A system and motor cooperative multi-parameter fusion insulation online monitoring method and system

Abstract

The application provides a kind of system and motor collaborative multi-parameter fusion insulation on-line monitoring method and system, the method includes obtaining the overall insulation resistance of bus and each branch leakage current by system insulation monitoring device;The insulation resistance, leakage current, zero sequence current, output voltage difference, absorption ratio and polarization index of the motor are obtained by the motor insulation monitoring device arranged in each high-voltage motor;According to the operating state of the motor, the DC injection of the motor insulation monitoring device is automatically controlled to start and stop, and the insulation monitoring responsibility is switched to the system insulation monitoring device when the motor is running;Based on the weighted fusion model, the comprehensive insulation health index of each motor is calculated;According to the comprehensive insulation health index and the preset threshold, the dynamic early warning level is output, and the standby motor whose comprehensive health index is lower than the preset threshold is automatically locked for closing operation.The application can realize full-dimensional insulation state perception, adaptive monitoring switching, fault accurate positioning and intelligent operation and maintenance decision.

Description

Technical Field

[0001] This invention relates to the field of online insulation monitoring technology for high-voltage electrical equipment in power systems, specifically to a multi-parameter integrated online insulation monitoring method and system that coordinates the system and motor. It can be widely applied to online insulation monitoring of 6-10kV systems with neutral point grounded by a small resistor, arc suppression coil grounded, or neutral point ungrounded. It is particularly suitable for power supply and distribution systems with a large number of high-voltage motors in continuous production enterprises such as petrochemical, power, metallurgy, and coal mining. Background Technology

[0002] In continuous production enterprises such as petrochemical and power plants, 6-10kV power supply and distribution systems are typically equipped with a large number of high-voltage motors, including both main and standby motors. To ensure power supply reliability, standby motors need to be in a hot or cold standby state for extended periods. Insulation monitoring is a crucial means of ensuring the safe operation of high-voltage motors and power supply and distribution systems. If insulation degradation is not detected in time, it may lead to equipment damage, unplanned shutdowns, or even system accidents.

[0003] Currently, the following technical solutions are mainly used for insulation monitoring of 6-10kV power supply and distribution systems and high-voltage motors: (a) System insulation monitoring device System insulation monitoring devices are typically installed on the busbar side and employ the DC superposition method. This method involves injecting a DC test voltage (usually DC 1500V–2500V) between the busbar neutral point and ground to measure the weak DC current in the power system insulation layer and convert it into insulation resistance. The DC superposition method is suitable for 3–10kV high-voltage motors, distribution transformers, and other equipment, and is particularly suitable for continuously operating equipment that cannot be shut down. The system insulation monitoring device can monitor the overall insulation resistance of the busbar and the leakage current to ground in each branch of the system in real time.

[0004] (ii) Motor insulation monitoring device In existing technologies, some high-voltage motors are equipped with independent insulation monitoring devices to measure the insulation resistance of the motor windings when the motor is stopped. The measurement principle is also based on the DC voltage method—a high DC voltage (usually 500V, 1000V, or 2500V) is applied to the motor windings, and the insulation resistance is calculated by measuring the leakage current. Some devices also have the function of measuring the absorption ratio (R60s / R15s) and polarization index (R10min / R60s). The relevant measurement methods can be found in GB / T 20833.4-2021 "Insulation of Rotating Electrical Machines - Part 4: Measurement of Insulation Resistance and Polarization Index". A polarization index ≥1.5 and an absorption ratio ≥1.3 are generally used as reference criteria for good insulation.

[0005] However, the above-mentioned existing technical solutions have the following drawbacks: 1. System insulation monitoring and motor insulation monitoring are independent of each other, with no data sharing and a lack of coordination. The system insulation monitoring device (based on the DC superposition method for monitoring bus insulation) and the motor insulation monitoring device operate independently. When bus insulation deteriorates, the system device can only report "low resistance of a certain section of bus insulation," unable to distinguish whether the problem lies with the bus itself or a specific motor branch. Maintenance personnel can only troubleshoot by performing line-by-line tests, disconnecting each branch one by one and observing whether the bus insulation recovers to locate the faulty branch. Each branch takes approximately 30 minutes to troubleshoot, and the entire bus section often requires several hours or even more than 10 hours, severely impacting production continuity.

[0006] 2. Limited Monitoring Parameters and Lack of Comprehensive Assessment. Most existing online insulation monitoring devices only monitor the single parameter of insulation resistance, failing to fully utilize auxiliary criteria such as leakage current, zero-sequence current, absorption ratio, and polarization index. Insulation resistance alone is insufficiently sensitive to progressive faults such as early moisture absorption and sheath damage. When the insulation resistance has not yet dropped to the alarm threshold, the insulation may already show a significant deterioration trend, making it difficult to accurately detect early faults. Furthermore, existing devices often use fixed-level reporting methods (such as pre-alarm / alarm), outputting only discrete alarm levels, failing to quantify the continuity and changing trends of insulation deterioration.

[0007] 3. Insulation testing of backup motors relies on manual labor, which is inefficient. Traditionally, before backup motors are put into operation, maintenance personnel must go to the site to cut off the power, disconnect the wiring, and use a megohmmeter to measure the insulation resistance of each motor, taking approximately 2 hours per unit. When putting them into operation in batches, the total time required can reach several hours or even a day, severely hindering production recovery efficiency.

[0008] 4. Conflict exists between the motor and the monitoring device during operation. Existing motor insulation monitoring devices may continue to inject DC test signals into the motor windings while the motor is running, interfering with the motor. DC injection may affect the normal operation of relay protection devices, accelerate insulation aging, and even cause safety hazards. Existing devices lack a mechanism to automatically start and stop DC injection based on the motor's operating status.

[0009] In summary, there is currently no existing online insulation monitoring method or system that can integrate system insulation monitoring and motor insulation monitoring into a unified collaborative architecture, perform continuous quantitative evaluation based on multi-parameter weighted fusion, and adaptively switch monitoring responsibilities according to the motor operating status. Summary of the Invention

[0010] To address the shortcomings of existing technologies, this invention provides a multi-parameter fusion insulation online monitoring method and system that coordinates the system and motor. Based on a weighted fusion algorithm, it comprehensively evaluates multiple parameters such as insulation resistance, leakage current, zero-sequence current, voltage difference, absorption ratio, and polarization index, thereby achieving full-dimensional insulation status perception, adaptive monitoring switching, accurate fault location, and intelligent operation and maintenance decision-making.

[0011] The present invention achieves the above objectives through the following technical solutions: A multi-parameter integrated online insulation monitoring system that coordinates the system and the motor, comprising: The overall insulation resistance of the busbar and the leakage current of each branch are obtained through the system insulation monitoring device. The insulation resistance, leakage current, zero-sequence current, output voltage difference, absorption ratio, and polarization index of each high-voltage motor are obtained by using a motor insulation monitoring device configured on each high-voltage motor. The DC injection start and stop of the motor insulation monitoring device is automatically controlled according to the motor operating status, and the insulation monitoring responsibility is switched to the system insulation monitoring device when the motor is running. The comprehensive insulation health index of each motor is calculated based on the weighted fusion model. The dimensions of the weighted fusion model include at least the basic insulation dimension, trend dimension, auxiliary diagnosis dimension and circuit health dimension. Each dimension includes at least one sub-indicator. After each sub-indicator is mapped to a sub-indicator score through a scoring function, the sub-indicator is weighted and summed in two stages according to the dimension weight and the sub-indicator weight to obtain the comprehensive insulation health index. Dynamic warning levels are output based on the comprehensive insulation health index and preset thresholds, and the closing operation of standby motors with comprehensive health indexes below preset thresholds is automatically locked.

[0012] According to the multi-parameter fusion insulation online monitoring system for system and motor coordination provided by the present invention, in the weighted fusion model: the basic insulation dimension has a weight of 40%, the trend dimension has a weight of 25%, the auxiliary diagnosis dimension has a weight of 20%, and the circuit health dimension has a weight of 15%; wherein: The sub-index of the basic insulation dimension is the normalized score of the measured insulation resistance value relative to a preset threshold. The sub-indicators of the trend dimension include the insulation resistance slope score and the leakage current cycle trend difference score. The sub-indicators of the auxiliary diagnostic dimension include the uptake ratio score and the polarization index score; The sub-indicators of the circuit health dimension include insulation voltage difference score, zero-sequence current score, and leakage current absolute value score.

[0013] According to the present invention, a multi-parameter integrated online insulation monitoring system for system and motor collaboration is provided, wherein the scoring function adopts a linear interpolation method: when the sub-index measurement value is between two preset endpoints, the score is calculated linearly between the scores of the corresponding endpoints; The scoring thresholds for absorption ratio are set as follows: 100 points for absorption ratio ≥ 1.3 and 0 points for absorption ratio ≤ 1.0. The scoring endpoints for the polarization index are set as follows: 100 points are awarded when the polarization index is ≥ 2.0, and 0 points are awarded when the polarization index is ≤ 1.2. The scoring endpoints for leakage current trend difference are set as follows: 100 points are awarded when the trend difference is ≤100mA, and 0 points are awarded when the trend difference is ≥2000mA. The scoring endpoints for insulation voltage difference are set as follows: 100 points are awarded when the voltage difference is ≤50V, and 0 points are awarded when the voltage difference is ≥200V.

[0014] The multi-parameter integrated online insulation monitoring system for system and motor coordination provided by the present invention further includes a dual-end low-resistance precise positioning step: When the system insulation monitoring device detects that the bus insulation resistance is lower than the alarm threshold, the online insulation monitoring and analysis screen automatically queries the comprehensive health index and insulation resistance value of all motors under that bus section based on the pre-stored bus-motor topology relationship. For each motor found, the following judgments are performed sequentially: determine whether the motor is currently in hot standby or cold standby mode; if not, skip the motor; if so, further determine whether its comprehensive health index is lower than 50 or whether its insulation resistance is lower than 6MΩ. If at least one motor simultaneously meets the conditions of being in hot standby or cold standby, and its comprehensive health index is below 50 or its insulation resistance is below 6MΩ, then the motor circuit is determined to be a faulty branch causing the bus insulation to deteriorate, and a fault location prompt containing the motor's identifier is output in the background.

[0015] The present invention provides a multi-parameter integrated online insulation monitoring system that coordinates the system and the motor, and further includes a backup motor insulation over-limit intelligent control step: The online insulation monitoring and analysis panel monitors the insulation status of each standby motor in real time based on the latest comprehensive health index and insulation resistance value of each standby motor. When a standby motor is detected to meet any of the following conditions, over-limit control is triggered: (a) the comprehensive health index is below 50; (b) the insulation resistance is below 6MΩ. In response to the triggering of the over-limit control, the analysis screen sends a closing interlock command to the background monitoring platform. The background monitoring platform automatically locks the remote closing operation of the standby motor according to the command and displays the motor information on the human-machine interface. Only after maintenance personnel use an independent insulation testing instrument to re-test the motor on-site and confirm that it is qualified, and then perform a manual confirmation operation on the human-machine interface of the background monitoring platform, will the background monitoring platform send the manual confirmation information to the analysis screen. After the analysis screen verifies the manual confirmation information, it will release the closing lock of the standby motor. Before the maintenance personnel perform the manual confirmation operation, the closing lock of the standby motor will remain effective.

[0016] The multi-parameter integrated online insulation monitoring system for system and motor coordination provided by the present invention further includes a rapid commissioning decision-making step for batch standby motors: The online insulation monitoring and analysis panel updates and stores the insulation status data of each standby motor in real time based on the comprehensive health index, insulation resistance, absorption ratio, polarization index and trend data of each standby motor. The back-end monitoring platform provides a batch commissioning decision interface, which displays the comprehensive health index, insulation resistance, absorption ratio, polarization index and trend indicators of all standby motors in a list format. The trend indicators are used to indicate the direction of change of each parameter within a preset time period. In response to the one-click screening operation performed by maintenance personnel on the batch commissioning decision interface, the background monitoring platform automatically screens all standby motors according to the preset screening threshold, marking motors with a comprehensive health index ≥ 70 as qualified and ready for commissioning, and marking motors with a comprehensive health index < 70 as unqualified and awaiting investigation. The background monitoring platform responds to the batch closing command issued by the operation and maintenance personnel to the motors marked as qualified and ready for operation. It sends the closing command to the circuit breaker corresponding to each qualified motor in a preset order, so that each qualified motor is put into operation in sequence. For motors marked as unqualified and pending inspection, the background monitoring platform automatically locks their closing operation. The closing prohibition status is displayed on the batch commissioning decision interface in a form that is different from qualified motors, and an inspection list is automatically generated. The inspection list includes at least the identification information of each unqualified motor, the comprehensive health index, and the scores of each sub-indicator.

[0017] According to the present invention, a multi-parameter integrated online insulation monitoring system for system and motor coordination is provided, wherein the dynamic early warning level is mapped to different early warning levels based on a comprehensive health index range, including: The online insulation monitoring and analysis panel uses the comprehensive health index calculated by the weighted fusion model as a continuous quantitative evaluation value. The value range of the comprehensive health index is 0 to 100. When the comprehensive health index is between 85 and 100, it corresponds to the first warning level. When the comprehensive health index is between 70 and 85, it is mapped to the second warning level, and a prompt message suggesting that patrols be strengthened is output. When the comprehensive health index is between 50 and 70, it corresponds to the third warning level. When the comprehensive health index is below 50, it corresponds to the fourth warning level. Based on the triggering of the fourth warning level, the analysis screen will perform at least one of the following control operations: for standby motors, automatically lock their closing operation and prohibit them from starting; for running motors, output a prompt message suggesting emergency shutdown.

[0018] The multi-parameter fusion insulation online monitoring system for system and motor coordination provided by the present invention further includes a trend-assisted alarm step: The online insulation monitoring and analysis panel records and stores the time series data of the insulation resistance of each motor in fixed time windows, and calculates the slope of the change in insulation resistance between adjacent time windows. If the slope of the change in insulation resistance is downward and its absolute value exceeds 30, and the slope condition is met for two consecutive monitoring windows, the analysis screen will trigger an alert message indicating accelerated insulation degradation and send it to the background monitoring platform for display. The analysis panel calculates the difference between the current week's average leakage current and the previous week's average leakage current for each motor, using a weekly cycle as the unit of measurement. When the leakage current cycle trend difference exceeds 2000mA, the analysis panel triggers an alarm and sends it to the background monitoring platform for display. The analysis screen continuously monitors the output voltage difference of each motor insulation monitoring device. This voltage difference is the absolute value of the difference between the injected voltage set by the insulation monitoring device and the measured output voltage. When the voltage difference exceeds 100V and continues for a preset time, the analysis screen triggers an alarm message and sends it to the background monitoring platform for display. At the same time, the analysis screen determines that the current insulation resistance measurement value is invalid, and in the weighted fusion model, the insulation resistance sub-index score is set to zero or the insulation resistance dimension weight is reduced to zero until the voltage difference recovers to below 100V for a predetermined time, after which the normal score calculation of the insulation resistance sub-index is resumed.

[0019] According to the present invention, a multi-parameter integrated online insulation monitoring system for system and motor coordination automatically controls the DC injection start / stop of the motor insulation monitoring device based on the motor operating status, including: The motor insulation monitoring device collects the following digital and analog signals in real time: circuit breaker open / close position signal, trolley working / test position signal, grounding switch open / close position signal, external maintenance button signal, and three-phase current signal; The motor insulation monitoring device automatically determines whether the motor is in running state, hot standby state, cold standby state, or maintenance state based on the collected signals and according to the preset state recognition rules. When the motor is determined to be in hot standby or cold standby state and there is no signal of an external maintenance button being pressed, the motor insulation monitoring device starts DC injection monitoring, applies DC test voltage to the motor windings and measures the insulation resistance. When the motor is determined to be in operation or maintenance state, the motor insulation monitoring device immediately stops DC injection, cuts off the DC test voltage applied to the motor windings, and sends a state switching signal to the online insulation monitoring and analysis panel. After receiving the status switching signal, the online insulation monitoring and analysis panel switches the insulation monitoring responsibility of the motor circuit from the motor insulation monitoring device to the system insulation monitoring device. The system insulation monitoring device then indirectly monitors the equivalent insulation status of the motor circuit through the leakage current of the branch where the motor is located or the bus insulation.

[0020] A multi-parameter integrated online insulation monitoring system that coordinates the system and the motor, comprising: At least one system insulation monitoring unit includes an effective grounding decoupling device and a system insulation monitoring device. The effective grounding decoupling device is connected in series between the neutral point of each bus section and the ground. The system insulation monitoring device measures the overall insulation resistance of the bus and the leakage current of each branch through the DC superposition method, and uploads the measurement data to the online insulation monitoring and analysis screen. Multiple motor insulation monitoring units are configured in high-voltage motors to acquire motor insulation resistance, leakage current, zero-sequence current, output voltage difference, absorption ratio, polarization index, identify motor operating status, automatically control the start and stop of DC injection based on the identified motor operating status, and upload the acquired motor insulation data and operating status data to the online insulation monitoring and analysis screen. The online insulation monitoring and analysis panel has a built-in weighted fusion evaluation model. It connects to all system insulation monitoring units and motor insulation monitoring units through an industrial communication network to perform data aggregation, insulation monitoring responsibility mode switching, weighted fusion evaluation, and intelligent decision-making. The back-end monitoring platform connects to the online insulation monitoring and analysis screen via an industrial communication network, providing a human-machine interface to display the insulation health index of the entire system, the comprehensive health index of each motor and its corresponding early warning level, the batch commissioning decision interface, and historical trends.

[0021] Therefore, compared with the prior art, the multi-parameter fusion insulation online monitoring method and system proposed in this invention, which coordinates the system with the motor, has the following beneficial effects: 1. This invention constructs a four-dimensional weighted fusion model that includes basic insulation dimension, trend dimension, auxiliary diagnosis dimension, and circuit health dimension. Compared with the existing technology that only monitors a single parameter of insulation resistance or adopts a fixed hierarchical reporting mode of pre-alarm / alarm binary / multi-class method, this invention realizes multi-dimensional cross-validation and continuous quantitative evaluation. It can capture subtle changes and gradual processes of insulation degradation, effectively overcome the shortcomings of single parameters being insensitive to gradual faults such as early moisture absorption and sheath damage, and substantially improve the accuracy and sensitivity of insulation degradation early warning.

[0022] 2. This invention integrates the system's insulation monitoring devices and the insulation monitoring devices of each motor into a unified data platform through an online insulation monitoring and analysis panel. It establishes a busbar-motor topology association, enabling cross-validation of data from both the system and motor sides. When busbar insulation deteriorates, the analysis panel actively queries the comprehensive health index and insulation resistance value of all hot-standby or cold-standby motors under that busbar section based on the topology association. Through hierarchical screening and dual-condition judgment, it pinpoints the faulty branch in one go. This invention reduces the location time from hours to seconds, and the location results are accurate and reliable.

[0023] 3. This invention provides a batch commissioning decision interface through a backend monitoring platform, centrally displaying the comprehensive health index, insulation resistance, absorption ratio, polarization index, and trend indicators of all standby motors in a list format. Maintenance personnel can easily filter motors that meet the comprehensive health index and issue batch closing commands. The system executes the closing operation one motor at a time according to a preset sequence. For motors with unqualified comprehensive health indices, the system automatically locks the closing and generates a checklist containing sub-indicator scores, providing maintenance personnel with precise troubleshooting directions. This invention improves commissioning efficiency by over 80%, significantly shortens production recovery time, and reduces the workload of maintenance personnel.

[0024] 4. This invention achieves adaptive start-stop of DC injection, eliminating interference from DC injection to the operating motor at the source. Simultaneously, for standby motors with a comprehensive health index below the severe threshold or insulation resistance below the absolute prohibition threshold, the system automatically locks the closing operation and maintains this lock until manual verification, forming a complete safety barrier from status awareness to proactive intervention, thus eliminating the safety risk of operating faulty motors.

[0025] 5. This invention continuously stores raw measurement data such as insulation resistance, leakage current, absorption ratio, and polarization index of each motor, as well as historical comprehensive health index data, through an online insulation monitoring and analysis screen. It supports historical tracing and trend analysis across any time span. Maintenance personnel can query the comprehensive health index change curve and detailed scores of each sub-indicator for any motor within a specified time period through the backend monitoring platform. Combined with trend-assisted alarm information such as insulation resistance slope alarm and leakage current cycle trend difference alarm, the speed and direction of insulation degradation can be accurately determined, and a predictive maintenance plan can be formulated accordingly, realizing an upgrade from passive response maintenance to proactive predictive maintenance.

[0026] 6. This invention is adaptable to various system grounding methods, such as 6-10kV neutral point grounded with a small resistor, arc suppression coil grounded, or neutral point ungrounded, and can be extended to other voltage levels. Through optional insulation isolation devices and their linkage control mechanisms, physical decoupling of the high-voltage system and monitoring devices is achieved in complex scenarios where the arc suppression coil is grounded or multiple monitoring devices coexist, effectively avoiding signal interference. Furthermore, when the system insulation monitoring device malfunctions due to communication interruption or other reasons, the analysis screen automatically switches to degraded operation mode. Each motor insulation monitoring device continues to work independently and continuously performs weighted fusion evaluation, maintaining a valid overall health index; only the overall bus insulation data is missing. Once the system devices are repaired, the collaborative operation mode is automatically restored, ensuring that the most important motor insulation monitoring is not interrupted even when some devices fail. The overall system availability and robustness are significantly better than existing solutions where a single point of failure leads to complete functional loss.

[0027] The present invention will now be described in further detail with reference to the accompanying drawings and specific embodiments. Attached Figure Description

[0028] Figure 1 This is a flowchart of an embodiment of a multi-parameter fusion insulation online monitoring method for system and motor coordination according to the present invention.

[0029] Figure 2 This is a schematic diagram of an embodiment of a multi-parameter fusion insulation online monitoring method for system and motor coordination according to the present invention.

[0030] Figure 3 This is a logic diagram of the double-end low-resistance precise positioning steps in an embodiment of a multi-parameter fusion insulation online monitoring method for system and motor collaboration according to the present invention.

[0031] Figure 4 This is a flowchart illustrating the decision-making process for rapid commissioning of batch standby motors in an embodiment of a multi-parameter fusion insulation online monitoring method for system-motor collaboration according to the present invention. Detailed Implementation

[0032] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0033] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0034] An Example of a Multi-parameter Integrated Insulation Online Monitoring Method for System and Motor Collaboration See Figures 1 to 4 This embodiment provides a multi-parameter integrated online insulation monitoring method for system and motor coordination, including the following steps: Step S1: Obtain the overall insulation resistance of the busbar and the leakage current of each branch through the system insulation monitoring device; Step S2: Obtain the insulation resistance, leakage current, zero-sequence current, output voltage difference, absorption ratio, and polarization index of each high-voltage motor by using a motor insulation monitoring device configured on each high-voltage motor. Step S3: Automatically control the start and stop of DC injection of the motor insulation monitoring device according to the motor operating status, and switch the insulation monitoring responsibility to the system insulation monitoring device when the motor is running; Step S4: Calculate the comprehensive insulation health index of each motor based on the weighted fusion model. The dimensions of the weighted fusion model include at least the basic insulation dimension, trend dimension, auxiliary diagnosis dimension, and circuit health dimension. Each dimension includes at least one sub-indicator. After each sub-indicator is mapped to a sub-indicator score through a preset scoring function, it is weighted and summed in two levels according to the dimension weight and the sub-indicator weight to obtain the comprehensive insulation health index. Step S5: Output a dynamic warning level based on the comprehensive insulation health index and preset threshold, and automatically lock the closing operation of standby motors whose comprehensive health index is lower than the preset threshold.

[0035] In the weighted fusion model, the basic insulation dimension has a weight of 40%, the trend dimension has a weight of 25%, the auxiliary diagnosis dimension has a weight of 20%, and the circuit health dimension has a weight of 15%; where: The sub-index of the basic insulation dimension is the normalized score of the measured insulation resistance value relative to a preset threshold. The sub-indicators of the trend dimension include the insulation resistance slope score and the leakage current cycle trend difference score. The sub-indicators of the auxiliary diagnostic dimension include the uptake ratio score and the polarization index score; The sub-indicators of the circuit health dimension include insulation voltage difference score, zero-sequence current score, and leakage current absolute value score.

[0036] In this embodiment, the scoring function uses linear interpolation. When the sub-index measurement value is between two preset endpoints, the score is calculated linearly between the scores of the corresponding endpoints. The scoring thresholds for absorption ratio are set as follows: 100 points for absorption ratio ≥ 1.3 and 0 points for absorption ratio ≤ 1.0. The scoring endpoints for the polarization index are set as follows: 100 points are awarded when the polarization index is ≥ 2.0, and 0 points are awarded when the polarization index is ≤ 1.2. The scoring endpoints for leakage current trend difference are set as follows: 100 points are awarded when the trend difference is ≤100mA, and 0 points are awarded when the trend difference is ≥2000mA. The scoring endpoints for insulation voltage difference are set as follows: 100 points are awarded when the voltage difference is ≤50V, and 0 points are awarded when the voltage difference is ≥200V.

[0037] In this embodiment, as Figure 3 As shown, it also includes a double-ended low-resistance precision positioning step: When the system insulation monitoring device detects that the bus insulation resistance is lower than the alarm threshold, the online insulation monitoring and analysis screen automatically queries the comprehensive health index and insulation resistance value of all motors under that bus section based on the pre-stored bus-motor topology relationship. For each motor found, the following judgments are performed sequentially: determine whether the motor is currently in hot standby or cold standby mode; if not, skip the motor; if so, further determine whether its comprehensive health index is lower than 50 or whether its insulation resistance is lower than 6MΩ. If at least one motor simultaneously meets the conditions of being in hot standby or cold standby, and its comprehensive health index is below 50 or its insulation resistance is below 6MΩ, then the motor circuit is determined to be a faulty branch causing the bus insulation to deteriorate, and a fault location prompt containing the motor's identifier is output in the background.

[0038] In this embodiment, an intelligent control step for insulation over-limit of the backup motor is also included: The online insulation monitoring and analysis panel monitors the insulation status of each standby motor in real time based on the latest comprehensive health index and insulation resistance value of each standby motor. When a standby motor is detected to meet any of the following conditions, over-limit control is triggered: (a) the comprehensive health index is below 50; (b) the insulation resistance is below 6MΩ. In response to the triggering of the over-limit control, the analysis screen sends a closing interlock command to the background monitoring platform. The background monitoring platform automatically locks the remote closing operation of the standby motor according to the command, and displays a red "Do Not Operate" mark on the corresponding icon of the motor on the human-machine interface. At the same time, a modal prompt window pops up, displaying the motor's identification information, comprehensive health index, insulation resistance value, and the prompt text "The insulation health index of this motor is too low. Manual verification is required before operation!" Only after maintenance personnel use an independent insulation testing instrument on-site to re-test the motor and confirm its qualification, and then perform a manual confirmation operation on the human-machine interface of the background monitoring platform, will the background monitoring platform send the manual confirmation information to the analysis screen. After the analysis screen verifies the manual confirmation information, it will release the closing lock of the standby motor, and the motor can then be put into operation. Before the maintenance personnel perform the manual confirmation operation, the closing lock of the standby motor remains effective.

[0039] In this embodiment, as Figure 4 As shown, it also includes decision-making steps for rapid deployment of batch standby motors: The online insulation monitoring and analysis panel updates and stores the insulation status data of each standby motor in real time based on the comprehensive health index, insulation resistance, absorption ratio, polarization index and trend data of each standby motor. The back-end monitoring platform provides a batch commissioning decision interface. The interface displays the comprehensive health index, insulation resistance, absorption ratio, polarization index and trend indicators of all standby motors in a list format. The trend indicators are used to indicate the direction of change of each parameter within a preset time period. In response to the one-click screening operation performed by maintenance personnel on the batch commissioning decision interface, the background monitoring platform automatically screens all standby motors according to the preset screening threshold, marking motors with a comprehensive health index ≥ 70 as qualified and ready for commissioning, and marking motors with a comprehensive health index < 70 as unqualified and awaiting investigation. The background monitoring platform responds to the batch closing command issued by the operation and maintenance personnel to the motors marked as qualified and ready for operation. It sends the closing command to the circuit breaker corresponding to each qualified motor in a preset order, so that each qualified motor is put into operation in sequence. For motors marked as unqualified and pending inspection, the background monitoring platform automatically locks their closing operation and displays the "closing prohibited" status on the batch commissioning decision interface in a form that is different from qualified motors. It also automatically generates a list of motors to be inspected, which includes at least the identification information, comprehensive health index and scores of each sub-indicator of each unqualified motor. The circuit breaker lockout remains effective until maintenance personnel complete the on-site inspection and treatment of the non-conforming motor and its overall health index recovers to ≥70.

[0040] In this embodiment, the dynamic early warning level is mapped to different early warning levels based on the comprehensive health index range, including: The online insulation monitoring and analysis panel uses the comprehensive health index calculated by the weighted fusion model as a continuous quantitative evaluation value. The value range of the comprehensive health index is 0 to 100. When the comprehensive health index is between 85 and 100, it corresponds to the first warning level and is judged as "normal". When the comprehensive health index is between 70 and 85, it is mapped to the second warning level, judged as "caution", and a prompt message suggesting that patrols be strengthened is output. When the comprehensive health index is between 50 and 70, it is mapped to the third warning level, judged as "abnormal", and outputs a prompt message suggesting that maintenance be arranged within the plan; When the comprehensive health index is below 50, it is mapped to the fourth warning level, which is judged as "serious" and an alarm message is immediately output. Based on the triggering of the fourth warning level, the analysis screen will perform at least one of the following control operations: for standby motors, automatically lock their closing operation and prohibit them from starting; for running motors, output a prompt message suggesting emergency shutdown. After completing the mapping of warning levels, the analysis screen sends the comprehensive health index value of each motor, its corresponding warning level, and recommended actions to the background monitoring platform for display. It also continuously updates the comprehensive health index of each motor and dynamically updates its warning level when the comprehensive health index changes across intervals.

[0041] In this embodiment, a trend-assisted alarm step is also included: The online insulation monitoring and analysis panel records and stores the time series data of the insulation resistance of each motor in fixed time windows, and calculates the slope of the change in insulation resistance between adjacent time windows. If the slope of the change in insulation resistance is downward and its absolute value exceeds 30, and the slope condition is met for two consecutive monitoring windows, the analysis screen will trigger an "accelerated insulation degradation" prompt and send it to the background monitoring platform for display. The analysis panel calculates the difference between the average value of the leakage current of each motor this week and the average value of the previous week as the leakage current periodic trend difference, using a weekly cycle as the unit. When the leakage current periodic trend difference exceeds 2000mA, the analysis panel triggers an "abnormal leakage current trend" alarm and sends it to the background monitoring platform for display. The analysis screen continuously monitors the output voltage difference of each motor insulation monitoring device. This voltage difference is the absolute value of the difference between the injection voltage set by the insulation monitoring device and the measured output voltage. When the voltage difference exceeds 100V and lasts for 30 seconds, the analysis screen triggers an "injection circuit abnormality" alarm and sends it to the background monitoring platform for display. At the same time, the analysis screen determines that the current insulation resistance measurement value is invalid. In the weighted fusion model, the insulation resistance sub-index score is reduced to zero or the insulation resistance dimension weight is reduced to zero until the voltage difference recovers to below 100V for a predetermined period of time, after which the normal score calculation of the insulation resistance sub-index is resumed.

[0042] In this embodiment, automatically controlling the DC injection start / stop of the motor insulation monitoring device according to the motor operating status includes: The motor insulation monitoring device collects the following digital and analog signals in real time: circuit breaker open / close position signal, trolley working / test position signal, grounding switch open / close position signal, external maintenance button signal, and three-phase current signal; The motor insulation monitoring device automatically determines whether the motor is in running state, hot standby state, cold standby state, or maintenance state based on the collected signals and according to the preset state recognition rules. When the motor is determined to be in hot standby or cold standby state and there is no signal of an external maintenance button being pressed, the motor insulation monitoring device starts DC injection monitoring, applies DC test voltage to the motor windings and measures the insulation resistance. When the motor is determined to be in operation or maintenance state, the motor insulation monitoring device immediately stops DC injection, cuts off the DC test voltage applied to the motor windings, and sends a status switching signal to the online insulation monitoring and analysis screen. The status switching signal includes at least the motor's identification information and the status information "switched to system monitoring". After receiving the status switching signal, the online insulation monitoring and analysis panel switches the insulation monitoring responsibility of the motor circuit from the motor insulation monitoring device to the system insulation monitoring device. The system insulation monitoring device then indirectly monitors the equivalent insulation status of the motor circuit through the leakage current of the branch where the motor is located or the bus insulation.

[0043] An embodiment of a multi-parameter integrated online insulation monitoring system that coordinates the system and the motor This embodiment provides a multi-parameter integrated online insulation monitoring system that coordinates the system and the motor, including: At least one system insulation monitoring unit includes an effective grounding decoupling device and a system insulation monitoring device. The effective grounding decoupling device is connected in series between the neutral point of each bus section and the ground. The system insulation monitoring device measures the overall insulation resistance of the bus and the leakage current of each branch through the DC superposition method, and uploads the measurement data to the online insulation monitoring and analysis screen. Multiple motor insulation monitoring units are configured in high-voltage motors to acquire motor insulation resistance, leakage current, zero-sequence current, output voltage difference, absorption ratio, polarization index, identify motor operating status, automatically control the start and stop of DC injection based on the identified motor operating status, and upload the acquired motor insulation data and operating status data to the online insulation monitoring and analysis screen. The online insulation monitoring and analysis panel has a built-in weighted fusion evaluation model. It connects to all system insulation monitoring units and motor insulation monitoring units through an industrial communication network to perform data aggregation, insulation monitoring responsibility mode switching, weighted fusion evaluation, and intelligent decision-making. The back-end monitoring platform connects to the online insulation monitoring and analysis screen via an industrial communication network, providing a human-machine interface to display the insulation health index of the entire system, the comprehensive health index of each motor and its corresponding early warning level, the batch commissioning decision interface, and historical trends.

[0044] In this embodiment, an insulation isolation device is also included. The insulation isolation device is linked with the online insulation monitoring and analysis panel to achieve physical decoupling between the high-voltage system and the motor monitoring device. When the bus is grounded by the arc suppression coil or there is an external system insulation monitoring device, the isolation device is automatically closed before monitoring is started, and the isolation device is opened when monitoring stops or the system enters maintenance mode.

[0045] In this embodiment, the online insulation monitoring and analysis panel also supports multiple waveform recording triggers such as motor start-up, stop, current surge, and timed recording to record waveforms before and after the fault. When the system insulation monitoring device fails, it automatically switches to the degraded operation mode, and each motor insulation monitoring device continues to work independently and perform weighted fusion evaluation. After the system insulation monitoring device recovers, it automatically resumes the collaborative operation mode.

[0046] The technical solution of the present invention will be described in detail below with reference to specific embodiments, but the scope of protection of the present invention is not limited to these embodiments.

[0047] (1) System and motor collaborative monitoring and weighted fusion evaluation under a single busbar A petrochemical plant's secondary substation has a 10kV I-section busbar with 20 high-voltage motors (8 in operation and 12 as backup). The system is equipped with one effective grounding decoupling device, one system insulation monitoring device, and one comprehensive motor insulation monitoring device for each motor. All devices are connected to an online insulation monitoring and analysis panel via a fiber optic ring network, and the back-end monitoring platform is deployed in the central control room.

[0048] Normal operation: The system insulation monitoring device measures the overall insulation resistance of the busbar in real time to be 50MΩ. The insulation monitoring devices of each motor operate according to their status. Among them, the standby motor M-01 is in hot standby mode. The motor device automatically starts DC injection and measures insulation resistance of 45MΩ, leakage current of 120mA, absorption ratio of 1.35, and polarization index of 2.1. Analysis screen operation weighted fusion algorithm: Basic insulation dimension score = min(100, 45 / 10×100) = 100 (actual normalization is based on a threshold of 10MΩ, 45 / 10 = 450, but the upper limit is 100, so 100 points are obtained); absorption ratio score 100 points, polarization index score 100 points; leakage current trend difference (comparison between this week and last week) only increased by 30mA, 100 points; insulation voltage difference of 20V, 100 points. The overall health index = 40%×100 + 25%×100 + 20%×100 + 15%×100 = 100, which is judged as "normal". The backend displays M-01 as green.

[0049] The insulation of a standby motor is slowly deteriorating: Over two consecutive weeks, the insulation resistance of standby motor M-09 gradually decreased from 32MΩ to 14MΩ, the absorption ratio decreased to 1.15, the polarization index decreased to 1.5, and the leakage current increased from 80mA to 480mA. The weighted fusion algorithm calculates the following scores: Basic insulation dimension score = min(100, 14 / 10×100) = 100 (still greater than the threshold of 10MΩ), but the resistance slope over 10 minutes (taking the data change over the most recent 10 minutes) in the trend dimension is -0.8MΩ / min, and the score drops to 40 points; the leakage current trend is worse this week, increasing by 400mA compared to last week, with a score of approximately 80 points; the absorption ratio score = (1.15-1.0) / (1.3-1.0)×100 = 50 points; the polarization index score = (1.5-1.2) / (2.0-1.2)×100 = 37.5 points; and the absolute value of the leakage current in the loop health dimension is 480mA, with a score of approximately 60 points. The weighted composite score is calculated as follows: 40%×100 + 25%×(40%×40 + 60%×80) + 20%×(60%×50 + 40%×37.5) + 15%×(40%×100 + 30%×100 + 30%×60) = 40 + 25%×(16+48=64) + 20%×(30+15=45) + 15%×(40+30+18=88) = 40 + 16 + 9 + 13.2 = 78.2 points, falling within the attention range (70-85). The backend displays M-09 as yellow and suggests increased inspection. Maintenance personnel arranged a planned power outage for inspection and found that the motor junction box was damp; after repair, the insulation was restored.

[0050] During motor startup: When M-09 is put into operation, its motor unit detects a phase current >10% of the rated current, immediately stops DC injection, and sends a "Switched to system monitoring" signal to the analysis panel. The analysis panel marks the monitoring responsibility for this circuit as "system side". During motor operation, the system insulation monitoring device indirectly monitors the equivalent insulation status of this circuit through the branch leakage current sensor, achieving seamless connection.

[0051] (2) Low resistance fault in double-ended low resistance precise positioning bus One day, the system insulation monitoring device reported that the insulation resistance of bus section I dropped to 2MΩ (low resistance alarm). Traditionally, this requires testing each branch individually, with each branch requiring approximately 30 minutes of power outage troubleshooting, and the entire bus section requiring over 10 hours. This embodiment deploys a dual-end positioning function. Upon receiving the low resistance event, the online insulation monitoring analysis panel automatically queries the comprehensive health index and insulation resistance value of the 20 motors associated with bus section I. It finds that the comprehensive health index of standby motor M-03 is only 38 points, its measured insulation resistance is 3MΩ, and this motor is in cold standby mode. The analysis panel excludes other motors (all with health indices above 85) and determines the faulty branch to be the M-03 circuit. The backend immediately displays: "Fault location: Low insulation resistance of motor M-03 caused a decrease in system bus insulation; please check the motor and cables." Maintenance personnel went directly to M-03 for inspection and found that the cable terminal was damp. After treatment, the bus insulation was restored to 168MΩ. The entire location process, from alarm to output of location results, took only 5 seconds, without any pull-circuit tests, significantly shortening the fault handling time.

[0052] (3) Rapid commissioning and intelligent locking of batch standby motors After a major overhaul of the equipment, all 12 standby motors need to be put into operation. The traditional method requires manually inspecting the insulation of each motor on-site, taking approximately 2 hours per motor, totaling 24 people per hour (2 people working together would take 12 hours). This invention employs a batch commissioning decision-making function.

[0053] Maintenance personnel can access the "Batch Commissioning Decision" interface in the backend. The system automatically lists the comprehensive health index, insulation resistance, absorption ratio, polarization index, and trends of 12 standby motors. The list displays: The health indices of the 11 motors were 92, 88, 95, ... (all ≥70); One motor (M-09) has a health index of 45, an insulation resistance of 8MΩ, and a leakage current trend of +2100mA.

[0054] The maintenance personnel clicked "Filter Health Index ≥ 70", automatically selected 11 qualified motors, and clicked "Batch Close". The system closed the circuit remotely one by one in sequence, taking about 10 minutes in total, and all 11 motors were successfully put into operation. For M-09, the system automatically locked the closing button, displayed a red "Do Not Enter" sign, and popped up a prompt "The insulation health index of this motor is too low (45), and manual verification is required before operation!"

[0055] Maintenance personnel used a megohmmeter on-site to check the insulation of M-09 and found it to be damp. After treatment, the insulation resistance was restored to 200MΩ, and the health index rose to 92. The maintenance personnel then clicked "manual confirmation unlock" in the backend and individually switched on M-09. The overall commissioning efficiency was improved by more than 95%, and the risk of operating a faulty motor was eliminated.

[0056] (4) Degraded operation when the system insulation monitoring device fails Assuming the system insulation monitoring device malfunctions due to communication interruption, the analysis panel automatically issues a "System Insulation Monitoring Failure" alarm and switches to degraded operation mode after failing to receive bus insulation data for three consecutive cycles. In this mode, the insulation monitoring devices for each motor continue to operate normally, and data such as insulation resistance, leakage current, and absorption ratio of all hot / cold standby motors continue to be uploaded and participate in the weighted fusion evaluation, maintaining the validity of the overall health index. The backend can still monitor the insulation status of each motor, with only the overall bus insulation data missing. Once the system devices are repaired, the analysis panel automatically resumes collaborative operation mode without manual intervention, ensuring uninterrupted monitoring of the crucial motor insulation and improving system robustness.

[0057] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0058] The above embodiments are merely preferred embodiments of the present invention and should not be construed as limiting the scope of protection of the present invention. Any non-substantial changes and substitutions made by those skilled in the art based on the present invention shall fall within the scope of protection claimed by the present invention.

Claims

1. A multi-parameter integrated online insulation monitoring method for system and motor coordination, characterized in that, Includes the following steps: The overall insulation resistance of the busbar and the leakage current of each branch are obtained through the system insulation monitoring device. The insulation resistance, leakage current, zero-sequence current, output voltage difference, absorption ratio, and polarization index of each high-voltage motor are obtained by using a motor insulation monitoring device configured on each high-voltage motor. The DC injection start and stop of the motor insulation monitoring device is automatically controlled according to the motor operating status, and the insulation monitoring responsibility is switched to the system insulation monitoring device when the motor is running. The comprehensive insulation health index of each motor is calculated based on the weighted fusion model. The dimensions of the weighted fusion model include at least the basic insulation dimension, trend dimension, auxiliary diagnosis dimension and circuit health dimension. Each dimension includes at least one sub-indicator. After each sub-indicator is mapped to a sub-indicator score through a scoring function, the sub-indicator is weighted and summed in two stages according to the dimension weight and the sub-indicator weight to obtain the comprehensive insulation health index. Dynamic warning levels are output based on the comprehensive insulation health index and preset thresholds, and the closing operation of standby motors with comprehensive health indices below preset thresholds is automatically locked.

2. The method according to claim 1, characterized in that: In the weighted fusion model: the basic insulation dimension has a weight of 40%, the trend dimension has a weight of 25%, the auxiliary diagnosis dimension has a weight of 20%, and the circuit health dimension has a weight of 15%; among which: The sub-index of the basic insulation dimension is the normalized score of the measured insulation resistance value relative to a preset threshold. The sub-indicators of the trend dimension include the insulation resistance slope score and the leakage current cycle trend difference score. The sub-indicators of the auxiliary diagnostic dimension include the uptake ratio score and the polarization index score; The sub-indicators of the circuit health dimension include insulation voltage difference score, zero-sequence current score, and leakage current absolute value score.

3. The method according to claim 1, characterized in that: The scoring function uses linear interpolation: when the sub-indicator measurement value is between two preset endpoints, the score is calculated linearly between the scores of the corresponding endpoints; The scoring thresholds for absorption ratio are set as follows: 100 points for absorption ratio ≥ 1.3 and 0 points for absorption ratio ≤ 1.

0. The scoring endpoints for the polarization index are set as follows: 100 points are awarded when the polarization index is ≥ 2.0, and 0 points are awarded when the polarization index is ≤ 1.

2. The scoring endpoints for leakage current trend difference are set as follows: 100 points are awarded when the trend difference is ≤100mA, and 0 points are awarded when the trend difference is ≥2000mA. The scoring endpoints for insulation voltage difference are set as follows: 100 points are awarded when the voltage difference is ≤50V, and 0 points are awarded when the voltage difference is ≥200V.

4. The method according to claim 1, characterized in that, It also includes a dual-end low-resistance precision positioning step: When the system insulation monitoring device detects that the bus insulation resistance is lower than the alarm threshold, the online insulation monitoring and analysis screen automatically queries the comprehensive health index and insulation resistance value of all motors under that bus section based on the pre-stored bus-motor topology relationship. For each motor found, the following judgments are performed sequentially: determine whether the motor is currently in hot standby or cold standby mode; if not, skip the motor; if so, further determine whether its comprehensive health index is lower than 50 or whether its insulation resistance is lower than 6MΩ. If at least one motor simultaneously meets the conditions of being in hot standby or cold standby, and its comprehensive health index is below 50 or its insulation resistance is below 6MΩ, then the motor circuit is determined to be a faulty branch causing the bus insulation to deteriorate, and a fault location prompt containing the motor's identifier is output in the background.

5. The method according to claim 1, characterized in that, It also includes intelligent control steps for backup motor insulation exceeding limits: The online insulation monitoring and analysis panel monitors the insulation status of each standby motor in real time based on the latest comprehensive health index and insulation resistance value of each standby motor. When a standby motor is detected to meet any of the following conditions, over-limit control is triggered: (a) the comprehensive health index is below 50; (b) the insulation resistance is below 6MΩ. In response to the triggering of the over-limit control, the analysis screen sends a closing interlock command to the background monitoring platform. The background monitoring platform automatically locks the remote closing operation of the standby motor according to the command and displays the motor information on the human-machine interface. Only after maintenance personnel use an independent insulation testing instrument to re-test the motor on-site and confirm that it is qualified, and then perform a manual confirmation operation on the human-machine interface of the background monitoring platform, will the background monitoring platform send the manual confirmation information to the analysis screen. After the analysis screen verifies the manual confirmation information, it will release the closing lock of the standby motor. Before the maintenance personnel perform the manual confirmation operation, the closing lock of the standby motor will remain effective.

6. The method according to claim 1, characterized in that, It also includes decision-making steps for rapid commissioning of batch of standby motors: The online insulation monitoring and analysis panel updates and stores the insulation status data of each standby motor in real time based on the comprehensive health index, insulation resistance, absorption ratio, polarization index and trend data of each standby motor. The back-end monitoring platform provides a batch commissioning decision interface, which displays the comprehensive health index, insulation resistance, absorption ratio, polarization index and trend indicators of all standby motors in a list format. The trend indicators are used to indicate the direction of change of each parameter within a preset time period. In response to the one-click screening operation performed by maintenance personnel on the batch commissioning decision interface, the background monitoring platform automatically screens all standby motors according to the preset screening threshold, marking motors with a comprehensive health index ≥ 70 as qualified and ready for commissioning, and marking motors with a comprehensive health index < 70 as unqualified and awaiting investigation. The background monitoring platform responds to the batch closing command issued by the operation and maintenance personnel to the motors marked as qualified and ready for operation. It sends the closing command to the circuit breaker corresponding to each qualified motor in a preset order, so that each qualified motor is put into operation in sequence. For motors marked as unqualified and pending inspection, the background monitoring platform automatically locks their closing operation. The closing prohibition status is displayed on the batch commissioning decision interface in a form that is different from qualified motors, and an inspection list is automatically generated. The inspection list includes at least the identification information of each unqualified motor, the comprehensive health index, and the scores of each sub-indicator.

7. The method according to claim 1, characterized in that, The dynamic early warning levels are mapped to different levels based on the comprehensive health index range, including: The online insulation monitoring and analysis panel uses the comprehensive health index calculated by the weighted fusion model as a continuous quantitative evaluation value. The value range of the comprehensive health index is 0 to 100. When the comprehensive health index is between 85 and 100, it corresponds to the first warning level. When the comprehensive health index is between 70 and 85, it is mapped to the second warning level, and a prompt message suggesting that patrols be strengthened is output. When the comprehensive health index is between 50 and 70, it corresponds to the third warning level. When the comprehensive health index is below 50, it corresponds to the fourth warning level. Based on the triggering of the fourth warning level, the analysis screen will perform at least one of the following control operations: for standby motors, automatically lock their closing operation and prohibit them from starting; for running motors, output a prompt message suggesting emergency shutdown.

8. The method according to any one of claims 1 to 7, characterized in that, It also includes trend-assisted alerting steps: The online insulation monitoring and analysis panel records and stores the time series data of the insulation resistance of each motor in fixed time windows, and calculates the slope of the change in insulation resistance between adjacent time windows. If the slope of the change in insulation resistance is downward and its absolute value exceeds 30, and the slope condition is met for two consecutive monitoring windows, the analysis screen will trigger an alert message indicating accelerated insulation degradation and send it to the background monitoring platform for display. The analysis panel calculates the difference between the average leakage current of each motor this week and the average leakage current of the previous week, using a weekly cycle as the periodic trend difference. When the leakage current periodic trend difference exceeds 2000mA, the analysis panel triggers an alarm and sends it to the background monitoring platform for display. The analysis screen continuously monitors the output voltage difference of each motor insulation monitoring device. This voltage difference is the absolute value of the difference between the injected voltage set by the insulation monitoring device and the measured output voltage. When the voltage difference exceeds 100V and continues for a preset time, the analysis screen triggers an alarm message and sends it to the background monitoring platform for display. At the same time, the analysis screen determines that the current insulation resistance measurement value is invalid, and in the weighted fusion model, the insulation resistance sub-index score is set to zero or the insulation resistance dimension weight is reduced to zero until the voltage difference recovers to below 100V for a predetermined time, after which the normal score calculation of the insulation resistance sub-index is resumed.

9. The method according to any one of claims 1 to 7, characterized in that, The automatic control of the DC injection start / stop of the motor insulation monitoring device based on the motor's operating status includes: The motor insulation monitoring device collects the following digital and analog signals in real time: circuit breaker open / close position signal, trolley working / test position signal, grounding switch open / close position signal, external maintenance button signal, and three-phase current signal; The motor insulation monitoring device automatically determines whether the motor is in running state, hot standby state, cold standby state, or maintenance state based on the collected signals and according to the preset state recognition rules. When the motor is determined to be in hot standby or cold standby state and there is no signal of an external maintenance button being pressed, the motor insulation monitoring device starts DC injection monitoring, applies DC test voltage to the motor windings and measures the insulation resistance. When the motor is determined to be in operation or maintenance state, the motor insulation monitoring device immediately stops DC injection, cuts off the DC test voltage applied to the motor windings, and sends a state switching signal to the online insulation monitoring and analysis panel. After receiving the status switching signal, the online insulation monitoring and analysis panel switches the insulation monitoring responsibility of the motor circuit from the motor insulation monitoring device to the system insulation monitoring device. The system insulation monitoring device then indirectly monitors the equivalent insulation status of the motor circuit through the leakage current of the branch where the motor is located or the bus insulation.

10. A multi-parameter integrated online insulation monitoring system that coordinates the system and the motor, characterized in that, include: At least one system insulation monitoring unit includes an effective grounding decoupling device and a system insulation monitoring device. The effective grounding decoupling device is connected in series between the neutral point of each bus section and the ground. The system insulation monitoring device measures the overall insulation resistance of the bus and the leakage current of each branch through the DC superposition method, and uploads the measurement data to the online insulation monitoring and analysis screen. Multiple motor insulation monitoring units are configured in high-voltage motors to acquire motor insulation resistance, leakage current, zero-sequence current, output voltage difference, absorption ratio, polarization index, identify motor operating status, automatically control the start and stop of DC injection based on the identified motor operating status, and upload the acquired motor insulation data and operating status data to the online insulation monitoring and analysis screen. The online insulation monitoring and analysis panel has a built-in weighted fusion evaluation model. It connects to all system insulation monitoring units and motor insulation monitoring units through an industrial communication network to perform data aggregation, insulation monitoring responsibility mode switching, weighted fusion evaluation, and intelligent decision-making. The back-end monitoring platform connects to the online insulation monitoring and analysis screen via an industrial communication network, providing a human-machine interface to display the insulation health index of the entire system, the comprehensive health index of each motor and its corresponding early warning level, the batch commissioning decision interface, and historical trends.

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