Cable laying stress monitoring method and system and storage medium

Abstract

The invention discloses a stress monitoring method and system for cable laying and a storage medium. A sensor module is used for collecting parameter data of cable laying machine driving force, cable contact force, cable arrangement machine cable side pressure, cable arrangement machine conveying speed and cable traction force; the signal processing module is used for sequentially carrying out voltage stabilization, noise reduction, filtering, signal amplification and AD conversion processing on the acquired data; filtering the digital signal of the data after AD conversion by using an oversampling technology; digital signals of the data are sorted and packaged through the FPGA module and are transmitted to the data analysis module; the data analysis module analyzes the data signals to obtain the stress change condition and the quantitative evaluation condition of the construction quality in the cable laying process, and the intelligent control terminal analyzes, predicts and controls the state of the laid cable according to the stress change condition and the online quantitative evaluation condition. The intelligent degree in the cable laying process is high, and the data calculation accuracy is high.

Description

Technical Field

[0001] The present invention belongs to the technical field of cable laying stress monitoring, and in particular relates to a cable laying stress monitoring method, system and storage medium. Background Art

[0002] The development of power cable construction technology is a process of continuous improvement in mechanization and intelligence. In the early days, cable laying construction relied entirely on manual traction and laying. As the cross-sectional area of ​​the cable increases, the weight also increases. Greater traction is required for laying. Therefore, mechanical equipment that can provide great traction has been widely used. The mechanized construction of power cables can realize the transformation of cable line construction from labor-intensive to equipment-intensive, thereby improving construction efficiency and meeting the needs of large-scale power grid construction. The laying of high-voltage or larger cross-section cables requires more advanced mechanical laying methods. At the same time, how to avoid mechanical damage to the cable during the laying process and how to effectively monitor the laying process are new issues that the cable laying process faces. At present, the mechanized construction of power cables has reached a certain scale and level, but intelligent construction is still in its infancy. The intelligent construction of power cables, combined with current artificial intelligence technology and integrated online monitoring equipment, can effectively judge the various states of power cables during the construction process and provide real-time data for safe and reliable construction. It is the next development direction of cable construction.

[0003] The key technologies of intelligent cable laying can improve construction efficiency and meet the needs of large-scale power grid construction; improve the process quality level of power cable construction; at the same time, monitor, analyze, judge and feedback the construction process in real time, provide construction management personnel with accurate monitoring data, and grasp the various states of cables and equipment during construction in real time to meet the requirements of intelligent laying.

[0004] A new method for stress monitoring of laid cables is needed. Summary of the invention

[0005] The object of the present invention is to provide a stress monitoring method, system and storage medium for laying cables, so as to solve the technical problems of low intelligence level and low data calculation accuracy in the prior art of laying cables.

[0006] The technical solution of the present invention to solve the technical problem is:

[0007] A stress monitoring method for laying cables comprises the following steps:

[0008] S1: The intelligent control terminal sends a collection instruction to the sensor module according to the demand; the sensor module collects parameter data of the cable laying machine driving force, cable contact force, cable side pressure of the cable laying machine, cable laying machine conveying speed, and cable traction force according to the collection instruction; and sends the collected data to the signal processing module;

[0009] S2: The signal processing module performs voltage stabilization, noise reduction, filtering, signal amplification, and AD conversion on the collected data in sequence; uses oversampling technology to filter the digital signal of the data after AD conversion; and then organizes, packages, and transmits the digital signal of the data to the data analysis module through the FPGA module;

[0010] S3: The data analysis module uses the tension and pressure signal time-frequency dynamic analysis and display submodule and the cable laying construction quality online quantitative evaluation submodule to analyze the data signal, obtain the stress change in the cable laying process and the quantitative evaluation of the construction quality, and send the stress change and online quantitative evaluation to the intelligent control terminal;

[0011] S4: The intelligent control terminal analyzes, predicts and controls the status of the laid cables according to stress changes and online quantitative evaluation.

[0012] The step S3 includes an analysis method performed by the tension and pressure signal time-frequency dynamic analysis and display submodule, which specifically includes the following steps:

[0013] Q1: According to the digital signal of the data, calculate the maximum amplitude, average value, variance, power and energy integral of the digital signal;

[0014] Q2: In the time domain, the correlation function between the traction force and the lateral pressure signals is optimized to obtain the time relationship between the signals; in the frequency domain, the traction force and the lateral pressure signals are decomposed in the frequency domain using Fourier transform to obtain the spectrum characteristics and energy distribution of the traction force and the lateral pressure;

[0015] Q3: Send the time relationship between signals, the frequency spectrum characteristics of traction and lateral pressure, and the energy distribution to the intelligent control terminal.

[0016] The correlation function between the traction force and the lateral pressure signal in step Q2 is:

[0017]

[0018] The relevant functions are optimized and become:

[0019]

[0020]

[0021] Among them, R x (τ) represents the correlation function of the traction force signal; R y (τ) represents the correlation function of the lateral pressure signal; R xy(τ) represents the correlation function between the traction signal and the lateral pressure signal; x(t) is the traction signal, y(t) is the lateral pressure signal, τ is the time delay, T is the observation time of the signal, and t is the current time point.

[0022] In step Q2, the traction force and lateral pressure signals are decomposed in the frequency domain, and the specific calculation formula is:

[0023]

[0024] Wherein, X(f) represents the spectral component of the traction force signal at frequency f; Y(f) represents the spectral component of the lateral pressure signal at frequency f; j represents an imaginary number; N is the number of sampling points, Δt is the sampling interval, and f is the frequency.

[0025] The step S3 includes an analysis method performed by the cable installation construction quality online quantitative evaluation submodule, which specifically includes the following steps:

[0026] The digital signal of the data is preprocessed to extract the maximum tensile pressure, average tensile pressure, tensile pressure change rate, and high-frequency tensile pressure frequency distribution characteristics of the digital signal, and the correlation coefficient and covariance of the traction force and the lateral pressure signal are calculated based on the extracted characteristics; the digital signal of the data is quantitatively evaluated in real time based on the set maximum tensile pressure value, the allowable range of high-frequency tensile pressure distribution, the tensile pressure energy distribution range, and the area of ​​maximum correlation between the two forces to obtain the comprehensive deviation, and the evaluation result is sent to the intelligent control terminal.

[0027] A stress monitoring system for laying cables, comprising:

[0028] The sensor module is used to collect the driving force of the cable unwinding machine through the cable unwinding machine driving force sensor, the cable contact force sensor collects the force generated when the cable contacts the cable unwinding machine and the cable unwinding machine, the cable side pressure sensor of the cable unwinding machine collects the side pressure applied by the cable unwinding machine to the cable, the cable unwinding machine conveying speed sensor collects the speed of the cable unwinding machine conveying the cable, and the cable traction force sensor collects the traction force received by the cable during the laying process; and sends the collected data to the signal processing module;

[0029] The data processing module is used to perform voltage stabilization, noise reduction, filtering, signal amplification, and AD conversion on the collected data in sequence; the digital signal of the data after AD conversion is filtered using oversampling technology; and the digital signal of the data is sorted, packaged, and transmitted to the data analysis module through the FPGA module;

[0030] The data analysis module analyzes the data signal through the time-frequency dynamic analysis and display submodule of the tension and pressure signal and the online quantitative evaluation submodule of the cable laying construction quality, obtains the stress change during the cable laying process and the quantitative evaluation of the construction quality, and sends the stress change and online quantitative evaluation to the intelligent control terminal;

[0031] The intelligent control terminal is used to analyze the status of the laid cables according to the stress changes and online quantitative evaluation, and adjust the operating parameters of the cable laying.

[0032] The data analysis module also includes a fuzzy algorithm submodule, which is used to obtain the control value of the cable release speed through fuzzy reasoning and clarification processing.

[0033] A computer-readable storage medium stores a computer program, wherein when the computer program is executed by a processor, the device where the computer-readable storage medium is located executes a stress monitoring method for laying cables.

[0034] The beneficial effects of the present invention are as follows: the parameter data of the cable laying machine driving force, cable contact force, cable side pressure of the cable laying machine, cable laying machine conveying speed, and cable traction force are collected by the sensor module according to the collection instruction; and the collected data is sent to the signal processing module; the signal processing module performs voltage stabilization, noise reduction, filtering, signal amplification, and AD conversion processing on the collected data in sequence; the digital signal of the data after AD conversion is filtered by oversampling technology; and the digital signal of the data is sorted, packaged, and transmitted to the data analysis module by the FPGA module; the data analysis module uses the time-frequency dynamic analysis and display submodule of the tension and pressure signal and the online quantitative evaluation submodule of the cable laying construction quality to analyze the data signal, obtain the stress change and the quantitative evaluation of the construction quality during the cable laying process, and send the stress change and the online quantitative evaluation to the intelligent control terminal; the intelligent control terminal analyzes, predicts, and controls the state of the cable laying according to the stress change and the online quantitative evaluation, and the user can set the work tasks and operating parameters through the terminal, and perform state monitoring and data tracing. The intelligent degree of the cable laying process is high and the data calculation accuracy is high. The problem of long laying cycle due to cable damage is avoided. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 is a flow chart of the stress monitoring method for laying cables of the present invention;

[0036] Figure 2 It is a structural diagram of the stress monitoring device for laying cables of the present invention. DETAILED DESCRIPTION

[0037] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0038] Embodiment 1:

[0039] like Figure 1 As shown, the present invention discloses a stress monitoring method for laying cables, comprising the following steps:

[0040] S1: The intelligent control terminal sends a collection instruction to the sensor module according to the demand; the sensor module collects parameter data of the cable laying machine driving force, cable contact force, cable side pressure of the cable laying machine, cable laying machine conveying speed, and cable traction force according to the collection instruction; and sends the collected data to the signal processing module;

[0041] S2: The signal processing module performs voltage stabilization, noise reduction, filtering, signal amplification, and AD conversion on the collected data in sequence; uses oversampling technology to filter the digital signal of the data after AD conversion; and then organizes, packages, and transmits the digital signal of the data to the data analysis module through the FPGA module;

[0042] S3: The data analysis module uses the tension and pressure signal time-frequency dynamic analysis and display submodule and the cable laying construction quality online quantitative evaluation submodule to analyze the data signal, obtain the stress change in the cable laying process and the quantitative evaluation of the construction quality, and send the stress change and online quantitative evaluation to the intelligent control terminal;

[0043] The analysis method performed by the tension and pressure signal time-frequency dynamic analysis and display submodule specifically includes the following steps:

[0044] Q1: According to the digital signal of the data, calculate the maximum amplitude, average value, variance, power and energy integral of the digital signal;

[0045] Q2: In the time domain, the correlation function between the traction force and the lateral pressure signals is optimized to obtain the time relationship between the signals; in the frequency domain, the traction force and the lateral pressure signals are decomposed in the frequency domain using Fourier transform to obtain the spectrum characteristics and energy distribution of the traction force and the lateral pressure;

[0046] The correlation function between the traction force and the lateral pressure signal is:

[0047]

[0048] The relevant functions are optimized and become:

[0049]

[0050] Among them, R x(f) represents the correlation function of the traction force signal; R y (τ) represents the correlation function of the lateral pressure signal; R xy (τ) represents the correlation function between the traction signal and the lateral pressure signal; x(t) is the traction signal, y(t) is the lateral pressure signal, τ is the time delay, T is the observation time of the signal, and t is the current time point.

[0051] In the calculation of the improved correlation function, T-τ is used as the denominator to avoid inaccurate calculation results when the integration interval exceeds the actual observation time when the time delay is large. Through such improvements, the correlation of signals under different time delays can be more accurately reflected, especially when processing long time series data, the accuracy of the correlation function can be improved. The effect is that the correlation between the traction force and the lateral pressure signal can be measured more accurately, which helps to gain a deeper understanding of the relationship between the two forces during the cable laying process, thereby providing a more accurate basis for optimizing the laying process.

[0052] The traction force and lateral pressure signals are decomposed in the frequency domain. Fast Fourier transform (FFT) can be used to decompose the traction force and lateral pressure signals in the frequency domain. The specific calculation formula is:

[0053]

[0054] Wherein, X(f) represents the spectral component of the traction force signal at frequency f; Y(f) represents the spectral component of the lateral pressure signal at frequency f; j represents an imaginary number; N is the number of sampling points, Δt is the sampling interval, and f is the frequency.

[0055] FFT is an algorithm for fast calculation of discrete Fourier transform, which can convert time domain signals into frequency domain signals, thereby revealing the frequency components of the signal. By performing FFT on the sampled signal, the spectral components of the signal at each frequency point can be obtained, and then the frequency domain characteristics of the signal can be analyzed. The effect is: FFT can greatly improve the efficiency of frequency domain analysis, so that the frequency domain information of the signal can be obtained more quickly in real-time monitoring and control systems. This helps to find abnormal frequency components in the signal more promptly, thereby quickly diagnosing and handling problems in the cable laying process.

[0056] Q3: Send the time relationship between signals, the frequency spectrum characteristics of traction and lateral pressure, and the energy distribution to the intelligent control terminal.

[0057] The analysis method performed by the online quantitative evaluation submodule of cable installation construction quality includes the following steps:

[0058] The digital signal of the data is preprocessed to extract the maximum tensile pressure, average tensile pressure, tensile pressure change rate, and high-frequency tensile pressure frequency distribution characteristics of the digital signal, and the correlation coefficient and covariance of the traction force and the lateral pressure signal are calculated based on the extracted characteristics; the digital signal of the data is quantitatively evaluated in real time based on the set maximum tensile pressure value, the allowable range of high-frequency tensile pressure distribution, the tensile pressure energy distribution range, and the area of ​​maximum correlation between the two forces to obtain the comprehensive deviation, and the evaluation result is sent to the intelligent control terminal.

[0059] For example,

[0060] For example, assuming that the maximum tension threshold is set to 80% of the cable's allowable tension, the average tension threshold is set to 50% of the cable's allowable tension, the high-frequency tension frequency distribution should be within a specific range, and the correlation coefficient between traction and lateral pressure should be greater than 0.8. The indicator weights are 40% for the maximum tension, 30% for the average tension, 20% for the high-frequency tension frequency distribution, and 10% for the correlation coefficient between traction and lateral pressure.

[0061] For a set of collected data, the maximum tensile pressure is calculated to be 75% of the allowable tension of the cable, the average tensile pressure is 45% of the allowable tension of the cable, the frequency distribution of high-frequency tensile pressure is within a reasonable range, and the correlation coefficient between traction force and lateral pressure is 0.9.

[0062] The comprehensive deviation score is:

[0063] (75%-80%)×40%+(45%-50%)×30%+0×20%+(0.9-0.8)×10%=-0.02-0.015+0+0.01=-0.025

[0064] Since the comprehensive deviation score does not exceed the preset threshold, the construction quality can be considered qualified.

[0065] Through the above refinement and algorithm evaluation, the cable installation quality can be more accurately and quantitatively evaluated online, problems can be found and adjusted in time, and the construction quality and reliability can be improved. In practical applications, appropriate algorithms and evaluation indicators can be selected according to specific circumstances, and the evaluation system can be continuously optimized and improved.

[0066] Step S3 also includes a fuzzy algorithm submodule, which controls the speed of cable laying and cable arrangement by taking the cable arrangement speed index as a reference instruction to control the cable laying speed; assuming that the cable arrangement speed is v p , the cable release speed is v r , the force signal fed back by the force sensor is F, then the fuzzy control rule can be expressed as:

[0067] If F is F1 and v p is v p1 then vr is v r1

[0068] If F is F2 and v p is v p2 then v r is v r2

[0069] …

[0070] The fuzzy control rules can be further refined to consider more input variables and fuzzy subsets to improve the control accuracy; for example, in addition to the force signal F and the cable speed v fed back by the force sensor, p In addition, factors such as the cable diameter D and the temperature T of the laying environment can also be considered; the fuzzy control rule can be expressed as:

[0071] If F is F1 and v p is v p1 and D is D1 and T is T1 then v r is v r1

[0072] If F is F2 and v p is v p2 and D is D2 and T is T2 then v r is v r2

[0073] …

[0074] Finally, according to the fuzzy control rules, the control quantity of the cable release speed can be obtained through fuzzy reasoning and clarification processing; in the fuzzy reasoning process, more complex reasoning methods can be used, such as multi-input multi-output fuzzy reasoning, to better adapt to complex control situations; clarification processing can use more precise methods, such as the center of gravity method or the weighted average method, to improve the accuracy of the control quantity.

[0075] Through the above optimization, the accuracy and adaptability of control are improved, and the cable laying requirements under different working conditions can be better met. For example, when the cable diameter is large or the laying environment temperature is high, the system can automatically adjust the cable release and cable arrangement speed to avoid excessive traction or cable accumulation. The system can respond to various changes more flexibly and improve the stability and reliability of the system. Through more precise control, faults and damages during cable laying can be reduced and construction quality can be improved. In this way, the intelligent control and monitoring of the cable laying process can be better realized; the improvement of these optimization algorithms can improve the performance of the intelligent cable stress monitoring and control system, so that it can more accurately monitor and control the stress during cable laying, thereby improving construction quality and efficiency.

[0076] S4: The intelligent control terminal analyzes, predicts and controls the status of the laid cables according to stress changes and online quantitative evaluation.

[0077] Embodiment 2:

[0078] like Figure 2 As shown, a stress monitoring system for laying cables comprises:

[0079] The sensor module is used to collect the driving force of the cable unwinding machine through the cable unwinding machine driving force sensor, the cable contact force sensor collects the force generated when the cable contacts the cable unwinding machine and the cable unwinding machine, the cable side pressure sensor of the cable unwinding machine collects the side pressure applied by the cable unwinding machine to the cable, the cable unwinding machine conveying speed sensor collects the speed of the cable unwinding machine conveying the cable, and the cable traction force sensor collects the traction force received by the cable during the laying process; and sends the collected data to the signal processing module;

[0080] The data processing module is used to perform voltage stabilization, noise reduction, filtering, signal amplification, and AD conversion on the collected data in sequence; the digital signal of the data after AD conversion is filtered using oversampling technology; and the digital signal of the data is sorted, packaged, and transmitted to the data analysis module through the FPGA module;

[0081] The data analysis module analyzes the data signal through the time-frequency dynamic analysis and display sub-module of the tension and pressure signal and the online quantitative evaluation sub-module of the cable laying construction quality, obtains the stress change in the cable laying process and the quantitative evaluation of the construction quality, and sends the stress change and the online quantitative evaluation to the intelligent control terminal; the fuzzy algorithm sub-module is used to obtain the control value of the cable laying speed through fuzzy reasoning and clarification processing.

[0082] The intelligent control terminal is used to analyze the status of the laid cables according to the stress changes and online quantitative evaluation, and adjust the operating parameters of the cable laying.

[0083] In practical applications, the hardware components of the intelligent control terminal include:

[0084] Display screen: used to display various information of the system, such as sensor data, construction quality assessment results, equipment operation status, etc.;

[0085] Operation buttons: at least including power switch, setting button, confirmation button, cancel button, etc., used to operate the terminal;

[0086] Data interface: used to connect the sensor module, signal processing module and data analysis module to realize data transmission and exchange;

[0087] Processor: responsible for processing and analyzing data from various modules, running intelligent control algorithms, and realizing control and management of the system;

[0088] Memory: used to store system setting parameters, historical data, control algorithms, etc.

[0089] The functional modules of the intelligent control terminal include at least:

[0090] System settings: Users can set the system's operating parameters through the intelligent control terminal, such as the sensor's sampling frequency, alarm threshold, control algorithm parameters, etc.

[0091] Task management: Users can set work tasks, such as the route, length, speed, etc. of cable laying, and monitor and manage the tasks;

[0092] Status monitoring: Real-time display of various data collected by the sensor module, including the driving force of the cable unwinding machine, the cable contact force, the cable side pressure of the cable unwinding machine, the conveying speed, the cable traction force, etc., and also displays the operating status of the equipment, such as the working status of the cable unwinding machine and the cable unwinding machine, fault information, etc.;

[0093] Data traceability: Store and record the system's historical data. Users can query and trace historical data to analyze and evaluate construction quality.

[0094] Prediction and control: Based on the construction quality assessment results provided by the data analysis module, the intelligent control terminal can predict potential problems and adjust the operating status of the equipment through the control algorithm to optimize the lateral pressure and traction during the laying process to ensure construction quality;

[0095] Alarm function: When the system detects an abnormal situation, such as cable stress exceeding the threshold, equipment failure, etc., the intelligent control terminal will send an alarm signal to remind the user to take timely measures.

[0096] Furthermore, the user interface of the intelligent control terminal includes at least:

[0097] Graphical interface: It uses an intuitive graphical interface to display real-time curves of sensor data, charts of construction quality assessment results, etc., so that users can clearly understand the operation of the system;

[0098] Menu navigation: Through menu navigation, users can easily switch between different functional modules to perform system settings, task management, status monitoring and other operations;

[0099] Prompt information: During the operation, the intelligent control terminal will provide corresponding prompt information to help users operate correctly;

[0100] Furthermore, the communication functions of the intelligent control terminal include at least:

[0101] Wired communication: Wired communication with other modules through the data interface to ensure stable data transmission;

[0102] Wireless communication: With wireless communication function, users can remotely access the intelligent control terminal through mobile devices such as mobile phones and tablets to achieve remote monitoring and management of the system;

[0103] In summary, through the above details, the intelligent control terminal can more intelligently and conveniently realize the control and management of the cable laying process, and improve the construction efficiency and quality.

[0104] In specific applications, the components of the stress monitoring device for laying cables can be as follows:

[0105] Sensor Module:

[0106] Cable unwinding machine driving force sensor: A force sensor is used and installed on the driving shaft of the cable unwinding machine. The measuring range is 0-500N and the accuracy is ±0.5%;

[0107] Cable contact force sensor: strain sensor, installed at the contact point between the cable and the cable unwinding machine, cable unwinding machine, with a measurement range of 0-5000N and an accuracy of ±0.5%;

[0108] Cable side pressure sensor of cable arranging machine: The pressure sensor is installed on the wire pressing part of the cable arranging machine, with a measuring range of 0-5000N and an accuracy of ±0.5%;

[0109] Cable conveyor speed sensor: encoder, connected to the rotating part of the cable conveyor, with a measuring range of 0-10m / s and an accuracy of ±0.1%;

[0110] Cable traction force sensor: The force sensor is installed at the traction part of the cable, with a measuring range of 0-8000N and an accuracy of ±0.5%.

[0111] Signal processing module:

[0112] Low-noise signal analog power supply: Design a stable low-noise power supply to provide power for sensors and analog signal change circuits, with power supply noise less than 1mV;

[0113] Low-pass and power frequency suppression filter circuit: The cut-off frequency of the low-pass filter is 50Hz, and the power frequency suppression filter has a suppression capability of more than 60dB for 50Hz mains interference;

[0114] Signal amplification and filtering: using high-performance amplifier, the amplification factor is 10 times, and the signal distortion is less than 0.1%;

[0115] Analog-to-digital conversion: Use a domestic low-cost FPGA with parallel processing capabilities to control 4-channel 24-bit resolution differential ADCs for parallel 10KHz rate analog-to-digital conversion;

[0116] Digital filtering and processing: Design digital low-pass filters and digital notch filters in FPGA, with out-of-band interference suppression capability greater than 40dB and in-band specific frequency interference suppression capability greater than 30dB.

[0117] Data Analysis Module:

[0118] Time-frequency dynamic analysis and display of tension and pressure signals: common signal analysis methods and modern signal analysis methods are used to analyze the traction and lateral pressure signals. In the time domain, the correlation function and time span correlation function are calculated; in the frequency domain, Fourier decomposition and transformation are performed to display the energy distribution. The analysis results are displayed dynamically in real time on the display screen, with an update frequency of 1Hz.

[0119] Online quantitative evaluation of cable installation quality based on signal analysis: Set quantitative evaluation indicators, such as the maximum tension threshold is 80% (6N) of the cable's allowable tension, the average tension threshold is 50% (0N) of the cable's allowable tension, the high-frequency tension frequency distribution should be in the range of 10-50Hz, and the correlation coefficient between traction and lateral pressure should be greater than 0.8. The indicator weights are 40% for maximum tension, 30% for average tension, 20% for high-frequency tension frequency distribution, and 10% for correlation coefficient between traction and lateral pressure. Use support vector machine algorithm for evaluation.

[0120] Intelligent control terminal:

[0121] Hardware composition: Equipped with a 10-inch display screen, operation buttons include power switch, setting button, confirmation button, cancel button, etc. The data interface uses RS485 and Ethernet interface. The processor is a high-performance embedded processor with a memory capacity of 16GB.

[0122] Functional modules: Users can set the sensor sampling frequency to Hz through the terminal, and the alarm threshold to the threshold of each evaluation indicator. Set the cable laying task, including route, length and speed. Monitor sensor data and equipment operation status in real time, store historical data, and make predictions and controls based on data analysis results. When an abnormal situation occurs, an audible and visual alarm signal is issued.

[0123] User interface: Graphical interface is used to display sensor data curves and construction quality assessment charts. Operation is carried out through menu navigation and detailed prompt information is provided.

[0124] Communication function: supports wired communication and wireless communication, and users can remotely access the terminal through the mobile phone APP.

[0125] Specific implementation process: During the cable laying process, the sensor module collects signals in real time and transmits the signals to the signal processing module. After the signal processing module processes the signals, it transmits the data to the data analysis module. The data analysis module analyzes and evaluates and sends the results to the intelligent control terminal. The intelligent control terminal controls and adjusts the equipment according to the evaluation results, such as adjusting the speed of the cable laying machine and the cable arranging machine to optimize the side pressure and traction. At the same time, the terminal displays system information in real time, and promptly alarms when abnormal situations occur to remind construction personnel to deal with them.

[0126] Embodiment 3:

[0127] A computer-readable storage medium stores a computer program, wherein when the computer program is executed by a processor, the device where the computer-readable storage medium is located executes a stress monitoring method for laying cables.

[0128] Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in the field without making any creative work shall fall within the scope of protection of the present invention.

Claims

1. A stress monitoring method for laying cables, characterized in that: The following steps are involved: S1: The intelligent control terminal sends a collection instruction to the sensor module according to the demand; the sensor module collects parameter data of the cable laying machine driving force, cable contact force, cable side pressure of the cable laying machine, cable laying machine conveying speed, and cable traction force according to the collection instruction; and sends the collected data to the signal processing module; S2: The signal processing module performs voltage stabilization, noise reduction, filtering, signal amplification, and AD conversion on the collected data in sequence; uses oversampling technology to filter the digital signal of the data after AD conversion; and then organizes, packages, and transmits the digital signal of the data to the data analysis module through the FPGA module; S3: The data analysis module uses the tension and pressure signal time-frequency dynamic analysis and display submodule and the cable laying construction quality online quantitative evaluation submodule to analyze the data signal, obtain the stress change in the cable laying process and the quantitative evaluation of the construction quality, and send the stress change and online quantitative evaluation to the intelligent control terminal; S4: The intelligent control terminal analyzes, predicts and controls the status of the laid cables according to stress changes and online quantitative evaluation.

2. The stress monitoring method for laying cables according to claim 1, characterized in that: The step S3 includes an analysis method performed by the tension and pressure signal time-frequency dynamic analysis and display submodule, which specifically includes the following steps: Q1: According to the digital signal of the data, calculate the maximum amplitude, average value, variance, power and energy integral of the digital signal; Q2: In the time domain, the correlation function between the traction force and the lateral pressure signals is optimized to obtain the time relationship between the signals; in the frequency domain, the traction force and the lateral pressure signals are decomposed in the frequency domain using Fourier transform to obtain the spectrum characteristics and energy distribution of the traction force and the lateral pressure; Q3: Send the time relationship between signals, the frequency spectrum characteristics of traction and lateral pressure, and the energy distribution to the intelligent control terminal.

3. The stress monitoring method for laying cables according to claim 2, characterized in that: The correlation function between the traction force and the lateral pressure signal in step Q2 is: ； ； ； The relevant functions are optimized and become: ； ； ； in, Represents the correlation function of the traction force signal; Represents the correlation function of the lateral pressure signal; Represents the correlation function between the traction force signal and the lateral pressure signal; is the traction signal, is the side pressure signal, For time delay, is the observation time of the signal, The current time point.

4. The stress monitoring method for laying cables according to claim 3, characterized in that: In step Q2, the traction force and lateral pressure signals are decomposed in the frequency domain, and the specific calculation formula is: ； ； in, Indicates the traction force signal at frequency The spectral components at ; Indicates the side pressure signal at frequency The spectral components at ; represents an imaginary number; is the number of sampling points, is the sampling interval, is the frequency.

5. The stress monitoring method for laying cables according to claim 1, characterized in that: The step S3 includes an analysis method performed by the cable installation construction quality online quantitative evaluation submodule, which specifically includes the following steps: The digital signal of the data is preprocessed to extract the maximum tensile pressure, average tensile pressure, tensile pressure change rate, and high-frequency tensile pressure frequency distribution characteristics of the digital signal, and the correlation coefficient and covariance of the traction force and the lateral pressure signal are calculated based on the extracted characteristics; the digital signal of the data is quantitatively evaluated in real time based on the set maximum tensile pressure value, the allowable range of high-frequency tensile pressure distribution, the tensile pressure energy distribution range, and the area of ​​maximum correlation between the two forces to obtain the comprehensive deviation, and the evaluation result is sent to the intelligent control terminal.

6. A stress monitoring system for laying cables, characterized in that: include: The sensor module is used to collect the driving force of the cable unwinding machine through the cable unwinding machine driving force sensor, the cable contact force sensor collects the force generated when the cable contacts the cable unwinding machine and the cable unwinding machine, the cable side pressure sensor of the cable unwinding machine collects the side pressure applied by the cable unwinding machine to the cable, the cable unwinding machine conveying speed sensor collects the speed of the cable unwinding machine conveying the cable, and the cable traction force sensor collects the traction force received by the cable during the laying process; and sends the collected data to the signal processing module; The data processing module is used to perform voltage stabilization, noise reduction, filtering, signal amplification, and AD conversion on the collected data in sequence; the digital signal of the data after AD conversion is filtered using oversampling technology; and the digital signal of the data is sorted, packaged, and transmitted to the data analysis module through the FPGA module; The data analysis module analyzes the data signal through the time-frequency dynamic analysis and display submodule of the tension and pressure signal and the online quantitative evaluation submodule of the cable laying construction quality, obtains the stress change during the cable laying process and the quantitative evaluation of the construction quality, and sends the stress change and online quantitative evaluation to the intelligent control terminal; The intelligent control terminal is used to analyze the status of the laid cables according to the stress changes and online quantitative evaluation, and adjust the operating parameters of the cable laying.

7. The cable laying stress monitoring system according to claim 6, characterized in that: The data analysis module also includes a fuzzy algorithm submodule, which is used to obtain the control value of the cable release speed through fuzzy reasoning and clarification processing.

8. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the device where the computer-readable storage medium is located executes the method according to any one of claims 1 to 5.

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