A tunnel cable ground loop current intelligent detection analysis system and method

Abstract

The application discloses a tunnel cable grounding ring current intelligent detection and analysis system and method, relates to the technical field of intelligent detection, and comprises the following steps: collecting the current, the sheath induced voltage, the equipment temperature and the tunnel humidity of the cable metal sheath grounding ring current by using a sensor; analyzing and processing the collected data to obtain comprehensive detection parameters; setting a threshold value, comparing and analyzing the obtained detection data, and judging whether an abnormal situation occurs; and warning and abnormally prompting the detected abnormal situation according to the generated instruction; the application can judge the specific type of the abnormal situation according to the analysis and detection of different parameters, trigger the safety detection mode when only the safety evaluation index is detected to be abnormal, analyze whether the numerical calculation process is abnormal, exclude the numerical abnormal situation caused by the calculation abnormality, reduce the detection failure of the equipment abnormal situation, and solve the problem of high false alarm rate in the detection process.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent detection, and particularly relates to a tunnel cable grounding loop intelligent detection and analysis system and method. BACKGROUND

[0002] Tunnel cable is a key component of power transmission and rail transit power supply system, and full operation of the tunnel cable can affect power supply reliability and equipment life. The tunnel cable grounding loop system is a system for monitoring the grounding current of the cable metal sheath such as aluminum sheath or copper shield layer when power cable is laid in the tunnel. The core function of the tunnel cable grounding loop system is to detect the insulation state of the cable, prevent sheath failure, and ensure safe operation of the cable. The cable grounding loop is an important indicator for reflecting the insulation state of the cable and the health of the grounding system. The occurrence of abnormal loop current may be caused by factors such as cable sheath damage, poor grounding, insulation deterioration or external interference. If not detected and handled in time, it may cause cable overheating, insulation breakdown and even fire accidents. The main technical means for detecting the tunnel cable grounding loop by traditional methods are manual inspection and periodic detection, fixed online monitoring system and detection based on differential current method. In recent years, with the development of artificial intelligence, intelligent means have been gradually introduced in the tunnel cable grounding loop. However, the current detection technology still has the shortcomings of single detection data and insufficient data fusion. Single detection data or insufficient data fusion degree will cause high false alarm rate in the detection process. SUMMARY

[0003] The present application aims to provide a tunnel cable grounding loop intelligent detection and analysis system and method to solve the problems in the prior art.

[0004] To achieve the above-mentioned purpose, the present application provides the following technical scheme: a tunnel cable grounding loop intelligent detection and analysis method, the method comprising the following steps:

[0005] S1, collecting the current, sheath induced voltage, equipment temperature and tunnel humidity of the cable metal sheath grounding loop by using a sensor;

[0006] S2, analyzing and processing the collected data, and analyzing and fusing the collected monitoring data to obtain comprehensive detection parameters;

[0007] S3, setting a threshold value, and comparing and analyzing the obtained detection data to determine whether an abnormal situation occurs;

[0008] S4, warning and abnormally prompting the detected abnormal situation according to the generated instruction.

[0009] Further, in step S1: the current data I in the cable metal sheath grounding loop current is collected in real time by using high-precision current sensors such as Rogowski coils or Hall effect sensors; the monitoring sheath induced voltage data U is collected in real time by using a voltage sensor; the temperature data T1 at the cable joint and the temperature data T2 at the sheath grounding are collected in real time by using a temperature sensor, which can detect abnormal conditions of local overheating; the humidity S in the tunnel is collected in real time by using a humidity sensor.

[0010] Further, in step S2: the collected data is analyzed and processed, and the collected current and voltage data is weighted and fused to form a loop current safety parameter W, which is calculated according to the following formula:

[0011] ;

[0012] Wherein, W represents the loop current safety parameter, I0 represents the standard value of the current data in the cable metal sheath grounding loop current; U0 represents the standard value of the monitoring sheath induced voltage data; f1 represents the influence weight of current on the loop current safety parameter, and f2 represents the influence weight of induced voltage on the loop current safety parameter.

[0013] The collected temperature and humidity data is analyzed and processed, and the collected temperature and humidity data is weighted and fused to form a device safety parameter M, which is calculated according to the following formula:

[0014] ;

[0015] Wherein, M represents the device safety parameter; T 10 represents the standard value of the temperature data at the cable joint; T 20 represents the standard value of the temperature data at the sheath grounding; S0 represents the standard value of the humidity data in the tunnel; f3 represents the influence weight of the temperature data at the cable joint on the device safety parameter; f4 represents the influence weight of the temperature data at the sheath grounding on the device safety parameter; and f5 represents the influence weight of the humidity data in the tunnel on the device safety parameter.

[0016] The loop current safety parameter and the device safety parameter obtained by analysis and calculation are fused to form a safety evaluation index Q, which is calculated by the following formula:

[0017] ;

[0018] Wherein, Q represents the safety evaluation index; p1 represents the influence weight of the loop current safety parameter on the safety evaluation index; and p2 represents the influence weight of the device safety parameter on the safety evaluation index.

[0019] Further, a threshold value Q0 of the safety evaluation index is set to monitor the safety evaluation index in real time; the detection condition is judged as follows:

[0020] If Q≤Q0, it is judged that the safety evaluation index is in the normal range, and no warning instruction is generated;

[0021] If Q>Q0, it is judged that the safety evaluation index is abnormally high, and the safety detection mode is triggered to detect the loop current safety and equipment safety in the tunnel cable;

[0022] After triggering the safety detection mode, the loop current safety parameter and the equipment safety parameter are detected respectively, and the loop current safety parameter threshold W0 and the equipment safety parameter threshold M0 are set. The calculated loop current safety parameter and equipment safety parameter are compared and analyzed with the set threshold, and it is analyzed whether there is an abnormal situation. The comparison and analysis results are as follows:

[0023] If W≤W0 and M≤M0, it is judged that the loop current safety parameter and the equipment safety parameter are normal, the detection result is fed back, the safety evaluation index is re-detected, and the detection time is set to△t1. The safety evaluation index, the loop current safety parameter and the equipment safety parameter are continuously detected, and the detection results within the time length△t1 are analyzed and judged. The analysis results are as follows:

[0024] Within the detection time length△t1, if the detection result of Q returns to the normal value, and the detection results of W and M are still W≤W0 and M≤M0, all three values are normal, it is judged that there is no abnormal situation, and the Q abnormality is a calculation error. No abnormal warning is given;

[0025] Within the detection time length△t1, if the detection result of Q is always abnormal, but the detection results of W and M are W≤W0 and M≤M0, it is judged that the Q calculation process is abnormal, and the instruction a1 is generated to control the abnormal prompt;

[0026] Within the detection time length△t1, the detection result of Q is always abnormal, and W>W0 and M≤M0 are detected. It is judged that the loop current safety parameter is abnormal, and the instruction a2 is generated to control the loop current abnormality warning;

[0027] Within the detection time length△t1, the detection result of Q is always abnormal, and W≤W0 and M>M0 are detected. It is judged that the equipment safety parameter is abnormal, and the instruction a3 is generated to control the equipment fault warning;

[0028] Within the detection time length△t1, the detection result of Q is always abnormal, and W>W0 and M>M0 are detected. It is judged that the loop current safety parameter and the equipment safety parameter are both abnormal, and the instruction a4 is generated to control the loop current abnormality and equipment fault warning;

[0029] If W>W0 and M≤M0, it is directly judged that the loop safety parameter is abnormal, and instruction a2 is directly generated to control the loop abnormality warning;

[0030] If W≤W0 and M>M0, it is directly judged that the device safety parameter is abnormal, and instruction a3 is directly generated to perform device fault warning;

[0031] If W>W0 and M>M0, it is directly judged that both the loop safety parameter and the device safety parameter are abnormal, and instruction a4 is directly generated to perform loop abnormality and device fault warning.

[0032] Further, in step S4: according to the generated instruction, the abnormal situation in the tunnel cable grounding loop current is warned:

[0033] If instruction a1 is generated, a blue light warning is issued, and a safety evaluation index calculation abnormality prompt is performed in the visualization module;

[0034] If instruction a2 is generated, a yellow light warning is issued, and a loop safety parameter abnormality prompt is performed in the visualization module;

[0035] If instruction a3 is generated, an orange light warning is issued, and a device safety parameter abnormality prompt is performed in the visualization module;

[0036] If instruction a4 is generated, a red light warning is issued, and a prompt that both the loop safety parameter and the device safety parameter are abnormal is performed in the visualization module.

[0037] A tunnel cable grounding loop current intelligent detection and analysis system, characterized in that: the system comprises a tunnel data acquisition module, a data processing module, an analysis and judgment module, and an abnormality warning module;

[0038] The tunnel data acquisition module is used to collect the current of the cable metal sheath grounding loop current, the sheath induced voltage, the device temperature, and the tunnel humidity through a sensor;

[0039] The data processing module is used to analyze and process the collected data, and analyze and fuse the collected monitoring data to obtain comprehensive detection parameters;

[0040] The analysis and judgment module is used to set a threshold and compare and analyze the obtained detection data to determine whether an abnormal situation occurs;

[0041] The abnormality warning module is used to warn and abnormally prompt the detected abnormal situation according to the generated instruction.

[0042] Further, the tunnel data acquisition module comprises a loop current data acquisition unit and a device data acquisition unit; the loop current data acquisition unit acquires current data in the cable metal sheath grounding loop current in real time through a high-precision current sensor, and acquires sheath induction voltage data in real time through a voltage sensor; the device data acquisition unit acquires temperature data at the cable joint and temperature data at the sheath grounding in real time through a temperature sensor, and acquires humidity in the tunnel in real time through a humidity sensor.

[0043] Further, the data processing module comprises a loop current safety parameter analysis unit, a device safety parameter analysis unit and a safety evaluation index analysis unit; the loop current safety parameter analysis unit is used for acquiring loop current safety parameters according to the acquired current and voltage data; the device safety parameter analysis unit is used for acquiring device safety parameters according to the acquired temperature and humidity data; and the safety evaluation index analysis unit is used for acquiring a safety evaluation index by weighted fusion of the loop current safety parameters and the device safety parameters.

[0044] Further, the analysis and judgment module comprises a threshold setting unit and a comparison analysis unit; the threshold setting unit is used for setting loop current safety parameter thresholds, device safety parameter thresholds and safety evaluation index thresholds; and the comparison analysis unit compares the values obtained through analysis and processing with the set thresholds to analyze and judge whether an abnormal situation exists.

[0045] Further, the abnormality early warning module is used for early warning the detected abnormal situation according to the generated instructions and performing abnormal type prompting on the visual device.

[0046] Compared with the prior art, the present application has the following beneficial effects:

[0047] The present application obtains three safety detection parameters of loop current safety parameters, device safety parameters and safety evaluation indexes through data analysis, and analyzes the real-time acquired safety detection parameters by setting thresholds to judge whether an abnormal situation exists; the three safety detection parameters introduced can achieve intelligent detection and classified early warning of the abnormality in the tunnel cable loop current, and the abnormal situation is judged through the detection process, first, the safety evaluation index is analyzed, then the loop current safety parameters and the device safety parameters are analyzed and judged when the abnormal situation is detected, the specific type of the abnormality can be judged according to the analysis and detection of different parameters, and the safety detection mode is triggered when only the safety evaluation index is detected to be abnormal, whether the numerical calculation process is abnormal is analyzed, the numerical abnormality caused by calculation abnormality can be excluded, the equipment abnormality detection failure can be reduced, and the problem of high false alarm rate in the detection process is solved. BRIEF DESCRIPTION OF DRAWINGS

[0048] Fig. 1A flowchart of a tunnel cable grounding loop current intelligent detection and analysis method of the present application is shown in the figure.

[0049] Fig. 2 A structural diagram of a tunnel cable grounding loop current intelligent detection and analysis system of the present application is shown in the figure. DETAILED DESCRIPTION

[0050] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work fall within the scope of protection of the present application.

[0051] As shown in the figure, Figs. 1-2 The present application provides a technical solution, a tunnel cable grounding loop current intelligent detection and analysis method, which comprises the following steps:

[0052] S1, collecting the current, sheath induced voltage, device temperature and tunnel humidity of the cable metal sheath grounding loop current by using a sensor;

[0053] S2, analyzing and processing the collected data, and analyzing and fusing the collected monitoring data to obtain comprehensive detection parameters;

[0054] S3, setting a threshold value, and comparing and analyzing the obtained detection data to determine whether an abnormal situation occurs;

[0055] S4, warning and abnormally prompting the detected abnormal situation according to the generated instructions.

[0056] In step S1: a high-precision current sensor is used to collect the current data I in the cable metal sheath grounding loop current in real time; a voltage sensor is used to collect the monitoring sheath induced voltage data U in real time; a temperature sensor is used to collect the temperature data T1 at the cable joint and the temperature data T2 at the sheath grounding in real time; and a humidity sensor is used to collect the humidity S in the tunnel in real time.

[0057] In step S2: the collected data is analyzed and processed, and the collected current and voltage data is weighted and fused to form a loop current safety parameter W. The loop current safety parameter is calculated according to the following formula:

[0058] ;

[0059] Wherein, W represents the loop current safety parameter, I0 represents the standard value of the current data in the cable metal sheath grounding loop current; U0 represents the standard value of the monitoring sheath induced voltage data; f1 represents the influence weight of the current on the loop current safety parameter, and f2 represents the influence weight of the induced voltage on the loop current safety parameter.

[0060] The collected temperature and humidity data are analyzed and processed, and the collected temperature and humidity data are weighted and fused to form a device safety parameter M. The device safety parameter is calculated according to the following formula:

[0061] ;

[0062] Wherein, M represents the device safety parameter; T 10 represents the standard value of the temperature data at the cable joint; T 20 represents the standard value of the temperature data at the sheath grounding; S0 represents the standard value of the humidity data in the tunnel; f3 represents the influence weight of the temperature data at the cable joint on the device safety parameter; f4 represents the influence weight of the temperature data at the sheath grounding on the device safety parameter; f5 represents the influence weight of the humidity data in the tunnel on the device safety parameter;

[0063] The circulating current safety parameter and the device safety parameter obtained by analysis and calculation are fused to form a safety evaluation index Q. The safety evaluation index is calculated by the following formula:

[0064] ;

[0065] Wherein, Q represents the safety evaluation index; p1 represents the influence weight of the circulating current safety parameter on the safety evaluation index; p2 represents the influence weight of the device safety parameter on the safety evaluation index.

[0066] A threshold value Q0 of the safety evaluation index is set to monitor the safety evaluation index in real time. The detection condition is as follows:

[0067] If Q≤Q0, it is judged that the safety evaluation index is within the normal range, and no warning instruction is generated;

[0068] If Q>Q0, it is judged that the safety evaluation index is abnormally high, and a safety detection mode is triggered to detect the circulating current safety and the device safety in the tunnel cable;

[0069] After triggering the safety detection mode, the circulating current safety parameter and the device safety parameter are detected respectively, and a circulating current safety parameter threshold value W0 and a device safety parameter threshold value M0 are set. The calculated circulating current safety parameter and device safety parameter are compared and analyzed with the set threshold value to analyze whether there is an abnormal situation. The comparison and analysis result is as follows:

[0070] If W≤W0 and M≤M0, it is judged that the circulating current safety parameter and the device safety parameter are normal, the detection result is fed back; and the safety evaluation index is re-detected, and the detection time is set to a detection time of△t1. The safety evaluation index, the circulating current safety parameter and the device safety parameter are continuously detected, and the detection results within the time length of△t1 are analyzed and judged. The analysis result is as follows:

[0071] If the detection result of Q returns to the normal value and the detection results of W and M are still W≤W0 and M≤M0 within the detection duration At1, all the three values are normal, it is determined that there is no abnormal situation, the abnormal situation of Q is calculation error or omission, and no abnormal warning is performed.

[0072] If the detection result of Q is always abnormal within the detection duration At1, but the detection results of W and M are W≤W0 and M≤M0, it is determined that the calculation process of Q is abnormal, and the instruction a1 is generated to control the generation of an abnormal prompt.

[0073] If the detection result of Q is always abnormal within the detection duration At1, and W>W0 and M≤M0 are detected, it is determined that the loop safety parameter is abnormal, and the instruction a2 is generated to control the loop abnormality warning.

[0074] If the detection result of Q is always abnormal within the detection duration At1, and W≤W0 and M>M0 are detected, it is determined that the device safety parameter is abnormal, and the instruction a3 is generated to perform the device fault warning.

[0075] If the detection result of Q is always abnormal within the detection duration At1, and W>W0 and M>M0 are detected, it is determined that the loop safety parameter and the device safety parameter are both abnormal, and the instruction a4 is generated to perform the loop abnormality and device fault warning.

[0076] If W>W0 and M≤M0, it is directly determined that the loop safety parameter is abnormal, and the instruction a2 is directly generated to control the loop abnormality warning.

[0077] If W≤W0 and M>M0, it is directly determined that the device safety parameter is abnormal, and the instruction a3 is directly generated to perform the device fault warning.

[0078] If W>W0 and M>M0, it is directly determined that the loop safety parameter and the device safety parameter are both abnormal, and the instruction a4 is directly generated to perform the loop abnormality and device fault warning.

[0079] In step S4, the abnormal situation in the tunnel cable grounding loop current is warned according to the generated instruction.

[0080] If the instruction a1 is generated, a blue light warning is issued, and an abnormal prompt of the safety evaluation index calculation is performed in the visualization module.

[0081] If the instruction a2 is generated, a yellow light warning is issued, and an abnormal prompt of the loop safety parameter is performed in the visualization module.

[0082] If the instruction a3 is generated, an orange light warning is issued, and a device safety parameter abnormality prompt is made in the visualization module;

[0083] If the instruction a4 is generated, a red light warning is issued, and a prompt is made in the visualization module that both the loop current safety parameter and the device safety parameter are abnormal.

[0084] A tunnel cable grounding loop current intelligent detection and analysis system, characterized in that the system comprises a tunnel data acquisition module, a data processing module, an analysis and judgment module, and an abnormality early warning module;

[0085] The tunnel data acquisition module is used to acquire the current of the cable metal sheath grounding loop current, the sheath induced voltage, the device temperature, and the tunnel humidity through sensors;

[0086] The data processing module is used to analyze and process the acquired data, and to analyze and fuse the acquired multiple monitoring data to obtain comprehensive detection parameters;

[0087] The analysis and judgment module is used to set threshold values and to compare and analyze the acquired detection data to determine whether an abnormal situation exists;

[0088] The abnormality early warning module is used to early warn and abnormally prompt the detected abnormal situation according to the generated instructions.

[0089] The tunnel data acquisition module comprises a loop current data acquisition unit and a device data acquisition unit; the loop current data acquisition unit acquires current data in the cable metal sheath grounding loop current in real time through a high-precision current sensor, and acquires sheath induced voltage data in real time through a voltage sensor; the device data acquisition unit acquires temperature data at the cable joint and temperature data at the sheath grounding in real time through a temperature sensor, and acquires the humidity in the tunnel in real time through a humidity sensor.

[0090] The data processing module comprises a loop current safety parameter analysis unit, a device safety parameter analysis unit, and a safety evaluation index analysis unit; the loop current safety parameter analysis unit is used to acquire the loop current safety parameter according to the acquired current and voltage data; the device safety parameter analysis unit is used to acquire the device safety parameter according to the acquired temperature and humidity data; and the safety evaluation index analysis unit is used to weight and fuse the loop current safety parameter and the device safety parameter to obtain a safety evaluation index.

[0091] The analysis and judgment module comprises a threshold value setting unit and a comparison and analysis unit; the threshold value setting unit is used to set the loop current safety parameter threshold value, the device safety parameter threshold value, and the safety evaluation index threshold value; and the comparison and analysis unit compares the values obtained by analysis and processing with the set threshold values to analyze and determine whether an abnormal situation exists.

[0092] The abnormality early warning module is configured to early warn the detected abnormality according to the generated instruction and to type prompt the abnormality on the visual device.

[0093] In step S1, the current data I=5A in the cable metal sheath grounding loop current is collected in real time by using a high-precision current sensor; the monitoring sheath induced voltage data U=10V is collected in real time by using a voltage sensor; the temperature data T1=35℃ at the cable joint and the temperature data T2=40℃ at the sheath grounding are collected in real time by using a temperature sensor; and the humidity S=30% in the tunnel is collected in real time by using a humidity sensor.

[0094] In step S2, the collected data is analyzed and processed, and the collected current and voltage data is weighted and fused to form the loop current safety parameter W, which is calculated according to the following formula:

[0095] ;

[0096] Wherein, W represents the loop current safety parameter, I0=10A represents the standard value of the current data in the cable metal sheath grounding loop current; U0=20V represents the standard value of the monitoring sheath induced voltage data; f1=0.6 represents the influence weight of the current on the loop current safety parameter, f2=0.4 represents the influence weight of the induced voltage on the loop current safety parameter; W=0.5;

[0097] The collected temperature and humidity data is analyzed and processed, and the collected temperature and humidity data is weighted and fused to form the equipment safety parameter M, which is calculated according to the following formula:

[0098] ;

[0099] Wherein, M represents the equipment safety parameter; T 10 =50℃ represents the standard value of the temperature data at the cable joint; T 20 =50℃ represents the standard value of the temperature data at the sheath grounding; S0=40% represents the standard value of the humidity data in the tunnel; f3=0.3 represents the influence weight of the temperature data at the cable joint on the equipment safety parameter; f4=0.3 represents the influence weight of the temperature data at the sheath grounding on the equipment safety parameter; f5=0.4 represents the influence weight of the humidity data in the tunnel on the equipment safety parameter; M=0.75;

[0100] The loop current safety parameter and the equipment safety parameter obtained by analysis and calculation are fused to form the safety evaluation index Q, which is calculated by the following formula:

[0101] ;

[0102] Wherein, Q represents the safety evaluation index; p1=0.6 represents the influence weight of the circulation safety parameter on the safety evaluation index; p2=0.4 represents the influence weight of the equipment safety parameter on the safety evaluation index; Q=0.6.

[0103] The threshold value Q0=0.84 of the safety evaluation index is set to monitor the safety evaluation index in real time; the circulation safety parameter threshold value W0=0.8 and the equipment safety parameter threshold value M0=0.9 are set; the detection condition is judged as follows:

[0104] The judgment result is Q=0.6≤Q0, the safety evaluation index is judged to be in the normal range, and no any early warning instruction is generated.

[0105] It is apparent for those skilled in the art that the present application is not limited to the details of the above exemplary embodiments, but can be implemented in other concrete forms without departing from the spirit or essential characteristics of the present application. Therefore, the embodiments should be considered in all aspects as exemplary and non-restrictive, and the scope of the present application is defined by the appended claims rather than the above description, and therefore all changes falling within the meaning and range of the equivalent elements of the claims are intended to be embraced in the present application. Any reference signs in the claims should not be considered as limiting the claims involved.

Claims

1. A method for intelligent detection and analysis of grounding circulation current in tunnel cables, characterized in that: The method includes the following steps: S1. Use sensors to collect data on the current of the grounding loop current of the cable's metal sheath, the sheath induced voltage, the equipment temperature, and the tunnel humidity; S2. Analyze and process the collected data, and analyze and fuse the collected monitoring data to obtain comprehensive detection parameters; S3. Set a threshold and compare and analyze the acquired detection data to determine if any abnormalities have occurred. S4. Provide early warnings and abnormal prompts for detected anomalies based on the generated instructions; In step S1: The current data I in the grounding circulation current of the cable's metal sheath is collected in real time using a high-precision current sensor; The voltage sensor is used to collect the induced voltage data U of the monitoring layer in real time; the temperature sensor is used to collect the temperature data T1 at the cable joint and the temperature data T2 at the sheath grounding point in real time; the humidity sensor is used to collect the humidity S in the tunnel in real time. In step S2: The collected data is analyzed and processed. The collected current and voltage data are weighted and fused to form the circulating current safety parameter W. The circulating current safety parameter is calculated according to the following formula: ； Where W represents the circulating current safety parameter, I0 represents the standard value of the current data in the grounding circulating current of the cable metal sheath; U0 represents the standard value of the induced voltage data of the monitoring layer; f1 represents the influence weight of the current on the circulating current safety parameter, and f2 represents the influence weight of the induced voltage on the circulating current safety parameter. The collected temperature and humidity data are analyzed and processed. The collected temperature and humidity data are weighted and fused to form the equipment safety parameter M. The equipment safety parameter is calculated according to the following formula: ； Where M represents the equipment safety parameter; T 10 Standard values ​​representing temperature data at cable joints; T 20 S0 represents the standard value of temperature data at the sheath grounding point; f3 represents the standard value of humidity data inside the tunnel; f4 represents the weight of the influence of temperature data at the cable joint on equipment safety parameters; f5 represents the weight of the influence of humidity data inside the tunnel on equipment safety parameters. The safety assessment index Q is formed by combining the circulating safety parameters and equipment safety parameters obtained from the analysis and calculation. The safety assessment index is calculated using the following formula: ； Where Q represents the safety assessment index; p1 represents the influence weight of the circulating safety parameters on the safety assessment index; and p2 represents the influence weight of the equipment safety parameters on the safety assessment index.

2. The intelligent detection and analysis method for grounding circulation current in tunnel cables according to claim 1, characterized in that: A threshold Q0 is set for the security assessment index, and the index is monitored in real time. The detection results are judged as follows: If Q≤Q0, the safety assessment index is considered to be within the normal range, and no warning instruction will be generated. If Q>Q0, the safety assessment index is judged to be abnormally high, and the safety detection mode is triggered to detect the circulating current safety and equipment safety in the tunnel cable; After triggering the safety detection mode, the circulating current safety parameters and equipment safety parameters are detected separately, and thresholds W0 for the circulating current safety parameters and M0 for the equipment safety parameters are set. The calculated circulating current safety parameters and equipment safety parameters are compared and analyzed with the set thresholds to analyze whether there are any abnormalities. The comparison and analysis results are as follows: If W≤W0 and M≤M0, it is determined that there are no abnormalities in the circulating safety parameters and equipment safety parameters, and the test results are then fed back. The safety assessment index was re-tested, and a testing duration of △t1 was set. Continuous testing was performed on the safety assessment index, circulating safety parameters, and equipment safety parameters. The testing results within the duration △t1 were analyzed and judged. The analysis results are as follows: If the detection result of Q returns to the normal value within the detection time △t1, and the detection results of W and M are still W≤W0 and M≤M0, and all three values ​​are normal, it is judged as no abnormality. If Q is abnormal, it is a calculation error and no abnormality warning is issued. If the detection result of Q value is always abnormal within the detection time △t1, but the detection results of W and M are W≤W0 and M≤M0, it is judged that there is an abnormality in the Q calculation process, and the instruction a1 is issued to control the generation of abnormal prompts. If the detection result of Q value is always abnormal within the detection time △t1, and W>W0 and M≤M0 are detected, it is determined that the circulation safety parameter is abnormal, and then instruction a2 is generated to control the circulation abnormality warning. If the detection result of Q value is always abnormal within the detection time △t1, and W≤W0 and M>M0 are detected, it is determined that the equipment safety parameters are abnormal, and then instruction a3 is generated to provide equipment fault warning. If the detection result of Q value is always abnormal within the detection time △t1, and W>W0 and M>M0 are detected, it is determined that both the circulating safety parameter and the equipment safety parameter are abnormal. Then, instruction a4 is generated to provide early warning of circulating abnormality and equipment failure. If W>W0 and M≤M0, it is directly determined that the circulating safety parameters are abnormal, and instruction a2 is directly generated to control the circulating abnormality warning. If W≤W0 and M>M0, it is directly determined that the equipment safety parameters are abnormal, and instruction a3 is directly generated to provide equipment fault warning. If W>W0 and M>M0, it is directly determined that both the circulating safety parameters and the equipment safety parameters are abnormal, and instruction a4 is directly generated to provide early warning of circulating abnormality and equipment failure.

3. The intelligent detection and analysis method for grounding current circulation in tunnel cables according to claim 1, characterized in that: In step S4: An early warning is issued for abnormal situations occurring in the grounding loop current of the tunnel cable based on the generated instructions. If instruction a1 is generated, a blue light warning will be issued, and an abnormality in the calculation of the security assessment index will be indicated in the visualization module. If instruction a2 is generated, a yellow light warning will be issued, and an abnormality in the circulation safety parameters will be indicated in the visualization module. If instruction a3 is generated, an orange light warning will be issued, and an abnormal device safety parameter will be displayed in the visualization module. If instruction a4 is generated, a red light warning will be issued, and a prompt will be displayed in the visualization module indicating that both the circulating safety parameters and the equipment safety parameters are abnormal.

4. A smart detection and analysis system for tunnel cable grounding circulating current, applied to the smart detection and analysis method for tunnel cable grounding circulating current as described in claim 1, characterized in that: The system includes a tunnel data acquisition module, a data processing module, an analysis and judgment module, and an anomaly early warning module; The tunnel data acquisition module is used to collect data on the current of the grounding loop current of the cable metal sheath, the sheath induced voltage, the equipment temperature, and the tunnel humidity through sensors. The data processing module is used to analyze and process the collected data, and to analyze and fuse the collected monitoring data to obtain comprehensive detection parameters. The analysis and judgment module is used to set thresholds and compare and analyze the acquired detection data to determine whether any abnormalities have occurred. The anomaly warning module is used to provide warnings and alerts for detected anomalies based on the generated instructions.

5. The intelligent detection and analysis system for grounding current in tunnel cables according to claim 4, characterized in that: The tunnel data acquisition module includes a circulating current data acquisition unit and an equipment data acquisition unit. The circulating current data acquisition unit acquires current data in the grounding circulating current of the cable metal sheath in real time through a high-precision current sensor, and acquires induced voltage data of the monitoring layer in real time through a voltage sensor. The equipment data acquisition unit acquires temperature data at the cable joint and the sheath grounding point in real time through a temperature sensor, and acquires humidity data in the tunnel in real time through a humidity sensor.

6. The intelligent detection and analysis system for grounding current in tunnel cables according to claim 4, characterized in that: The data processing module includes a circulating current safety parameter analysis unit, an equipment safety parameter analysis unit, and a safety assessment index analysis unit. The circulating current safety parameter analysis unit is used to obtain circulating current safety parameters based on the collected current and voltage data. The equipment safety parameter analysis unit is used to obtain equipment safety parameters based on the collected temperature and humidity data. The safety assessment index analysis unit is used to weightedly fuse the circulating current safety parameters and the equipment safety parameters to obtain a safety assessment index.

7. The intelligent detection and analysis system for grounding current in tunnel cables according to claim 4, characterized in that: The analysis and judgment module includes a threshold setting unit and a comparison analysis unit; the threshold setting unit is used to set the threshold values ​​for circulating safety parameters, equipment safety parameters, and safety assessment index; the comparison analysis unit compares the values ​​obtained from the analysis with the set threshold values ​​to analyze and judge whether there are any abnormalities.

8. The intelligent detection and analysis system for grounding current in tunnel cables according to claim 4, characterized in that: The anomaly warning module is used to issue warnings for detected anomalies based on generated instructions and to display the anomaly type on the visualization device.

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