Motor insulation state monitoring method and device, computer equipment, readable storage medium and program product

Abstract

The invention relates to an insulation state monitoring method and device, computer equipment, a computer readable storage medium and a computer program product, relates to the technical field of insulation state monitoring, and can improve the accuracy of motor insulation state monitoring. The method comprises the following steps: receiving a monitoring demand for a motor; determining a plurality of target sensing paths from a plurality of candidate sensing paths used for acquiring different types of insulation state parameters according to monitoring requirements, and acquiring a plurality of target insulation state parameters through the target sensing paths; determining a plurality of insulation characteristics of the motor based on the plurality of target insulation state parameters, fusing the plurality of insulation characteristics, and determining an insulation degradation type according to the fused insulation characteristics; and displaying the insulation degradation type and the plurality of insulation state parameters corresponding to the insulation degradation type.

Description

Technical Field

[0001] This application relates to the field of insulation condition monitoring technology, and in particular to a method, apparatus, computer equipment, computer-readable storage medium, and computer program product for monitoring the insulation condition of an electric motor. Background Technology

[0002] Existing online monitoring technologies for motor insulation often rely on single-dimensional data and have fixed device functions. This not only creates data silos but also makes it difficult to accurately distinguish the types of insulation degradation, resulting in insufficient diagnostic reliability. Furthermore, many monitoring systems lack convenient on-site data display and interactive capabilities, hindering rapid assessment. Therefore, how to achieve localized and rapid presentation of monitoring results for accurate assessment of motor insulation status has become an urgent technical problem to be solved. Summary of the Invention

[0003] Therefore, it is necessary to provide an insulation condition monitoring method, device, computer equipment, computer-readable storage medium, and computer program product to address the aforementioned technical problems.

[0004] In a first aspect, this application provides an insulation condition monitoring method, comprising:

[0005] Receive monitoring requests for the motor;

[0006] Based on the monitoring requirements, multiple target sensing paths are determined from multiple candidate sensing paths used to obtain different types of insulation state parameters, and multiple target insulation state parameters are obtained through the target sensing paths.

[0007] Based on various target insulation state parameters, multiple insulation characteristics of the motor are determined, the multiple insulation characteristics are fused, and the insulation degradation type is determined based on the fused insulation characteristics.

[0008] The insulation degradation type and the corresponding insulation state parameters are displayed.

[0009] In one embodiment, determining multiple target sensing paths from multiple candidate sensing paths for acquiring different types of insulation state parameters according to the monitoring requirements includes:

[0010] If the monitoring requirements include motor type information or motor operating scenario information, then based on the motor type information or the motor operating scenario information, a matching parameter configuration recommendation strategy is determined, and in response to the user's confirmation operation of the parameter configuration recommendation strategy, multiple target sensing paths are determined from the candidate sensing paths;

[0011] If the monitoring requirement includes a desired sensing path, then it is determined whether the desired sensing paths meet a preset conflict condition. If the preset conflict condition is met, the desired sensing paths are filtered to determine the multiple target sensing paths that do not conflict. If the preset conflict condition is not met, then the desired sensing path is determined as one of the multiple target sensing paths.

[0012] In one embodiment, the acquisition of multiple target insulation state parameters through the target sensing path includes:

[0013] The module insertion guide page displays the interface positions of each of the target sensing paths on the current monitoring device; the interface positions are used to connect to the sensing modules, the sensing modules are used to collect target insulation status parameters, and the sensing modules store preset collection configuration parameters that can be configured.

[0014] When the detection device detects that each of the sensor modules is inserted into the corresponding interface position, the monitoring device identifies the preset acquisition configuration parameters in each of the connected sensor modules, and obtains the target insulation state parameters from each of the target sensing paths based on the preset acquisition configuration parameters.

[0015] In one embodiment, prior to receiving the monitoring request for the motor, the method further includes:

[0016] Set up a simulated motor operation scenario and the expected insulation state parameters corresponding to the simulated motor operation scenario;

[0017] The motor operation scenario is applied to the motor for simulation to determine the simulated insulation state parameters obtained by multiple candidate sensing paths;

[0018] The simulated insulation state parameters and the expected insulation state parameters corresponding to each candidate sensing path are compared to obtain the comparison error.

[0019] If the comparison error is within a preset error range, the candidate sensing path is retained; if the comparison error exceeds the preset error range, the candidate sensing path is eliminated.

[0020] In one embodiment, before acquiring multiple target insulation state parameters through the target sensing path, the method further includes:

[0021] The temperature monitored by the motor is obtained and displayed.

[0022] If the temperature is greater than or equal to a preset first temperature threshold and less than a preset second temperature threshold, then at least one built-in cooling fan is activated to perform air cooling operation; and,

[0023] If the temperature is greater than or equal to the preset second temperature threshold, then a backup heat dissipation channel is activated in the preset area to perform heat dissipation operation.

[0024] In one embodiment, after acquiring the temperature monitored by the motor, the method further includes:

[0025] The humidity of the external environment of the motor is obtained and displayed.

[0026] The humidity threshold for motor monitoring is determined based on the ambient humidity of the motor's external environment and the preset humidity threshold rules.

[0027] The humidity level monitored by the motor is obtained and displayed.

[0028] If the humidity is greater than the humidity threshold and the temperature is less than a preset first temperature threshold, then dehumidification is performed through a preset heating operation; and,

[0029] If the humidity is greater than the humidity threshold and the temperature is greater than the preset first temperature threshold, then condensation dehumidification is performed through a preset condensation operation.

[0030] Secondly, this application also provides an insulation condition monitoring device, comprising:

[0031] The monitoring requirement acquisition module is used to receive monitoring requirements for the motor.

[0032] An insulation state parameter acquisition module is used to determine multiple target sensing paths from multiple candidate sensing paths for acquiring different types of insulation state parameters according to the monitoring requirements, and to acquire multiple target insulation state parameters through the target sensing paths.

[0033] An insulation degradation type determination module is used to determine multiple insulation characteristics of the motor based on various target insulation state parameters, fuse the multiple insulation characteristics, and determine the insulation degradation type based on the fused insulation characteristics.

[0034] The visualization module is used to display the insulation degradation type and the multiple insulation state parameters corresponding to the insulation degradation type.

[0035] Thirdly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0036] Receive monitoring requests for the motor;

[0037] Based on the monitoring requirements, multiple target sensing paths are determined from multiple candidate sensing paths used to obtain different types of insulation state parameters, and multiple target insulation state parameters are obtained through the target sensing paths.

[0038] Based on various target insulation state parameters, multiple insulation characteristics of the motor are determined, the multiple insulation characteristics are fused, and the insulation degradation type is determined based on the fused insulation characteristics.

[0039] The insulation degradation type and the corresponding insulation state parameters are displayed.

[0040] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, performs the following steps:

[0041] Receive monitoring requests for the motor;

[0042] Based on the monitoring requirements, multiple target sensing paths are determined from multiple candidate sensing paths used to obtain different types of insulation state parameters, and multiple target insulation state parameters are obtained through the target sensing paths.

[0043] Based on various target insulation state parameters, multiple insulation characteristics of the motor are determined, the multiple insulation characteristics are fused, and the insulation degradation type is determined based on the fused insulation characteristics.

[0044] The insulation degradation type and the corresponding insulation state parameters are displayed.

[0045] Fifthly, this application also provides a computer program product, including a computer program that, when executed by a processor, performs the following steps:

[0046] Receive monitoring requests for the motor;

[0047] Based on the monitoring requirements, multiple target sensing paths are determined from multiple candidate sensing paths used to obtain different types of insulation state parameters, and multiple target insulation state parameters are obtained through the target sensing paths.

[0048] Based on various target insulation state parameters, multiple insulation characteristics of the motor are determined, the multiple insulation characteristics are fused, and the insulation degradation type is determined based on the fused insulation characteristics.

[0049] The insulation degradation type and the corresponding insulation state parameters are displayed.

[0050] The aforementioned insulation condition monitoring method, apparatus, computer equipment, computer-readable storage medium, and computer program product receive monitoring requests for motors, determine multiple target sensing paths from multiple candidate sensing paths for acquiring different types of insulation condition parameters based on the monitoring requests, acquire multiple target insulation condition parameters through the target sensing paths, determine multiple insulation characteristics of the motor based on the multiple target insulation condition parameters, fuse the multiple insulation characteristics, determine the insulation degradation type based on the fused insulation characteristics, and display the insulation degradation type and the corresponding multiple insulation condition parameters. In this application, by receiving monitoring requests for specific motors, a clear direction for the monitoring task and the premise of on-demand configuration are established. Based on this request, multiple target sensing paths highly relevant to the request are determined and activated from multiple candidate sensing paths to acquire multiple target insulation condition parameters. This makes the monitoring method highly flexible and scalable, enabling customized monitoring schemes for different motor types and operating conditions and comprehensive collection of multi-dimensional data. Subsequently, the method further extracts multiple key insulation features based on the acquired various target insulation condition parameters, and performs deep fusion analysis on these multi-source features. Based on the fused comprehensive features, the insulation degradation type is accurately determined, overcoming the limitations of single-parameter diagnosis and significantly improving the accuracy of fault diagnosis and the ability to identify complex degradation modes. Finally, by clearly and intuitively visualizing the diagnosed insulation degradation type and the relevant insulation condition parameters supporting the conclusion, efficient human-computer interaction is achieved. This allows maintenance personnel to quickly grasp the motor's health status and understand the diagnostic basis, thereby improving maintenance efficiency and the timeliness of decision-making, ultimately enhancing the accuracy of motor insulation condition monitoring. Attached Figure Description

[0051] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0052] Figure 1 This is a flowchart illustrating a method for monitoring the insulation status of a motor in one embodiment;

[0053] Figure 2 This is a flowchart illustrating the motor insulation condition monitoring method in another embodiment;

[0054] Figure 3 This is a structural block diagram of a motor insulation condition monitoring device in one embodiment;

[0055] Figure 4This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0056] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0057] In one embodiment, Figure 1 As shown, a method for monitoring the insulation status of a motor is provided. This embodiment illustrates the application of this method to a terminal (such as a monitoring device). It is understood that this method can also be applied to a server, and further to a system including both a terminal and a server, and is implemented through interaction between the terminal and the server. In this embodiment, the method includes the following steps:

[0058] Step S102: Receive monitoring requests for the motor.

[0059] The monitoring requirements can be defined with various information such as monitoring reasons, monitoring objects, and monitoring degree / in-depth. They can be structured data or unstructured instructions. In terms of operation, the monitoring requirements can be manually input by the user in the human-machine interface, automatically issued by the superior management system according to the preset maintenance plan, or automatically generated by the monitoring equipment itself based on the analysis of preliminary sensing information (such as motor starting current, basic vibration) or external environmental conditions (such as high humidity), and obtained by the monitoring equipment through its communication interface or human-machine interface module.

[0060] Step S104: Based on the monitoring requirements, determine multiple target sensing paths from multiple candidate sensing paths used to obtain different types of insulation state parameters, and obtain multiple target insulation state parameters through the target sensing paths.

[0061] The candidate sensing paths can be multiple alternative information acquisition channels pre-set within the motor insulation online monitoring equipment or dynamically identifiable and configurable, used to collect raw signals or related physical quantities of the insulation status of a specific type of motor. Each candidate sensing path can correspond to a specific sensing technology or monitoring principle (such as high-frequency current sensing, vibration sensing, temperature sensing, voltage sensing, acoustic sensing, electromagnetic field sensing, etc.) and is associated with the hardware resources (such as specific sensor interfaces, signal conditioning circuits, data acquisition interfaces, etc.) and parameter acquisition capabilities required to realize the sensing function.

[0062] The target sensing path can refer to multiple designated sensing paths selected by the current monitoring equipment from the set of candidate sensing paths based on the specific monitoring requirements received for the motor, and ultimately used to perform this motor insulation status monitoring task.

[0063] The target insulation status parameters can be various specific physical quantities or characteristic quantities that are actually collected and obtained through a determined target sensing path and can directly or indirectly reflect the current insulation health status of the monitored motor. For example, the pulse amplitude, occurrence rate, and phase distribution of partial discharge signals, the time-domain waveform and frequency-domain characteristics (such as amplitude and phase at a specific frequency) of vibration signals at the motor end or core, the amplitude and frequency components of shaft voltage or shaft current, winding temperature, ambient temperature and humidity, etc.

[0064] For example, upon receiving a monitoring request for a motor, the monitoring device can access its internally stored or dynamically queried candidate sensor path information. This information records the types of insulation condition parameters that can be collected for each candidate sensor path, the required resources, and possible applicable scenarios or constraints. Based on information such as motor type, fault mode of interest, and operating environment included in the monitoring request, the monitoring device uses preset matching logic or decision algorithms to filter and determine one or more target sensor paths most relevant to the current monitoring request. Subsequently, the monitoring device activates the sensing hardware (such as installed monitoring sensor modules or integrated sensor units) corresponding to these target sensor paths, configures their operating parameters, and initiates the data acquisition process to obtain various target insulation condition parameters corresponding to each target sensor path.

[0065] Step S106: Based on multiple target insulation state parameters, determine multiple insulation characteristics of the motor, fuse the multiple insulation characteristics, and determine the insulation degradation type based on the fused insulation characteristics.

[0066] Among them, insulation features can be quantitative indicators or feature patterns extracted from one or more target insulation state parameters through signal processing, pattern recognition or statistical analysis, which can more directly characterize a certain aspect of the insulation state of the motor or its changing trend.

[0067] Insulation degradation type refers to the main degradation mode or fault category of the motor insulation system as determined by the integrated insulation characteristics. This includes, but is not limited to, stator winding turn-to-turn short circuit, main insulation breakdown to ground, end corona discharge, insulation carbonization caused by local overheating of the iron core, moisture degradation, and wear discharge caused by mechanical loosening. It is used to provide motor maintenance personnel with clear fault diagnosis conclusions and guide subsequent maintenance strategies and decisions.

[0068] For example, after acquiring multiple target insulation state parameters, the monitoring equipment first uses its internal processing unit (which can be a dedicated algorithm module within an FPGA or IPC) to analyze and calculate these parameters to extract multiple insulation features that characterize the motor's insulation state. These insulation features may include, but are not limited to, time-domain statistics, frequency-domain features, time-frequency joint features, or specific mode parameters of each parameter. Subsequently, the monitoring equipment's processing unit (which may be an IPC industrial computer) uses a preset fusion strategy or algorithm model to synthesize the multiple insulation features extracted from parameters of different sources or natures. This fusion can be based on logical judgments according to predetermined rules, or it can be based on data-driven statistical models or machine learning models. Finally, based on the fused comprehensive insulation feature result, the monitoring equipment's IPC industrial computer determines the most likely type of insulation degradation of the current motor by comparing it with an internally stored fault feature library or by executing a classification decision algorithm.

[0069] Optionally, the monitoring equipment's IPC industrial computer utilizes a pre-trained deep neural network model (such as a convolutional neural network (CNN) or a recurrent neural network (RNN). Multidimensional insulation feature vectors or time series extracted from different target insulation state parameters are used as input to the neural network. Through its multi-layer nonlinear transformations and learned weights, the network directly outputs the classification probability for different insulation degradation types.

[0070] Optionally, the knowledge base stores typical insulation characteristic combinations or threshold ranges corresponding to various known insulation degradation types. Through pattern matching or threshold discrimination, the insulation degradation type that best matches the current fused characteristics is determined. For example, if the fused characteristics simultaneously show a significant increase in high-frequency partial discharge energy, abnormal specific vibration frequencies, and persistently high winding temperatures, it may be judged as the initial stage of an inter-turn short circuit.

[0071] Step S108 displays the insulation degradation type and the multiple insulation status parameters corresponding to the insulation degradation type.

[0072] For example, after determining the type of insulation degradation, the monitoring device will call its internal display processing function or communication output function to organize and output the insulation degradation type and multiple target insulation state parameters (or key insulation features extracted from these parameters) that are directly related to the determination of the degradation type or that the user has specified in the monitoring requirements to the configured display interface, or send them to a preset external receiving end through its communication interface.

[0073] Optionally, if the identified insulation degradation type has a clear spatial orientation (e.g., end discharge, loosening of a specific slot wedge), the monitoring device can display a simplified schematic diagram of the motor structure on its display screen, and mark the specific physical location where insulation degradation has occurred or is suspected to have occurred by means of highlighted areas, arrow indicators or superimposed icons, while annotating the relevant insulation status parameter values ​​next to it.

[0074] Alternatively, the monitoring equipment can also use auxiliary methods such as indicator lights on its display screen (e.g., different colored LEDs corresponding to different degradation levels or types) and sound alarms (emitting sounds of specific frequencies or patterns) to indicate the occurrence of insulation degradation types, especially when the on-site environment is not conducive to observing the screen.

[0075] Optionally, the monitoring equipment encapsulates the insulation degradation type and corresponding insulation status parameters into data packets conforming to a specific industrial communication protocol. While reporting the data to the upper-level control system through its network interface, it also displays the current communication status to achieve remote centralized monitoring, alarm, and data archiving.

[0076] In this embodiment, by receiving monitoring requests for a specific motor, a clear direction for the monitoring task and the premise of on-demand configuration are established. Based on this request, multiple target sensing paths highly relevant to the request are selected and activated from multiple candidate sensing paths to obtain various target insulation status parameters. This makes the monitoring method highly flexible and scalable, enabling customized monitoring schemes for different motor types and operating conditions, and comprehensive collection of multi-dimensional data. Subsequently, the method further extracts multiple key insulation features based on the acquired target insulation status parameters and performs deep fusion analysis on these multi-source features. Based on the fused comprehensive features, the insulation degradation type is accurately determined, overcoming the limitations of single-parameter diagnosis and significantly improving the accuracy of fault diagnosis and the ability to identify complex degradation modes. Finally, by clearly and intuitively visually displaying the diagnosed insulation degradation type and the relevant insulation status parameters supporting the conclusion, efficient human-computer interaction is achieved. This allows maintenance personnel to quickly grasp the motor's health status and understand the diagnostic basis, thereby improving maintenance efficiency and the timeliness of decision-making, thus improving the accuracy of motor insulation status monitoring.

[0077] In one exemplary embodiment, based on monitoring requirements, multiple target sensing paths are determined from multiple candidate sensing paths used to acquire different types of insulation state parameters, including:

[0078] If the monitoring requirement includes motor type information or motor operating scenario information, then a matching parameter configuration recommendation strategy is determined based on the motor type information or motor operating scenario information. In response to the user's confirmation operation of the parameter configuration recommendation strategy, multiple target sensor paths are determined from the candidate sensor paths. If the monitoring requirement includes a desired sensor path, then it is determined whether the desired sensor paths meet the preset conflict conditions. If the preset conflict conditions are met, the desired sensor paths are filtered to determine multiple target sensor paths without conflict. If the preset conflict conditions are not met, the desired sensor paths are determined as multiple target sensor paths.

[0079] Among them, motor type information can be data that can characterize the type, specifications, design characteristics or manufacturing process of the monitored motor, including but not limited to the motor's rated power, rated voltage, rated current and its specific application type (such as wind turbine, water pump motor, compressor motor, traction motor, etc.).

[0080] Motor operating scenario information can be data used to describe the motor's current or expected operating environment, load characteristics, operating mode, or external influencing factors. For example, whether the motor is operating in harsh environments such as high temperature, high humidity, high altitude, high dust, or corrosive gases; whether its load is constant, periodically changing, or randomly impactful; whether the motor frequently starts and stops; and whether there is strong external electromagnetic interference, etc.

[0081] The parameter configuration recommendation strategy is a mechanism that generates one or more suggested combinations of target sensing paths and their corresponding monitoring parameter configuration schemes for users, based on motor type information and / or motor operating scenario information, combined with built-in expert knowledge, historical data analysis or algorithm models.

[0082] The desired sensing path can be one or more sets of sensing paths that the user actively selects through the human-machine interface (display screen) or that are directly specified by the superior system for this motor monitoring task. The preset conflict conditions can be a set of rules or constraints that are predefined or stored within the monitoring equipment to determine whether there are incompatibilities or other problems between multiple desired sensing paths.

[0083] Specifically, when the monitoring device receives a monitoring request for a motor that includes motor type information and / or motor operating scenario information, the monitoring device will query its built-in decision logic based on this received information to determine one or more matching parameter configuration recommendation strategies. For example, its decision logic may include rules: for high-voltage motors, common fault points are stator winding ends and slot insulation, so monitoring partial discharge and winding temperature is recommended; furthermore, for high salt spray environments, insulation surfaces are prone to moisture and corrosion, so adding shaft voltage / shaft current monitoring to assess bearing insulation condition and real-time monitoring of internal humidity is recommended. Based on this, the monitoring device may generate a recommended strategy, suggesting the activation of high-frequency partial discharge sensing paths, winding temperature sensing paths, shaft voltage / shaft current sensing paths, and internal humidity sensing paths. This strategy can further refine the recommended sensor models, sampling frequencies, and preliminary alarm thresholds. Subsequently, the monitoring device will present this parameter configuration recommendation strategy to the user (e.g., displaying the recommended monitoring items and reasons in a list on the display screen). When the monitoring device receives confirmation from the user regarding the recommended strategy for configuring the parameter (for example, the user clicks the "Apply this recommendation" button, or makes minor adjustments based on the recommendation and confirms it), it determines the sensor paths included in the strategy from its multiple candidate sensor paths as the multiple target sensor paths for this monitoring task.

[0084] Specifically, when the monitoring equipment receives a monitoring request for the motor that directly includes the user-specified desired sensing paths (for example, the user manually selects sensing path A - partial discharge monitoring, sensing path B - end vibration monitoring, and sensing path C - rotor inter-turn short circuit monitoring through its human-machine interface), the monitoring equipment will first check whether there are any conflicts or non-compliance with preset operating conditions among these user-specified sensing paths. The preset conflict conditions may cover various types, such as physical interface conflicts (e.g., the number of selected modules exceeds the existing slots), resource contention conflicts (e.g., insufficient processing or storage bandwidth to support simultaneous operation of all high sampling rate paths), electrical conflicts (e.g., insufficient or unstable power supply), signal interference conflicts (e.g., electromagnetic fields generated by a module during operation interfere with the acquisition of other high-sensitivity signals), functional redundancy or contradictory conflicts (e.g., selecting path combinations with different principles but similar target parameters and no gain), and safety condition conflicts (e.g., certain close-contact sensing paths are not allowed to be used under specific high-risk conditions of the motor).

[0085] After performing the aforementioned conflict checks, if the monitoring device determines that these desired sensing paths meet at least one preset conflict condition, it will filter these desired sensing paths. Filtering methods may include prompting the user with conflict details and asking them to reselect, automatically eliminating lower-priority paths from the conflicts based on preset priorities, attempting to adjust the sensing path operating parameters to resolve resource conflicts, or eliminating paths if the conflict cannot be resolved. Finally, the monitoring device will determine the remaining conflict-free sensing paths after filtering as multiple target sensing paths. Conversely, if it determines that these desired sensing paths do not meet any preset conflict conditions—that is, all desired paths are mutually compatible and meet operating conditions—the monitoring device will directly determine the user-specified desired sensing paths as multiple target sensing paths for this monitoring task.

[0086] In this embodiment, through the above steps, the monitoring device can proactively provide professional and targeted parameter configuration recommendation strategies, which greatly simplifies the user's operation difficulty and reduces the risk of poor monitoring results due to improper configuration. At the same time, it can effectively avoid hardware resource conflicts, signal interference, functional redundancy or security issues caused by improper sensor path combinations, ensuring the feasibility of the selected combination and the reliability of the monitoring data.

[0087] In one exemplary embodiment, multiple target insulation state parameters are obtained through the target sensing path, including:

[0088] The module insertion guide page displays the interface locations of multiple target sensing paths on the current monitoring device. The interface locations are used to connect sensing modules, which are used to collect target insulation status parameters. The sensing modules store preset acquisition configuration parameters that can be configured. When each sensing module is detected to be inserted into the corresponding interface location, the monitoring device identifies the preset acquisition configuration parameters in each connected sensing module and obtains the target insulation status parameters from each target sensing path based on the preset acquisition configuration parameters.

[0089] The module insertion guidance page can be a visual auxiliary display interface provided to users on the human-machine interface of the motor insulation online monitoring equipment, guiding them on how to correctly install or replace different sensor modules to the corresponding interface positions. This page can dynamically highlight the interface positions where modules need to be inserted based on multiple currently determined target sensor paths, or provide the interface number, type, functional description, and module correspondence.

[0090] Interface locations can be standardized slots or connection ports reserved on the motor insulation online monitoring equipment for physical connection and electrical communication of specific sensor modules. These interfaces can take the form of aviation plugs, PCI-E slots, USB interfaces, or manufacturer-defined dedicated connectors to enable fast, stable access to sensor modules and reliable data transmission. Each interface location is associated with one or more potential candidate sensing paths within the device.

[0091] A sensing module can be a pluggable hardware unit that integrates specific sensors and corresponding signal conditioning circuits. Its core function is to selectively acquire one or more target insulation state parameters of the motor. Examples include partial discharge sensing modules, vibration sensing modules, temperature sensing modules, shaft voltage / shaft current sensing modules, and rotor inter-turn short circuit monitoring modules. These modules, as the physical carriers for realizing the key functions of the target sensing path, can convert specific physical quantities of the motor (such as high-frequency current pulses, mechanical vibration, temperature, etc.) into electrical signals that can be further processed by the monitoring equipment.

[0092] Specifically, to assist users in correctly installing the physical sensor modules corresponding to the selected multiple target sensing paths, the monitoring equipment activates and displays a module insertion guide page on its human-machine interface (e.g., a 7-inch industrial display). This guide page clearly indicates which specific interface location on or inside the monitoring equipment's chassis panel should be inserted for each target sensing path. For example, the guide page might graphically display the layout of the equipment's back panel and highlight, flash, or mark the available slots (such as aviation connectors or PCI-E interfaces) where sensor modules need to be installed using highlighting, flashing, or arrows. It might also display recommended sensor module models or images to prevent incorrect insertion. These interface locations are designed with a standardized structure to facilitate quick and secure physical and electrical connections between different types of sensor modules.

[0093] Each sensor module to be inserted is designed as a plug-and-play unit capable of acquiring specific target insulation state parameters, and internally stores its preset acquisition configuration parameters. These parameters are set at the factory or updated during subsequent calibration, and include the module's identification information (such as module ID, type, and version), the sensor's specific specifications, recommended operating mode, data output format, and necessary calibration coefficients. When the user inserts each sensor module into its corresponding interface position according to the instructions on the module insertion guide page, the monitoring device will detect this event in real time through an interface detection mechanism (e.g., detecting changes in the interface connection status or through a specific handshake protocol).

[0094] Once a new sensor module is detected, the monitoring device immediately communicates with it via the communication bus connected to the interface location to identify the preset acquisition configuration parameters of each connected sensor module. For example, the device reads information from the module's storage chip to parse the module's type, ID, supported sampling rate range, default gain setting, etc. After obtaining these preset acquisition configuration parameters, the monitoring device automatically configures or fine-tunes the module based on these parameters and the overall monitoring requirements, and ultimately obtains the target insulation state parameters from each target sensing path based on the preset acquisition configuration parameters. This means that the device instructs the sensor module to start working according to the identified or negotiated configuration (such as a specific sampling rate and filter bandwidth), collect the insulation state parameters it is responsible for, and transmit the data to the subsequent processing unit inside the monitoring device.

[0095] In this embodiment, the above steps achieve a high degree of intelligence in the plug-and-play or plug-and-configure capability of the sensing module. Since the sensing module itself carries key configuration parameters, the monitoring device can automatically identify and adapt after the module is connected, which greatly simplifies the complexity of system configuration and shortens the system deployment and debugging time; thereby ensuring the accuracy and consistency of the target insulation state parameters obtained from each target sensing path.

[0096] In one exemplary embodiment, before receiving a monitoring request for the motor, the method further includes:

[0097] Set up a simulated motor operation scenario and the corresponding expected insulation state parameters; apply the motor operation scenario to the motor for simulation to determine the simulated insulation state parameters obtained by multiple candidate sensing paths; compare the simulated insulation state parameters and expected insulation state parameters corresponding to each candidate sensing path to obtain the comparison error; if the comparison error is within the preset error range, the candidate sensing path is retained; if the comparison error exceeds the preset error range, the candidate sensing path is eliminated.

[0098] The simulated motor operating scenario refers to the operating conditions of one or more motor operating states that are artificially set or reproduced to verify the effectiveness of candidate sensing paths, in order to determine the ideal or known response of the insulation state parameters that the motor may generate under these operating conditions. The expected insulation state parameters are the ideal values ​​of the motor insulation state parameters that each candidate sensing path should be able to accurately acquire or reflect under a given simulated motor operating scenario, theoretically or through measurement using high-precision reference equipment. The comparison error can be the difference or degree of deviation obtained by quantitatively comparing the simulated insulation state parameters obtained by a specific candidate sensing path during the simulation process with its corresponding expected insulation state parameters.

[0099] Specifically, the monitoring equipment instructs its internal signal generation unit to inject simulated signals into the input of the candidate sensing path to be verified; or, if the monitoring equipment is connected to an external motor fault simulation test bench, it controls the test bench to reproduce the set motor operating conditions and allows the sensors (such as vibration sensors and temperature sensors) installed on the test bench motor corresponding to the candidate sensing paths to perform actual measurements. During this process, each candidate sensing path being tested will acquire and output its simulated insulation state parameters. For example, the rotor inter-turn short circuit monitoring path will output the measured differential mode current amplitude and phase, and the partial discharge monitoring path will output the characteristics of the acquired pulse signals.

[0100] Next, the monitoring device compares the simulated insulation state parameters acquired by each candidate sensing path with the corresponding preset expected insulation state parameters under the simulated motor operating scenario, thereby calculating the comparison error. For example, for the rotor inter-turn short circuit monitoring path, the measured differential mode current amplitude is compared with the expected amplitude range to calculate the percentage deviation; for the partial discharge monitoring path, the acquired pulse amplitude and repetition rate are compared with the set values ​​of the standard source to calculate the error. In some embodiments, if the comparison error is a vector or a complex data structure, its norm or the deviation of key features may be calculated.

[0101] Finally, the monitoring device processes these comparison errors according to preset judgment rules. For example, in some embodiments, if the relative error of the differential mode current amplitude is less than 5% and the phase error is less than 2 degrees, the candidate sensing path for rotor inter-turn short circuit is qualified; if the amplitude error of the acquired partial discharge pulse is less than 10% and the repetition rate error is less than 5%, the candidate sensing path for partial discharge is qualified. If the comparison error of a candidate sensing path is within the preset allowable error range, the monitoring device marks it as qualified or usable and retains it in the candidate sensing path list for subsequent selection according to actual monitoring needs. Conversely, if the comparison error of a candidate sensing path exceeds the preset error range, the monitoring device marks it as unqualified or faulty and removes it from the list of usable candidate sensing paths, or at least provides a warning when the user selects it, or even prohibits its selection until it is repaired or calibrated.

[0102] In this embodiment, by introducing a simulated actual operating scenario and quantifying the error comparison method, this verification is not just a simple continuity test, but a deep verification of the accuracy and reliability of the sensing path. This ensures the measurement accuracy of the sensing path under near-real operating conditions and improves the quality and reliability of the raw data obtained from subsequent online monitoring of motor insulation.

[0103] In an exemplary embodiment, before acquiring various target insulation state parameters via the target sensing path, the method further includes:

[0104] The system acquires and displays the temperature monitored by the motor; if the temperature is greater than or equal to a preset first temperature threshold and less than a preset second temperature threshold, it starts at least one built-in cooling fan to perform air cooling operation; and if the temperature is greater than or equal to the preset second temperature threshold, it activates a backup cooling channel in a preset area to perform cooling operation.

[0105] The temperature monitored by the motor can be the surface temperature of key electronic components (such as PCB motherboard, processor, signal acquisition module, etc.) inside the motor insulation online monitoring equipment, or the ambient temperature inside its chassis. The preset first temperature threshold can refer to a lower temperature critical value set inside the monitoring equipment. When the internal temperature of the equipment reaches or exceeds this threshold but has not yet reached a higher danger threshold, the first-level heat dissipation response (such as starting the fan) will be triggered.

[0106] The preset second temperature threshold can be a higher temperature critical value set by the monitoring device, which is higher than the preset first temperature threshold. When the internal temperature of the device reaches or exceeds this threshold, it indicates that the conventional fan cooling alone is insufficient to control the temperature rise, and stronger or backup cooling measures need to be activated to prevent the device from being damaged or malfunctioning due to severe overheating.

[0107] Backup heat dissipation channels can be additional or enhanced heat dissipation paths or mechanisms in monitoring equipment, besides conventional fan cooling, activated under specific high-temperature conditions. This may include, but is not limited to: activating additional, more powerful fan sets; opening special vents that are normally closed to create a more direct airflow path; or, for specific preset areas of the monitoring equipment, such as data processing (FPGA+IPC section) and signal acquisition (sensor modules or sensor paths), adjusting the temperature of these specific preset areas according to preset control rules.

[0108] Specifically, the monitoring equipment can be configured with a high-resolution infrared thermal imager (e.g., with a resolution of no less than 256×192 pixels) to perform non-contact, global, real-time scanning and monitoring of the surface temperature distribution of key electronic components inside the equipment, especially printed circuit boards (PCBs), thereby obtaining accurate temperature data and thermal maps of the temperature field. The acquired current internal temperature or the highest temperature information of a specific area is then displayed on the monitoring equipment's human-machine interface, for example, in the form of digital readings, color-coded thermal maps, or temperature change curves, allowing maintenance personnel to intuitively understand the real-time thermal status of the equipment.

[0109] Secondly, the monitoring device executes tiered heat dissipation control logic based on the acquired internal temperature and its preset internal temperature thresholds. For example, when the internal temperature T of the monitoring device is greater than or equal to a preset first temperature threshold (e.g., 50°C) and less than a preset second temperature threshold (e.g., 70°C), i.e., 50°C ≤ T < 70°C, the monitoring device will activate at least one built-in cooling fan to perform active air cooling. These fans will accelerate the airflow inside the chassis, carrying heat away from the surface of heat-generating components and expelling it through the vents to maintain stable operation of the device within this temperature range. When the temperature is below the first temperature threshold (e.g., T < 50°C), the device can primarily rely on natural convection for heat dissipation. In this case, the fans may not be activated or may operate at a lower speed to achieve energy saving and noise reduction.

[0110] Finally, if the internal temperature T of the monitoring device continues to rise, reaching or exceeding a preset second temperature threshold (e.g., 70°C), i.e., T≥70°C, it indicates that conventional built-in fan cooling alone is insufficient to effectively control the temperature rise. In this case, the monitoring device will activate a backup heat dissipation channel within a preset area to perform enhanced cooling operations. The preset area can be defined according to the principle of heat dissipation channel zoning control, prioritizing areas with high heat generation or high temperature sensitivity, such as the data processing area (which may contain high-power chips like the CPU and FPGA) or the signal acquisition area (which may contain temperature-sensitive components like the ADC and analog front-end circuitry). Activating the backup heat dissipation channel can involve starting additional auxiliary fan groups, opening normally closed enhanced vents, or adjusting the internal airflow structure to optimize cooling airflow to these critical areas. This ensures that even under high internal temperature conditions, the core components of the device receive sufficient heat dissipation, preventing performance degradation, data errors, and even hardware damage due to overheating.

[0111] In this embodiment, by accurately sensing and visualizing the operating temperature of the monitoring device in real time, and by setting multiple temperature thresholds and linking different heat dissipation mechanisms, a dynamic and efficient temperature control strategy is constructed. This strategy can significantly reduce the temperature fluctuation range of electronic components (e.g., from ±15℃ to ±3℃), thereby extending the service life of key components such as PCBs (e.g., by more than 2 times). It effectively avoids problems such as monitoring data drift, performance degradation, or even shutdown caused by uncontrolled internal temperature rise of the device, and ensures the continuity and reliability of online monitoring of motor insulation.

[0112] In one exemplary embodiment, after obtaining the temperature monitored by the motor, the method further includes:

[0113] The system acquires and displays the ambient humidity outside the motor; determines the humidity threshold for motor monitoring based on the ambient humidity and a preset humidity threshold rule; acquires and displays the humidity monitored by the motor; if the humidity is greater than the humidity threshold and the temperature is less than the preset first temperature threshold, it performs dehumidification through a preset heating operation; and if the humidity is greater than the humidity threshold and the temperature is greater than the preset first temperature threshold, it performs dehumidification through a preset condensation operation.

[0114] The preset humidity threshold rules can be a set of logical rules or mapping relationships stored inside the monitoring equipment. These rules are used to dynamically determine the allowable humidity threshold for motor monitoring (i.e., the humidity control target inside the enclosure) based on the acquired external ambient humidity. The preset heating operation can be a dehumidification method initiated by the monitoring equipment under specific temperature and humidity conditions (high humidity and low temperature), which increases the saturated water vapor pressure of the air by raising the temperature of the heating element, reducing relative humidity, and preventing condensation. The preset condensation operation can be a dehumidification method initiated by the monitoring equipment under specific temperature and humidity conditions, which lowers the temperature of a specific cooling surface to condense water vapor in the air into liquid water and discharge it, possibly supplemented by forced ventilation to accelerate the exchange of humid air.

[0115] Specifically, the monitoring equipment acquires the ambient humidity outside the motor through its configured humidity sensor, such as a humidity sensor integrated into the device's external interface. The acquired ambient humidity value is displayed on the monitoring equipment's human-machine interface, allowing users to understand the external environmental conditions. More importantly, the monitoring equipment determines the humidity threshold for motor monitoring based on the ambient humidity and preset humidity threshold rules. For example, when the detected ambient humidity is below 60%RH, the internal allowable humidity threshold is set to no higher than 40%RH; conversely, when the ambient humidity reaches or exceeds 60%RH, the internal humidity threshold is automatically adjusted to a stricter no higher than 30%RH. This dynamic adjustment mechanism ensures that the internal humidity control target adapts to changes in the external environment.

[0116] Meanwhile, the monitoring equipment acquires the humidity monitored by the motor in real time (i.e., the actual humidity inside the equipment chassis) through the installed humidity sensor, and displays this internal humidity value on its human-machine interface. Based on this actual internal humidity, a dynamically determined internal humidity threshold, and the internal temperature of the equipment obtained in the above steps, the monitoring equipment performs temperature and humidity coordinated dehumidification control. Specifically, when the monitoring equipment determines that its actual internal humidity is greater than the dynamically determined humidity threshold, and the temperature monitored by its motor is less than a preset first temperature threshold for determining whether to start heating dehumidification (which may correspond to the critical temperature at which condensation may occur, such as the dew point temperature), the monitoring equipment performs heating dehumidification through a preset heating operation. For example, it activates the PTC heating element installed inside the equipment, heating it to a specific temperature (such as 50°C) to increase the ambient air temperature, reduce relative humidity, and evaporate potential condensation.

[0117] Furthermore, when the monitoring device determines that the actual internal humidity is still greater than the dynamically determined humidity threshold, but the internal temperature is greater than another preset first temperature threshold used to determine the activation of condensation dehumidification (which may correspond to a relatively high temperature point, such as 40°C, at which point heating dehumidification may not be the optimal choice or may be ineffective), the monitoring device will perform condensation dehumidification through a preset condensation operation. For example, it may activate the internal micro-semiconductor cooling chip or other small cooling unit to form a condensation surface, causing water vapor in the air to condense on the surface, and may simultaneously activate the internal fan for forced ventilation, extracting humid air and introducing dry air to accelerate the dehumidification process. By using different dehumidification strategies for different temperature zones in this way, the internal humidity of the equipment can be controlled more efficiently and energy-savingly.

[0118] In this embodiment, by combining real-time temperature and humidity data inside the equipment, precise heating dehumidification or condensation dehumidification operations are performed based on different operating conditions. This ensures that moisture inside the equipment can be effectively suppressed or removed under different temperature and humidity combinations, preventing condensation. Ultimately, this significantly improves the operational reliability and long-term stability of the online motor insulation monitoring equipment in humid environments, effectively avoiding problems such as corrosion of electronic components, short circuits, and signal acquisition distortion caused by excessive internal humidity. This further ensures the accuracy of monitoring data and the safety of the equipment itself, enhancing its adaptability to harsh environments.

[0119] In an exemplary embodiment, this application provides an online monitoring method for the insulation status of a motor and a monitoring device driven by the method. To make the objectives, technical solutions, and advantages of this invention clearer, the technical solution of this invention will be described in detail below with reference to a preferred embodiment. It should be understood that this specific embodiment is only used to explain this invention and is not intended to limit the scope of protection of this invention. In this embodiment, the various operations are mainly performed by the monitoring device, whose hardware architecture adopts a four-level layered design, including a hardware access layer (supporting rapid module plug-in and plug-out, for example, using aviation plugs and PCI-E bus technology), a data processing layer (containing a dual processing center composed of an FPGA processor and an IPC industrial computer, with the FPGA undertaking approximately 90% of signal preprocessing and the IPC focusing on high-order algorithms), a device self-test layer (integrating a thermal imaging system and a standard analog partial discharge signal source, etc.), and a status display layer (configured with, for example, a 7-inch industrial touch screen), all encapsulated in a chassis with good electromagnetic shielding performance and protection level (such as ABS material).

[0120] In one specific embodiment, for example, when comprehensive online insulation status monitoring and health management of a critical large asynchronous motor installed on an offshore drilling platform in harsh environmental conditions (such as high salt spray, high humidity, and large temperature variations) is required, the user inputs the monitoring requirements for the motor via the industrial touchscreen display of the monitoring equipment before monitoring begins. This includes selecting a high-risk continuous monitoring mode and entering the motor's unique identification code. The equipment will also acquire the current external ambient humidity and temperature through its integrated environmental sensors. This information will serve as the basis for subsequent environmental control and adjustments to some monitoring strategies.

[0121] In one exemplary embodiment, the workflow steps of the monitoring device may be as follows: Figure 2 As shown, it specifically includes the following:

[0122] Step S201: Upon receiving the monitoring request, the monitoring device pre-verifies the available candidate sensor paths before formally configuring them. Specifically, for partial discharge (PD) monitoring paths, the device activates its built-in standard analog PD signal source, injecting a pulse train with known amplitude and repetition rate as the expected signal into the path. Then, it compares the error between the actual acquired and processed signal and the expected signal. If the error exceeds a preset allowable range (e.g., amplitude error greater than 5%), the PD sensing path is marked as needing calibration or faulty and temporarily removed from the currently available list or its recommended priority is reduced. Similarly, for other types of candidate sensor paths, such as vibration sensing paths and temperature sensing paths, validity verification and screening can be performed by connecting an external calibration signal source or utilizing other internal self-testing mechanisms (such as applying specific excitation to the sensor and checking the response) to ensure that all sensor paths participating in subsequent monitoring are in good working order.

[0123] In step S202, the monitoring equipment, based on the received and confirmed monitoring requirements (including the motor type being a large asynchronous motor and the operating scenario being a high-humidity, high-salt-fog environment like a marine platform), determines multiple target sensor paths from the pre-verified candidate sensor paths to perform the monitoring task. At this point, the equipment queries its internally stored expert knowledge base or executes a built-in decision algorithm to generate a parameter configuration recommendation strategy for the current operating condition. For example, considering the stringent insulation requirements of the marine platform environment and common fault modes of large asynchronous motors, the recommended strategy might prioritize enabling: a high-frequency partial discharge sensor path (for detecting internal and surface discharges), a multi-point triaxial vibration sensor path (for monitoring mechanical loosening, imbalance, and abnormal electromagnetic vibration), a composite shaft voltage and shaft current monitoring sensor path, and temperature sensing paths for key motor components (such as stator windings and bearings) and the equipment's own internal environment (temperature and humidity) monitoring path. This recommended strategy, along with the specific sensor module types suggested (such as salt spray resistant UHF partial discharge sensors, high-precision IEPE accelerometers, non-contact infrared temperature sensors, pluggable PTC heating and condensation dehumidification modules, etc.) and their recommended physical interface locations on the device panel (e.g., specific numbered aviation plugs or high-bandwidth PCI-E slots), will be clearly and intuitively displayed to maintenance personnel on a touch screen through a module insertion guide page.

[0124] Maintenance personnel can accept this recommendation or adjust it based on experience or specific concerns (e.g., recently suspecting a problem with a certain phase winding of the motor and wanting to strengthen the inter-turn short circuit monitoring of that phase), manually adding or removing certain desired sensing paths. Before final confirmation, the monitoring equipment will perform a preset conflict condition check on the selected sensing path combination. For example, it will check whether the total power consumption of the selected modules exceeds the internal power margin, whether the required data processing bandwidth will overload the FPGA or IPC, or whether there is physical interference or signal crosstalk at the installation locations of certain sensors. If a conflict is detected, the equipment will issue an alarm and suggest modifying the scheme, or automatically adjust according to preset optimization rules (e.g., selecting the combination with the least resource consumption while meeting the core monitoring objectives) until a conflict-free and efficient multi-target sensing path scheme is formed. After the scheme is determined, maintenance personnel should follow the instructions on the guide page to firmly insert the corresponding sensing modules (each module has its own ID, type, calibration data, recommended sampling rate, filter settings, and other configurable preset acquisition configuration parameters permanently stored in its internal non-volatile memory) into the designated interface position on the equipment. Once the monitoring equipment detects successful module insertion via the interface, it immediately communicates with the newly connected module through an internal bus (such as I2C, SPI, or PCI-E) to read and identify the preset acquisition configuration parameters stored internally. Based on these parameters and the current overall monitoring requirements, the equipment automatically initializes and configures the operating parameters of each sensing module (e.g., setting an acquisition window synchronized with the power grid frequency for the partial discharge module, and setting a characteristic frequency analysis range for the motor's rated speed for the vibration module). Subsequently, it instructs these modules to start working, thereby acquiring multiple target insulation state parameters in real time from multiple activated target sensing paths in parallel or in an optimized sequence. All acquired data is precisely correlated with timestamps and aggregated.

[0125] In step S203, after acquiring the original multiple target insulation state parameters, the FPGA and IPC dual processing centers of the monitoring equipment work together to determine the insulation state characteristics and, based on these characteristics, determine the current insulation state type. First, the FPGA undertakes most of the signal preprocessing tasks, such as digital filtering, pulse identification and extraction of high-frequency partial discharge signals, and time-domain statistics and preliminary FFT transformation of vibration signals to reduce the computational burden on the IPC, and extracts multiple preliminary insulation characteristics in real time. For example, features such as maximum discharge amplitude, number of discharges per unit time, discharge energy, and discharge phase concentration are extracted from the partial discharge data; features at power frequency, harmonics, and other characteristic frequencies are extracted from the vibration data; AC / DC components and specific harmonic content are extracted from the shaft voltage / current data; and average temperature, temperature rise rate, and multi-point temperature difference are calculated from the temperature data. These preliminarily refined insulation characteristics are then sent to the IPC. The IPC then focuses on executing more complex, high-order fusion algorithms and intelligent diagnostic logic. It integrates and analyzes multiple heterogeneous insulation features from different sensing paths (e.g., combining partial discharge features, vibration features, temperature features, and shaft voltage / current features). The fusion method can be a multi-level decision-making process. For example, it first uses a Bayesian network-based model to preliminarily determine whether there are anomalies. If so, it further calls upon a deep learning model or a complex expert rule base pre-trained with a large number of motor fault cases and expert knowledge to perform pattern recognition and deep mining on these fused features to distinguish the specific type and severity of insulation degradation.

[0126] Based on the results of integrating insulation condition characteristics, the monitoring equipment's IPC ultimately determines the most likely type of insulation degradation in the current motor. For example, the diagnostic conclusion might be: early corona discharge has occurred in the stator winding end insulation, accompanied by slight signs of slot wedge loosening; degradation level: moderate; monitoring and planned inspection in the near future are recommended. In determining the degradation type, the IPC also comprehensively considers the changing trends of various insulation characteristics over time (by comparing and analyzing data with historical databases, calculating growth rates, fluctuations, etc.), as well as the degree of deviation from the benchmark model of a healthy motor of the same type, to improve the accuracy of the diagnosis and the judgment of the degradation development stage.

[0127] In step S204, after determining the insulation degradation type of the motor, the monitoring equipment provides a visual display based on the insulation degradation type. The displayed content will highlight the diagnostic conclusion in a prominent manner (such as alarm pop-ups or color differentiation). To facilitate understanding and decision-making by maintenance personnel, the interface will also simultaneously display in detail the current values, historical trends, and comparisons with alarm thresholds of multiple insulation status parameters directly related to the diagnostic conclusion in various forms such as numerical values, trend curves, bar graphs, spectrum graphs, or dashboards. Furthermore, it can highlight the physical location of suspected faults or degradation on a simplified motor structure diagram. For example, it will display the partial discharge parameters that lead to the judgment of end corona discharge and the vibration spectrum characteristics indicating slot wedge loosening.

[0128] In addition, the device's self-test dashboard clearly displays the monitoring equipment's various operating statuses, including power supply voltage, connection and operating status of each sensor module, temperature of the main internal chips, storage space usage, current network connection status, and ongoing temperature and humidity control actions. Important diagnostic conclusions, raw data summaries, and equipment status information are also pushed in real-time to a remote monitoring center server or cloud platform via its configured Ethernet interface using industrial IoT protocols such as OPCUA or MQTT. This facilitates centralized data analysis, fault alarm management, maintenance work order dispatch, and the establishment of long-term health records. If the diagnosed degradation type or parameter exceeds the preset critical level, the equipment will also trigger a local audible and visual alarm, alerting on-site personnel to pay immediate attention.

[0129] Step S205: The monitoring device continuously monitors and adjusts its own operating environment. It uses a built-in infrared thermal imager (e.g., resolution not less than 256×192) to monitor the temperature distribution of its internal PCB board in real time and displays the temperature information (such as real-time temperature values ​​and temperature field thermal maps) on its screen. If the internal temperature T reaches or exceeds a preset first temperature threshold (e.g., 50℃) but is below a second temperature threshold (e.g., 70℃), the device automatically starts the internal cooling fan for forced air cooling. If the temperature T reaches or exceeds the second temperature threshold (e.g., 70℃), in addition to the fan running at full speed, it also activates backup heat dissipation channels for critical heat-generating areas (such as data processing areas and signal acquisition areas), for example, by opening specific vents or activating auxiliary heat dissipation devices, to ensure that core electronic components operate at a safe temperature. Simultaneously, the device also determines the current allowable upper limit of internal humidity based on the acquired external ambient humidity (e.g., previously recorded 85%RH) and the preset internal humidity threshold rules (e.g., when the external humidity is ≥60%RH, the internal humidity setting should be ≤30%RH). The device uses an internal humidity sensor to monitor the actual humidity inside the chassis in real time (e.g., currently 55% RH, exceeding the 30% RH limit), and combines this with internal temperature for coordinated dehumidification: if the internal temperature is low (e.g., below the preset dew point temperature), the internal PTC heating element is activated (e.g., heated to 50°C) for heating and dehumidification; if the internal temperature is relatively high (e.g., above 40°C), the internal condensation dehumidification module is activated in conjunction with forced ventilation for dehumidification. The device's own temperature and humidity control status is also displayed on the interface.

[0130] In this embodiment, by adopting a modular and reconfigurable hardware architecture, an intelligent multi-parameter fusion diagnostic algorithm, and an intuitive status visualization interaction system, and integrating an advanced intelligent control mechanism for the device's own operating environment, many pain points of traditional motor insulation monitoring devices in terms of flexibility, diagnostic reliability, operation and maintenance efficiency, and environmental adaptability are successfully overcome. Specifically, this invention significantly enhances the flexibility and scalability of the monitoring system, allowing users to freely select and quickly replace monitoring modules based on different motor types and operating conditions, and shortens configuration time through quick-plug interfaces. Through multi-dimensional data fusion analysis (e.g., combining information from multiple sources such as partial discharge, vibration, and temperature) and hardware self-testing functions, it greatly improves the accuracy and reliability of fault diagnosis and increases the efficiency of fault tracing. By directly displaying key diagnostic conclusions and related parameters through a local visualization interface, and combining it with early warning mechanisms such as thermal imaging temperature control, it achieves a significant breakthrough in operation and maintenance efficiency, reducing reliance on the backend system and on-site fault diagnosis time. Simultaneously, through a dynamic temperature and humidity collaborative control strategy, it optimizes the working environment of internal electronic components, significantly reducing the temperature fluctuation range of components, effectively extending the service life of equipment (such as PCBs) and improving long-term operational stability, reducing electromagnetic interference, and improving the signal-to-noise ratio of signal acquisition. Ultimately, through the above collaborative innovations, it comprehensively reduces the overall operation and maintenance cost of the motor insulation online monitoring system, providing strong technical support for ensuring the safe, efficient, and economical operation of motor equipment.

[0131] It should be understood that although the steps in the flowcharts of the above embodiments are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the above embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0132] Based on the same inventive concept, this application also provides an insulation condition monitoring device for implementing the insulation condition monitoring method described above. The solution provided by this device is similar to the solution described in the above method; therefore, the specific limitations in one or more insulation condition monitoring device embodiments provided below can be found in the limitations of the insulation condition monitoring method described above, and will not be repeated here.

[0133] In one exemplary embodiment, such as Figure 3As shown, an insulation condition monitoring device is provided, including: a monitoring requirement acquisition module 310, an insulation condition parameter acquisition module 320, an insulation degradation type determination module 330, and a visualization display module 340, wherein:

[0134] The monitoring requirement acquisition module 310 is used to receive monitoring requirements for the motor;

[0135] The insulation state parameter acquisition module 320 is used to determine multiple target sensing paths from multiple candidate sensing paths for acquiring different types of insulation state parameters according to the monitoring requirements, and to acquire multiple target insulation state parameters through the target sensing paths.

[0136] The insulation degradation type determination module 330 is used to determine multiple insulation characteristics of the motor based on multiple target insulation state parameters, fuse the multiple insulation characteristics, and determine the insulation degradation type based on the fused insulation characteristics.

[0137] The visualization module 340 is used to display the insulation degradation type and the multiple insulation state parameters corresponding to the insulation degradation type.

[0138] In one embodiment, the insulation state parameter acquisition module 320 is further configured to, if the monitoring requirement includes motor type information or motor operating scenario information, determine a matching parameter configuration recommendation strategy based on the motor type information or the motor operating scenario information, and, in response to the user's confirmation operation of the parameter configuration recommendation strategy, determine multiple target sensing paths from the candidate sensing paths;

[0139] If the monitoring requirement includes a desired sensing path, then it is determined whether the desired sensing paths meet a preset conflict condition. If the preset conflict condition is met, the desired sensing paths are filtered to determine the multiple target sensing paths that do not conflict. If the preset conflict condition is not met, then the desired sensing path is determined as one of the multiple target sensing paths.

[0140] In one embodiment, the insulation state parameter acquisition module 320 is further configured to insert a guide page through the module, displaying the interface positions of each of the multiple target sensing paths on the current monitoring device; the interface positions are used to connect sensing modules, the sensing modules are used to collect target insulation state parameters, and the sensing modules store preset collection configuration parameters that can be configured; when each of the sensing modules is detected to be inserted into the corresponding interface position, the monitoring device identifies the preset collection configuration parameters in each connected sensing module, and obtains the target insulation state parameters from each target sensing path based on the preset collection configuration parameters.

[0141] In one embodiment, the insulation state parameter acquisition module 320 is further configured to: set a simulated motor operation scenario and the expected insulation state parameters corresponding to the simulated motor operation scenario; apply the motor operation scenario to the motor for simulation to determine the simulated insulation state parameters acquired by multiple candidate sensing paths; compare the simulated insulation state parameters corresponding to each candidate sensing path with the expected insulation state parameters to obtain a comparison error; if the comparison error is within a preset error range, retain the candidate sensing path; if the comparison error exceeds the preset error range, discard the candidate sensing path.

[0142] In one embodiment, the insulation state parameter acquisition module 320 is further configured to acquire the temperature monitored by the motor and display the temperature; if the temperature is greater than or equal to a preset first temperature threshold and less than a preset second temperature threshold, then at least one built-in cooling fan is started to perform air cooling operation; and if the temperature is greater than or equal to the preset second temperature threshold, then a backup heat dissipation channel is activated in a preset area to perform heat dissipation operation.

[0143] In one embodiment, the insulation state parameter acquisition module 320 is further configured to acquire the ambient humidity of the motor external environment and display the ambient humidity of the motor external environment; determine the humidity threshold monitored by the motor according to the ambient humidity of the motor external environment and a preset humidity threshold rule; acquire the humidity monitored by the motor and display the humidity; if the humidity is greater than the humidity threshold and the temperature is less than a preset first temperature threshold, then perform heating dehumidification through a preset heating operation; and if the humidity is greater than the humidity threshold and the temperature is greater than the preset first temperature threshold, then perform condensation dehumidification through a preset condensation operation.

[0144] Each module in the aforementioned insulation condition monitoring device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of a computer device in hardware form or independent of it, or stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0145] In one exemplary embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 4As shown, the computer device includes a processor, memory, input / output interface, communication interface, display unit, and input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interface. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The input / output interface is used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, Near Field Communication (NFC), or other technologies. When executed by the processor, the computer program implements an insulation condition monitoring method. The display unit is used to form a visually visible image and can be a display screen, projection device, or virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device casing, or an external keyboard, touchpad or mouse.

[0146] Those skilled in the art will understand that Figure 4 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0147] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments.

[0148] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0149] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above method embodiments.

[0150] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0151] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0152] 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 application.

[0153] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present application. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present application, and these modifications and improvements fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. A method for monitoring the insulation condition of an electric motor, characterized in that, The method includes: Receive monitoring requests for the motor; Based on the monitoring requirements, multiple target sensing paths are determined from multiple candidate sensing paths used to obtain different types of insulation state parameters, and multiple target insulation state parameters are obtained through the target sensing paths. Based on various target insulation state parameters, multiple insulation characteristics of the motor are determined, the multiple insulation characteristics are fused, and the insulation degradation type is determined based on the fused insulation characteristics. The insulation degradation type and the corresponding insulation state parameters are displayed.

2. The method according to claim 1, characterized in that, The step of determining multiple target sensing paths from multiple candidate sensing paths used to obtain different types of insulation state parameters according to the monitoring requirements includes: If the monitoring requirements include motor type information or motor operating scenario information, then based on the motor type information or the motor operating scenario information, a matching parameter configuration recommendation strategy is determined, and in response to the user's confirmation operation of the parameter configuration recommendation strategy, multiple target sensing paths are determined from the candidate sensing paths; If the monitoring requirement includes a desired sensing path, then it is determined whether the desired sensing paths meet a preset conflict condition. If the preset conflict condition is met, the desired sensing paths are filtered to determine the multiple target sensing paths that do not conflict. If the preset conflict condition is not met, then the desired sensing path is determined as one of the multiple target sensing paths.

3. The method according to claim 1, characterized in that, The process of obtaining various target insulation state parameters through the target sensing path includes: The module insertion guide page displays the interface positions of each of the target sensing paths on the current monitoring device; the interface positions are used to connect to the sensing modules, the sensing modules are used to collect target insulation status parameters, and the sensing modules store preset collection configuration parameters that can be configured. When the detection device detects that each of the sensor modules is inserted into the corresponding interface position, the monitoring device identifies the preset acquisition configuration parameters in each of the connected sensor modules, and obtains the target insulation state parameters from each of the target sensing paths based on the preset acquisition configuration parameters.

4. The method according to claim 1, characterized in that, Before receiving the monitoring request for the motor, the process also includes: Set up a simulated motor operation scenario and the expected insulation state parameters corresponding to the simulated motor operation scenario; The motor operation scenario is applied to the motor for simulation to determine the simulated insulation state parameters obtained by multiple candidate sensing paths; The simulated insulation state parameters and the expected insulation state parameters corresponding to each candidate sensing path are compared to obtain the comparison error. If the comparison error is within a preset error range, the candidate sensing path is retained; if the comparison error exceeds the preset error range, the candidate sensing path is eliminated.

5. The method according to claim 1, characterized in that, Before acquiring multiple target insulation state parameters through the target sensing path, the process further includes: The temperature monitored by the motor is obtained and displayed. If the temperature is greater than or equal to a preset first temperature threshold and less than a preset second temperature threshold, then at least one built-in cooling fan is activated to perform air cooling operation; and, If the temperature is greater than or equal to the preset second temperature threshold, then a backup heat dissipation channel is activated in the preset area to perform heat dissipation operation.

6. The method according to claim 5, characterized in that, After obtaining the temperature monitored by the motor, the method further includes: The humidity of the external environment of the motor is obtained and displayed. The humidity threshold for motor monitoring is determined based on the ambient humidity of the motor's external environment and the preset humidity threshold rules. The humidity level monitored by the motor is obtained and displayed. If the humidity is greater than the humidity threshold and the temperature is less than a preset first temperature threshold, then dehumidification is performed through a preset heating operation; and, If the humidity is greater than the humidity threshold and the temperature is greater than the preset first temperature threshold, then condensation dehumidification is performed through a preset condensation operation.

7. A motor insulation condition monitoring device, characterized in that, The device includes: The monitoring requirement acquisition module is used to receive monitoring requirements for the motor. An insulation state parameter acquisition module is used to determine multiple target sensing paths from multiple candidate sensing paths for acquiring different types of insulation state parameters according to the monitoring requirements, and to acquire multiple target insulation state parameters through the target sensing paths. An insulation degradation type determination module is used to determine multiple insulation characteristics of the motor based on various target insulation state parameters, fuse the multiple insulation characteristics, and determine the insulation degradation type based on the fused insulation characteristics. The visualization module is used to display the insulation degradation type and the multiple insulation state parameters corresponding to the insulation degradation type.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

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