Cable pipe trench stability evaluation method, device, equipment and medium

Abstract

The invention discloses a cable duct stability evaluation method and device, equipment and a medium. The method comprises the steps that probability distribution data of random influence variables and response correlation coefficients among the random influence variables are obtained through calculation according to historical measurement data of the random influence variables influencing the stability of a target cable duct; and constructing a three-dimensional simulation model of the target cable duct according to the real-time measurement data, optimizing and adjusting the three-dimensional simulation model according to the response correlation coefficients, and simulating and generating a plurality of cable duct working condition events by adopting a Monte Carlo method to calculate the stability index of the target cable duct. And evaluating the state stability of the cable duct by adopting the stability index. According to the method, the Monte Carlo algorithm is introduced, probability analysis and stochastic simulation technologies are combined, the randomness and uncertainty of the influence factors of the stability of the cable duct are comprehensively considered, evaluation result deviation caused by excessively simplified assumed conditions is avoided, and the accuracy and reliability of stability evaluation of the cable duct are remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of power facility monitoring, and in particular, to a method, device, equipment and medium for evaluating the stability of a cable trench. Background Art

[0002] With the rapid development of modern urban infrastructure construction, power, telecommunications and other types of underground pipeline systems increasingly rely on cable trenches for laying. As an important underground facility, the cable trench undertakes the key function of ensuring the normal operation of the city.

[0003] Traditional methods for analyzing the stability of cable trenches are mainly based on deterministic models, assuming that all input parameters are known and determined. The stability assessment results provided by these methods often have obvious limitations when facing complex geological and construction environments. The spatial variability of geological conditions, the physical and mechanical parameters of soil, the fluctuation of the groundwater level, the change of construction loads, and the deformation of the support structure all have strong randomness. Traditional deterministic analysis methods are difficult to fully consider these uncertain factors, resulting in the assessment results that may underestimate risks and cannot accurately reflect the stability state of the cable trench under actual working conditions.

[0004] Therefore, how to improve the accuracy of the assessment of the stability of the cable trench has become a technical problem that needs to be urgently solved by those skilled in the art. Summary of the Invention

[0005] The present invention provides a method, device, equipment and medium for evaluating the stability of a cable trench to monitor and evaluate the state of the cable trench in real time.

[0006] To solve the above technical problem, an embodiment of the present invention provides a method for evaluating the stability of a cable trench, including: Determine the influencing variables that affect the stability of the target cable trench, where the influencing variables at least include environmental influencing variables.

[0007] Obtain the historical measurement data corresponding to each of the influencing variables, and calculate the probability distribution data of each of the influencing variables and the response correlation coefficients between the influencing variables according to the historical measurement data.

[0008] Obtain the real-time measurement data corresponding to the influencing variables of the target cable trench, construct a three-dimensional simulation model of the target cable trench according to the real-time measurement data, quantitatively adjust the real-time measurement data corresponding to the influencing variables of the three-dimensional simulation model according to the response correlation coefficients, obtain the response difference data of the three-dimensional simulation model for each of the influencing variables, and optimize and adjust the three-dimensional simulation model based on the response difference data.

[0009] Generate a number of cable trench working condition events by Monte Carlo simulation, apply each of the cable trench working condition events to the 3D simulation model, and generate a stability index set based on the feedback of the 3D simulation model.

[0010] During the actual monitoring of the cable trench, evaluate the state stability of the cable trench using the influencing variables corresponding to the stability index set to obtain the cable trench stability evaluation result.

[0011] Further, the influencing variables further include cable operation influencing variables.

[0012] The environmental influencing variables include at least one of trench size, soil physical properties, groundwater level, load, support parameters, and adjacent buildings.

[0013] The cable operation influencing variables include at least one of cable operation temperature, degree of insulation layer aging, and vibration frequency of the cable.

[0014] Further, the obtaining of the historical measurement data of each of the influencing variables and the calculation of the probability distribution data of each of the influencing variables and the response correlation coefficients between the influencing variables according to the historical measurement data include: Obtain the historical measurement data of each of the influencing variables.

[0015] Use the maximum likelihood estimation method to fit the probability distribution of the historical measurement data to obtain the probability distribution data of each of the influencing variables.

[0016] Use the correlation analysis method to calculate the response relationship between the historical measurement data to obtain the response correlation coefficients between the influencing variables.

[0017] Further, the obtaining of the historical measurement data of each of the influencing variables includes: According to the historical exploration report and construction records, obtain the first historical data of each of the influencing variables.

[0018] Calibrate the first historical data according to the sensor type corresponding to each of the first historical data to obtain the second historical data.

[0019] Use the linear interpolation method to interpolate the missing values of the second historical data to obtain the third historical data.

[0020] Use the moving average method to suppress the fluctuations of the third historical data to obtain the historical measurement data.

[0021] Further, the use of the correlation analysis method to calculate the response relationship between the historical measurement data to obtain the response correlation coefficients between the influencing variables includes: Construct a measurement data matrix composed of each of the historical measurement data.

[0022] Calculate the Pearson correlation coefficient of each of the historical measurement data as the response correlation coefficient according to the measurement data matrix.

[0023] Further, quantitatively adjusting each of the influencing variables of the three-dimensional simulation model according to each of the response correlation coefficients to obtain response difference data of the three-dimensional simulation model for each of the influencing variables, including: Determine the variable adjustment order according to the dependence relationship between each of the influencing variables and the magnitude of the response correlation coefficient.

[0024] Quantitatively adjust each of the influencing variables step by step according to the variable adjustment order, and the adjustment value is: Wherein, is the single adjustment value of the influencing variable , is the influencing variable and another influencing variable The response correlation coefficient between them, is the number of adjustment levels.

[0025] Calculate according to the response difference value of the three-dimensional simulation model after quantitatively adjusting each of the influencing variables to obtain the response difference data of the three-dimensional simulation model for each of the influencing variables.

[0026] Further, using the stability index to evaluate the state stability of the cable trench to obtain the cable trench stability evaluation result, including: Use the stability index to evaluate the state stability of the cable trench during actual operation, and generate a risk level evaluation report according to the evaluation result; the risk level evaluation report at least includes the cable trench instability risk evaluation result, the visualization probability distribution map and the cumulative probability curve.

[0027] Obtain the corresponding risk control plan through big data analysis according to the risk level evaluation report.

[0028] Another embodiment of the present invention provides a cable trench stability evaluation device, including: A variable determination module, configured to determine the influencing variables that affect the stability of the target cable trench, wherein the influencing variables at least include environmental influence variables.

[0029] A probability calculation module, configured to obtain the historical measurement data corresponding to each of the influencing variables, and calculate the probability distribution data of each of the influencing variables and the response correlation coefficients between each of the influencing variables according to the historical measurement data.

[0030] A model optimization module, configured to obtain real-time measurement data corresponding to influence variables of the target cable trench, construct a three-dimensional simulation model of the target cable trench according to the real-time measurement data, quantitatively adjust the real-time measurement data corresponding to each influence variable of the three-dimensional simulation model according to each response correlation coefficient, obtain response difference data of the three-dimensional simulation model for each influence variable, and perform optimization adjustment on the three-dimensional simulation model based on the response difference data.

[0031] An index calculation module, configured to simulate and generate a number of cable trench working condition events by using the Monte Carlo method, apply each cable trench working condition event to the three-dimensional simulation model, and generate a stability index set based on the feedback of the three-dimensional simulation model.

[0032] A state evaluation module, configured to evaluate the state stability of the cable trench by using influence variables corresponding to the stability index set during the actual cable trench monitoring process, and obtain a cable trench stability evaluation result.

[0033] Another embodiment of the present invention provides a computer device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, the cable trench stability evaluation method as described above is implemented.

[0034] Another embodiment of the present invention provides a computer-readable storage medium storing a computer program. When the computer program is executed by a device where the computer-readable storage medium is located, the cable trench stability evaluation method as described above is implemented.

[0035] Compared with the prior art, the beneficial effects of the embodiments of the present invention are at least one of the following: (1) By introducing the Monte Carlo algorithm and combining probability analysis and stochastic simulation techniques, the randomness and uncertainty of the factors affecting the stability of the cable trench are comprehensively considered, avoiding the deviation of the evaluation result caused by overly simplified assumptions, and significantly improving the accuracy and reliability of the cable trench stability evaluation.

[0036] (2) Through a large number of stochastic simulation calculations, the probability distribution of the cable trench stability index is obtained, and based on this, the instability probability is quantitatively evaluated and the risk level is divided, which can provide more intuitive risk information for engineering personnel and help engineering personnel make more scientific and reasonable decisions during the design, construction, and management processes of the cable trench. Description of the Drawings

[0037] Figure 1The flowchart of the steps of the cable trench stability evaluation method provided by the embodiment of the present invention; Figure 2 The structural block diagram of the cable trench stability evaluation device provided by the embodiment of the present invention; Figure 3 The structural diagram of the computer device provided by the embodiment of the present invention. Detailed implementation manners

[0038] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. The purpose of providing these embodiments is to make the disclosure of the present invention more thorough and comprehensive. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without making creative efforts shall fall within the protection scope of the present invention.

[0039] In the description of the present application, the terms "first", "second", "third", etc. are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, features defined with "first", "second", "third", etc. may explicitly or implicitly include one or more of such features. In the description of the present application, unless otherwise stated, the meaning of "a plurality" is two or more.

[0040] In the description of the present application, it should be noted that unless otherwise clearly defined and limited, the terms "installed", "connected", "connected" should be understood in a broad sense. For example, it may be a fixed connection, a detachable connection, or an integral connection; it may be a mechanical connection or an electrical connection; it may be directly connected or indirectly connected through an intermediate medium, and it may be the communication inside two components. The terms "vertical", "horizontal", "left", "right", "up", "down" and similar expressions used herein are only for the purpose of illustration and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus cannot be understood as a limitation of the present invention. The term "and / or" used herein includes any and all combinations of one or more of the related listed items. For those of ordinary skill in the art, the specific meanings of the above terms in the present application can be understood according to specific circumstances.

[0041] In the description of the present application, it should be noted that unless otherwise defined, all technical and scientific terms used in the present invention have the same meaning as those commonly understood by those skilled in the technical field to which the present invention belongs. The terms used in the specification of the present invention are only for the purpose of describing specific embodiments, and are not intended to limit the present invention. For those of ordinary skill in the art, the specific meanings of the above terms in the present application can be understood according to specific circumstances.

[0042] An embodiment of the present invention provides a method for evaluating the stability of a cable trench. Specifically, please refer to Figure 1 , Figure 1 which is shown as the step flow chart of the method for evaluating the stability of a cable trench in one of the embodiments of the present invention, including steps S11 to S15: Step S11: Determine the influencing variables that affect the stability of the target cable trench.

[0043] Among them, the influencing variables include environmental influencing variables and cable operation influencing variables. The stability of the cable trench is affected by a variety of factors, mainly including environmental factors and cable operation factors. Identifying these influencing variables is the basis for conducting stability evaluation.

[0044] The environmental influencing variables include at least one of trench size, soil physical properties, groundwater level, load, support parameters, and adjacent buildings; The cable operation influencing variables include at least one of cable operation temperature, degree of insulation layer aging, and vibration frequency of the cable.

[0045] By identifying the key influencing variables, the types of key data that affect the stability of the cable trench can be collected in a targeted manner, improving the accuracy and efficiency of the evaluation.

[0046] Step S12: Obtain the historical measurement data corresponding to each influencing variable, and calculate the probability distribution data of each influencing variable and the response correlation coefficient between the influencing variables according to the historical measurement data.

[0047] Historical data reflects the state change law of the cable trench during long-term operation and is an important basis for evaluating its stability. By analyzing historical data, the statistical characteristics of each influencing variable and their mutual relationship can be understood. To obtain the historical measurement data of each influencing variable, specifically, in this embodiment, the first historical data of each influencing variable is obtained according to the historical exploration report and construction records.

[0048] Sensors may have problems such as drift, aging, or accuracy degradation during long-term operation, resulting in inaccurate measurement data. Data calibration can correct these deviations. In this embodiment, the first historical data is calibrated according to the sensor type corresponding to each first historical data to obtain the second historical data, ensuring its consistency with the actual physical quantity through the calibrated data.

[0049] During actual operation, data may be missing due to reasons such as equipment failures and data transmission interruptions. Missing value imputation can fill these gaps to ensure data integrity. Therefore, linear interpolation can be used to perform missing value imputation on the second historical data to fill the data gaps and obtain the third historical data.

[0050] In addition, the actual measurement data may contain random noise or short-term fluctuations, which may obscure the true trend of the data and affect subsequent analysis. It is necessary to use the moving average method to suppress the fluctuations in the third historical data, smooth the data, and reduce the impact of short-term fluctuations, thereby obtaining the historical measurement data.

[0051] Through data calibration, imputation, and fluctuation suppression, ensure the accuracy and integrity of the data, and reduce the evaluation bias caused by data quality problems.

[0052] Use the maximum likelihood estimation method to fit the probability distribution of the historical measurement data, quantify the uncertainty of each influencing variable, and obtain the probability distribution data of each influencing variable.

[0053] In addition to the fact that each influencing variable will affect the state of the cable trench, there may also be interdependent relationships between the influencing variables, and these relationships have an important impact on the stability of the cable trench. Use the correlation analysis method to calculate the response relationship between the historical measurement data to obtain the response correlation coefficients between the influencing variables and quantify the dependence relationship between the variables.

[0054] The specific process of obtaining the response correlation coefficients in this embodiment is as follows: Construct a measurement data matrix composed of the historical measurement data.

[0055] Calculate the Pearson correlation coefficient of each historical measurement data according to the measurement data matrix as the response correlation coefficient.

[0056] Step S13: Obtain the real-time measurement data corresponding to the influencing variables of the target cable trench. According to the real-time measurement data, combined with information such as the geometric structure and material properties of the cable trench, construct a three-dimensional simulation model of the target cable trench to simulate the response of the cable trench under different working conditions and provide support for stability evaluation.

[0057] There are interdependent relationships between the influencing variables, and this relationship will affect the accuracy and reliability of the model. Through quantitative adjustment, the bias in the model can be corrected. Considering the interaction between the influencing variables, adjust the values of the variables in the model to make it closer to the actual situation.

[0058] Quantitatively adjust the real-time measurement data corresponding to each influencing variable of the three-dimensional simulation model according to each response correlation coefficient to obtain the response difference data of the three-dimensional simulation model for each influencing variable. The response difference data reflects the deviation between the adjusted model and the actual situation.

[0059] Based on each response difference data, optimize and adjust the three-dimensional simulation model to improve the accuracy of the model and ensure that the model can truly reflect the actual operating state of the cable trench.

[0060] Among them, the process of quantitatively adjusting each influencing variable of the three-dimensional simulation model according to each response correlation coefficient to obtain the response difference data of the three-dimensional simulation model for each influencing variable is as follows: The dependence relationship between variables determines the order of adjustment. A reasonable adjustment order can reduce the accumulation of errors and improve the adjustment efficiency. According to the dependence relationship between each influencing variable and the magnitude of the response correlation coefficient, determine the variable adjustment order, and it can be determined which variables have a greater impact on the model, and these key variables are adjusted first.

[0061] In order to gradually optimize and adjust the model and ensure the stability and accuracy of the adjustment process, perform step-by-step quantitative adjustment on each influencing variable according to the variable adjustment order. The purpose of step-by-step adjustment is to slightly increase or decrease the value of the data corresponding to a single influencing variable each time, avoiding affecting the accuracy of obtaining the response difference data of the model due to too large an adjustment value. The adjustment value is: Among them, is the single adjustment value of the influencing variable , is the response correlation coefficient between the influencing variable and another influencing variable , is the number of adjustment levels.

[0062] Calculate according to the response difference value of the three-dimensional simulation model after quantitatively adjusting each influencing variable to obtain the response difference data of the three-dimensional simulation model for each influencing variable.

[0063] Step S14: Use the Monte Carlo method to simulate and generate several cable trench working condition events, apply each cable trench working condition event to the three-dimensional simulation model, and generate a stability index set based on the feedback of the three-dimensional simulation model.

[0064] The Monte Carlo method is a numerical calculation method based on random sampling, which is suitable for dealing with uncertainty problems in complex systems. The stability of the cable trench is affected by various factors, and these factors have randomness and uncertainty. Therefore, it is necessary to generate various possible working condition events through the Monte Carlo method to comprehensively evaluate its stability.

[0065] According to the probability distribution data of various influencing variables (such as groundwater level, cable temperature, etc.), a large number of possible working condition event samples are randomly generated. These working condition events cover various possible operating conditions and can reflect the behavior of the cable trench under different environments and operating states.

[0066] Step S15: During the actual monitoring of the cable trench, use the influencing variables corresponding to the stability index set to evaluate the state stability of the cable trench, and obtain the stability evaluation result of the cable trench.

[0067] The stability of the cable trench is affected by various factors, including environmental changes, cable operating states, etc. By evaluating its state stability through stability indexes, the safety of the cable trench can be quantified. Use the stability indexes (such as displacement, stress, strain, etc.) generated from the three-dimensional simulation model to evaluate the cable trench in actual operation and determine whether it is in a safe state.

[0068] Generate a risk level evaluation report according to the evaluation result, visually display the stability state of the cable trench, and provide decision-making support for operation and maintenance personnel; the risk level evaluation report at least includes the evaluation result of the instability risk of the cable trench, the visualized probability distribution map, and the cumulative probability curve.

[0069] The evaluation result of the instability risk can clarify the instability risk level of the cable trench in the current state, help operation and maintenance personnel judge whether measures need to be taken, and the visualized probability distribution map and cumulative probability curve display the probability distribution and cumulative probability of the stability indexes through visualization tools, which is convenient to understand the probability of the cable trench at different risk levels.

[0070] According to the risk level evaluation report, identify potential risk patterns through big data analysis, obtain corresponding risk control solutions, and improve the stability of the cable trench through specific control measures, such as strengthening monitoring, reinforcing the structure, or adjusting operating parameters.

[0071] The cable trench stability evaluation method of the present invention introduces the Monte Carlo algorithm, combines probability analysis and stochastic simulation techniques, comprehensively considers the randomness and uncertainty of the influencing factors of the cable trench stability, avoids the deviation of the evaluation result caused by overly simplified assumption conditions, and significantly improves the accuracy and reliability of the cable trench stability evaluation. Through a large number of stochastic simulation calculations, the probability distribution of the cable trench stability indexes is obtained, and based on this, the instability probability is quantitatively evaluated and the risk levels are divided, which can provide more intuitive risk information for engineering personnel and help engineering personnel make more scientific and reasonable decisions in the design, construction, and management processes of the cable trench.

[0072] The embodiment of the present invention also provides a cable trench stability evaluation device for executing the cable trench stability evaluation method as described above.Figure 2 The structural block diagram of the cable trench stability evaluation device according to an embodiment of the present invention, the device includes: A variable determination module 21, configured to determine influence variables that affect the stability of a target cable trench, where the influence variables at least include environmental influence variables.

[0073] A probability calculation module 22, configured to obtain historical measurement data corresponding to each of the influence variables, and calculate probability distribution data for each of the influence variables and response correlation coefficients between the influence variables according to the historical measurement data.

[0074] A model optimization module 23, configured to obtain real-time measurement data corresponding to the influence variables of the target cable trench, construct a three-dimensional simulation model of the target cable trench according to the real-time measurement data, quantitatively adjust the real-time measurement data corresponding to the influence variables of the three-dimensional simulation model according to the response correlation coefficients, obtain response difference data of the three-dimensional simulation model for each of the influence variables, and optimize and adjust the three-dimensional simulation model based on the response difference data.

[0075] An index calculation module 24, configured to simulate and generate a plurality of cable trench condition events by using the Monte Carlo method, apply each of the cable trench condition events to the three-dimensional simulation model, and generate a stability index set based on the feedback of the three-dimensional simulation model.

[0076] A state evaluation module 25, configured to evaluate the state stability of the cable trench by using the influence variables corresponding to the stability index set during the actual monitoring of the cable trench, and obtain a cable trench stability evaluation result.

[0077] The technical features and technical effects of the device proposed in the embodiment of the present invention are the same as those of the method proposed in the embodiment of the present invention, and will not be elaborated here. Each module in the above device can be implemented in whole or in part by software, hardware, and their combination. Each of the above modules can be embedded in a processor in a computer device in a hardware form or independent of the processor, or stored in a memory in the computer device in a software form, so as to facilitate the processor to call and execute the operations corresponding to the above modules.

[0078] The embodiment of the present invention further provides a computer-readable storage medium, the computer-readable storage medium includes a stored computer program; wherein, the computer program controls the device where the computer-readable storage medium is located to execute the cable trench stability evaluation method as described above when running.

[0079] The embodiment of the present invention further provides a computer device, Figure 3A structural block diagram of a preferred embodiment of a computer device provided by the present invention. The computer device includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, the cable trench stability evaluation method described above is implemented.

[0080] Preferably, the computer program can be divided into one or more modules / units (such as computer program 1, computer program 2,...). The one or more modules / units are stored in the memory and executed by the processor to complete the present invention. The one or more modules / units can be a series of computer program instruction segments capable of performing specific functions, and these instruction segments are used to describe the execution process of the computer program in the computer device.

[0081] The processor can be a Central Processing Unit (CPU), or other general-purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field-Programmable Gate Arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor, or the processor can also be any conventional processor. The processor is the control center of the computer device, connecting various parts of the computer device through various interfaces and lines.

[0082] The memory mainly includes a program storage area and a data storage area. Among them, the program storage area can store an operating system, application programs required for at least one function, etc., and the data storage area can store relevant data, etc. In addition, the memory can be a high-speed random access memory, or a non-volatile memory, such as a plug-in hard disk, a SmartMedia Card (SMC), a Secure Digital (SD) card, a Flash Card, etc., or the memory can also be other volatile solid-state storage devices.

[0083] It should be noted that the above computer device may include, but is not limited to, a processor and a memory. Those skilled in the art can understand that Figure 3 The structural block diagram is only an example of the computer device and does not constitute a limitation on the computer device. It may include more or fewer components than those shown, or combine some components, or have different components.

[0084] In summary, compared with the prior art, the cable trench stability evaluation method, device, equipment and storage medium provided by the embodiments of the present invention have at least one of the following beneficial effects: By introducing the Monte Carlo algorithm and combining probability analysis and stochastic simulation techniques, the cable trench stability evaluation method of the present invention comprehensively considers the randomness and uncertainty of the factors affecting the stability of the cable trench, avoids the deviation of the evaluation results caused by overly simplified assumptions, and significantly improves the accuracy and reliability of the cable trench stability evaluation.

[0085] Through a large number of stochastic simulation calculations, the probability distribution of the cable trench stability index is obtained, and based on this, the instability probability is quantitatively evaluated and the risk level is divided, which can provide more intuitive risk information for engineering personnel and help engineering personnel make more scientific and reasonable decisions in the design, construction and management processes of the cable trench.

[0086] The above-described embodiments merely represent several implementation manners of the present invention. The description is relatively specific and detailed, but it should not be construed as a limitation on the scope of the invention patent of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present invention, several modifications and improvements can still be made, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the invention patent of the present invention shall be subject to the appended claims.

Claims

1. A cable trench stability assessment method, characterized in that: include: Determining influencing variables that affect the stability of the target cable trench, wherein the influencing variables at least include environmental influencing variables; Acquire historical measurement data corresponding to each of the influencing variables, and calculate probability distribution data of each of the influencing variables and response correlation coefficients between the influencing variables according to the historical measurement data; Acquire real-time measurement data corresponding to the influencing variables of the target cable trench, construct a three-dimensional simulation model of the target cable trench according to the real-time measurement data, quantitatively adjust the real-time measurement data corresponding to each of the influencing variables of the three-dimensional simulation model according to each of the response correlation coefficients, obtain response difference data of the three-dimensional simulation model to each of the influencing variables, and optimize and adjust the three-dimensional simulation model based on each of the response difference data; A Monte Carlo method is used to simulate and generate a plurality of cable trench working condition events, each of the cable trench working condition events is applied to the three-dimensional simulation model, and a stability index set is generated based on feedback from the three-dimensional simulation model; In the actual cable trench monitoring process, the influencing variables corresponding to the stability index set are used to evaluate the state stability of the cable trench to obtain the cable trench stability evaluation result.

2. The cable trench stability assessment method according to claim 1, characterized in that: The influencing variables also include cable operation influencing variables; The environmental influencing variables include at least one of trench size, soil physical properties, groundwater level, load, support parameters and adjacent buildings; The cable operation influencing variables include at least one of the cable operation temperature, the aging degree of the insulation layer and the vibration frequency of the cable.

3. The cable trench stability assessment method according to claim 1, characterized in that: The acquiring of historical measurement data of each of the influencing variables, and calculating the probability distribution data of each of the influencing variables and the response correlation coefficient between the influencing variables according to the historical measurement data, includes: Acquiring historical measurement data of each of the influencing variables; Using the maximum likelihood estimation method to perform probability distribution fitting on the historical measurement data to obtain probability distribution data of each of the influencing variables; The response relationship between each of the historical measurement data is calculated using a correlation analysis method to obtain a response correlation coefficient between each of the influencing variables.

4. The cable trench stability assessment method according to claim 3, characterized in that: The obtaining of the historical measurement data of each of the influencing variables comprises: First historical data of each of the influencing variables according to historical survey reports and construction records; According to the sensor type corresponding to each of the first historical data, data calibration is performed on the first historical data to obtain second historical data; Using a linear interpolation method to interpolate missing values ​​of the second historical data to obtain third historical data; The third historical data is subjected to fluctuation suppression using a moving average method to obtain historical measurement data.

5. The cable trench stability assessment method according to claim 3, characterized in that: The method of using the correlation analysis method to calculate the response relationship between the historical measurement data to obtain the response correlation coefficient between the influencing variables includes: Constructing a measurement data matrix composed of each of the historical measurement data; The Pearson correlation coefficient of each of the historical measurement data is calculated according to the measurement data matrix as a response correlation coefficient.

6. The cable trench stability assessment method according to claim 1, characterized in that: The quantitatively adjusting each of the influencing variables of the three-dimensional simulation model according to each of the response correlation coefficients to obtain response difference data of the three-dimensional simulation model to each of the influencing variables includes: Determining the variable adjustment sequence according to the dependency relationship between the influencing variables and the magnitude of the response correlation coefficient; According to the variable adjustment sequence, each of the influencing variables is quantitatively adjusted step by step, and the adjustment value is: in, Influencing variables A single adjustment value of Influencing variables With another influencing variable The response correlation coefficient between To adjust the level; The response difference data of the three-dimensional simulation model to each of the influencing variables is obtained by performing calculations based on the response difference of the three-dimensional simulation model after quantitatively adjusting each of the influencing variables.

7. The cable trench stability assessment method according to claim 1, characterized in that: The stability index is used to evaluate the state stability of the cable trench to obtain the cable trench stability evaluation result, including: The stability index is used to evaluate the state stability of the cable trench during actual operation, and a risk level assessment report is generated according to the assessment result; the risk level assessment report at least includes the cable trench instability risk assessment result, a visualized probability distribution map and a cumulative probability curve; According to the risk level assessment report, a corresponding risk control plan is obtained through big data analysis.

8. A cable trench stability assessment device, characterized in that: include: A variable determination module, used to determine influencing variables that affect the stability of the target cable trench, wherein the influencing variables at least include environmental influencing variables; A probability calculation module, used to obtain the historical measurement data corresponding to each of the influencing variables, and calculate the probability distribution data of each of the influencing variables and the response correlation coefficient between the influencing variables according to the historical measurement data; A model optimization module is used to obtain real-time measurement data corresponding to the influencing variables of the target cable trench, construct a three-dimensional simulation model of the target cable trench according to the real-time measurement data, quantitatively adjust the real-time measurement data corresponding to each of the influencing variables of the three-dimensional simulation model according to each of the response correlation coefficients, obtain response difference data of the three-dimensional simulation model to each of the influencing variables, and optimize and adjust the three-dimensional simulation model based on each of the response difference data; An index calculation module, used to simulate and generate a number of cable trench working condition events by using the Monte Carlo method, apply each of the cable trench working condition events to the three-dimensional simulation model, and generate a stability index set based on feedback from the three-dimensional simulation model; The state assessment module is used to assess the state stability of the cable trench using the influencing variables corresponding to the stability indicator set in the actual cable trench monitoring process to obtain the cable trench stability assessment result.

9. A computer device, characterized in that: The method comprises a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, the method for evaluating the stability of a cable trench as claimed in any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, wherein when the device where the computer-readable storage medium is located executes the computer program, the cable trench stability assessment method according to any one of claims 1 to 7 is implemented.

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