.

[0019] The feature data collected by sensors is compressed and then uploaded to the cloud database, reducing data transmission volume and storage space usage, and improving data transmission efficiency. Historical fault models based on features and statistical patterns extracted from past fault data are retrieved from the cloud database, and the current feature data is compared with these historical fault models to calculate similarity. This fully utilizes the value of historical data and provides rich reference for assessing the current harness condition. A Bayesian variable point detection algorithm is used in conjunction with the comparison results to calculate a risk function value. Different levels of early warning signals are triggered based on the risk function value, achieving accurate assessment and graded early warning of harness breakage risk. This allows operators to take appropriate measures based on the warning level, preventing harness breakage accidents in advance and improving production safety and reliability.

[0020] As a preferred embodiment of the technical solution of the present invention, S44b specifically includes: Define Variable Point Points where the data distribution changes in a time series represent abrupt changes in the bundle state; Calculating change points using Bayes' theorem posterior probability : Calculate the risk function The value; and according to the risk function The value is used to determine whether the harness is at risk of breakage. if It was determined to be low risk and recorded as low risk; if It was determined to be of medium risk, and a medium risk warning was issued; if It was determined to be high-risk and a high-risk alarm was issued.

[0021] This method defines change points and calculates their posterior probabilities using Bayes' theorem. By calculating the risk function, it determines whether the harness is at risk of breakage. Based on different risk thresholds, it determines the risk level, outputs the real-time breakage probability, and issues corresponding warnings. This risk assessment and early warning method, based on rigorous mathematical models and algorithms, can scientifically and accurately assess the breakage risk of the harness, providing operators with clear and explicit risk information. Different levels of warning signals help operators rationally plan maintenance and take targeted measures, improving production efficiency and reducing maintenance costs while ensuring safe equipment operation. This achieves intelligent and refined harness condition monitoring.

[0022] Secondly, the present invention also provides a wire harness breakage early warning and positioning system based on multi-sensor fusion, comprising: A current sensor module is used to acquire the current value of the wiring harness in real time. The tension sensor module is installed at the inlet and outlet of the cable chain for collecting tension data of the cable harness; The distributed resistance strain gauge sensor module includes strain gauges and a bridge circuit. The strain gauges detect the strain changes of the wire harness. The strain gauges are distributed and arranged below the wire harness in the wire groove and contact the wire harness through the wire harness strap. The bridge circuit converts the resistance changes of the strain gauges into voltage signals. The data processing module is used to process the collected data, specifically to calculate the current change rate in real time. When the current change rate is greater than the change threshold and the difference between the current and the reference current value exceeds the preset threshold, an alarm is triggered and tensile detection is started. The variance of the tensile data is calculated. If the variance exceeds the first threshold, strain detection is started. The early warning and location module is used to process electrical signals to obtain the resistance change of each strain gauge, and locate the fracture location by comparing the resistance change of each strain gauge; or, it retrieves historical fault models from the cloud database, compares the current feature data with the historical fault models, calculates the real-time fracture risk value, and triggers graded early warnings.

[0023] By integrating current sensors, tension sensors, and resistance strain gauge sensors into a single system, collaborative monitoring and processing of multi-sensor data is achieved, improving the overall system performance. Through data processing and early warning / location modules, real-time monitoring, fault diagnosis, and early warning of the wiring harness status are realized, enhancing the system's intelligence and automation levels and reducing manual intervention costs.

[0024] As a preferred embodiment of the technical solution of the present invention, the data processing module is further configured to maintain the current detection state and periodically upload the collected data to the cloud through the data upload module when the detected current change rate is less than or equal to the change threshold, or the difference between the current and the reference current value is less than or equal to the preset threshold, or the variance of the tensile data is less than or equal to the first threshold.

[0025] As a preferred embodiment of the technical solution of the present invention, the current sensor module records a reference current value during the device startup phase. Specifically, it records the current value once per second within the first m seconds of device startup to obtain m transient reference values. After the device is running stably, it continuously records the current value m times and takes the average value to generate a steady-state reference value. The m transient reference values ​​and the steady-state reference value are used together as the reference current value set for current anomaly determination.

[0026] As a preferred embodiment of the technical solution of the present invention, the arrangement of the tension sensor module is as follows: a set of tension sensors is set at each of the inlet and outlet of the cable chain, and the number of sensors in each set is the same as the number of wire harnesses; each wire harness is fixed by a comb and contacts the corresponding tension sensor.

[0027] As a preferred embodiment of the present invention, the distributed resistance strain gauge sensor includes strain gauges and a bridge circuit. The strain gauges detect the strain changes of the wire harness. The strain gauges are distributed and arranged below the wire harness in the wire groove and contact the wire harness through the wire harness strap. The bridge circuit converts the resistance changes of the strain gauges into voltage signals.

[0028] As a preferred embodiment of the technical solution of the present invention, the early warning and positioning module is used to process the voltage signal to obtain the resistance change; compare the resistance changes of each strain gauge, locate the strain gauge with the largest resistance change, determine the fracture location, and output fracture early warning information; the specific fracture location positioning method is as follows: calculate the resistance change ΔR of each strain gauge; calculate the average value B of the resistance changes of all strain gauges; compare the difference between each resistance change ΔR and the average value B, and the location of the strain gauge with the largest difference is the fracture location.

[0029] As a preferred embodiment of the technical solution of the present invention, the early warning and positioning module includes: The data receiving unit is used to receive the uploaded feature data; The model retrieval unit is used to retrieve historical fault models from the cloud database; The data comparison unit is used to compare the current feature data with the historical fault model and calculate the similarity between the current data and the historical fault features; The risk assessment unit is used to calculate the risk function value by combining the Bayesian change point detection algorithm with the comparison results, and to trigger different levels of early warning signals based on the magnitude of the risk function value.

[0030] As a preferred embodiment of the technical solution of the present invention, the risk assessment unit is specifically used for: Define Variable Point Points where the data distribution changes in a time series represent abrupt changes in the bundle state; Calculating change points using Bayes' theorem posterior probability : Calculate the risk function The value; and according to the risk function The value is used to determine whether the harness is at risk of breakage. if If the risk is deemed low, the real-time fracture probability is output. And record it as low risk; if The risk level is determined to be medium, and the real-time fracture probability is output. And issued a medium-risk warning; if If deemed high-risk, output the real-time fracture probability. It also issued a high-risk alert.

[0031] As can be seen from the above technical solution, this application has the following advantages: It comprehensively utilizes current sensors, tension sensors, and resistance strain gauge sensors to monitor the wire harness in all aspects. The current sensor collects current values ​​in real time, quickly capturing abnormal current changes, triggering early warnings, and initiating subsequent detection processes, providing a basis for preliminary judgment of the wire harness status. The tension sensor collects wire harness tension data, and through variance analysis, further determines whether the wire harness is under abnormal stress, deciding whether to initiate strain detection, thus increasing the accuracy of the judgment. The resistance strain gauge sensor detects changes in wire harness strain, achieving precise location of the breakage. The collaborative work of multiple sensors overcomes the limitations of single-sensor monitoring, improving the accuracy and reliability of wire harness breakage early warning and location, effectively avoiding equipment failure, safety accidents, and economic losses caused by wire harness breakage, and ensuring the stable operation of the cutting machine during the cutting process. Attached Figure Description

[0032] To more clearly illustrate the technical solution of this application, the accompanying drawings used in the description will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0033] Figure 1 A flowchart of a method provided in one embodiment of the present invention.

[0034] Figure 2 A block diagram of a system provided in an embodiment of the present invention.

[0035] Figure 3 This is a circuit diagram for starting the tensile force detection.

[0036] Figure 4 This is a diagram showing the connection of a series potentiometer.

[0037] Figure 5This is a diagram illustrating the connection method of resistance-capacitance adjustment balance.

[0038] Figure 6 A method flowchart provided for another embodiment of the present invention. Detailed Implementation

[0039] To make the purpose, features, and advantages of this application more apparent and understandable, specific embodiments and accompanying drawings will be used to clearly and completely describe the technical solution protected by this application. Obviously, the embodiments described below are only some embodiments of this application, and not all embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0040] Unless otherwise defined, all technical and scientific terms used in this application have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used in this application and in the specification of this invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention.

[0041] like Figure 1 As shown in the figure, an embodiment of the present invention provides a method for early warning and location of wire harness breakage based on multi-sensor fusion, comprising the following steps: S1. The current value of the wire harness is collected in real time by the current sensor. When the current change rate is detected to be greater than the change threshold and the difference between the current and the reference current value exceeds the preset threshold, an alarm is triggered and tensile detection is started; otherwise, the current detection state is maintained and the collected data is periodically uploaded to the cloud. S2. By deploying tension sensors at the inlet and outlet of the cable harness drag chain, the tension data of the cable harness is collected; the variance of the tension data is calculated. If the variance exceeds the first threshold, strain detection is initiated; otherwise, the current detection state is maintained, and the collected data is periodically uploaded to the cloud. S3. The strain change of the wire harness is detected by a distributed resistance strain gauge sensor and the strain change is converted into an electrical signal; S4. Based on the collected signals, perform early warning and location of wire harness breakage.

[0042] In some embodiments, S1 specifically includes: S11. The current signal of the wire harness is collected in real time by a current sensor, and the reference current value is recorded during the equipment startup phase. S12. Calculate the rate of change of current in real time. If the following conditions are met simultaneously, the current is judged to be abnormal: The rate of change of current exceeds the preset dynamic change threshold; The deviation between the current value and the reference current value exceeds the preset static difference threshold; S13. When the current is abnormal, a warning signal is sent to the host computer and the tension sensor is triggered to start detection.

[0043] In this embodiment of the invention, the tensile force detection is initiated as follows: An abnormal current signal is transmitted to the host computer via a relay outputting a low-level signal. After receiving the signal, the host computer wakes up the corresponding tension sensor via the 485 bus.

[0044] When a continuous periodic fluctuation or sustained decrease in current value is detected, an alarm is issued to provide a warning and trigger the current anomaly relay. The warning range is: the cable may break or there is a risk of breakage. After the alarm is issued, a sudden current change triggers the relay, causing the host computer to receive data from the tension sensor. For the cable harness with the sudden current change, the system locates and initiates tension detection on the harness.

[0045] In some embodiments, the step of recording the reference current value during the device startup phase in S1 includes: In the first m seconds after the device starts up, the current value is recorded once per second to obtain m transient reference values ​​for startup; in this embodiment of the invention, m is 4. After the equipment is running stably, the current value is recorded continuously m times and the average value is taken to generate a steady-state reference value. The m transient reference values ​​and 1 steady-state reference value are used together as the reference current value set for current anomaly determination.

[0046] Here, the current change rate is calculated as follows: The current signal is processed by sliding window differential processing, with a window length of N sampling points (N≥5). The threshold value is dynamically adjusted according to the type of harness, and the range is ±5% to ±20% of the reference current / second.

[0047] In some embodiments, in S2, the tension sensor is arranged as follows: A set of tension sensors is installed at the inlet and outlet of the cable chain, with the number of sensors in each set matching the number of wire harnesses; each wire harness is fixed by a comb and contacts the corresponding tension sensor.

[0048] The method for initiating strain detection is as follows: The host computer sends a command to activate the distributed resistance strain gauge sensor below the corresponding wire harness, so that the strain gauge sensor uses an AC bridge circuit to convert the deformation signal into a voltage signal output.

[0049] The wire harness is threaded inside the cable chain. The cable chain is divided into five parts. In the first part, combs are added at both ends to fix the wire harness and prevent it from going off course during the cable chain's movement. A tension sensor is added below each wire harness passing through the comb, and these sensors are added at the cable chain's inlet and outlet. The tension sensor's force-bearing part is the wire harness. When a sudden change in current is detected, the system first activates the tension detection circuit. The activation tension detection circuit diagram is as follows: Figure 3 As shown, to save system resources, an external start-up method is used. When a sudden change in current is detected, an external relay triggers a low-level signal to the host computer, which then begins to receive the detection data from the tension sensor. The data type is 485 communication. Multiple tension sensors are connected in parallel, forming a slave station. There are currently 5 cables in the cable chain, meaning there are 5 tension sensors at the cable chain inlet and outlet. The tension sensors in the cable chain are slave stations 1 to 5 from left to right. By detecting the current, it is determined which cable harness has a sudden current change, and then tension data analysis and strain detection are performed on this slave station. When subjected to external tensile force, the stressed part will deform or deform by using tensile force sensor feedback values. The deformation data is used to determine whether the wire harness has reached the critical value for breakage or has already broken. The judgment is based on the following: each time the device is initially powered on, a set of tensile force data for each wire is automatically recorded. This tensile force data is compared with the previously recorded data to calculate the variance and determine if there is any abnormality. If there is an abnormality, the strain gauge resistance strain gauge sensor around the abnormal wire harness is activated. Then, the strain gauge resistance strain gauge sensor data is analyzed to determine whether breakage has occurred and an early warning is issued. If there is no abnormality, data acquisition is stopped, and data acquisition is resumed after a sudden current change signal appears. The variance calculation is repeated, and the data is compared with the baseline value to determine whether breakage has occurred.

[0050] Record the change in tension each time the power is first applied, where M is the average value and s is the value of the tension. 2 The variance value obtained; s 2 When less than 1, it includes the following: When s 2 Pre-stored value greater than s 2 The current value indicates that the wiring harness is in good condition and has no problems. When s 2 Pre-stored value equals s 2 The current value indicates that the wiring harness is functioning correctly and is in good condition. When s 2 Pre-stored value less than s 2 When the current value is used, the difference between the two values ​​is taken. If the difference is less than 0.1, the output cable status is deteriorating and the cable harness signal needs to be tidied up. If the difference is greater than or equal to 0.2, the output cable status is abnormal and the cable harness signal needs to be tidied up and checked for twisting. When s 2 If the value is greater than 1, the distributed resistance strain gauge sensors of the corresponding wire harness will be activated to detect the breakage location and issue a signal indicating that the wire harness is broken and is being detected.

[0051] In some embodiments, the distributed resistive strain gauge sensor includes a strain gauge and a bridge circuit, and S3 specifically includes: S31. The strain change of the wire harness is detected by strain gauges, wherein the strain gauges are distributed and arranged below the wire harness in the wire groove and are in contact with the wire harness through the wire harness strip; S32. Use a bridge circuit to convert the resistance change of the strain gauge into a voltage signal.

[0052] In this embodiment of the invention, the strain gauge is installed as follows: The strain gauge is fixed in the cable chain fixing groove using an adhesive that has a high shear modulus and electrical insulation properties.

[0053] In one embodiment of the present invention, the steps of performing wire harness breakage early warning and location based on the collected signals include: S41a. Process the voltage signal to obtain the resistance change; S42a. Compare the resistance changes of each strain gauge, locate the strain gauge with the largest resistance change, determine the fracture location, and output fracture warning information; the specific method for locating the fracture location is as follows: Calculate the resistance change ΔR of each strain gauge; Calculate the average value B of the resistance changes of all strain gauges; Compare the difference between each resistance change ΔR and the average value B. The location of the strain gauge with the largest difference is the fracture location.

[0054] The resistance strain gauge sensor is distributed and installed below the wire harness in the wire groove. The wire harness is pressed above the strain gauge by the wire strap. The friction between the wire harness and the strain gauge generates a change in resistance, which is then converted into a voltage signal and transmitted to the host computer. When the stressed part deforms, the strain gauge will correspondingly produce a strain change. The strain gauge is connected to a 24V power supply. The friction of the wire harness converts the strain change signal into an electrical signal, which is the deformation sensing part. Here, the strain sensor uses a bridge circuit. The bridge circuit consists of four resistors, two of which are fixed, and the other two are piezoresistors. When the strain gauge is subjected to external force, its resistance value changes, causing an imbalance in the bridge and generating a small voltage signal. The small voltage signal output by the bridge is amplified and processed to improve the signal stability and readability. Since DC amplifiers are prone to zero drift, this application uses an AC bridge strain gauge, and the analog signal is converted into a digital signal by an analog-to-digital converter (ADC) before being input to the host computer. The bridge must be balanced before the strain gauge operates. For DC bridge circuits, series or parallel potentiometers can be used. For strain detection, the method is not limited to series or parallel potentiometers; series potentiometer connections are as follows: Figure 4 As shown, for the AC bridge, it is also necessary to add methods such as, but not limited to, resistance-capacitance balancing or differential capacitor balancing, such as... Figure 5 As shown.

[0055] Resistance strain gauge sensors are attached to the cable chain mounting groove using adhesive. The adhesive layer must accurately and rapidly transfer the strain of the measured component to the sensing grid. When selecting the adhesive, the properties of both the strain gauge and the measured component materials must be considered. Not only must the adhesion be strong and the mechanical properties reliable after bonding, but the adhesive layer must also have a sufficiently high shear modulus and good electrical insulation; creep and hysteresis will be correspondingly reduced. A wire harness is used to secure the wire bundle. During initial machine operation, the strain sensing function is activated. During normal machine operation, measurements are taken every ten seconds. The average value is then calculated after the first ten minutes of measurement. The stress calculation is as follows: When a strain gauge is not under stress, its original resistance is R = ρ / A, where ρ is the resistivity of the metal, l is the axial length, and A is the cross-sectional area. When the resistance wire is subjected to a tensile force F, it elongates Δl axially and shortens Δr radially, resulting in a corresponding decrease in the cross-sectional area ΔA. The resistivity changes Δρ due to factors such as deformation of the material's crystal lattice, thus causing a relative change in the resistance value. Taking the logarithm of both sides of the resistance expression and substituting it into A = πr... 2 Differentiation yields: dR / R=dρ / ρ+dl / l-2dr / r(1) Expressed in terms of relative change, we have: ΔR / R=Δρ / ρ+Δl / l-2Δr / r (2) The longitudinal strain is defined as ε = Δl / l, and the radial strain is defined as εr = Δr / r. Furthermore, there exists a relationship between the radial and longitudinal strains: εr = -με, where μ is the Poisson coefficient. Therefore, equation (2) can be transformed into: ΔR / R=Δρ / ρ+ (1+2μ)ε When deformation occurs, the change in resistance of the strain gauge is ΔR.

[0056] B = ΔR1 + ΔR1 + ΔR1 + ... + ΔR n / n(3) By comparing the ΔR and B values ​​of each strain gauge, the strain gauge with the largest difference is identified, and the wear of this unit harness is finally located, requiring rectification, replacement, or repair.

[0057] In another embodiment of the present invention, the step of performing wire harness breakage early warning and location based on the collected signals includes: S41b: Compress the feature data collected by the current sensor, tension sensor and resistance strain gauge sensor and upload it to the cloud database; S42b: Retrieve historical fault models from the cloud database. The historical fault models are based on features and statistical patterns extracted from past fault data. S43b. Compare the uploaded current feature data with the historical fault model, and calculate the similarity between the current data and the historical fault features; S44b: Using the Bayesian variable point detection algorithm combined with the comparison results, calculate the risk function value, and trigger different levels of early warning signals based on the magnitude of the risk function value.

[0058] It should be further noted that S42b specifically includes: Historical fault models are retrieved from the cloud database. These models are based on features and statistical patterns extracted from past fault data, including but not limited to current changes, abnormal tensile forces, and strain changes during fault occurrence. The uploaded current feature data is compared with the historical fault models, and the distance between the current feature vector and the historical fault feature vector is calculated to determine the similarity between the current data and the historical fault features.

[0059] S44b specifically includes: Define Variable Point Points where the data distribution changes in a time series represent abrupt changes in the bundle state; Calculating change points using Bayes' theorem posterior probability : Calculate the risk function The value; and according to the risk function The value is used to determine whether the harness is at risk of breakage. if If the risk is deemed low, the real-time fracture probability is output. And record it as low risk; if The risk level is determined to be medium, and the real-time fracture probability is output. And issued a medium-risk warning; if If deemed high-risk, output the real-time fracture probability. It also issued a high-risk alert.

[0060] in,

[0061]

[0062] In the formula, At the turning point Data observed when it occurs The likelihood probability, It is the prior probability of the change point, estimated based on the frequency of the change point in historical data. It is data The marginal probability is estimated by using statistical patterns from historical data.

[0063] In some embodiments, maintenance recommendations are automatically generated based on the steps described above, and the wiring harness health record is updated.

[0064] like Figure 6 As shown in the figure, an embodiment of the present invention provides a method for early warning and location of wire harness breakage based on multi-sensor fusion, comprising the following steps: SS1: Real-time acquisition of the current value of the wiring harness via a current sensor; SS2. Determine whether the rate of change of current is greater than the threshold value. If yes, proceed to step SS3; otherwise, return to step SS1. SS3. Does the difference between the current and the reference current value exceed a preset threshold? If yes, execute SS4; otherwise, return to SS1. SS4, triggers an early warning and initiates tensile force detection; SS5. Collect tension data of the wire harness by arranging tension sensors at the inlet and outlet of the wire harness cable chain; calculate the variance of the tension data; SS6. Determine if the variance exceeds the first threshold; If yes, proceed to step SS7; otherwise, return to SS5. SS7. The strain change of the wire harness is detected by a distributed resistance strain gauge sensor, and the strain change is converted into an electrical signal by a bridge circuit. SS8. Locate the fracture location by comparing the resistance changes of each strain gauge; SS9 uploads data collected by current sensors, tensile sensors, and resistance strain gauge sensors to the cloud, calculates the real-time fracture probability by comparing with historical fault models, and triggers graded early warnings.

[0065] like Figure 2 As shown, this embodiment of the invention also provides a wire harness breakage early warning and positioning system based on multi-sensor fusion, including: A current sensor module is used to acquire the current value of the wiring harness in real time. The tension sensor module is installed at the inlet and outlet of the cable chain for collecting tension data of the cable harness; The distributed resistance strain gauge sensor module includes strain gauges and a bridge circuit. The strain gauges detect the strain changes of the wire harness. The strain gauges are distributed and arranged below the wire harness in the wire groove and contact the wire harness through the wire harness strap. The bridge circuit converts the resistance changes of the strain gauges into voltage signals. The data processing module is used to process the collected data, specifically to calculate the current change rate in real time. When the current change rate is greater than the change threshold and the difference between the current and the reference current value exceeds the preset threshold, an alarm is triggered and tensile detection is started. The variance of the tensile data is calculated. If the variance exceeds the first threshold, strain detection is started. The early warning and location module is used to process electrical signals to obtain the resistance change of each strain gauge, and locate the fracture location by comparing the resistance change of each strain gauge; or, it retrieves historical fault models from the cloud database, compares the current feature data with the historical fault models, calculates the real-time fracture risk value, and triggers graded early warnings.

[0066] By integrating current sensors, tension sensors, and resistance strain gauge sensors into a single system, collaborative monitoring and processing of multi-sensor data is achieved, improving the overall system performance. Through data processing and early warning / location modules, real-time monitoring, fault diagnosis, and early warning of the wiring harness status are realized, enhancing the system's intelligence and automation levels and reducing manual intervention costs.

[0067] In some embodiments, the data processing module is further configured to maintain the current detection state and periodically upload the collected data to the cloud through the data upload module when the detected current change rate is less than or equal to a change threshold, or the difference between the current and the reference current value is less than or equal to a preset threshold, or the variance of the tensile data is less than or equal to a first threshold.

[0068] In some embodiments, the current sensor module records a reference current value during the device startup phase. Specifically, it records the current value once per second within the first m seconds of device startup to obtain m transient reference values. After the device is running stably, it continuously records the current value m times and takes the average value to generate a steady-state reference value. The m transient reference values ​​and the steady-state reference value are used together as a reference current value set for current anomaly determination.

[0069] In some embodiments, the tension sensor module is arranged as follows: a set of tension sensors is set at each of the inlet and outlet of the cable chain, and the number of sensors in each set is the same as the number of wire harnesses; each wire harness is fixed by a comb and contacts the corresponding tension sensor.

[0070] In some embodiments, the distributed resistance strain gauge sensor includes strain gauges and a bridge circuit. The strain gauges detect strain changes in the wire harness. The strain gauges are distributed and arranged below the wire harness in the wire groove and contact the wire harness through the wire harness strap. The bridge circuit converts the resistance changes of the strain gauges into voltage signals.

[0071] In some embodiments, the early warning and positioning module is used to process the voltage signal to obtain the resistance change; compare the resistance changes of each strain gauge, locate the strain gauge with the largest resistance change, determine the fracture location, and output fracture early warning information; the specific fracture location positioning method is as follows: calculate the resistance change ΔR of each strain gauge; calculate the average value B of the resistance changes of all strain gauges; compare the difference between each resistance change ΔR and the average value B, and the location of the strain gauge with the largest difference is the fracture location.

[0072] In some embodiments, the early warning and positioning module includes: The data receiving unit is used to receive the uploaded feature data; The model retrieval unit is used to retrieve historical fault models from the cloud database; The data comparison unit is used to compare the current feature data with the historical fault model and calculate the similarity between the current data and the historical fault features; The risk assessment unit is used to calculate the risk function value by combining the Bayesian change point detection algorithm with the comparison results, and to trigger different levels of early warning signals based on the magnitude of the risk function value.

[0073] In some embodiments, the risk assessment unit is specifically used for: Define Variable Point Points where the data distribution changes in a time series represent abrupt changes in the bundle state; Calculating change points using Bayes' theorem posterior probability : Calculate the risk function The value; and according to the risk function The value is used to determine whether the harness is at risk of breakage. if If the risk is deemed low, the real-time fracture probability is output. And record it as low risk; if The risk level is determined to be medium, and the real-time fracture probability is output. And issued a medium-risk warning; if If deemed high-risk, output the real-time fracture probability. It also issued a high-risk alert.

[0074] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for early warning and location of wire harness breakage based on multi-sensor fusion, characterized in that, Includes the following steps: S1. The current value of the wire harness is collected in real time by the current sensor. When the current change rate is detected to be greater than the change threshold and the difference between the current and the reference current value exceeds the preset threshold, an early warning is triggered and the tension detection is started. S2. By arranging tension sensors at the inlet and outlet of the cable harness drag chain, the tension data of the cable harness is collected; Calculate the variance of the tensile data; if the variance exceeds the first threshold, initiate strain detection. S3. The strain change of the wire harness is detected by a distributed resistance strain gauge sensor and the strain change is converted into a voltage signal; S4. Based on the collected signals, perform harness breakage early warning and location; specifically including: S41a. Process the voltage signal to obtain the resistance change; S42a. Compare the resistance changes of each strain gauge, locate the strain gauge with the largest resistance change, determine the fracture location, and output fracture warning information. The specific method for locating the fracture location is as follows: calculate the resistance change ΔR of each strain gauge; calculate the average resistance change B of all strain gauges; compare the difference between each resistance change ΔR and the average value B, and the strain gauge with the largest difference is the fracture location. S41b: Compress the feature data collected by the current sensor, tension sensor and resistance strain gauge sensor and upload it to the cloud database; S42b: Retrieve historical fault models from the cloud database. The historical fault models are based on features and statistical patterns extracted from past fault data. S43b. Compare the uploaded current feature data with the historical fault model, and calculate the similarity between the current data and the historical fault features; S44b: Using the Bayesian variable point detection algorithm combined with the comparison results, calculate the risk function value, and trigger different levels of early warning signals based on the magnitude of the risk function value.

2. The method for early warning and location of wire harness breakage based on multi-sensor fusion according to claim 1, characterized in that, The method also includes: When the detected current change rate is less than or equal to the change threshold, or the difference between the current and the reference current value is less than or equal to the preset threshold, or the variance of the tensile data is less than or equal to the first threshold, the current detection state is maintained, and the collected data is periodically uploaded to the cloud.

3. The method for early warning and location of wire harness breakage based on multi-sensor fusion according to claim 2, characterized in that, S1 specifically includes: S11. The current signal of the wire harness is collected in real time by a current sensor, and the reference current value is recorded during the equipment startup phase. S12. Calculate the rate of change of current in real time. If the following conditions are met simultaneously, the current is judged to be abnormal: The rate of change of current exceeds the preset dynamic change threshold; The deviation between the current value and the reference current value exceeds the preset static difference threshold; S13. When the current is abnormal, a warning signal is sent to the host computer and the tension sensor is triggered to start detection.

4. The method for early warning and location of wire harness breakage based on multi-sensor fusion according to claim 3, characterized in that, In S1, the steps for recording the reference current value during the device startup phase include: During the first m seconds of device startup, the current value is recorded once per second to obtain m startup transient reference values; After the equipment is running stably, the current value is recorded continuously m times and the average value is taken to generate a steady-state reference value. The m transient reference values ​​and 1 steady-state reference value are used together as the reference current value set for current anomaly determination.

5. The method for early warning and location of wire harness breakage based on multi-sensor fusion according to claim 4, characterized in that, In S2, the tension sensor is arranged as follows: A set of tension sensors is installed at each of the inlet and outlet of the cable chain, with the number of sensors in each set matching the number of wire harnesses. Each wire bundle is secured by a comb and comes into contact with a corresponding tension sensor.

6. The method for early warning and location of wire harness breakage based on multi-sensor fusion according to claim 5, characterized in that, Distributed resistive strain gauge sensors include strain gauges and bridge circuits. S3 specifically includes: S31. The strain change of the wire harness is detected by strain gauges, wherein the strain gauges are distributed and arranged below the wire harness in the wire groove and are in contact with the wire harness through the wire harness strip; S32. Use a bridge circuit to convert the resistance change of the strain gauge into a voltage signal.

7. The method for early warning and location of wire harness breakage based on multi-sensor fusion according to claim 6, characterized in that, S44b specifically includes: Define Variable Point Points where the data distribution changes in a time series represent abrupt changes in the bundle state; Calculating change points using Bayes' theorem posterior probability , The data observed at the point of change; Calculate the risk function The value; and according to the risk function The value is used to determine whether the harness is at risk of breakage. if It was determined to be low risk and recorded as low risk; if It was determined to be of medium risk, and a medium risk warning was issued; if It was determined to be high-risk and a high-risk alarm was issued.

8. A wire harness breakage early warning and positioning system based on multi-sensor fusion, characterized in that, include: A current sensor module is used to acquire the current value of the wiring harness in real time. The tension sensor module is installed at the inlet and outlet of the cable chain for collecting tension data of the cable harness; The distributed resistance strain gauge sensor module includes strain gauges and a bridge circuit. The strain gauges detect the strain changes of the wire harness. The strain gauges are distributed and arranged below the wire harness in the wire groove and contact the wire harness through the wire harness strap. The bridge circuit converts the resistance changes of the strain gauges into voltage signals. The detection and processing module is used to process the collected data, specifically to calculate the current change rate in real time. When the current change rate is greater than the change threshold and the difference between the current and the reference current value exceeds the preset threshold, an alarm is triggered and tensile detection is started. The variance of the tensile data is calculated. If the variance exceeds the first threshold, strain detection is started. The strain change of the wire harness is detected by a distributed resistance strain gauge sensor and the strain change is converted into a voltage signal. The data processing module is used to process the voltage signal to obtain the resistance change of each strain gauge. The fracture location is located by comparing the resistance change of each strain gauge. The specific method for locating the fracture location is to calculate the resistance change ΔR of each strain gauge. Calculate the average resistance change B of all strain gauges; compare the difference between each resistance change ΔR and the average value B, and the strain gauge with the largest difference is the fracture location; retrieve historical fault models from the cloud database, compare the current feature data with the historical fault models, calculate the real-time fracture risk value and trigger graded early warning, where the current feature data is the feature data collected by the current sensor, tensile sensor and resistance strain gauge sensor.

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