Explosion-proof motor junction box fault monitoring device and method based on multi-source data collaborative analysis

Abstract

The application provides an explosion-proof motor junction box fault monitoring device and method based on multi-source data collaborative analysis, belonging to the technical field of explosion-proof motor monitoring. The device comprises a thermal imaging type temperature and humidity intelligent terminal and a temperature and humidity fusion terminal. The thermal imaging type temperature and humidity intelligent terminal is installed inside the junction box, and the temperature and humidity fusion terminal is installed outside the junction box. The thermal imaging type temperature and humidity intelligent terminal comprises an ozone sensor for collecting ozone concentration data, a thermal imaging array for collecting regional temperature data, a box-in temperature and humidity sensor module for collecting internal temperature and humidity data, and a box-in data processing and communication module for data preprocessing and obtaining box-in data. The temperature and humidity fusion terminal comprises a box-out temperature and humidity sensor module for collecting external temperature and humidity data, and a box-out data processing and communication module for full-factor fault collaborative diagnosis, determination of fault state and fault root. The application can improve the diagnostic accuracy and fault coverage.

Description

Technical Field

[0001] This application relates to the field of explosion-proof motor monitoring technology, and in particular to a fault monitoring device and method for explosion-proof motor junction boxes based on multi-source data collaborative analysis. Background Technology

[0002] Currently, 6KV and above medium- and high-voltage explosion-proof motors are widely used in high-risk industries such as petrochemicals. Their junction box operating conditions exhibit four main characteristics: high voltage, high heat generation, high discharge risk, and high sealing requirements. Furthermore, they are mostly deployed in high-risk locations such as petrochemical plants, where the requirements for network security, monitoring accuracy, fault coverage, and data transmission stability are far higher than in low-voltage scenarios. However, current monitoring technologies still have many shortcomings. They are mostly designed for low-voltage motor junction boxes and cannot meet the full-process fault monitoring needs of medium- and high-voltage scenarios. They also do not consider the stringent explosion-proof sealing requirements of medium- and high-voltage junction boxes. Inadequate monitoring can easily lead to major safety accidents such as insulation breakdown and arcing fires, causing huge economic losses. Summary of the Invention

[0003] The main objective of this application is to propose a fault monitoring device and method for explosion-proof motor junction boxes based on multi-source data collaborative analysis, aiming to improve diagnostic accuracy and fault coverage without damaging the original explosion-proof sealing structure of the junction box.

[0004] To achieve the above objectives, one aspect of this application proposes a fault monitoring device for explosion-proof motor junction boxes based on multi-source data collaborative analysis. The device includes a thermal imaging temperature and humidity smart terminal and a temperature and humidity fusion terminal. The thermal imaging temperature and humidity smart terminal is installed inside the junction box, and the temperature and humidity fusion terminal is installed outside the junction box. The thermal imaging temperature and humidity smart terminal includes an ozone sensor, a thermal imaging array, an internal temperature and humidity sensor module, and an internal data processing and communication module. The temperature and humidity fusion terminal includes an external temperature and humidity sensor module and an external data processing and communication module. The internal temperature and humidity sensor module is used to collect internal temperature and humidity data. The ozone sensor is used to collect ozone concentration data inside the junction box; The thermal imaging array is used to collect regional temperature data of a preset thermal imaging area. The in-box data processing and communication module is used to preprocess the regional temperature data based on the internal temperature and humidity data to obtain effective regional temperature data, and wirelessly transmit the internal temperature and humidity data, the ozone concentration data, and the effective regional temperature data as in-box data to the external data processing and communication module. The external temperature and humidity sensor module is used to collect external temperature and humidity data. The external data processing and communication module is used to perform comprehensive fault diagnosis based on the data inside the box and the external temperature and humidity data, and to determine the fault status and root cause of the fault.

[0005] In some embodiments, the thermal imaging temperature and humidity smart terminal and the temperature and humidity fusion terminal are fixedly connected to the junction box by adhesive or magnetic attraction.

[0006] In some embodiments, the thermal imaging area includes a three-phase terminal area and a heat-prone area, the thermal imaging array includes at least one thermal imaging probe, the thermal imaging probe is plugged into the thermal imaging temperature and humidity smart terminal, the detection distance between the thermal imaging probe and the terminal is greater than or equal to the safe distance, and the detection field of the thermal imaging probe covers the three-phase terminal area and the heat-prone area.

[0007] In some embodiments, the thermal imaging temperature and humidity smart terminal further includes an in-box power module, which is connected to the ozone sensor, the thermal imaging array, the in-box temperature and humidity sensor module, and the in-box data processing and communication module. The in-box power module includes a lithium battery and a backup battery. The lithium battery provides the operating power for the thermal imaging temperature and humidity smart terminal during operation, and the backup battery provides the power for continued measurement when the thermal imaging temperature and humidity smart terminal is powered off. The temperature and humidity fusion terminal also includes an external power module, which uses an explosion-proof battery.

[0008] To achieve the above objectives, another aspect of this application proposes a method for fault monitoring of explosion-proof motor junction boxes based on multi-source data collaborative analysis, the method comprising the following steps: Acquire internal temperature and humidity data, ozone concentration data, area temperature data, and external temperature and humidity data; The temperature data of the area is preprocessed based on the internal temperature and humidity data to obtain the effective temperature data of the area, and the internal temperature and humidity data, the ozone concentration data and the effective temperature data of the area are used as the data inside the box. Based on the data inside the box and the external temperature and humidity data, a comprehensive fault diagnosis is performed to determine the fault status and root cause.

[0009] In some embodiments, acquiring regional temperature data includes the following steps: Acquire an infrared thermal image of a preset thermal imaging area, wherein the thermal imaging area includes a three-phase terminal area and a heat-prone area; Based on the target location information, the target location area is extracted from the infrared thermal image, and the highest local temperature within the target location area is determined as the current area temperature. The infrared thermal image is color-mapped based on the local temperature to obtain the current thermal map; The infrared thermal image, the current area temperature, and the current heat map are used as area temperature data.

[0010] In some embodiments, the step of performing comprehensive fault collaborative diagnosis based on the data inside the box and the external temperature and humidity data to determine the fault status and root cause includes the following steps: Based on the ozone concentration data, discharge diagnosis is performed to determine whether a discharge fault exists, and the discharge diagnosis result is obtained. Temperature diagnosis is performed based on the effective temperature data of the area to determine whether there is a temperature fault and to obtain the temperature diagnosis result. The difference between the internal temperature and humidity data and the external temperature and humidity data is calculated to obtain the internal and external temperature and humidity difference value. Based on the internal and external temperature and humidity difference value, a seal diagnosis is performed to determine whether there is a seal failure and obtain the seal diagnosis result. Based on the temperature diagnosis results, the discharge diagnosis results, and the sealing diagnosis results, a collaborative diagnosis is performed to determine the root cause of the fault.

[0011] In some embodiments, the step of performing discharge diagnosis based on the ozone concentration data to determine whether a discharge fault exists and obtaining a discharge diagnosis result includes the following steps: Based on the ozone concentration data and the baseline concentration value, the concentration change trend is predicted to obtain the unit concentration increment, wherein the baseline concentration value is the average value of the ozone concentration data under normal operation without discharge phenomenon. The first discharge condition is determined based on the ozone concentration data and the preset ozone concentration threshold. The first discharge condition is that the ozone concentration data is greater than the ozone concentration threshold and the duration is greater than the sampling period. The second discharge condition is determined based on the unit concentration increment and the preset increment threshold, wherein the second discharge condition is that the unit concentration increment is greater than the increment threshold and the duration is greater than the sampling period. When both the first discharge condition and the second discharge condition are met, the discharge diagnosis result is determined to be a discharge fault.

[0012] In some embodiments, the step of performing temperature diagnosis based on the effective temperature data of the area to determine whether a temperature fault exists and obtain a temperature diagnosis result includes the following steps: The temperature difference is calculated based on the current temperature of the three-phase terminals to obtain the three-phase temperature difference. It is then determined whether the three-phase temperature difference is greater than a preset temperature difference threshold. If the three-phase temperature difference is greater than the temperature difference threshold, the temperature diagnosis result is determined to be a temperature fault in the three-phase terminals. Determine whether the temperature of the current area corresponding to the heat-prone point is greater than a preset local temperature threshold. If the temperature of the current area corresponding to the heat-prone point is greater than the temperature threshold, then determine that the temperature diagnosis result is that the heat-prone point has a temperature fault. The step of performing a coordinated diagnosis based on the temperature diagnosis result, the discharge diagnosis result, and the sealing diagnosis result to determine the root cause of the fault includes the following steps: Based on historical heat maps and motor operating conditions, anomalies are identified in the temperature diagnosis results to determine whether the temperature fault is a persistent fault. If the temperature fault is not a persistent fault, the root cause of the fault is determined to be abnormal temperature caused by loose wiring, poor contact, or uneven current. When the temperature fault is a persistent fault, the root cause of the fault is determined to be an insulation abnormality. The cause of the insulation abnormality is determined based on the discharge diagnosis results and the sealing diagnosis results. The cause includes local overheating factors, discharge factors, or moisture ingress factors.

[0013] In some embodiments, the step of identifying anomalies in the temperature diagnosis results based on historical thermal maps and motor operating conditions, and determining whether the temperature fault is a persistent fault, includes the following steps: The fault percentage is calculated by comparing the number of faults in the temperature diagnosis results for the three-phase terminals and the heat-prone points. Based on the historical heat map and motor operating conditions, features of temperature and load are extracted to obtain temperature-load correlation features. Anomaly identification is performed based on the fault percentage and the temperature load correlation characteristics to determine whether the temperature fault is a persistent fault.

[0014] In some embodiments, the method further includes the following steps: If the explosion-proof motor junction box does not exhibit the aforementioned fault condition within the preset maintenance cycle, then the monthly periodic opening and inspection will cease, and the box will only be opened for maintenance after the maintenance cycle expires.

[0015] To achieve the above objectives, another aspect of this application provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the above-described method.

[0016] To achieve the above objectives, another aspect of the embodiments of this application proposes a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method.

[0017] The embodiments of this application include at least the following beneficial effects: This application provides a fault monitoring device and method for explosion-proof motor junction boxes based on multi-source data collaborative analysis. The device includes a thermal imaging temperature and humidity smart terminal and a temperature and humidity fusion terminal. The thermal imaging temperature and humidity smart terminal is installed inside the junction box, and the temperature and humidity fusion terminal is installed outside the junction box. The thermal imaging temperature and humidity smart terminal includes an ozone sensor for collecting ozone concentration data, a thermal imaging array for collecting regional temperature data, an internal temperature and humidity sensor module for collecting internal temperature and humidity data, and an internal data processing and communication module for performing data preprocessing to obtain internal data. The temperature and humidity fusion terminal includes an external temperature and humidity sensor module for collecting external temperature and humidity data and an external data processing and communication module for performing comprehensive fault collaborative diagnosis to determine the fault state and root cause. This application can improve diagnostic accuracy and fault coverage without damaging the original explosion-proof sealing structure of the junction box. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of the structure of the explosion-proof motor junction box fault monitoring device based on multi-source data collaborative analysis provided in the embodiments of this application; Figure 2 This is a flowchart of the explosion-proof motor junction box fault monitoring method based on multi-source data collaborative analysis provided in the embodiments of this application; Figure 3 This is a schematic diagram of the structure of an explosion-proof motor junction box fault monitoring device based on multi-source data collaborative analysis provided in another embodiment of this application; Figure 4 This is a schematic diagram of the hardware structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0019] 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 of this application and are not intended to limit it. In the following description, when referring to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with those of this application; they are merely examples of systems and methods consistent with some aspects of the embodiments of this application as detailed in the appended claims.

[0020] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0021] Before providing a detailed description of the embodiments of this application, the relevant technologies involved in the embodiments of this application will be described first.

[0022] With the widespread application of 6KV and above medium and high voltage explosion-proof motors in the petrochemical industry, the demand for safe operation and maintenance of their junction boxes is becoming increasingly urgent. However, most current monitoring technologies are unable to meet the stringent requirements of medium and high voltage scenarios, and are also unable to meet the core needs of the petrochemical industry for "precise monitoring and intelligent operation and maintenance," as detailed below: 1. Insufficient adaptability, unable to meet the needs of medium and high voltage scenarios of 6KV and above: Current monitoring technologies are mostly designed for low-voltage motor junction boxes, and have not optimized monitoring solutions for the high voltage, high heat generation, and high discharge risk of medium and high voltage scenarios. Their monitoring accuracy, explosion-proof level and anti-electromagnetic interference capabilities cannot match the operating requirements of medium and high voltage. Furthermore, the stringent explosion-proof sealing requirements of medium and high voltage junction boxes have not been considered. Some monitoring solutions require damage to the sealing structure of the junction box, further exacerbating safety hazards.

[0023] II. Safety Hazards of Temperature Measurement Methods: Within medium- and high-voltage motor junction boxes, due to safety distance requirements and potential creepage hazards, commonly used contact temperature measurement and passive wireless temperature measurement methods tied to three-phase power lines are no longer suitable. Contact temperature measurement requires direct or close contact with live parts (three-phase terminals), which not only fails to meet safety distance requirements but also easily leads to creepage, short circuits, and other safety accidents. While passive wireless temperature measurement tied to three-phase power lines does not require direct contact with live parts, the binding process can easily damage the internal insulation structure of the junction box, also increasing the risk of creepage. More importantly, both methods can only collect temperature at a single point, failing to cover all heat-prone areas and are susceptible to temperature measurement deviations due to high-temperature conduction from the terminals. Furthermore, in medium- and high-voltage scenarios, discharge phenomena caused by loose wiring and insulation damage are accompanied by local temperature rises. Single-point temperature measurement methods cannot capture such local temperature rises, creating a "temperature rise monitoring blind spot." Because a precise temperature measurement and positioning scheme has not been designed for the three-phase terminals of medium- and high-voltage motors (high voltage, concentrated heat generation), temperature anomalies are inferred indirectly through conventional temperature and humidity data. It is impossible to directly collect the real-time temperature of the three-phase terminal area and other areas prone to heat generation, making it difficult to accurately calculate the three-phase temperature difference. Temperature measurement deviations can easily lead to missed or misjudged core faults such as loose wiring, oxidation corrosion, and local overheating, which can then lead to serious accidents such as insulation breakdown.

[0024] Third, the lack of discharge fault monitoring creates blind spots for safety hazards: In junction boxes of medium and high voltage motors at 6KV and above, the probability of partial discharge and corona discharge caused by loose wiring, insulation damage, and excessive potential difference is much higher than in low-voltage scenarios. Such discharges produce characteristic gases such as ozone, which, if left unchecked, can easily lead to serious accidents such as insulation breakdown and arc fires, resulting in major safety accidents such as shutdowns of petrochemical plants or even explosions and leaks. Because discharge phenomena and potential hazards cannot be identified, monitoring blind spots are formed. Moreover, the single ozone monitoring technology is not deeply integrated with the temperature and humidity monitoring and temperature monitoring of medium and high voltage explosion-proof motor junction boxes, making it impossible to eliminate interference based on operating conditions, leading to misjudgments and failing to meet the needs of medium and high voltage scenarios. Insufficient accuracy of temperature monitoring not only leads to missed detections of loose wiring and localized overheating but also affects the prediction of insulation anomalies. The lack of discharge monitoring further exacerbates insulation aging, creating a compounded risk with temperature anomalies. Related technologies cannot form a synergistic monitoring system, making it difficult to cope with the complex faults in medium and high voltage scenarios.

[0025] IV. Lack of Synchronous Data Collection on Temperature and Humidity Inside and Outside the Junction Box, Leading to Low Accuracy in Sealing Fault Diagnosis: The sealing performance of medium- and high-voltage junction boxes directly affects explosion-proof safety and the insulation performance of internal components. Poor sealing leading to moisture and water ingress further exacerbates the risks of creepage and insulation damage. Although prior patents have achieved synchronous collection of temperature and humidity data inside and outside the junction box, in-depth collaborative analysis based on this synchronously collected data is not performed. It is impossible to accurately analyze sealing performance through the temperature and humidity difference between the inside and outside of the box, making it difficult to accurately determine faults such as poor sealing, external high humidity penetration, moisture, or water ingress. This can easily lead to misjudgments due to environmental interference. Currently, the diagnostic accuracy is insufficient to meet the safety monitoring needs of medium- and high-voltage scenarios.

[0026] V. Incomplete Fault Coverage and Failure to Achieve Integrated Monitoring of All Common Fault Types: Related technologies primarily focus on abnormal temperature and humidity and basic sealing faults, failing to integrate core fault types such as abnormal temperature, three-phase temperature differences, and discharge hazards. Furthermore, the accuracy of sealing fault diagnosis is insufficient, failing to meet the demand for "one-stop, full-coverage, and high-precision" fault monitoring in medium- and high-voltage scenarios. Therefore, monitoring still requires on-site inspections by maintenance personnel and the use of multiple monitoring devices, resulting in high maintenance costs and posing a risk of electric shock during inspections in medium- and high-voltage scenarios. Real-time remote monitoring is also impossible, making it difficult to meet the core needs of the petrochemical industry for "remote supervision and precise early warning."

[0027] VI. Failure to consider explosion-proof sealing requirements for medium and high voltage scenarios: The thermal imaging temperature measurement or ozone monitoring technologies are all single-function designs, not deeply integrated with the sealing fault and temperature and humidity fault monitoring of medium and high voltage explosion-proof motor junction boxes. They cannot meet the explosion-proof, accurate, and comprehensive monitoring needs of medium and high voltage scenarios, nor do they achieve collaborative data acquisition and multi-mode transmission between the inside and outside of the box. Furthermore, the design of extending the antenna from inside the junction box to the outside is a penetrating antenna approach that damages the original explosion-proof sealing structure of the junction box, failing to meet the explosion-proof rating requirements of medium and high voltage explosion-proof motor junction boxes and posing a safety hazard.

[0028] In view of this, this application provides a fault monitoring device and method for explosion-proof motor junction boxes based on multi-source data collaborative analysis. The device includes a thermal imaging temperature and humidity smart terminal and a temperature and humidity fusion terminal. The thermal imaging temperature and humidity smart terminal is installed inside the junction box, and the temperature and humidity fusion terminal is installed outside the junction box. The thermal imaging temperature and humidity smart terminal includes an ozone sensor for collecting ozone concentration data, a thermal imaging array for collecting regional temperature data, an internal temperature and humidity sensor module for collecting internal temperature and humidity data, and an internal data processing and communication module for performing data preprocessing to obtain internal data. The temperature and humidity fusion terminal includes an external temperature and humidity sensor module for collecting external temperature and humidity data and an external data processing and communication module for performing comprehensive fault collaborative diagnosis to determine the fault state and root cause. This application can improve diagnostic accuracy and fault coverage without damaging the original explosion-proof sealing structure of the junction box.

[0029] The explosion-proof motor junction box fault monitoring method based on multi-source data collaborative analysis provided in this application relates to the field of explosion-proof motor monitoring. This method can be applied to a terminal, a server, or software running on either a terminal or a server. In some embodiments, the terminal can be a smartphone, tablet, laptop, desktop computer, smart speaker, smartwatch, or vehicle terminal, but is not limited to these. The server can be configured as an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms. The server can also be a node server in a blockchain network. The software can be an application implementing the explosion-proof motor junction box fault monitoring method based on multi-source data collaborative analysis, but is not limited to the above forms.

[0030] This application can be used in a wide variety of general-purpose or special-purpose computer system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics devices, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices. This application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform specific tasks or implement specific abstract data types. This application can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0031] Figure 1 This is a schematic diagram of the structure of the explosion-proof motor junction box fault monitoring device based on multi-source data collaborative analysis provided in this application embodiment. The device includes a thermal imaging temperature and humidity smart terminal and a temperature and humidity fusion terminal. The thermal imaging temperature and humidity smart terminal is installed inside the junction box, and the temperature and humidity fusion terminal is installed outside the junction box. The thermal imaging temperature and humidity smart terminal includes an ozone sensor, a thermal imaging array, an internal temperature and humidity sensor module and an internal data processing and communication module. The temperature and humidity fusion terminal includes an external temperature and humidity sensor module and an external data processing and communication module.

[0032] The internal temperature and humidity sensor module is used to collect internal temperature and humidity data.

[0033] The ozone sensor is used to collect ozone concentration data inside the junction box.

[0034] Thermal imaging arrays are used to acquire regional temperature data of a preset thermal imaging area.

[0035] The in-box data processing and communication module is used to preprocess the regional temperature data based on the internal temperature and humidity data to obtain the effective regional temperature data, and wirelessly transmit the internal temperature and humidity data, ozone concentration data and effective regional temperature data as in-box data to the external data processing and communication module.

[0036] The external temperature and humidity sensor module is used to collect external temperature and humidity data.

[0037] The external data processing and communication module is used to perform comprehensive fault diagnosis based on internal data and external temperature and humidity data, and to determine the fault status and root cause.

[0038] In this embodiment, addressing the shortcomings of related technologies, this embodiment focuses on the scenario of 6KV and above medium and high voltage explosion-proof motor junction boxes, with core design... Figure 1 The "thermal imaging temperature and humidity smart terminal" inside the junction box integrates three core functions: thermal imaging, temperature and humidity acquisition, and ozone monitoring. At the same time, a "temperature and humidity fusion terminal" is added outside the junction box. This terminal ultimately realizes collaborative data acquisition inside and outside the box, multi-mode transmission, and collaborative diagnosis of all types of faults, filling the technical gap in medium and high voltage scenarios and improving the reliability and comprehensiveness of monitoring.

[0039] Specifically, such as Figure 1 As shown, the thermal imaging-based smart temperature and humidity terminal has three core objectives: Firstly, a thermal imaging array is used to accurately collect regional temperature data of the thermal imaging area inside the motor junction box, providing support for monitoring temperature and insulation anomalies. Through non-contact thermal imaging temperature measurement, accurate temperature measurement can be completed from a safe distance, avoiding risks such as creepage and seal damage. It also enables regional temperature measurement, overcoming the limitations of single-point temperature measurement by covering the three-phase terminals and all heat-prone points with the thermal imaging area. Furthermore, it is adaptable to medium- and high-voltage electromagnetic environments, ensuring uninterrupted temperature measurement accuracy, perfectly meeting the monitoring needs of medium- and high-voltage junction boxes.

[0040] Secondly, by using an ozone sensor to monitor the ozone concentration in real time inside the motor junction box, the discharge phenomenon and potential hazards inside the box can be accurately identified.

[0041] Third, the internal temperature and humidity data of the junction box are monitored in real time by the internal temperature and humidity sensor module, and the external temperature and humidity data of the junction box are collected by the external temperature and humidity sensor module in the temperature and humidity fusion terminal. This enables the diagnosis and prediction of poor sealing and water ingress (dampness) of the motor junction box.

[0042] The thermal imaging temperature and humidity smart terminal also includes an in-cabin data processing and communication module. This module can preprocess the regional temperature data based on the internal temperature and humidity data. After initially determining that the data is useful, the internal temperature and humidity data, ozone concentration data, and regional temperature data are then used as in-cabin data to interact with the external data processing and communication module.

[0043] Ultimately, by relying on data inside the box and external temperature and humidity data through the external data processing and communication module, the system can perform comprehensive fault diagnosis and prediction for motor junction box issues such as poor sealing, water ingress (dampness), abnormal temperature, abnormal humidity, and insulation abnormalities. This significantly improves the diagnostic accuracy of sealing faults, abnormal humidity, and abnormal insulation, achieving the goal of one-stop, full-coverage, and high-precision fault monitoring without the need for multiple monitoring devices, thus reducing operation and maintenance costs and complexity.

[0044] Optionally, the in-box data processing and communication module and the external data processing and communication module have four wireless module transmission modes during wireless communication: 5G, 4G, NB-IoT, and LoRa. In actual transmission, one of the four modes can be selected according to the on-site wireless network conditions to achieve communication via 5G intranet or public network, NB-IoT intranet or public network, or wireless self-organizing network. The complete dataset, fault judgment results, and alarm information are uploaded to the remote monitoring platform in real time. At the same time, it receives calibration, parameter adjustment and other instructions issued by the remote platform, realizing long-distance and highly stable remote monitoring and control. It adapts to the monitoring challenges of remote deployment of medium and high voltage motors in different network environments, further improves data transmission rate and stability, and adapts to the long-distance monitoring needs of medium and high voltage scenarios in different network environments.

[0045] It should be noted that, compared to extending the antenna outside the box, this embodiment uses wireless communication, relying on the collaborative wireless interaction between the two terminals inside and outside the box. This not only ensures the multi-mode transmission effect, but also strictly preserves the original explosion-proof sealing structure of the junction box, avoiding explosion hazards caused by damage to the explosion-proof sealing structure.

[0046] In some embodiments, the thermal imaging temperature and humidity smart terminal and the temperature and humidity fusion terminal are fixedly connected to the junction box by adhesive or magnetic attraction.

[0047] In this embodiment, to facilitate installation and avoid damaging the original explosion-proof sealing structure of the junction box, both the thermal imaging temperature and humidity smart terminal and the temperature and humidity fusion terminal are fixedly connected to the inside and outside of the junction box by adhesive or magnetic means, without the need for bolts.

[0048] In some embodiments, the thermal imaging area includes a three-phase terminal area and a heat-prone area, the thermal imaging array includes at least one thermal imaging probe, the thermal imaging probe and the thermal imaging temperature and humidity smart terminal are connected by a plug-in connection, the detection distance between the thermal imaging probe and the terminal is greater than or equal to the safe distance, and the detection field of the thermal imaging probe covers the three-phase terminal area and the heat-prone area.

[0049] In this embodiment, in order to expand the high temperature monitoring range, during installation, near-field communication debugging is used to precisely align the image of the thermal imaging array with the positions of the three-phase terminals and the locations of easily heated points.

[0050] Specifically, multiple positioning thermal imaging areas are preset, and thermal imaging probes monitor these areas in real time, outputting the regional temperature data for each area.

[0051] The thermal imaging area includes a three-phase terminal area and a heat-prone point area. Each three-phase terminal area corresponds to one phase terminal, and each heat-prone point area corresponds to one heat-prone point. Heat-prone points are other locations besides the three-phase terminals that may generate abnormal heat due to changes in electrical contact or insulation conditions, such as insulation sheaths, phase spacers, and creepage paths.

[0052] The thermal imaging probe supports multiple pixel specifications, including ultra-high definition, high definition, and standard definition. The corresponding pixel count of the thermal imaging probe can be selected according to the site budget, and it is plug-and-play connected to the thermal imaging temperature and humidity smart terminal.

[0053] Meanwhile, considering that the voltage inside the junction box of medium and high voltage motors is as high as 6KV and above, in order to avoid the high voltage safety risks of contact temperature measurement requiring direct or close contact with live parts (three-phase terminals), which may easily cause short circuits, arc discharges and other safety accidents, the detection distance between the thermal imaging probe and the terminal needs to be greater than or equal to the safe distance, so as to complete the temperature acquisition outside the safe distance, fundamentally eliminate the hidden danger of high voltage electric shock, and meet the safety requirements of medium and high voltage scenarios.

[0054] Secondly, unlike contact temperature measurement which requires fixing the temperature probe and wiring to the inner wall of the junction box, which can easily damage the original explosion-proof sealing structure of the junction box and cause explosion-proof failure, non-contact thermal imaging temperature measurement does not need to penetrate the sealing structure or be fixed at close range to a live body. It can achieve temperature measurement without damaging the integrity of the seal and is suitable for medium and high voltage explosion-proof requirements.

[0055] Furthermore, contact-type temperature probes require precise alignment and fixation with live conductors, making installation difficult. They are also prone to damage from prolonged exposure to high temperatures and strong electromagnetic fields, necessitating power outages and production shutdowns for replacement. In contrast, non-contact thermal imaging probes can be installed remotely without touching live conductors, offering convenient installation and lower energy loss. This makes them suitable for the long-term continuous operation and low maintenance costs required for medium and high voltage motors. Therefore, compared to infrared detection technology, non-contact thermal imaging offers superior temperature measurement accuracy, positioning accuracy, and feature richness, making it more suitable for medium and high voltage scenarios and diverse budget requirements.

[0056] Finally, the medium and high voltage junction boxes contain complex environments such as strong electromagnetic interference and oil and gas accumulation. Contact temperature measurement is susceptible to electromagnetic interference, which can lead to data distortion. Non-contact thermal imaging temperature measurement has stronger anti-electromagnetic interference performance and can stably collect temperature data under complex working conditions, ensuring temperature measurement accuracy.

[0057] In some embodiments, the thermal imaging temperature and humidity smart terminal further includes an in-box power module, which is connected to the ozone sensor, the thermal imaging array, the in-box temperature and humidity sensor module, and the in-box data processing and communication module. The in-box power module includes a lithium battery and a backup battery. The lithium battery provides the operating power for the thermal imaging temperature and humidity smart terminal during operation, and the backup battery provides the power for continued measurement when the thermal imaging temperature and humidity smart terminal is powered off.

[0058] The temperature and humidity fusion terminal also includes an external power module, which uses an explosion-proof battery.

[0059] In this embodiment, considering that the A and B machines serve as backups for each other, and that using inductive power may result in data loss during motor downtime, both the internal and external terminals are powered by dedicated long-life explosion-proof batteries.

[0060] Specifically, the thermal imaging temperature and humidity smart terminal also includes an in-box power module, which powers all modules inside the box. Through low power consumption design, it does not require a backup power supply for the motor and can ensure continuous, stable and reliable operation within a major overhaul cycle of 5 years. It does not require frequent battery replacements, thus reducing maintenance costs.

[0061] Meanwhile, this embodiment is also equipped with a backup battery in the power module inside the box to support continued testing after power failure and ensure the explosion-proof performance of medium and high voltage.

[0062] For example, the power module inside the box is a 3.5V lithium battery, and the backup battery provides a battery life of ≥60 minutes.

[0063] The temperature and humidity fusion terminal also includes an external power module, such as a built-in 3.5V dedicated long-life explosion-proof battery to ensure power supply stability and adapt to the long-term continuous operation requirements of medium and high voltage motors.

[0064] Figure 2 This is an optional flowchart of the explosion-proof motor junction box fault monitoring method based on multi-source data collaborative analysis provided in the embodiments of this application. Figure 2 The method may include, but is not limited to, steps S101 to S103.

[0065] Step S101: Obtain internal temperature and humidity data, ozone concentration data, regional temperature data, and external temperature and humidity data.

[0066] Step S102: Perform data preprocessing on the regional temperature data based on the internal temperature and humidity data to obtain effective regional temperature data, and use the internal temperature and humidity data, ozone concentration data, and effective regional temperature data as the data inside the box.

[0067] Step S103: Perform a comprehensive fault diagnosis based on the data inside the box and the external temperature and humidity data to determine the fault status and the root cause of the fault.

[0068] In this embodiment, the explosion-proof motor junction box fault monitoring method based on multi-source data collaborative analysis uses a thermal imaging temperature and humidity smart terminal and a temperature and humidity fusion terminal to perform dual-terminal collaborative data collection and interaction, and combines data from inside and outside the junction box to perform collaborative diagnosis of all types of faults.

[0069] Specifically, the thermal imaging temperature and humidity smart terminal is responsible for collecting regional temperature data, internal temperature and humidity data, and ozone concentration data inside the junction box, while the temperature and humidity fusion terminal is responsible for collecting external temperature and humidity data outside the junction box.

[0070] Next, before transmitting the multidimensional data collected inside the junction box, the area temperature data is preprocessed based on the internal temperature and humidity data using preset temperature trigger thresholds and rate of change thresholds.

[0071] For example, after setting the temperature trigger threshold to 40 degrees and the change rate threshold to 5 degrees, the area temperature data collected by the thermal imaging array is only packaged and uploaded to the outside of the box when the internal temperature and humidity data reaches 40 degrees during sampling. Alternatively, if the temperature of the internal temperature and humidity data at the later sampling time is greater than 5 degrees compared to the temperature of the internal temperature and humidity data at the previous sampling time, the area temperature data collected by the thermal imaging array is considered as valid data and packaged together with the internal temperature and humidity data and ozone concentration data as in-box data and uploaded to the outside of the box.

[0072] Optionally, in some embodiments, the thermal imaging array may be triggered to collect temperature data of the area only after the temperature at the time of sampling reaches a temperature trigger threshold or the rate of change of adjacent sampling times reaches a rate of change threshold, thereby reducing the collection of invalid data.

[0073] Finally, by integrating thermal imaging box temperature measurement, ozone box discharge monitoring, and coordinated monitoring of temperature and humidity inside and outside the box, it can not only diagnose and determine the fault status of various faults such as poor sealing, water ingress (dampness), abnormal temperature, abnormal humidity, and abnormal insulation, but also accurately determine the root cause of the fault when multiple faults exist.

[0074] In some embodiments, obtaining regional temperature data in step S101 may include, but is not limited to, steps S201 to S204.

[0075] Step S201: Obtain an infrared thermal image of a preset thermal imaging area, wherein the thermal imaging area includes a three-phase terminal area and a heat-prone area.

[0076] Step S202: Extract the target location area from the infrared thermal image based on the target location information, and determine the highest local temperature in the target location area as the current area temperature.

[0077] Step S203: Perform color mapping on the infrared thermal image based on the local temperature to obtain the current thermal map.

[0078] Step S204: Use the infrared thermal image, the current area temperature, and the current heat map as area temperature data.

[0079] In this embodiment, an array-based regional positioning technique is used to accurately acquire infrared thermal images of the three-phase terminal area and other areas prone to overheating. These infrared thermal images can reflect the temperature distribution of the thermal imaging area.

[0080] Target location information is generated by maintenance personnel viewing images recorded by thermal imaging probes. They select areas within the image based on the positions of the three-phase terminals and areas prone to overheating. The system records the row and column coordinates of these areas in a pixel matrix, forming the target location information. For example, the target location information for phase A terminals in its corresponding infrared thermal image corresponds to rows 20-35 and columns 40-60. Based on the coordinate range provided by the target location information, a matrix corresponding to the target location area is cropped from the thermal infrared image. In this matrix, each pixel represents the local temperature at that point. By iterating through the pixels in each target location area, the highest local temperature within that area is determined as the current temperature of that area (T_A, T_B, T_C, T_heat1, T_heat2...).

[0081] Furthermore, color mapping is performed using the temperature value matrix of infrared thermal images. For example, temperature values ​​are normalized to [0,1] and then converted to RGB color values ​​using a mapping function. The temperature data is then visualized through color changes, generating a heatmap that facilitates viewing the temperature distribution. In the heatmap, the magnitude or density of data is represented by the intensity or brightness of the color. While preserving the spatial distribution characteristics of temperature, the maximum, minimum, and trend of change in the data can be quickly identified by using the contrast of color intensity.

[0082] Finally, the acquired infrared thermal images, the current temperature of each target location area, and the heat map are packaged into regional temperature data to provide a data foundation for subsequent fault diagnosis.

[0083] In some embodiments, step S103 may include, but is not limited to, steps S301 to S304.

[0084] Step S301: Perform discharge diagnosis based on ozone concentration data to determine whether a discharge fault exists and obtain the discharge diagnosis result.

[0085] Step S302: Perform temperature diagnosis based on the effective temperature data of the area to determine whether there is a temperature fault and obtain the temperature diagnosis result.

[0086] Step S303: Calculate the difference between the internal and external temperature and humidity data to obtain the internal and external temperature and humidity difference value, and perform a seal diagnosis based on the internal and external temperature and humidity difference value to determine whether there is a seal failure and obtain the seal diagnosis result.

[0087] Step S304: Perform a collaborative diagnosis based on the temperature diagnosis results, discharge diagnosis results, and sealing diagnosis results to determine the root cause of the fault.

[0088] In this embodiment, a single fault is first determined, and then the results of multiple fault diagnosis are combined for collaborative optimization.

[0089] In response to discharge phenomena and potential hazards, this embodiment addresses the high discharge risk of 6KV and above medium and high voltage motor junction boxes. It also considers the ozone-generating properties of discharge phenomena (partial discharge, corona discharge). This embodiment uses an ozone sensor to monitor ozone concentration data within the motor junction box for discharge diagnosis. When determining whether a discharge fault exists, both the concentration change trend and the real-time absolute value are considered to judge the discharge phenomenon and obtain the discharge diagnosis result.

[0090] Furthermore, after obtaining the discharge diagnosis results, temperature data can be linked to diagnose and predict insulation abnormalities such as insulation damage and insulation aging caused by the discharge, thereby strengthening the core value of discharge monitoring inside the ozone box.

[0091] To address temperature anomalies, this embodiment uses effective temperature data collected by a thermal imaging probe within the motor junction box to extract temperature values ​​from the three-phase terminal areas and other areas prone to overheating. By combining preset thresholds for medium- and high-voltage scenarios, the temperature difference between the three phases is calculated based on the three-phase terminal areas. Simultaneously, areas where local temperatures exceed the thresholds are identified based on the areas prone to overheating, determining whether a temperature fault exists and obtaining a temperature diagnosis result.

[0092] Furthermore, after obtaining the temperature diagnosis results, the image recognition function of the temperature anomaly in the thermal imaging area can be used to help confirm the type of anomaly, thereby diagnosing and predicting insulation anomalies caused by local overheating, and strengthening the core value of temperature measurement inside the thermal imaging array box.

[0093] To address sealing faults, this embodiment simultaneously collects internal temperature and humidity data inside the junction box and external temperature and humidity data outside the junction box. Based on this, it calculates the difference between the internal and external temperature and humidity data, and compares the internal and external temperature and humidity differences with trends over a period of time. Combined with sealing fault diagnosis logic, it accurately determines faults such as abnormal humidity, moisture / water ingress, and poor sealing. At the same time, it combines abnormal humidity data to diagnose and predict insulation abnormalities caused by moisture and water ingress. This fully realizes the goal of "relying on the collaborative acquisition of data from both inside and outside the box and 5G transmission technology to achieve the goal of diagnosing and predicting all elements of faults such as poor sealing, water ingress (moisture), abnormal temperature, abnormal humidity, and insulation abnormalities in the motor junction box without changing the motor explosion-proof structure."

[0094] Finally, based on the temperature diagnosis results, discharge diagnosis results, and sealing diagnosis results, combined with the operating conditions of medium and high voltage motors, a collaborative diagnosis is performed to eliminate misjudgments (such as distinguishing between abnormal humidity caused by high temperature and water ingress, distinguishing between abnormal temperature caused by discharge and loose wiring, and concentration fluctuations caused by external environmental interference), clarify the root cause of the fault, and adapt to the complex fault characteristics of medium and high voltage scenarios.

[0095] In some embodiments, step S301 may include, but is not limited to, steps S401 to S404.

[0096] Step S401: Based on ozone concentration data and baseline concentration values, predict the concentration change trend to obtain the unit concentration increment.

[0097] Step S402: Determine whether the first discharge condition is met based on the ozone concentration data and the preset ozone concentration threshold.

[0098] Step S403: Determine whether the second discharge condition is met based on the unit concentration increment and the preset increment threshold.

[0099] Step S404: When the first discharge condition and the second discharge condition are met simultaneously, the discharge diagnosis result is determined to be that a discharge fault exists.

[0100] In this embodiment, the baseline concentration value is the average value of ozone concentration data under normal operating conditions without discharge.

[0101] Because different motor junction boxes vary in size, sealing degree, etc., this benchmark concentration value can be measured individually for each junction box.

[0102] Specifically, to achieve baseline calibration, after each equipment startup, sampling concentration data is collected within 15 minutes while confirming that the motor is running normally. The average value is taken as the baseline concentration value C0, which is used as a reference in subsequent calculations to adapt to ozone concentration fluctuations during the startup phase of medium and high voltage motors.

[0103] Understandably, considering that environmental conditions may change over time, the system can also recalibrate the baseline concentration value periodically according to a preset update cycle, such as automatically performing calibration once a month or quarter.

[0104] After obtaining the baseline concentration value, the ozone concentration data (C real-time) collected by the ozone sensor inside the junction box is monitored in real time. By analyzing the concentration change trend, the unit concentration increment ΔC per unit time is calculated. The unit concentration increment represents the change of the currently collected ozone concentration data relative to the baseline concentration value per unit time. The specific calculation method is to subtract the baseline concentration value from the ozone concentration data collected per unit time to obtain the unit concentration increment.

[0105] Next, the system simultaneously performs the judgment of the first discharge condition and the second discharge condition. The core of the first discharge condition is to determine whether the absolute value of the ozone concentration data has exceeded the safety threshold, and the core of the second discharge condition is to determine whether the trend of the ozone concentration data shows a continuous upward characteristic.

[0106] Specifically, the first discharge condition is that the ozone concentration data is greater than the ozone concentration threshold and the duration is greater than the sampling period. The ozone concentration threshold must be set in a way that can capture ozone concentration fluctuations caused by partial discharge, while avoiding false alarms caused by background noise or zero-point drift of the sensor itself. Therefore, after the ozone concentration threshold is determined, the first discharge condition is determined to be met only when the ozone concentration data exceeds the ozone concentration threshold and lasts for at least one sampling period.

[0107] The second discharge condition is that the unit concentration increment is greater than the increment threshold and the duration is greater than the sampling period. The increment threshold represents the rate of ozone rise, used to distinguish between slow and rapid increases. If a discharge occurs, the ozone concentration inside the junction box will rise continuously at a certain rate, while the increment change caused by environmental drift is usually slower. Therefore, by setting a reasonable increment threshold, the unit concentration increment change caused by the discharge phenomenon can be effectively distinguished from the unit concentration increment change caused by drift, effectively identifying the true discharge phenomenon. Similar to the first discharge condition, the second discharge condition also requires that the state of unit concentration increment being greater than the increment threshold lasts for more than one sampling period to eliminate the random fluctuations of a single sampling. Only when the unit concentration increment is greater than the increment threshold and the duration is greater than the sampling period is the second discharge condition determined to be valid.

[0108] By combining the first discharge condition and the second discharge condition, the discharge diagnosis result is determined to be that a discharge fault exists only when both the first discharge condition and the second discharge condition are met simultaneously.

[0109] For example, assuming the ozone concentration threshold is 0.4 ppm and the incremental threshold is 0.15 ppm / h, if ΔC ≥ 0.15 ppm / h, and C ≥ 0.4 ppm in real time, and the duration is ≥ 1 sampling cycle or multiple sampling cycles, then a discharge phenomenon (such as partial discharge or corona discharge) is determined to exist. At this time, the insulation inside the junction box may have been damaged, and an alarm needs to be triggered to avoid the rapid development of insulation breakdown in medium and high voltage scenarios.

[0110] In some embodiments, step S302 may include, but is not limited to, steps S501 to S502.

[0111] Step S501: Calculate the temperature difference based on the current area temperature corresponding to the three-phase terminals to obtain the three-phase temperature difference, and determine whether the three-phase temperature difference is greater than the preset temperature difference threshold. If the three-phase temperature difference is greater than the temperature difference threshold, the temperature diagnosis result is determined to be a temperature fault in the three-phase terminals.

[0112] Step S502: Determine whether the temperature of the current area corresponding to the hot spot is greater than the preset local temperature threshold. If the temperature of the current area corresponding to the hot spot is greater than the temperature threshold, then the temperature diagnosis result is determined to be that there is a temperature fault at the hot spot.

[0113] Step S304 may include, but is not limited to, steps S503 to S505.

[0114] Step S503: Based on the historical heat map and motor operating conditions, identify the abnormalities in the temperature diagnosis results and determine whether the temperature fault is a persistent fault.

[0115] Step S504: If the temperature fault is not a persistent fault, the root cause of the fault is determined to be abnormal temperature caused by loose wiring, poor contact, or uneven current.

[0116] Step S505: When the temperature fault is a persistent fault, the root cause of the fault is determined to be an insulation abnormality, and the cause of the insulation abnormality is determined based on the discharge diagnosis results and the sealing diagnosis results.

[0117] In this embodiment, when performing temperature diagnosis, if there is a temperature fault in the three-phase terminals, the heat points are mostly concentrated in the metal conductors of the terminals, and the three-phase temperature difference between the three-phase terminals is significant. Therefore, the temperature difference between the three-phase terminals can be calculated in real time based on the current area temperature corresponding to the three-phase terminals: ΔT1=|T_A-T_B|, ΔT2=|T_A-T_C|, ΔT3=|T_B-T_C|, where ΔT1 represents the temperature difference between the A-phase terminal and the B-phase terminal, ΔT2 represents the temperature difference between the A-phase terminal and the C-phase terminal, and ΔT3 represents the temperature difference between the B-phase terminal and the C-phase terminal.

[0118] Furthermore, considering the operating characteristics of medium and high voltage motors, a preset temperature difference threshold is established (≤10℃ under normal operating conditions, which can be set according to site requirements). This threshold is stricter than that for low-voltage scenarios and is suitable for the heating characteristics of medium and high voltage motors. By judging whether the three-phase temperature difference is greater than the preset temperature difference threshold, if any one of the three-phase temperature differences is greater than the preset temperature difference threshold, the temperature diagnosis result is determined to be a temperature fault in the three-phase terminals.

[0119] Considering that temperature faults can occur not only on the three-phase terminals but also at hot spots, the thermal imaging area temperature anomaly image recognition function is used to automatically identify temperature anomaly areas (such as the current temperature of the area corresponding to the hot spot exceeding the preset local temperature threshold of 80℃). If a temperature anomaly area exists, the temperature diagnosis result is determined to be a temperature fault at the hot spot.

[0120] After confirming the existence of a temperature fault, the historical heat map comparison function is invoked. By analyzing the temperature difference between the current heat map and the historical heat map of the same period (or normal operating conditions), and combining it with the motor operating conditions, the correlation between temperature and load is determined, thereby helping to determine whether the abnormality is a persistent fault.

[0121] When a temperature fault is not a persistent fault, and there is a strong correlation between temperature and load, and the temperature cools down rapidly after the motor stops, this fault can be identified as an abnormal temperature caused by loose wiring, poor contact, or uneven current.

[0122] When a temperature fault is a persistent fault, the correlation between temperature and load is weak, and it exhibits regional slow heating characteristics, with a continuous temperature rise even after light load and shutdown, and a gradual spread of the heat zone and an overall synchronous upward trend compared to historical thermal maps, it can be identified as an insulation-related anomaly.

[0123] It should be noted that insulation faults in the junction boxes of medium and high voltage motors are caused by the combined effect of multiple factors and are clearly related to temperature, humidity, human operation, and material characteristics. Based on the temperature diagnosis results, the causes of insulation abnormalities can be determined according to the discharge diagnosis results and the sealing diagnosis results. The causes include local overheating factors, discharge factors, or moisture ingress factors.

[0124] For example, the above-mentioned insulation faults can be identified by monitoring temperature, humidity, and ozone in tandem and combining their abnormal characteristics. A summary is as follows: Abnormal humidity (too high, drastic fluctuations, or condensation) can directly indicate moisture absorption-related degradation of insulation. Combined with a continuous and slow increase in temperature and no obvious load correlation, it can be judged as insulation aging induced by moisture ingress.

[0125] In cases of abnormal temperature, localized, point-like high temperatures that are strongly correlated with the load often correspond to localized overheating and secondary insulation faults caused by improper human operation (loose wiring, damaged insulation). Regional slow heating with slow cooling often corresponds to insulation deterioration caused by material defects or natural aging.

[0126] An abnormally high ozone concentration is a characteristic signal of partial discharge and creepage in insulation. Combined with abnormal humidity, it can be identified as a discharge-type insulation fault induced by moisture. Combined with abnormal temperature, it can be identified as a discharge fault caused by accelerated insulation deterioration. The coordinated monitoring of these three factors can achieve accurate identification and early warning of various insulation faults.

[0127] In some embodiments, step S503 may include, but is not limited to, steps S601 to S603.

[0128] Step S601: Calculate the ratio of the number of faults in the temperature diagnosis results for the three-phase terminals and the hottest points to obtain the fault percentage.

[0129] Step S602: Based on historical heat maps and motor operating conditions, feature extraction is performed on temperature and load to obtain temperature-load correlation features.

[0130] Step S603: Based on the fault ratio and temperature load correlation characteristics, anomaly identification is performed to determine whether the temperature fault is a persistent fault.

[0131] In this embodiment, the abnormality of temperature faults can be divided into two fundamentally different types according to different heating mechanisms.

[0132] The first type is primary overheating problems such as loose wiring or poor contact, which can cause secondary insulation damage through high-temperature ablation and carbonization. This type of temperature fault is characterized by the heat point being concentrated on the metal conductor of the terminal, significant three-phase temperature difference, strong correlation between temperature and load, and rapid cooling after shutdown. It is not a continuous fault.

[0133] The second type is primary insulation defects caused by factors such as insulation aging, moisture, and cracking of the insulation material, which trigger partial discharge and increased dielectric loss, leading to abnormal heating. The heating further accelerates insulation deterioration, forming a vicious cycle. This type of temperature fault is located in the insulation sheath, phase spacer, and creepage path, exhibits regional slow heating characteristics, has a weak correlation with the load, and continues to rise in temperature even under light load and after shutdown. Moreover, compared with historical thermal maps, it shows the characteristics of gradual spread of the heat zone and overall synchronous rise trend, which is a persistent fault.

[0134] To differentiate temperature faults, this embodiment determines whether the abnormality is concentrated at the three-phase terminals or distributed in easily heated points such as insulation sheaths, phase separators, and creepage paths, based on the spatial distribution characteristics of the temperature anomalies. Each abnormal area is labeled either "Three-phase terminal area" or "Easily heated point area." By statistically analyzing the number of three-phase terminal faults and easily heated point faults identified during the current diagnostic process, and calculating the ratio of the number of three-phase terminal faults to the number of easily heated point faults, the fault percentage is obtained.

[0135] For example, if two of the three-phase terminals have temperature faults, but the heat-prone points on the insulation material surface do not show any abnormalities, the fault percentage tends to indicate that the fault is concentrated in the three-phase terminal area. Conversely, if the temperatures of the three-phase terminals are all normal, but multiple areas of the insulation material surface show slow heating, the fault percentage tends to indicate that the fault is concentrated in the heat-prone point area.

[0136] Furthermore, based on historical heat maps and motor operating conditions, the correlation between temperature changes over time and motor load is analyzed from the perspective of thermal response characteristics to obtain temperature-load correlation characteristics. By aligning the temperature time series and load series over time and performing correlation analysis, the stronger the correlation of the temperature-load correlation characteristics, the stronger the trend of temperature changing in the same direction as the load.

[0137] Finally, anomaly identification is performed based on the fault percentage and temperature-load correlation characteristics. If the fault percentage tends to indicate that the faults are concentrated in the three-phase terminal area, and the temperature-load correlation characteristics reflect a strong correlation between temperature and load and rapid cooling after shutdown, then it is determined that the temperature fault is not a persistent fault.

[0138] If the fault rate indicates that the faults are concentrated in areas prone to overheating, and the temperature-load correlation characteristics show a weak correlation between temperature and load, and there is a continuous temperature rise even after light load and shutdown, then the temperature fault is determined to be a persistent fault.

[0139] In some embodiments, the method for fault monitoring of explosion-proof motor junction boxes based on multi-source data collaborative analysis further includes step S701.

[0140] Step S701: If the explosion-proof motor junction box is not faulty within the preset maintenance cycle, the monthly periodic opening inspection will be stopped, and the box will only be opened for maintenance after the maintenance cycle expires.

[0141] Specifically, since regular opening and inspection would damage the original explosion-proof sealing structure of the junction box and increase the risk of explosion-proof failure, this embodiment uses a 3.5V lithium battery for power supply. The low power consumption design ensures that the battery life can guarantee continuous, stable and reliable operation within a maintenance cycle (e.g., 5 years). Through continuous real-time monitoring and accurate early warning prediction, if no abnormality is detected in the motor junction box within the maintenance cycle, it replaces the monthly or several-monthly external temperature measurement and regular opening and inspection process. The box is only opened for maintenance when the maintenance cycle expires, ensuring the continuous production operation of the device and reducing operation and maintenance costs and safety risks.

[0142] The following is a detailed description and explanation of the solutions in the embodiments of the present invention, using specific application examples: Taking the petrochemical industry as an example, current maintenance procedures for explosion-proof motors require that critical motors undergo manual temperature measurement outside the junction box using thermal imaging every month to several months. A major overhaul cycle requires opening the junction box for inspection, with a cycle of 4 or 5 years. However, external temperature measurement is susceptible to environmental interference and cannot accurately capture the temperature of the three-phase terminals and hot spots inside the box in real time. Regularly opening the box for inspection not only damages the original explosion-proof sealing structure of the junction box, increasing the risk of explosion-proof failure, but also requires shutdown, affecting production continuity. Furthermore, frequent opening and on-site inspections increase the risk of high-voltage electric shock for maintenance personnel. In the long run, maintenance costs remain high, and the existing maintenance model is no longer suitable for the petrochemical industry's core needs of "cost reduction and efficiency improvement, and safe operation and maintenance."

[0143] To address the shortcomings of current fault monitoring technologies, such as insufficient accuracy in temperature monitoring, lack of discharge fault monitoring, inadequate collaborative analysis of data from inside and outside the junction box, unstable data transmission, and incomplete fault coverage, this embodiment provides a fault monitoring solution adapted to 6KV and above medium- and high-voltage explosion-proof motor junction boxes, aiming to achieve the following objectives: 1. Compatible with 6KV and above medium and high voltage explosion-proof motor junction boxes. All modules meet the requirements of medium and high voltage explosion-proof level and are suitable for high voltage, high heat generation and high discharge risk conditions in medium and high voltage scenarios.

[0144] 2. The temperature is measured by the thermal imaging array of the intelligent temperature and humidity terminal inside the box to achieve regional positioning, accurately collect the temperature of the three-phase terminal area and other areas prone to heat generation, realize the accurate calculation of the highest temperature of the three phases and the temperature difference of the three phases, and provide abnormal alarms, which is suitable for the concentrated heat generation characteristics of medium and high voltage motors.

[0145] 3. By integrating an ozone sensor into a thermal imaging temperature and humidity smart terminal, the ozone concentration change trend can be monitored in real time inside the motor junction box. This allows for accurate identification of discharge phenomena and potential discharge hazards within the junction box, providing early warnings of insulation breakdown and arc fire risks, thus meeting the monitoring needs of high discharge risks in medium and high voltage scenarios.

[0146] 4. The system collects internal temperature and humidity, ozone concentration, temperature of the three-phase terminal area, and temperature of the heat-prone area through the in-box terminal, and external temperature and humidity data through the external 5G temperature and humidity fusion terminal. Based on the collaborative analysis of the internal and external temperature and humidity data, the system can achieve full-element fault diagnosis and prediction, such as "using the internal and external temperature and humidity terminals to detect faults in the motor junction box, such as poor sealing, water ingress (dampness), abnormal temperature, abnormal humidity, and abnormal insulation", which greatly improves the diagnostic accuracy of sealing faults, abnormal humidity, and abnormal insulation.

[0147] 5. It integrates three core functions: internal temperature measurement of thermal imaging box, internal discharge monitoring of ozone box, and coordinated monitoring of internal and external temperature and humidity. It optimizes fault diagnosis logic and realizes full-element fault diagnosis and prediction for abnormal temperature, abnormal three-phase temperature, abnormal humidity, dampness or water ingress, poor sealing of junction box, discharge hazard, and insulation abnormality. It achieves the goal of one-stop, full-coverage, and high-precision fault monitoring without the need for multiple monitoring devices, thus reducing operation and maintenance costs and complexity.

[0148] 6. Relying on the 5G transmission function of the external 5G temperature and humidity fusion terminal, it realizes the real-time remote transmission of all monitoring data and fault alarm information, adapts to the needs of remote deployment and long-distance monitoring of medium and high voltage motors, and adapts to the original near-field communication mechanism, reducing the cost of transformation and operation and maintenance, and meeting the core needs of industry network security, data security, explosion protection, intelligent operation and maintenance, and remote supervision.

[0149] Reference Figure 3 , Figure 3 This is a schematic diagram of the structure of a fault monitoring device for explosion-proof motor junction boxes based on multi-source data collaborative analysis, provided in another embodiment of this application. The core of this device is designed for 6KV and above medium- and high-voltage explosion-proof motor junction box scenarios, featuring a dual-terminal collaborative structure of an "intelligent thermal imaging temperature and humidity terminal (integrated ozone sensor)" inside the box and a "5G temperature and humidity fusion terminal" outside the box. The overall structure is compatible with medium- and high-voltage explosion-proof design, and all modules meet the national standards for medium- and high-voltage explosion-proof electrical equipment.

[0150] Specifically, the thermal imaging temperature and humidity smart terminal (integrated with an ozone sensor) is installed inside the junction box, adapting to the spatial structure of medium and high voltage junction boxes. It supports near-field communication, with temperature and humidity acquisition accuracy of ±0.5℃ and ±2.0%RH. It features an intrinsically safe explosion-proof design, is suitable for 6KV and above medium and high voltage operating conditions, and integrates an ozone sensor and a thermal imaging probe. Its core integrated functions are: First, a thermal imaging array is used to accurately collect the temperature of the three-phase terminal area and other heat-prone areas inside the motor junction box, providing data support for monitoring temperature and insulation anomalies. Second, an integrated ozone sensor is used to monitor discharge phenomena and potential hazards inside the motor junction box. Third, temperature and humidity data inside the junction box are collected and combined with external temperature and humidity data to achieve comprehensive fault diagnosis. At the same time, data processing and near-field communication functions are integrated to achieve internal data acquisition and preliminary fault judgment, and work in collaboration with external terminals to ultimately support comprehensive fault diagnosis and prediction of the motor junction box.

[0151] The thermal imaging temperature and humidity smart terminal is equipped with a temperature and humidity sensor installed close to the inner wall of the junction box and away from live parts to collect temperature and humidity data inside the junction box. This provides data support for the diagnosis of sealing faults and abnormal humidity. It is suitable for high-temperature environments in medium and high voltage scenarios. It has the same temperature and humidity acquisition accuracy as the thermal imaging temperature and humidity smart terminal, and the temperature measurement range is -40℃ to 300℃, which is suitable for the heating characteristics of medium and high voltage motors.

[0152] Within the thermal imaging-based intelligent temperature and humidity terminal, the three-phase terminals in medium- and high-voltage junction boxes experience concentrated and fluctuating temperatures. Contact-based temperature measurement can only collect temperature data at a single point, failing to cover all heat-prone areas and is susceptible to measurement errors due to high-temperature conduction from the terminals. Non-contact thermal imaging, on the other hand, enables regional temperature measurement, simultaneously capturing the temperatures of the three-phase terminals and surrounding heat-prone areas, accurately presenting the temperature distribution. This aligns with the concentrated and multi-point heating characteristics of medium- and high-voltage systems. Therefore, this embodiment employs a thermal imaging array composed of thermal imaging probes. The probes are positioned directly facing the three-phase terminal area or heat-prone area, without obstructing the terminals or touching live parts, maintaining a safe distance. Its core function is to accurately collect the temperature of the three-phase terminal area and other heat-prone areas within the motor junction box using area positioning technology within the array, outputting temperature distribution images and temperature data for each area. This provides crucial data support for the diagnosis and prediction of temperature and insulation anomalies. The thermal imaging probe has a temperature measurement range of -40℃ to 300℃ and a temperature measurement accuracy of ±(1.5+temp*1.5%)℃. It supports area positioning and division, abnormal image recognition, historical heat map storage and comparison, and is resistant to electromagnetic interference. It adopts a plug-in connection with the temperature and humidity smart terminal, which is plug-and-play.

[0153] The thermal imaging temperature and humidity smart terminal also includes an ozone sensor, kept away from the terminal block area to avoid obstructing the sensor probe and at a safe distance from high-temperature areas and live parts. Its core function is to collect ozone concentration data in real time within the motor junction box, monitor concentration trends, and accurately capture trace amounts of ozone generated by partial discharge and corona discharge within the box, providing data support for determining discharge phenomena and potential hazards. The ozone sensor's measurement range is designed to match stable operation within a major overhaul cycle within the motor junction box, such as 0~100ppm, with a measurement accuracy of ±0.05ppm, a response time ≤8s, resistance to medium and high voltage electromagnetic interference, and suitability for high-temperature, oil and gas accumulation, and high-voltage environments within the junction box. It can capture trace amounts of ozone generated by corona discharge.

[0154] The motor junction box also houses a data processing and communication module, specifically including a processor module and a near-field communication module. These modules are used for data synchronization, initial fault diagnosis, and data interaction with external terminals. The data processing and communication module is equipped with an STM32 microcontroller, supports near-field communication such as Bluetooth / LoRa, is resistant to medium- and high-voltage electromagnetic interference, adapts to strong electromagnetic environments in medium- and high-voltage scenarios, and features low-power operation, meeting the long-term power supply requirements of terminals.

[0155] It should be noted that the initial fault determination can be triggered by a threshold (such as setting the temperature inside the box to 40 degrees, and the temperature reaching 40 degrees when the terminal inside the box samples) or a rate of change (such as the temperature at the time of the later sampling being greater than 5 degrees compared to the temperature at the time of the previous sampling), which will then package the array data and upload it to the outside of the box.

[0156] The power management battery pack inside the box serves as the power module, powered by a 3.5V lithium battery. Its low-power design supplies power to all modules within the box. The battery life guarantees continuous, stable, and reliable operation for up to 5 years over a major overhaul cycle. The backup battery provides at least 60 minutes of runtime, supports power outage testing, resists medium- and high-voltage electromagnetic interference, is overload and short-circuit resistant, and is compatible with built-in installation requirements for medium- and high-voltage terminals, ensuring explosion-proof performance.

[0157] A 5G temperature and humidity fusion terminal is installed near the junction box on the outside of the motor junction box. This terminal collects real-time temperature and humidity data from outside the junction box, enabling high-speed 5G transmission (uploading all monitoring data and fault alarm information from inside and outside the box to a remote platform). It also interacts with the terminal inside the box to receive remote commands. The terminal has a temperature and humidity acquisition accuracy of ±0.5℃ and ±2%RH, an ultra-low power consumption design, and is powered by a built-in 3.5V long-life explosion-proof battery. The battery life can guarantee continuous, stable, and reliable operation for up to 5 years during a major overhaul cycle. It has a built-in data storage module with a data storage duration of ≥2 days, enabling data integration from inside and outside the box, uploading in corresponding modes, and receiving remote commands. It also supports wireless collaborative interaction with the thermal imaging temperature and humidity smart terminal inside the box. The explosion-proof rating is Ex ia IIC T4 Ga, suitable for Zone 0, Zone 1, and Zone 2 hazardous locations in petrochemical sites, meeting the explosion-proof requirements of high-risk petrochemical environments.

[0158] The aforementioned explosion-proof motor junction box fault monitoring device based on multi-source data collaborative analysis achieves data synchronization through wireless collaborative interaction, without requiring modifications to the motor wiring or damaging the original explosion-proof sealing structure of the junction box. It is specifically adapted to the structural dimensions and operating conditions of 6KV and above medium- and high-voltage motor junction boxes. Both terminals adopt a dedicated explosion-proof design for medium and high voltage, effectively resisting strong electromagnetic interference generated by medium- and high-voltage motors and avoiding data acquisition and transmission distortion. The external 5G temperature and humidity fusion terminal is powered by a built-in 3.5V dedicated long-life explosion-proof battery, ensuring power supply stability and meeting the long-term continuous operation requirements of medium- and high-voltage motors. Through continuous real-time monitoring and accurate early warning prediction, if no abnormality is detected in the motor junction box, it replaces the existing periodic external temperature measurement and periodic opening inspection process within a major overhaul cycle (4 or 5 years). The device is only opened for maintenance when the major overhaul cycle expires, ensuring continuous production operation and reducing maintenance costs and safety risks.

[0159] The core technical principle of the explosion-proof motor junction box fault monitoring device based on multi-source data collaborative analysis provided in this embodiment is as follows: (1) Principle of dual-terminal collaborative acquisition and data interaction.

[0160] Data acquisition tasks are divided as follows: The in-box thermal imaging temperature and humidity smart terminal completes three main acquisition tasks: acquiring the temperature of the three-phase terminal area and other heat-prone areas inside the motor junction box through a thermal imaging array; acquiring the temperature and humidity inside the junction box through an in-box temperature and humidity sensing module; and acquiring the ozone concentration inside the motor junction box through an integrated ozone sensor. The external 5G temperature and humidity fusion terminal is responsible for acquiring external temperature and humidity data of the junction box, providing data for collaborative analysis of temperature and humidity inside and outside the box, supporting full-element fault diagnosis and prediction of poor sealing, water ingress (dampness), abnormal temperature, abnormal humidity, and abnormal insulation, and avoiding interference from the external environment with internal data acquisition.

[0161] Data collaborative interaction: The internal terminal and the external terminal achieve data synchronization through anti-interference wireless communication. The internal terminal transmits all the data collected internally to the external terminal in real time. The external terminal integrates the data inside and outside the box to form a complete dataset.

[0162] (2) High-definition thermal imaging array area positioning temperature measurement and three-phase temperature difference determination logic.

[0163] The use of thermal imaging array positioning and temperature measurement technology enables precise location and temperature measurement of three-phase terminal areas and other areas prone to overheating, significantly improving measurement accuracy and fault diagnosis reliability, and making it more suitable for medium and high voltage scenarios. By pre-setting area positioning parameters, the thermal imaging screen is divided into independent monitoring areas corresponding to the three-phase terminals and monitoring areas for overheating points, achieving precise acquisition and separation of temperatures from the three-phase terminals and overheating points.

[0164] Regional positioning calibration: During installation, near-field communication debugging is used to accurately align the thermal imaging array image with the three-phase terminal positions and the positions of easily heated points. Multiple positioning areas are preset (each area corresponds to one phase terminal and one easily heated point) to expand the high temperature monitoring range, eliminate temperature interference from irrelevant areas around the terminal, ensure the accuracy of temperature measurement, and adapt to the layout characteristics of medium and high voltage terminal positions.

[0165] Temperature acquisition: The temperature and humidity sensor in the smart terminal inside the junction box refreshes its data every 10 seconds. The thermal imaging probe collects temperature data of the three-phase terminals and other areas prone to heat in the junction box in real time, refreshing its data every 60 seconds. The data is then transmitted synchronously to the data processing module inside the box to generate the highest temperature values ​​(T_A, T_B, T_C, T_heat1, T_heat2...) of the three-phase terminal area and other areas prone to heat, as well as real-time temperature values ​​of the highest temperature of the areas prone to heat (T_A, T_B, T_C, T_heat1, T_heat2...), temperature distribution images, and heat maps.

[0166] Three-phase temperature difference calculation and anomaly judgment: The data processing module calculates the temperature difference between the three-phase terminals in real time. Combined with the operating characteristics of medium and high voltage motors, a preset temperature difference threshold is set. At the same time, through the image recognition function of temperature anomalies in the thermal imaging area, the abnormal temperature area is automatically identified. The historical thermal map comparison function is called. By analyzing the temperature difference between the current thermal map and the historical thermal map of the same period (or normal operating conditions), it helps to determine whether the anomaly is a persistent fault.

[0167] If the heat source is concentrated on the metal conductor of the terminal block, the three-phase temperature difference is significant, the temperature is strongly correlated with the load, and the temperature cools down rapidly after shutdown, it is determined that the abnormal temperature is caused by loose wiring, poor contact, or uneven current.

[0168] If the heating area is located in the insulation sheath, phase spacer, and creepage path, exhibits regional slow heating characteristics, has a weak correlation with the load, and continues to rise in temperature even under light load and after shutdown, and shows a gradual spread of the heat zone and an overall synchronous upward trend when compared with historical thermal maps, then it is determined to be an insulation-related abnormality caused by insulation deterioration, moisture, partial discharge, or creepage.

[0169] By using the above multi-dimensional criteria, the fault type can be accurately located, providing support for early warning and differentiated operation and maintenance strategies.

[0170] Abnormal Alarm: When the temperature and humidity sensor temperature rises to a certain value (e.g., 3℃, adjustable) within one or several sampling cycles, thermal imaging is triggered. When any temperature difference exceeds the corresponding threshold, or when the thermal imaging image identifies an abnormal temperature area, or when historical thermal maps show a persistent abnormal temperature difference, it is determined to be a temperature-related abnormality (three-phase temperature difference abnormality / temperature abnormality of easily heated points), triggering a graded alarm (mild alarm: such as 5℃ < temperature difference ≤ 10℃ or easily heated point temperature 80-100℃; severe alarm: temperature difference > 10℃ or easily heated point temperature > 100℃; trigger values ​​can be set according to the actual site conditions), simultaneously outputting fault location (clearly identifying the abnormal area and thermal map comparison results) and maintenance suggestions (such as checking for loose wiring, oxidation corrosion, excessive contact resistance, etc.), and transmitting the alarm information to the external terminal, which is then uploaded to the remote platform through the corresponding transmission mode.

[0171] (3) Ozone sensor monitoring and discharge phenomenon, discharge hazard judgment logic.

[0172] Given the high discharge risk of 6KV and above medium and high voltage motor junction boxes, and considering the ozone generation characteristic of discharge phenomena (partial discharge, corona discharge), this embodiment uses an ozone sensor to monitor the concentration change trend inside the motor junction box. Combined with motor operating conditions and temperature and humidity data inside and outside the box, it can accurately determine discharge phenomena and potential hazards, avoiding misjudgments caused by a single concentration threshold. At the same time, it provides support for the diagnosis and prediction of insulation abnormalities (caused by discharge).

[0173] Reference value calibration: After the equipment is started, ozone concentration data is collected within 15 minutes under normal motor operation and no discharge phenomenon, and the average value is taken as the reference concentration value (C0).

[0174] Real-time monitoring and trend analysis: The ozone sensor collects the ozone concentration (C_real-time) in the junction box in real time. The data processing module in the box analyzes the concentration change trend (concentration increment ΔC = C_real-time - C0 per unit time). At the same time, it combines the temperature and humidity difference between the inside and outside of the box to eliminate environmental interference (such as external high humidity infiltration, oil and gas interference).

[0175] Discharge phenomenon judgment criteria: When ΔC≥0.15ppm / h, and C in real time≥0.4ppm, and the duration≥1 sampling cycle or multiple sampling cycles (ΔC, C and duration can be set according to on-site requirements), it is judged that a discharge phenomenon exists.

[0176] Interference elimination: When the motor stops, temperature and humidity change suddenly (such as water ingress or high humidity infiltration), or external oil and gas intrusion causes abnormal fluctuations in ozone concentration, the system combines the temperature and humidity difference between the inside and outside of the box with the results of sealing fault diagnosis to determine interference and not trigger an alarm, ensuring the accuracy of the determination and adapting to the complex operating environment of medium and high voltage scenarios.

[0177] (4) Collaborative diagnosis of data inside and outside the box and collaborative diagnosis logic for all types of faults.

[0178] The external 5G temperature and humidity fusion terminal integrates all data inside and outside the box. Combined with the fault characteristics of medium and high voltage scenarios, it can realize full-element fault diagnosis and prediction by "using the temperature and humidity inside and outside the box to measure the motor junction box for poor sealing, water ingress (dampness), abnormal temperature, abnormal humidity, and abnormal insulation". It forms a closed-loop process of "data acquisition - feature extraction - logic judgment - hierarchical alarm - maintenance suggestion - multi-mode transmission".

[0179] Data Synchronous Collection and Integration: The thermal imaging temperature and humidity smart terminal inside the box and the 5G temperature and humidity fusion terminal outside the box collect data synchronously with a unified timestamp to ensure data correlation. The external terminal integrates all data (temperature of the three-phase terminal area and other areas prone to heat, ozone concentration, temperature and humidity inside the box, and temperature and humidity outside the box).

[0180] Single fault diagnosis: (a) Determination of temperature anomalies, three-phase temperature difference anomalies, and insulation anomalies (caused by local overheating): Based on the data collected by the thermal imaging probe in the motor junction box, the temperature values ​​of the three-phase terminal area and other areas prone to heat generation are extracted, the three-phase temperature difference is calculated, and the temperature anomalies and three-phase temperature difference anomalies are determined by combining the preset thresholds for medium and high voltage scenarios; at the same time, the image recognition function of temperature anomalies in the thermal imaging area is used to identify the local temperature exceeding the threshold area, and the historical thermal map comparison function is called. By comparing and analyzing the current and historical thermal maps, the anomaly type is confirmed, and then the insulation anomalies caused by local overheating are diagnosed and predicted.

[0181] (b) Discharge phenomenon and hidden danger, insulation abnormality (caused by discharge) judgment: Based on the ozone concentration data collected by the ozone sensor in the motor junction box, the concentration change trend is analyzed, and the discharge phenomenon and discharge hidden danger are judged in combination with the benchmark value C0 and the judgment standard of medium and high voltage scenarios. At the same time, the temperature data is linked to diagnose and predict insulation abnormalities such as insulation damage and insulation aging caused by discharge.

[0182] (c) Determination of abnormal humidity, dampness / water ingress, poor sealing, and insulation abnormalities (caused by dampness): Based on the temperature and humidity data inside and outside the box, the difference between the temperature and humidity inside and outside the box is calculated and compared with the trend over a period of time. Combined with the optimized sealing fault diagnosis logic, the abnormal humidity, dampness / water ingress, and poor sealing faults are accurately determined. At the same time, combined with the abnormal humidity data, insulation abnormalities caused by dampness and water ingress are diagnosed and predicted. The goal of "relying on the collaborative acquisition of dual terminals inside and outside the box and 5G transmission technology, the goal of full-element fault diagnosis and prediction of motor junction box sealing abnormalities, water ingress (dampness), temperature abnormalities, humidity abnormalities, and insulation abnormalities without changing the motor explosion-proof structure" is fully realized.

[0183] Collaborative optimization determination: In medium and high voltage motor junction boxes, insulation, humidity, and temperature are bidirectionally coupled. Abnormal humidity is the initial trigger for insulation degradation and indirectly causes temperature anomalies; moisture intrusion exacerbates insulation loss and discharge, initiating the aging process and leading to localized temperature increases. Insulation degradation is the core link between the two; its degradation enhances moisture absorption and exacerbates dielectric loss, further driving the escalation of temperature anomalies. Temperature anomalies, in turn, accelerate insulation thermal aging and humidity sensitivity, creating an irreversible vicious cycle of failure.

[0184] Among them, insulation failures in high-voltage motor junction boxes are caused by the combined effects of multiple factors, and are clearly related to temperature, humidity, human operation, and material characteristics: abnormal humidity is an important environmental factor that induces insulation degradation. Moisture intrusion reduces the resistivity of insulation materials, exacerbates dielectric loss and surface discharge, thereby initiating insulation aging and indirectly causing local temperature anomalies; abnormal temperature will inversely accelerate the thermal aging of insulation, while amplifying the moisture absorption sensitivity of insulation materials, forming a vicious cycle of bidirectional coupling with abnormal humidity; improper human operation (such as bumps or scratches to the insulation layer during installation or maintenance, or insulation damage caused by the squeezing of wiring bolts) will directly damage the integrity of the insulation structure and cause insulation failures; defects in the material itself (such as unreasonable insulation material formulation or manufacturing process defects leading to substandard initial insulation performance) or natural aging of materials (natural breakage of molecular chains and performance degradation after long-term use) will reduce the insulation's resistance to electric fields and environmental interference, making it prone to degradation and failure under normal operating conditions; in addition, factors such as electrical stress and chemical corrosion can also cause insulation failures independently or in combination with the above factors.

[0185] In view of this, this embodiment combines data from multiple modules and the operating conditions of medium and high voltage motors to eliminate misjudgments (such as distinguishing between abnormal humidity caused by high temperature and water ingress, distinguishing between abnormal temperature caused by discharge and loose wiring, and concentration fluctuations caused by external environmental interference) and clarify the root cause of the fault.

[0186] Finally, based on the severity of the fault, three levels of alarms (mild, moderate, and severe) are output, along with targeted maintenance suggestions (adapting to the operation and maintenance requirements of medium and high voltage scenarios). All data and alarm information are uploaded to the remote monitoring platform through the 5G module of the external 5G temperature and humidity fusion terminal. Local data export is supported through near-field communication, adapting to the original operation and maintenance process. At the same time, remote command issuance is supported to achieve remote calibration and parameter adjustment.

[0187] In summary, this embodiment addresses the high voltage, high heat generation, high discharge risk, and long-distance monitoring requirements of 6KV and above medium-high voltage scenarios. For the first time, it designs a dual-terminal collaborative structure for 6KV and above medium-high voltage explosion-proof motor junction boxes: an in-box thermal imaging temperature and humidity smart terminal (integrating thermal imaging array, temperature and humidity, and ozone monitoring functions) + an external 5G temperature and humidity fusion terminal. This integrates the thermal imaging array, temperature and humidity, and ozone monitoring into the in-box smart terminal, and has three core advantages: First, a thermal imaging array is used to measure the temperature inside the motor junction box, accurately collecting the temperature of the three-phase terminals and easily heated points. At the same time, the innovative thermal imaging array temperature measurement technology is adopted, adding image recognition of temperature anomalies in the thermal imaging area and the function of comparing historical heat maps, breaking through the limitations of traditional single-point temperature measurement and realizing regionalized and precise temperature measurement.

[0188] Secondly, ozone monitoring is used to detect discharge inside the motor junction box, capturing discharge phenomena and potential hazards inside the box, thus filling the blind spot in discharge monitoring inside the box.

[0189] Third, by using the temperature and humidity inside and outside the box, we can achieve full-element fault diagnosis and prediction for motor junction box problems such as poor sealing, water ingress (dampness), abnormal temperature, abnormal humidity, and abnormal insulation, thus overcoming the shortcoming of incomplete fault coverage.

[0190] In addition, this embodiment also designs a multi-pixel specification and plug-and-play structure for the thermal imaging probe, which can be adapted to different on-site budgets and monitoring needs, and overcomes the limitations of infrared detection in terms of accurate positioning and insufficient temperature measurement accuracy.

[0191] In medium- and high-voltage scenarios, the explosion-proof motor junction box fault monitoring device based on multi-source data collaborative analysis provided in this embodiment accurately collects the temperature of easily heated points inside the junction box through thermal imaging array temperature measurement technology. The accuracy rate of three-phase temperature difference judgment is ≥99.5%, and the accuracy rate of easily heated point temperature monitoring is ≥99%. It can accurately capture temperature differences of 0.5℃, avoiding missed detection of faults such as loose wiring, oxidation, and local overheating in medium- and high-voltage scenarios.

[0192] The newly added features include image recognition of abnormal temperatures in thermal imaging areas and comparison with historical heat maps, which can intuitively present the trend of fault development and help maintenance personnel quickly locate the root cause.

[0193] Ozone monitoring can provide early warning of potential discharge hazards up to 1 hour in advance, preventing serious accidents such as insulation breakdown and arc fires. The accuracy rate of discharge phenomenon identification is ≥90%.

[0194] Collaborative diagnostics of data both inside and outside the box reduces the false positive rate to below 1%, significantly improves fault coverage, reduces data transmission latency, and significantly enhances monitoring reliability and transmission stability.

[0195] Meanwhile, the thermal imaging probe supports ultra-high definition, high definition, and standard definition, with multiple pixel specifications such as 160×120. It is plug-and-play, adaptable to different site budgets and monitoring accuracy requirements, making it more practical. No antenna is required, resulting in superior explosion-proof performance. Furthermore, it employs thermal imaging array positioning and temperature measurement technology, offering significantly higher temperature measurement and positioning accuracy than infrared detection technology. It fully meets the requirements of medium- and high-voltage explosion-proof levels and high-precision monitoring, resolving its core safety hazards and technical shortcomings.

[0196] This application also provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the above-described method. This electronic device can be any smart terminal, including tablet computers, in-vehicle computers, etc.

[0197] It is understood that the content of the above method embodiments is applicable to this device embodiment. The specific functions implemented by this device embodiment are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0198] Reference Figure 4 , Figure 4 The hardware structure of an electronic device according to another embodiment is illustrated. The electronic device includes: The processor 901 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this application.

[0199] The memory 902 can be implemented as a read-only memory (ROM), static storage device, dynamic storage device, or random access memory (RAM). The memory 902 can store the operating system and other application programs. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 902 and is called and executed by the processor 901 using the methods described in the embodiments of this application.

[0200] The input / output interface 903 is used to implement information input and output.

[0201] The communication interface 904 is used to enable communication and interaction between this device and other devices. Communication can be achieved through wired means (such as USB, Ethernet cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.).

[0202] Bus 905 transmits information between various components of the device, such as processor 901, memory 902, input / output interface 903, and communication interface 904.

[0203] The processor 901, memory 902, input / output interface 903, and communication interface 904 are connected to each other within the device via bus 905.

[0204] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method.

[0205] It is understood that the content of the above method embodiments is applicable to this storage medium embodiment. The specific functions implemented in this storage medium embodiment are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved in the above method embodiments.

[0206] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. Furthermore, memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory may optionally include memory remotely located relative to the processor, and these remote memories can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0207] The embodiments described in this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided by the embodiments of this application. As those skilled in the art will know, with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of this application are also applicable to similar technical problems.

[0208] Those skilled in the art will understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of this application, and may include more or fewer steps than shown, or combine certain steps, or different steps.

[0209] The system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0210] Those skilled in the art will understand that all or some of the steps in the methods disclosed above, as well as the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, or suitable combinations thereof.

[0211] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0212] It should be understood that in this application, "at least one (item)" means one or more, and "more than" means two or more. "And / or" is used to describe the relationship between related objects, indicating that three relationships can exist. For example, "A and / or B" can represent three cases: only A exists, only B exists, and both A and B exist simultaneously, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one (item) of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one (item) of a, b, or c can represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0213] In the embodiments provided in this application, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative; for instance, the division of the units described above is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between systems or units may be electrical, mechanical, or other forms.

[0214] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0215] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0216] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes multiple instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing programs, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0217] The preferred embodiments of the present application have been described above with reference to the accompanying drawings, but this does not limit the scope of the claims of the present application. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and substance of the embodiments of the present application shall be within the scope of the claims of the present application.

Claims

1. A fault monitoring device for explosion-proof motor junction boxes based on multi-source data collaborative analysis, characterized in that, The device includes a thermal imaging temperature and humidity smart terminal and a temperature and humidity fusion terminal. The thermal imaging temperature and humidity smart terminal is installed inside the junction box, and the temperature and humidity fusion terminal is installed outside the junction box. The thermal imaging temperature and humidity smart terminal includes an ozone sensor, a thermal imaging array, an in-box temperature and humidity sensor module, and an in-box data processing and communication module. The temperature and humidity fusion terminal includes an external-box temperature and humidity sensor module and an external-box data processing and communication module. The internal temperature and humidity sensor module is used to collect internal temperature and humidity data. The ozone sensor is used to collect ozone concentration data inside the junction box; The thermal imaging array is used to collect regional temperature data of a preset thermal imaging area. The in-box data processing and communication module is used to preprocess the regional temperature data based on the internal temperature and humidity data to obtain effective regional temperature data, and wirelessly transmit the internal temperature and humidity data, the ozone concentration data, and the effective regional temperature data as in-box data to the external data processing and communication module. The external temperature and humidity sensor module is used to collect external temperature and humidity data. The external data processing and communication module is used to perform comprehensive fault diagnosis based on the data inside the box and the external temperature and humidity data, and to determine the fault status and root cause of the fault.

2. The apparatus according to claim 1, characterized in that, The thermal imaging temperature and humidity smart terminal and the temperature and humidity fusion terminal are fixedly connected to the junction box by adhesive or magnetic attraction.

3. The apparatus according to claim 1, characterized in that, The thermal imaging area includes a three-phase terminal area and a heat-prone area. The thermal imaging array includes at least one thermal imaging probe. The thermal imaging probe is plugged into the thermal imaging temperature and humidity smart terminal. The detection distance between the thermal imaging probe and the terminal is greater than or equal to the safe distance. The detection field of the thermal imaging probe covers the three-phase terminal area and the heat-prone area.

4. The apparatus according to claim 1, characterized in that, The thermal imaging temperature and humidity smart terminal also includes an in-box power module, which is connected to the ozone sensor, the thermal imaging array, the in-box temperature and humidity sensor module and the in-box data processing and communication module. The in-box power module includes a lithium battery and a backup battery. The lithium battery is used to provide the working power for the thermal imaging temperature and humidity smart terminal during operation, and the backup battery is used to provide the power for continued measurement when the thermal imaging temperature and humidity smart terminal loses power. The temperature and humidity fusion terminal also includes an external power module, which uses an explosion-proof battery.

5. A method for fault monitoring of explosion-proof motor junction boxes based on multi-source data collaborative analysis, characterized in that, The method includes the following steps: Acquire internal temperature and humidity data, ozone concentration data, area temperature data, and external temperature and humidity data; The temperature data of the area is preprocessed based on the internal temperature and humidity data to obtain the effective temperature data of the area, and the internal temperature and humidity data, the ozone concentration data and the effective temperature data of the area are used as the data inside the box. Based on the data inside the box and the external temperature and humidity data, a comprehensive fault diagnosis is performed to determine the fault status and root cause.

6. The method according to claim 5, characterized in that, The acquisition of regional temperature data includes the following steps: Acquire an infrared thermal image of a preset thermal imaging area, wherein the thermal imaging area includes a three-phase terminal area and a heat-prone area; Based on the target location information, the target location area is extracted from the infrared thermal image, and the highest local temperature within the target location area is determined as the current area temperature. The infrared thermal image is color-mapped based on the local temperature to obtain the current thermal map; The infrared thermal image, the current area temperature, and the current heat map are used as area temperature data.

7. The method according to claim 6, characterized in that, The step of performing comprehensive fault diagnosis based on the data inside the box and the external temperature and humidity data to determine the fault status and root cause includes the following steps: Based on the ozone concentration data, discharge diagnosis is performed to determine whether a discharge fault exists, and the discharge diagnosis result is obtained. Temperature diagnosis is performed based on the effective temperature data of the area to determine whether there is a temperature fault and to obtain the temperature diagnosis result. The difference between the internal temperature and humidity data and the external temperature and humidity data is calculated to obtain the internal and external temperature and humidity difference value. Based on the internal and external temperature and humidity difference value, a seal diagnosis is performed to determine whether there is a seal failure and obtain the seal diagnosis result. Based on the temperature diagnosis results, the discharge diagnosis results, and the sealing diagnosis results, a collaborative diagnosis is performed to determine the root cause of the fault.

8. The method according to claim 7, characterized in that, The process of performing discharge diagnosis based on the ozone concentration data to determine whether a discharge fault exists and obtain the discharge diagnosis result includes the following steps: Based on the ozone concentration data and the baseline concentration value, the concentration change trend is predicted to obtain the unit concentration increment, wherein the baseline concentration value is the average value of the ozone concentration data under normal operation without discharge phenomenon. The first discharge condition is determined based on the ozone concentration data and the preset ozone concentration threshold. The first discharge condition is that the ozone concentration data is greater than the ozone concentration threshold and the duration is greater than the sampling period. The second discharge condition is determined based on the unit concentration increment and the preset increment threshold, wherein the second discharge condition is that the unit concentration increment is greater than the increment threshold and the duration is greater than the sampling period. When both the first discharge condition and the second discharge condition are met, the discharge diagnosis result is determined to be a discharge fault.

9. The method according to claim 8, characterized in that, The process of performing temperature diagnosis based on the effective temperature data of the area to determine whether a temperature fault exists and obtain the temperature diagnosis result includes the following steps: The temperature difference is calculated based on the current temperature of the three-phase terminals to obtain the three-phase temperature difference. It is then determined whether the three-phase temperature difference is greater than a preset temperature difference threshold. If the three-phase temperature difference is greater than the temperature difference threshold, the temperature diagnosis result is determined to be a temperature fault in the three-phase terminals. Determine whether the temperature of the current area corresponding to the heat-prone point is greater than a preset local temperature threshold. If the temperature of the current area corresponding to the heat-prone point is greater than the temperature threshold, then determine that the temperature diagnosis result is that the heat-prone point has a temperature fault. The step of performing a coordinated diagnosis based on the temperature diagnosis result, the discharge diagnosis result, and the sealing diagnosis result to determine the root cause of the fault includes the following steps: Based on historical heat maps and motor operating conditions, anomalies are identified in the temperature diagnosis results to determine whether the temperature fault is a persistent fault. If the temperature fault is not a persistent fault, the root cause of the fault is determined to be abnormal temperature caused by loose wiring, poor contact, or uneven current. When the temperature fault is a persistent fault, the root cause of the fault is determined to be an insulation abnormality. The cause of the insulation abnormality is determined based on the discharge diagnosis results and the sealing diagnosis results. The cause includes local overheating factors, discharge factors, or moisture ingress factors.

10. The method according to claim 9, characterized in that, The step of identifying anomalies in the temperature diagnosis results based on historical heat maps and motor operating conditions, and determining whether the temperature fault is a persistent fault, includes the following steps: The fault percentage is calculated by comparing the number of faults in the temperature diagnosis results for the three-phase terminals and the heat-prone points. Based on the historical heat map and motor operating conditions, features of temperature and load are extracted to obtain temperature-load correlation features. Anomaly identification is performed based on the fault percentage and the temperature load correlation characteristics to determine whether the temperature fault is a persistent fault.

11. The method according to claim 5, characterized in that, The method further includes the following steps: If the explosion-proof motor junction box does not exhibit the aforementioned fault condition within the preset maintenance cycle, then the monthly periodic opening and inspection will cease, and the box will only be opened for maintenance after the maintenance cycle expires.

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