Distribution network non-power-cut operation bypass flexible cable situation awareness method and device integrated with multi-parameter monitoring

Abstract

The invention discloses a distribution network non-power-cut operation bypass flexible cable situation awareness method and device integrated with multi-parameter monitoring, relates to the technical field of cable detection, and aims to solve the problems that an existing bypass flexible cable monitoring technology is insufficient, and potential safety hazards are large. The method comprises the following steps: S1, synchronously acquiring parameters such as cable current and environment temperature and humidity, and adding timestamps; S2, preprocessing data by using a two-factor moving average algorithm; S3, calculating a coupling influence coefficient based on a parameter coupling characteristic; S4, fusing the coefficient and a safety threshold to calculate a health index; real-time fine monitoring of the bypass cable is realized, faults can be early warned in advance, power failure loss and operation and maintenance cost are reduced, operation safety is improved, power supply enterprises are assisted to optimize services, a good social image is established, and a support is provided for power-on operation technology upgrading of a distribution network.

Description

Technical Field

[0001] This invention relates to the field of cable testing technology, specifically to a method and device for situational awareness of flexible bypass cables in power distribution networks during uninterrupted power supply operations, integrating multi-parameter monitoring. Background Technology

[0002] In the process of continuous innovation and evolution in the power industry, State Grid Jiaozuo Power Supply Company has always regarded improving power supply reliability and service quality as an important goal. Under the current industry trend of pursuing efficient, stable and intelligent power supply, live-line working technology plays a vital role in ensuring the continuity of electricity supply for people's livelihood and reducing the negative effects of power outages on the social economy.

[0003] In uninterrupted power supply maintenance, the main technical approach involves establishing a complete bypass system using bypass cables, bypass cable connectors, and bypass load switches. With the continuous development and widespread application of bypass operation technology, the complexity of the work is also constantly increasing. It involves different voltage levels, different types of lines and equipment, which places higher demands on the technical skills and operational experience of the operators. On the other hand, the types and quantities of equipment used are constantly increasing, making coordination between equipment more difficult. Against this backdrop, the operational safety of bypass systems is becoming increasingly prominent and urgently requires serious attention.

[0004] Bypass cables, as a key carrier for temporary power supply, primarily serve to temporarily replace the main line during maintenance, providing short-term power supply, rather than being intended for long-term fixed installation. Bypass cables lack the comprehensive protection measures found in main lines. The robust overcurrent and short-circuit protection devices commonly found in main lines are not present in bypass flexible cables. Furthermore, current monitoring technology for the operational status of bypass flexible cables is inadequate, lacking refined and intelligent monitoring methods. We cannot accurately and in real-time grasp key parameters such as temperature changes, current distribution, and insulation performance of bypass flexible cables. If abnormalities occur during operation, such as insulation aging or localized overheating, it is difficult to detect them promptly and take effective countermeasures, undoubtedly posing a hidden danger to the safe operation of the bypass system.

[0005] The future development direction for bypass maintenance is towards intelligent and digital transformation, improving the monitoring and management level of power equipment and realizing a shift from passive maintenance to proactive prevention. Therefore, the research and development of real-time monitoring solutions and supporting facilities for key parameters of bypass cables is of great significance for proactively improving the operating efficiency and safety of power equipment. Summary of the Invention

[0006] The purpose of this invention is to provide a method and device for situational awareness of flexible cables used in power distribution network live-line maintenance (DPVM) operations, integrating multi-parameter monitoring. This involves proposing a monitoring and early warning scheme for flexible cables during DPVM operations, and simultaneously developing a corresponding situational awareness device for flexible cables. This effectively compensates for the shortcomings of existing bypass systems in operational safety monitoring, enabling real-time and precise monitoring of the bypass system's operating status, and timely detection of potential faults. This will significantly improve the safety of bypass operations, reduce the probability of power outages, ensure the smooth progress of DPVM operations, and further promote the company's technological advancement.

[0007] To achieve the above objectives, the present invention provides the following technical solution:

[0008] A method for situational awareness of flexible bypass cables in power distribution networks during live-line maintenance, integrating multi-parameter monitoring, is characterized by the following steps:

[0009] S1: Multi-source parameter synchronous acquisition steps: Synchronously acquire cable current, ambient temperature and humidity, joint temperature, running time, and power supply, add timestamps to form a raw parameter set, which is used as preprocessing input;

[0010] S2: Data preprocessing steps: Use the time decay weighted-humidity compensated two-factor moving average algorithm to process the original parameters and obtain a set of clean parameters, which are used as inputs for coupling coefficient calculation;

[0011] S3: Calculation steps for multi-parameter coupling influence coefficient: Based on cleanroom parameters and current-temperature, humidity-insulation coupling characteristics, calculate the multi-parameter coupling influence coefficient as input for health assessment;

[0012] S4: Cable comprehensive health status assessment steps: integrate coupling coefficient, parameter safety threshold, and cable design life to calculate real-time health index as early warning input;

[0013] S5: Dynamic Hierarchical Early Warning and Decision Output Steps: Based on the real-time value, trend, and cumulative number of warnings of the health index, trigger hierarchical early warnings, push information to the APP, and output operation and maintenance suggestions; Summary of this step: Trigger early warnings based on relevant parameters of the health index, push information and suggestions.

[0014] Step S1, the multi-source parameter synchronous acquisition step, specifically involves synchronously acquiring six core parameters of the bypass flexible cable at a frequency of 1 time per second through a sensor array and power extraction module, including the real-time cable current. Ambient temperature Ambient humidity Intermediate joint temperature , cumulative operating time of the cable Output voltage of inductive power supply module Real-time power supply The clock module adds a timestamp to each set of parameters. This forms the original parameter set. , , , , , , , ;in For the number of collections, This original set of parameters serves as input for subsequent data preprocessing.

[0015] Step S2, the data preprocessing step, specifically involves processing the original parameter set. The noise interference and environmental offset of each parameter are preprocessed using a two-factor weighted moving average algorithm with time decay weight and environmental compensation. The calculation formula is as follows:

[0016] ;

[0017] In the formula, For the first Cleanliness parameters after pretreatment represent , , , , , , Any parameter in; The length of the sliding window is 15. For the first Time decay weight of each data collection session τ is the time decay constant; For parameter-specific correction factors, The value is 1.03. The value is 0.97. The value is 1.04. Value 1.08 The value is 0.96. Value 1.01 The value is 1.02; This is the environmental humidity compensation coefficient. ;

[0018] The cleanliness parameter set obtained after the above pretreatment process is expressed as follows: .

[0019] Step S3, the calculation of the multi-parameter coupling influence coefficient, specifically involves using a cleanroom parameter set. Based on the core characteristics of bypass flexible cables during operation—namely, "current-temperature thermal coupling, humidity-power-insulation coupling, time-aging accumulation, and load-loss correlation"—a multi-parameter coupling influence coefficient is constructed, and the calculation formula is as follows:

[0020] ;

[0021] in: For the first The multi-parameter coupling influence coefficient of the second order; The weighting for the impact of current overload is set to 0.004; This refers to the real-time current of the pre-processed cable. The temperature coupling weight for the current connector is set to 0.06. The temperature of the intermediate joint after pretreatment; The humidity-voltage coupling weight is set to 0.015. The ambient humidity after pretreatment; This is the pre-processed output voltage of the power acquisition module; This is the runtime aging weight, with a value of 0.9. The cumulative operating time of the pre-treated cable; The load strength weight is set to 0.18. This is the pre-processed real-time power supply. The joint-ambient temperature difference weight is set to 0.03. The temperature difference between the intermediate joint and the environment;

[0022] Based on cleanliness parameters, a coupling effect coefficient is constructed that includes thermal coupling, insulation coupling, aging accumulation, and load correlation to quantify the comprehensive risk of cable operation.

[0023] Step S4, the comprehensive health status assessment of cables, specifically involves combining multi-parameter coupling influence coefficients. Based on the safety thresholds of various parameters and the cable design life, the real-time health index is calculated using the following formula:

[0024] ;

[0025] In the formula: Let k be the cable health index for the kth time. The maximum safe threshold for the coupling effect coefficient is set to 95, which is determined based on the critical fault data of the 10kV bypass cable and the sensor measurement range fitting. The safety percentage of the coupling coefficient; The safe temperature for intermediate joints is set at 90℃, with reference to the maximum allowable temperature for long-term operation of 10kV cable joints. This is the minimum operating temperature of the cable; For the safe percentage of joint temperature; The maximum allowable current for the cable is 400A. This is the minimum operating current for the cable, taken as 10A. The current safety ratio is 0.004; the aging degradation coefficient is 0.004. For the cable's design life; The percentage of safety during aging over time; This is the upper limit of the output voltage of the power supply module; This is the lower limit of the power module's output voltage. The safe percentage of the power supply voltage reflects the power supply stability of the power supply module;

[0026] By integrating coupling coefficient, parameter safety threshold, aging attenuation, and power supply stability, a quantitative health index is calculated to assess the real-time health status of the cable.

[0027] Step S5, the dynamic hierarchical early warning and decision output step, is specifically based on the health index. The real-time values, trends, and cumulative number of warnings trigger tiered warnings and output maintenance decisions. The calculation formula and logic are as follows:

[0028] ;

[0029] Early warning logic:

[0030] ;

[0031] In the formula: The rate of change in the health index; For the future Predicted health index over the duration Values ​​are taken for 30 minutes; To accumulate the number of warnings, the health index is accumulated when it is <0.6 and cleared when it is ≥0.8, avoiding false alarms from single fluctuations. The warning information includes the level and triggering reason, and is pushed to the embedded operation and maintenance management APP and remote monitoring center through the edge computing device. At the same time, operation and maintenance suggestions are output. The first-level warning suggests on-site handling within 1 hour, and the second-level warning suggests the development of an operation and maintenance plan within 24 hours.

[0032] By combining real-time health index values, change rates, predicted values, and cumulative number of warnings, tiered warnings are triggered and targeted operation and maintenance decisions are output.

[0033] The protective box includes a hinged upper and lower housing, which together form a sealed protective cavity when closed. Several wire holes are provided on both sides of the protective box to form a joint protection channel, and the connection between the channel and the cable is sealed with an interference fit. A multi-parameter sensor array is installed inside the protective box, and the outer shell of the protective box has an opening and an embedded edge computing convergence terminal.

[0034] The inner wall of the protective box is fitted with a flexible inner panel to prevent the joint from colliding with the box body.

[0035] The multi-parameter sensor array includes a Hall current sensor, an ambient temperature and humidity sensor, a wireless temperature sensor for the intermediate connector, and a clock module. The Hall current sensor is installed inside the protective box near the wiring hole and is sleeved on the bypass flexible cable leading out from the wiring hole. The ambient temperature and humidity sensor is close to the inner wall of the connector protective channel, corresponding to the installation position of the intermediate connector. The ambient temperature and humidity sensor is fixed to the corner or top of the lower box inside the protective box. The clock module is installed in the bottom area of ​​the edge computing convergence terminal inside the protective box.

[0036] It also includes a card-mounted inductive power supply module: consisting of two semi-annular high-permeability iron cores, with high-permeability rubber pasted on the inner surface of the iron cores to reduce magnetic field leakage, and fixed to the bypass flexible cable by clamps.

[0037] This situational awareness system uses "energy self-supply - multi-parameter collaborative monitoring - intelligent data processing - health assessment - hierarchical early warning" as its core closed loop to achieve full-state awareness of the bypass flexible cables for live-line maintenance in distribution networks. The specific mechanism is as follows:

[0038] First, the card-mounted inductive power extraction module is installed in the non-joint section of the bypass flexible cable using two semi-ring-shaped high-permeability iron cores. Utilizing the alternating magnetic field generated by the alternating current in the cable, an induced electromotive force is generated in the power extraction coil based on the principle of electromagnetic induction. After processing by a bridge rectifier, LC filter, and Buck-Boost power conversion circuit, a stable 12V voltage is output. At the same time, it is equipped with a supercapacitor and a lithium battery energy storage unit to continuously power the multi-parameter sensor array and edge computing aggregation terminal inside the protective box, ensuring that the system can still operate reliably when there is no external power supply.

[0039] Secondly, in terms of parameter monitoring, the protective box forms a sealed cavity by hinged upper and lower housings, with the cable insertion holes on both sides sealed with an interference fit to isolate dust and rainwater; the multi-parameter sensor array inside the box collects data collaboratively according to functional zones: Hall current sensors are sleeved on the cables leading out from the insertion holes to capture real-time current signals non-contactly; the wireless temperature sensor of the intermediate connector is close to the inner wall of the connector's protective channel to directly monitor the temperature of the intermediate connector; the ambient temperature and humidity sensor is fixed to the corner of the lower housing to collect the overall temperature and humidity inside the box; the clock module is installed near the edge computing aggregation terminal to add a unified timestamp to all collected parameters, ensuring data synchronization in time and space, and the data from each sensor is transmitted to the edge computing aggregation terminal in real time.

[0040] At the data processing and health assessment level, the edge computing aggregation terminal first performs a two-factor weighted moving average preprocessing of the raw parameters using "time decay weight - humidity compensation". Environmental interference is corrected by the time decay weight and humidity compensation coefficient, and noise is filtered out to obtain clean parameters. Then, based on the clean parameters, a multi-parameter coupling influence coefficient is constructed to quantify the comprehensive influence of "current-temperature thermal coupling, humidity-power supply insulation coupling, time-aging accumulation, and load-loss correlation". Finally, the safety threshold of the coupling coefficient, the cable design life and the safety range of each parameter are integrated to calculate the health index in the 0-1 range, which intuitively reflects the real-time health status of the cable.

[0041] Finally, at the early warning decision-making level, the system dynamically triggers tiered early warnings based on the health index: the predicted health index for the next 30 minutes is calculated by the rate of change of the health index, and combined with the cumulative number of early warnings, if the real-time health index is <0.4 or the predicted value is <0.5 and the cumulative number of early warnings is ≥3, a level 1 early warning is triggered; if the real-time health index is 0.4-0.7 and the predicted value is ≥0.5, a level 2 early warning is triggered; if the health index is ≥0.7 and the predicted value is ≥0.5, it is determined to be in a normal state, and the early warning information is pushed to the embedded operation and maintenance management APP through the edge computing terminal, realizing the transformation from "passive emergency repair" to "proactive prevention" operation and maintenance mode.

[0042] Compared with the prior art, the beneficial effects of the present invention are:

[0043] Reducing power outage losses: The application of the situational awareness device for bypass flexible cables in live-line maintenance of distribution networks can promptly detect potential faults in bypass flexible cables, allowing for proactive measures to prevent power outages. Statistics show that each reduction in power outage incidents can avoid economic losses of hundreds of thousands or even millions of yuan. By promoting the application of this device, the annual reduction in power outage losses can be immeasurable.

[0044] Reduced Operation and Maintenance Costs: Traditional bypass operations require manual inspection and monitoring of cable operating status, which is prone to oversights and inefficient. The distribution network live-line maintenance bypass cable situational awareness device enables real-time, automatic monitoring of cables, reducing the workload of manual inspections and lowering personnel costs. Simultaneously, the device can provide early warnings of faults, improving the timeliness and accuracy of fault handling and reducing fault repair time and costs.

[0045] Improved operational efficiency: By monitoring the bypass system's operational status in real time, maintenance personnel can adjust work plans and strategies promptly based on actual conditions, avoiding unnecessary waiting and delays. Furthermore, the device's intelligent functions can provide operators with operational guidance and safety tips, improving both safety and efficiency.

[0046] Enhancing Social Image: As a power supply company, improving power supply reliability and service quality is an important manifestation of social responsibility. The widespread application of distribution network live-line work bypass cable situational awareness devices will help the company better meet users' power supply needs, reduce the impact of power outages on users, and enhance the company's social image and brand value.

[0047] Promoting technological innovation and industrial upgrading: The research results of this project will provide new research directions for the development of live-line working technology for power distribution networks, and promote the innovation and progress of related technologies.

[0048] Data Value Mining: The massive amount of operational data collected by the system has significant value. Through data mining and analysis, it can provide optimization suggestions, health status assessments, and fault predictions for cable design, manufacturing, operation and maintenance. Attached Figure Description

[0049] Figure 1 This is a flowchart of a situational awareness method for bypass flexible cables in power distribution networks that integrates multi-parameter monitoring for uninterrupted power supply operations, according to the present invention.

[0050] Figure 2 This is a three-dimensional structural diagram of a power distribution network bypass flexible cable situational awareness device integrating multi-parameter monitoring for uninterrupted power supply operations according to the present invention.

[0051] Figure 3 This is a schematic diagram of the inductive power extraction module of a power distribution network uninterrupted power supply bypass flexible cable situational awareness device integrating multi-parameter monitoring according to the present invention. Detailed Implementation

[0052] The technical solutions of the present invention will now be described in detail with reference to the accompanying drawings.

[0053] like Figure 1-2 As shown, step S1, the multi-source parameter synchronous acquisition step, specifically involves synchronously acquiring six core parameters of the bypass flexible cable at a frequency of 1 time / second through a sensor array and power extraction module, including the real-time cable current. Ambient temperature Ambient humidity Intermediate joint temperature , cumulative operating time of the cable Output voltage of inductive power supply module Real-time power supply The clock module adds a timestamp to each set of parameters. This forms the original parameter set, whose formula is as follows:

[0054] , , , , , , , ;

[0055] in For the number of collections, This original set of parameters serves as input for subsequent data preprocessing.

[0056] Step S2, the data preprocessing step, specifically involves processing the original parameter set. The noise interference and environmental offset of each parameter are preprocessed using a two-factor weighted moving average algorithm with time decay weight and environmental compensation. The calculation formula is as follows:

[0057] ;

[0058] In the formula, For the first Cleanliness parameters after pretreatment represent , , , , , , Any parameter in; The length of the sliding window is 15. For the first Time decay weight of each data collection session τ is the time decay constant; For parameter-specific correction factors, The value is 1.03. The value is 0.97. The value is 1.04. Value 1.08 The value is 0.96. Value 1.01 The value is 1.02; This is the environmental humidity compensation coefficient. ;

[0059] The cleanliness parameter set obtained after the above pretreatment process is expressed as follows: .

[0060] Step S3, the calculation of the multi-parameter coupling influence coefficient, specifically involves using a cleanroom parameter set. Based on the core characteristics of bypass flexible cables during operation—namely, "current-temperature thermal coupling, humidity-power-insulation coupling, time-aging accumulation, and load-loss correlation"—a multi-parameter coupling influence coefficient is constructed, and the calculation formula is as follows:

[0061] ;

[0062] in: For the first The multi-parameter coupling influence coefficient of the second order; The weighting for the impact of current overload is set to 0.004; This refers to the real-time current of the pre-processed cable. The temperature coupling weight for the current connector is set to 0.06. The temperature of the intermediate joint after pretreatment; The humidity-voltage coupling weight is set to 0.015. The ambient humidity after pretreatment; This is the pre-processed output voltage of the power acquisition module; This is the runtime aging weight, with a value of 0.9. The cumulative operating time of the pre-treated cable; The load strength weight is set to 0.18. This is the pre-processed real-time power supply. The joint-ambient temperature difference weight is set to 0.03. The temperature difference between the intermediate joint and the environment;

[0063] Based on cleanliness parameters, a coupling effect coefficient is constructed that includes thermal coupling, insulation coupling, aging accumulation, and load correlation to quantify the comprehensive risk of cable operation.

[0064] Step S4, the comprehensive health status assessment of cables, specifically involves combining multi-parameter coupling influence coefficients. Based on the safety thresholds of various parameters and the cable design life, the real-time health index is calculated using the following formula:

[0065] ;

[0066] In the formula: Let k be the cable health index for the kth time. The maximum safe threshold for the coupling effect coefficient is set to 95, which is determined based on the critical fault data of the 10kV bypass cable and the sensor measurement range fitting. The safety percentage of the coupling coefficient; The safe temperature for intermediate joints is set at 90℃, with reference to the maximum allowable temperature for long-term operation of 10kV cable joints. This is the minimum operating temperature of the cable; For the safe percentage of joint temperature; The maximum allowable current for the cable is 400A. This is the minimum operating current for the cable, taken as 10A. The current safety ratio is 0.004; the aging degradation coefficient is 0.004. For the cable's design life; The percentage of safety during aging over time; This is the upper limit of the output voltage of the power supply module; This is the lower limit of the power module's output voltage. The safe percentage of the power supply voltage reflects the power supply stability of the power supply module;

[0067] By integrating coupling coefficient, parameter safety threshold, aging attenuation, and power supply stability, a quantitative health index is calculated to assess the real-time health status of the cable.

[0068] Step S5, the dynamic hierarchical early warning and decision output step, is specifically based on the health index. The real-time values, trends, and cumulative number of warnings trigger tiered warnings and output maintenance decisions. The calculation formula and logic are as follows:

[0069] ;

[0070] Early warning logic:

[0071] ;

[0072] In the formula: The rate of change in the health index; For the future Predicted health index over the duration Values ​​are taken for 30 minutes; To accumulate the number of warnings, the health index is accumulated when it is <0.6 and cleared when it is ≥0.8, avoiding false alarms from single fluctuations. The warning information includes the level and triggering reason, and is pushed to the embedded operation and maintenance management APP and remote monitoring center through the edge computing device. At the same time, operation and maintenance suggestions are output. The first-level warning suggests on-site handling within 1 hour, and the second-level warning suggests the development of an operation and maintenance plan within 24 hours.

[0073] By combining real-time health index values, change rates, predicted values, and cumulative number of warnings, a tiered early warning system is triggered, and targeted operation and maintenance decisions are output. A situational awareness device for flexible cables bypassing power distribution networks with integrated multi-parameter monitoring includes a protective box 1. The protective box 1 comprises a hinged upper and lower housing, which, when closed, form a sealed protective cavity. Several through-holes 2 are provided on both sides of the protective box 1, forming joint protection channels. The channels are sealed with an interference fit at the cable connection points. A multi-parameter sensor array is installed inside the protective box 1, and the outer shell of the protective box 1 has openings and an embedded edge computing convergence terminal 3.

[0074] The inner wall of the protective box 1 is fitted with a flexible inner panel to prevent the joint from colliding with the box body.

[0075] The multi-parameter sensor array includes a Hall current sensor, an ambient temperature and humidity sensor, a wireless temperature sensor for the intermediate connector, and a clock module. The Hall current sensor is installed inside the protective box 1 near the wiring hole 2 and is sleeved on the bypass flexible cable leading out from the wiring hole. The ambient temperature and humidity sensor is close to the inner wall of the connector protection channel, corresponding to the installation position of the intermediate connector. The ambient temperature and humidity sensor is fixed to the corner or top of the lower box of the protective box 1. The clock module is installed in the bottom area of ​​the edge computing convergence terminal inside the protective box 1.

[0076] It also includes a card-mounted inductive power supply module: consisting of two semi-annular high-permeability iron cores, with high-permeability rubber pasted on the inner surface of the iron cores to reduce magnetic field leakage, and fixed to the bypass flexible cable by clamps.

[0077] In a 10kV distribution network uninterrupted operation scenario, after deploying the aforementioned situational awareness device and execution sensing method on a YJV22-10kV-3×120mm² bypass flexible cable, the device's protective box is securely installed at the cable's intermediate joint, forming a sealed, impact-resistant cavity. A multi-parameter sensor array is installed according to preset positions: a Hall current sensor is fitted onto the cable leading out of the through-hole; a wireless temperature sensor at the intermediate joint is attached to the inner wall of the joint's protective channel; an ambient temperature and humidity sensor is fixed to the corner of the lower casing of the protective box; a clock module is located near the edge computing aggregation terminal; and a clip-on inductive power extraction module is clipped onto the non-joint section of the cable and stably outputs 12V to power the system. The data processing and evaluation end collects parameters such as cable current, ambient temperature and humidity, and joint temperature at 1 time / second and adds a timestamp. After preprocessing with a two-factor weighted moving average, cleanliness parameters are obtained. Based on these cleanliness parameters, a multi-parameter coupling influence coefficient is calculated, and the calculation of a certain moment is performed. =82, which is less than the maximum safety threshold of 95. The real-time health index is calculated by combining the safety threshold parameter with the cable design life. =0.65; The early warning decision-making system combines the real-time health index value with the predicted health index for the next 30 minutes. =0.056 and cumulative number of warnings =0, triggering a level 2 warning. The edge computing aggregation terminal will push the warning information, including a health index of 0.65, predicting a decline in 30 minutes, and the triggering reason being the slow rise in joint temperature, to the embedded operation and maintenance management APP and the remote monitoring center. Simultaneously, it will output the operation and maintenance suggestion of "checking the heat dissipation of the intermediate joint on-site and retesting the parameters within 24 hours". The remote monitoring center will generate an operation and maintenance work order based on this, realizing effective perception of cable operation status and risk warning.

Claims

1. A method for situational awareness of flexible bypass cables in power distribution networks during live-line maintenance, integrating multi-parameter monitoring, characterized in that: Includes the following steps: S1: Multi-source parameter synchronous acquisition steps: Synchronously acquire cable current, ambient temperature and humidity, joint temperature, running time, and power supply, add timestamps to form a raw parameter set, which is used as preprocessing input; S2: Data preprocessing steps: Use the time decay weighted-humidity compensated two-factor moving average algorithm to process the original parameters and obtain a set of clean parameters, which are used as inputs for coupling coefficient calculation; S3: Calculation steps for multi-parameter coupling influence coefficient: Based on cleanroom parameters and current-temperature, humidity-insulation coupling characteristics, calculate the multi-parameter coupling influence coefficient as input for health assessment; S4: Cable comprehensive health status assessment steps: integrate coupling coefficient, parameter safety threshold, and cable design life to calculate real-time health index as early warning input; S5: Dynamic Hierarchical Early Warning and Decision Output Steps: Based on the real-time value, trend, and cumulative number of early warnings of the health index, trigger hierarchical early warnings, push information to the APP, and output operation and maintenance suggestions; Summary of this step: Trigger early warnings based on relevant parameters of the health index, push information and suggestions.

2. The method for situational awareness of flexible cables bypassing power distribution networks with integrated multi-parameter monitoring as described in claim 1, characterized in that, Step S1, the multi-source parameter synchronous acquisition step, specifically involves synchronously acquiring six core parameters of the bypass flexible cable at a frequency of 1 time per second through a sensor array and power extraction module, including the real-time cable current. Ambient temperature Ambient humidity Intermediate joint temperature , cumulative operating time of cable Output voltage of inductive power supply module Real-time power supply The clock module adds a timestamp to each set of parameters. This forms the original parameter set. , , , , , , , ;in For the number of collections, This original set of parameters serves as input for subsequent data preprocessing.

3. The method for situational awareness of flexible cables bypassing power distribution networks with integrated multi-parameter monitoring as described in claim 1, characterized in that, Step S2, the data preprocessing step, specifically involves processing the original parameter set. The noise interference and environmental offset of each parameter are preprocessed using a two-factor weighted moving average algorithm with time decay weight and environmental compensation. The calculation formula is as follows: ； In the formula, For the first Cleanliness parameters after pretreatment represent , , , , , , Any parameter in; The length of the sliding window is 15. For the first Time decay weight of each data collection session τ is the time decay constant; For parameter-specific correction factors, The value is 1.

03. The value is 0.

97. The value is 1.

04. Value 1.08 The value is 0.

96. Value 1.01 The value is 1.02; This is the environmental humidity compensation coefficient. ; The cleanliness parameter set obtained after the above pretreatment process is expressed as follows: .

4. The method for situational awareness of flexible cables bypassing power distribution networks with integrated multi-parameter monitoring as described in claim 1, characterized in that, Step S3, the calculation of the multi-parameter coupling influence coefficient, specifically involves using a cleanroom parameter set. Based on the core characteristics of bypass flexible cables during operation—namely, "current-temperature thermal coupling, humidity-power extraction insulation coupling, time-aging accumulation, and load-loss correlation"—a multi-parameter coupling influence coefficient is constructed, and the calculation formula is as follows: ； in: For the first The multi-parameter coupling influence coefficient of the second order; The weighting for the impact of current overload is set to 0.004; This refers to the real-time current of the pre-processed cable. The temperature coupling weight for the current connector is set to 0.

06. The temperature of the intermediate joint after pretreatment; The humidity-voltage coupling weight is set to 0.

015. The ambient humidity after pretreatment; This is the pre-processed output voltage of the power acquisition module; This is the runtime aging weight, with a value of 0.

9. The cumulative operating time of the pre-treated cable; The load strength weight is set to 0.

18. This is the pre-processed real-time power supply. The joint-ambient temperature difference weight is set to 0.

03. The temperature difference between the intermediate joint and the environment; Based on cleanliness parameters, a coupling effect coefficient is constructed that includes thermal coupling, insulation coupling, aging accumulation, and load correlation to quantify the comprehensive risk of cable operation.

5. The method for situational awareness of flexible cables bypassing power distribution networks during uninterrupted power supply operations, integrating multi-parameter monitoring, as described in claim 1, is characterized in that... Step S4, the comprehensive health status assessment of cables, specifically involves combining multi-parameter coupling influence coefficients. Based on the safety thresholds of various parameters and the cable design life, the real-time health index is calculated using the following formula: ； In the formula: Let k be the cable health index for the kth time. The maximum safe threshold for the coupling effect coefficient is set to 95, which is determined based on the critical fault data of the 10kV bypass cable and the sensor measurement range fitting. The safety percentage of the coupling coefficient; The safe temperature for intermediate joints is set at 90℃, with reference to the maximum allowable temperature for long-term operation of 10kV cable joints. This is the minimum operating temperature of the cable; For the safe percentage of joint temperature; The maximum allowable current for the cable is 400A. This is the minimum operating current for the cable, taken as 10A. The current safety ratio is 0.004; the aging degradation coefficient is 0.

004. For the cable's design life; The percentage of safe aging over time; This is the upper limit of the output voltage of the power supply module; This is the lower limit of the power module's output voltage. The safe percentage of the power supply voltage reflects the power supply stability of the power supply module; By integrating coupling coefficient, parameter safety threshold, aging attenuation, and power supply stability, a quantitative health index is calculated to assess the real-time health status of the cable.

6. The method for situational awareness of flexible cables bypassing power distribution networks during uninterrupted power supply operations, integrating multi-parameter monitoring, as described in claim 1, is characterized in that... Step S5, the dynamic hierarchical early warning and decision output step, is specifically based on the health index. The real-time values, trends, and cumulative number of warnings trigger tiered warnings and output maintenance decisions. The calculation formula and logic are as follows: ； Early warning logic: ； In the formula: The rate of change in the health index; For the future Predicted health index over the duration Values ​​are taken for 30 minutes; To prevent false alarms from a single fluctuation, the health index is accumulated when it is <0.6 and reset to zero when it is ≥0.

8. The warning information includes the level and triggering reason, and is pushed to the embedded operation and maintenance management APP and remote monitoring center through the edge computing device. At the same time, operation and maintenance suggestions are output. The first-level warning suggests on-site handling within 1 hour, and the second-level warning suggests the development of an operation and maintenance plan within 24 hours. By combining real-time health index values, change rates, predicted values, and cumulative number of warnings, tiered warnings are triggered and targeted operation and maintenance decisions are output.

7. A situational awareness device for flexible cables bypassing power distribution networks with integrated multi-parameter monitoring, comprising a protective box (1), characterized in that, The protective box (1) includes a hinged upper box and a lower box, which form a sealed protective cavity after being closed; the protective box (1) has several wire holes (2) on both sides and forms a joint protection channel, and the channel and the cable connection are sealed with an interference fit; the protective box (1) is equipped with a multi-parameter sensor array inside, and the protective box (1) has an opening in the outer shell and an embedded edge computing convergence terminal (3).

8. According to claim 7, the protective box (1) has a flexible inner plate attached to its inner wall to avoid the joint from colliding with the box body.

9. According to claim 7, a situational awareness device for a bypass flexible cable of a power distribution network with integrated multi-parameter monitoring, wherein the multi-parameter sensor array includes a Hall current sensor, an ambient temperature and humidity sensor, a wireless temperature sensor for intermediate joints, and a clock module. The Hall current sensor is installed in the protective box (1) near the wire hole (2) and sleeved on the bypass flexible cable leading out from the wire hole. The ambient temperature and humidity sensor is close to the inner wall of the joint protection channel, corresponding to the installation position of the intermediate joint. The ambient temperature and humidity sensor is fixed in the corner or top of the lower box of the protective box (1). The clock module is installed in the bottom area of ​​the edge calculation and aggregation terminal inside the protective box (1).

10. The situational awareness device for bypass flexible cable of power distribution network with integrated multi-parameter monitoring according to claim 7 further includes a clip-on inductive power extraction module: comprising two semi-annular high permeability iron cores, with high permeability rubber pasted on the inner surface of the iron cores to reduce magnetic field leakage, and fixed to the bypass flexible cable by clamps.

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