Power transformation cabinet intelligent early warning method and monitoring system based on infrared imaging

Abstract

The invention relates to a power transformation cabinet intelligent early warning method based on infrared imaging and a monitoring system. The method comprises the steps that infrared thermal images of power transformation cabinets at all levels in a construction site are cooperatively collected through a fixed-point type infrared temperature measuring device and a movable type infrared temperature measuring device; performing real-time analysis on the infrared thermal image in an edge calculation unit, and identifying a temperature anomaly region in combination with a preset fault thermal feature library; based on the temperature value, the temperature rise rate, the duration and the equipment type of the abnormal region, constructing a multi-dimensional risk assessment model, and outputting a short-circuit risk level; according to the method, risk level information is pushed to an early warning platform, and a visual alarm and hierarchical response strategy is triggered, so that the defect of incomplete coverage of manual routing inspection is overcome through'fixed point + mobile 'cooperative acquisition, and non-blind area all-weather monitoring is realized, and the invention further comprises a power transformation cabinet monitoring system for executing the method.

Description

Technical Field

[0001] This application relates to the field of building construction inspection technology, specifically to the field of intelligent early warning method and monitoring system for substations based on infrared imaging. Background Technology

[0002] During construction, temporary power systems are widely distributed across various work areas. Due to the complex environment of construction sites, large fluctuations in power load, long equipment operating hours, and untimely maintenance, problems such as loose electrical connections, overload operation, and insulation aging can easily cause localized temperature anomalies. If these issues are not detected in time, they may develop into short circuits, threatening safety and project progress.

[0003] Currently, temperature monitoring of electrical equipment on construction sites mainly relies on manual inspections, using infrared thermometers to measure key points. This makes it difficult to achieve real-time monitoring without blind spots around the clock, posing significant safety hazards.

[0004] In existing technologies, infrared imaging technology has been attempted for non-destructive testing of building facilities. For example, CN107202638A discloses a method for detecting building HVAC pipes based on thermal infrared imaging, which uses an infrared thermal imager to obtain the surface temperature distribution of the pipes and identify areas of insulation layer damage or leakage; CN118258855A proposes a method for detecting defects in building exterior walls based on infrared images, which uses thermal imaging technology to discover hidden defects such as wall hollowing and leakage.

[0005] However, the aforementioned existing technologies are mainly aimed at static building components with low dynamic changes (such as pipes and walls). Their detection modes are mostly phased and one-time acceptance tests, focusing on the identification and location of defects, and lacking continuous monitoring of equipment operating status and intelligent judgment of risk evolution trends.

[0006] Electrical equipment such as transformer cabinets at construction sites are characterized by high dynamism, high risk, and multi-level distribution. Their temperature changes are often sudden and cumulative, and relying solely on periodic thermal imaging scans cannot provide early warning of short circuit precursors. Summary of the Invention

[0007] This application proposes an intelligent early warning method and monitoring system for substations based on infrared imaging, aiming to achieve all-weather, multi-modal, adaptive temperature monitoring and intelligent early warning for key electrical equipment at all levels on construction sites.

[0008] To achieve the above objectives, the present application adopts the following technical solution: Firstly, this application proposes an intelligent early warning method for substations based on infrared imaging, including: Infrared thermal images of various levels of substations in construction sites are collected through the coordinated use of fixed-point and mobile infrared temperature measurement devices. The infrared thermal image is analyzed in real time in the edge computing unit, and abnormal temperature areas are identified by combining it with a preset fault thermal feature library. Based on the temperature value, temperature rise rate, duration and equipment type of the abnormal area, a multi-dimensional risk assessment model is constructed to output the short circuit risk level. Risk level information is pushed to the early warning platform, triggering visual alarms and tiered response strategies.

[0009] Thus, this method overcomes the shortcomings of incomplete coverage by manual inspection through "fixed-point + mobile" collaborative data collection, achieving blind-spot-free all-weather monitoring; it improves the speed and accuracy of anomaly identification through real-time edge analysis and comparison with fault feature database; it upgrades from "threshold alarm" to "intelligent hierarchical early warning" through a multi-dimensional risk assessment model, enabling earlier identification of short-circuit precursors; and combined with a hierarchical response strategy, it significantly enhances the intelligence and proactive prevention and control capabilities of construction site electrical safety management.

[0010] In some possible implementations, the substations are classified into high-risk and medium-low-risk categories based on voltage level, load characteristics, and installation location; The high-risk category includes high-voltage switchgear, prefabricated substations and main transformers, which are equipped with fixed and mobile temperature measurement devices for joint monitoring; The low-to-medium risk category includes low-voltage distribution cabinets and terminal distribution boxes, which are only equipped with fixed-point or periodically mobile temperature measurement devices.

[0011] In some possible implementations, the fixed-point temperature measurement device provides targeted coverage for key heat-generating components of high-risk substations, including busbar connection points, circuit breaker moving and stationary contacts, and cable terminals.

[0012] In some possible implementations, after receiving continuous abnormal alarms from the fixed-point temperature measuring device, the edge computing unit generates an emergency inspection task for the mobile temperature measuring device and performs high-resolution thermal imaging verification on the strain gauge cabinet.

[0013] In some possible implementations, the routine inspection cycle of the mobile temperature measuring device is dynamically adjusted according to the equipment risk category, with high-risk equipment being inspected once a week and medium- and low-risk equipment being inspected once a quarter. When the ambient temperature exceeds the threshold or the overall load on the construction site increases, the inspection cycle is automatically shortened.

[0014] In some possible implementations, the fault thermal feature library stores the normal thermal distribution patterns of various substations under different operating conditions, as well as abnormal thermal feature vectors corresponding to poor contact, three-phase imbalance, and harmonic overload. The edge computing unit compares the real-time heatmap with the feature vector using a similarity matching algorithm and outputs the abnormal matching degree.

[0015] In some possible implementations, the multi-dimensional risk assessment model further incorporates the equipment's service life, historical maintenance records, and current ambient temperature and humidity to perform a weighted calculation of the short-circuit risk level.

[0016] Secondly, this application also proposes a substation monitoring system based on infrared imaging, which executes the intelligent early warning method for substations based on infrared imaging as described above, including: The multimodal infrared sensing unit includes a fixed-point thermal imager that is fixedly installed in a high-risk substation cabinet, and a mobile infrared inspection device. The edge intelligent analysis unit, deployed locally on the construction site, is used to receive thermal images and perform anomaly identification and risk assessment. The early warning and management platform is used to display heat maps, alarm information, and generate electronic acceptance reports; The mobile infrared inspection device automatically travels to the target device to perform a verification inspection after receiving a trigger command from the edge intelligent analysis unit.

[0017] In some possible implementations, the mobile infrared inspection device is integrated into a track robot or drone platform, supporting autonomous navigation and obstacle avoidance in complex construction site environments.

[0018] In some possible implementations, the early warning and management platform generates a temperature change trend chart of the equipment based on multiple detection data, and predicts the probability of short circuit risk within a preset time period based on the trend slope, and generates preventive maintenance suggestions. Attached Figure Description

[0019] Figure 1 This is a schematic diagram of the intelligent early warning method for substations in this application; Figure 2 This is a schematic diagram of the infrared imaging-based monitoring system in this application. Detailed Implementation

[0020] The following examples further illustrate the features of this application and other related features in detail, so as to facilitate understanding by those skilled in the art: It should be noted that the terms “front,” “back,” “left,” “right,” “up,” and “down” used in the following description refer to the directions in the attached diagrams, while the terms “bottom surface,” “top surface,” “inner,” and “outer” refer to the directions toward or away from the geometric center of a specific component, respectively.

[0021] Furthermore, unless otherwise expressly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection between two components. Those skilled in the art can understand the specific meaning of the above terms in this case based on the specific circumstances.

[0022] Please refer to Figure 1 and Figure 2 This application provides an intelligent early warning method and monitoring system for substations based on infrared imaging, applicable to construction sites. This system is suitable for multi-level, highly dynamic electrical equipment on construction sites, including 10kV high-voltage switchgear, 0.4kV low-voltage switchgear, prefabricated substations, and main transformers. It aims to solve the problems of incomplete coverage and delayed response in traditional manual inspections, and the fact that existing infrared detection technology is mostly used for static component phased acceptance and is difficult to achieve continuous risk early warning.

[0023] Specifically, the monitoring system includes a multimodal infrared sensing unit, an edge intelligent analysis unit, and an early warning and management platform. The multimodal infrared sensing unit comprises a fixed-point infrared thermal imager and a mobile infrared inspection device, which work together to achieve all-weather, blind-spot-free temperature monitoring of critical electrical equipment. For high-risk equipment such as high-voltage substations, prefabricated substations, and main transformers, an industrial-grade infrared thermal imager is fixedly installed inside the cabinet, covering areas prone to heat generation such as busbar connection points, circuit breaker contacts, and cable terminals, enabling periodic thermal image acquisition every 5 minutes. In practical applications, the thermal image acquisition cycle can be adjusted appropriately according to actual working conditions. The thermal imager uses PoE power supply and data transmission, has an IP65 protection rating, and is adaptable to complex construction site environments. For metal-enclosed cabinets, infrared temperature measurement tags with known emissivity can be affixed to key temperature measurement areas for temperature calibration, improving measurement accuracy. For low- to medium-risk equipment such as low-voltage distribution cabinets and terminal distribution boxes, the main method is to rely on mobile infrared inspection devices for periodic scanning to optimize resource allocation.

[0024] Furthermore, in this embodiment, the mobile infrared inspection device employs a track-mounted robot that covers all high-risk equipment areas within the power distribution room along a preset track. The robot is equipped with a lightweight infrared and visible light dual-spectrum imaging module, enabling it to perform comprehensive thermal imaging inspections weekly in normal mode. Crucially, when the edge intelligent analysis unit receives continuous temperature anomaly signals reported by a thermal imager at a fixed point (e.g., temperature rise exceeding a set threshold and duration exceeding a preset time), the system automatically triggers an emergency verification mechanism, dispatching the mobile robot to the device for high-resolution, multi-angle, close-range thermal imaging verification. This achieves intelligent linkage between "fixed-point alarm—mobile verification," improving the reliability of anomaly detection. In some embodiments, for construction sites without track installation conditions, drones can also be used as mobile infrared inspection devices; specific applications can be tailored to the actual working conditions of the construction site.

[0025] The edge intelligent analysis unit is deployed on a local server or edge computing device at the construction site. It receives infrared thermal image data from fixed-point and mobile sensing units and performs localized real-time analysis. The analysis process includes preprocessing steps such as image denoising, region of interest extraction, and temperature data parsing, and performs anomaly identification based on a built-in fault thermal feature library. This feature library stores the normal thermal distribution patterns of various substations under different load conditions, as well as abnormal thermal feature vectors corresponding to typical faults such as poor contact, three-phase imbalance, and harmonic overload. Through a similarity matching algorithm, the system can quickly determine whether the current thermal image matches a known fault pattern. Based on this, a multi-dimensional short-circuit risk assessment model is constructed, comprehensively considering factors such as the temperature value, temperature rise rate, duration, equipment type, service life, historical maintenance records, and environmental temperature and humidity of the abnormal area, and outputs a graded risk level, including four levels: normal, warning, danger, and emergency.

[0026] When the risk level reaches "Warning" or higher, the system pushes risk information to the early warning and management platform and triggers corresponding response strategies. The platform overlays thermal imaging data onto the electrical system diagram in a visual manner, allowing managers to remotely view equipment temperature status. Simultaneously, alarm information is sent via SMS, app push notifications, or on-site audio-visual devices to notify relevant personnel for timely handling. For "Emergency" level events, the system can link with the power outage control module or fire protection system to achieve proactive safety protection. Furthermore, the platform has the function of generating electronic acceptance reports, including the inspection time, equipment number, highest temperature, temperature rise, risk level, and handling recommendations, serving as a digital basis for the safety and quality acceptance of concealed electrical works. The platform can also generate temperature change trend charts based on historical inspection data and predict the probability of short-circuit risks within a preset timeframe through trend extrapolation, generating preventative maintenance recommendations and promoting a shift in operation and maintenance models from "passive response" to "proactive prevention."

[0027] The following example illustrates a real-world application scenario. At a large urban complex construction site, the temporary power supply system includes one 10kV prefabricated substation, three secondary distribution rooms, and dozens of terminal distribution boxes. Electrical equipment is widely distributed, load fluctuations are frequent, and the site presents complex environmental factors such as high temperature, dust, and humidity. Traditional manual inspections are insufficient for comprehensive and timely temperature monitoring.

[0028] In the third week after the system was put into operation, the edge intelligent analysis unit, while performing real-time analysis of fixed-point thermal imager data from a high-voltage outgoing switchgear in a secondary power distribution room, detected that the temperature at the A-phase busbar connection point rose continuously from 52℃ to 78℃ within 15 minutes, with a three-phase temperature difference exceeding 15K. This was initially determined to be a sign of poor contact, and the risk level was assessed as "warning." The system immediately generated a visual alarm on the early warning and management platform and pushed the warning information to the on-site safety supervisor and electrician via the APP. Simultaneously, based on the "fixed-point alarm triggering mobile verification" mechanism, a track-mounted inspection robot was automatically dispatched to the switchgear to perform an emergency thermal imaging verification. The mobile robot acquired a high-resolution infrared image within a distance of 0.8 meters, confirming the existence of a local hotspot at the connection point. The thermal distribution pattern matched the "loose bolt type poor contact" pattern in the fault thermal feature database with a matching degree of 89%, further verifying the authenticity of the anomaly.

[0029] Following system recommendations, the on-site electrician inspected the cabinet after completing the power outage procedures. They discovered that the fixing bolts had loosened due to prolonged vibration, causing increased contact resistance and overheating. After tightening the bolts and applying conductive paste, power was restored. Subsequent monitoring showed that the temperature at that point returned to the normal range (53℃), and the three-phase temperature difference was less than 5K. The system automatically deactivated the warning. The entire process, from anomaly detection to resolution, took only 2.5 hours, preventing potential insulation aging, arcing, or even short-circuit accidents caused by continuous overheating.

[0030] Furthermore, during a period of high summer temperatures, the overall load on the construction site increased, and the ambient temperature exceeded 35°C for several consecutive days. Based on a dynamic adjustment strategy based on the "environment-load" relationship, the system automatically shortened the mobile inspection cycle of all prefabricated substations from "once a week" to "once every three days," and increased the monitoring frequency of heat-generating equipment such as main transformer cabinets and capacitor compensation cabinets. During this period, the system detected a slow upward trend in the temperature of a certain prefabricated substation's cable compartment through trend analysis. Although the temperature had not reached the alarm threshold, it was predicted that it might exceed the limit after 72 hours. Therefore, a "preventive maintenance suggestion" was generated, prompting the system to schedule a special infrared inspection during low-load periods at night. The inspection revealed slight oxidation on the cable joints, which was promptly addressed, preventing a potential fault.

[0031] Thus, the method described in this application overcomes the shortcomings of traditional manual inspections, such as incomplete coverage, long cycles, and easy omissions, by using coordinated data collection from fixed-point and mobile infrared temperature measurement devices, achieving all-weather, blind-spot-free monitoring of substations at construction sites. By integrating a fault thermal feature library and real-time analysis algorithms into the edge computing unit, it avoids the latency issues caused by relying on cloud processing, enabling rapid identification of temperature anomalies locally and improving response speed and system reliability. Furthermore, by constructing a multi-dimensional risk assessment model that integrates temperature values, temperature rise rates, durations, and equipment types, it achieves a shift from "single threshold alarm" to "intelligent hierarchical early warning," enabling earlier and more accurate identification of short-circuit precursors and effectively preventing electrical fire risks. Finally, through the automatic triggering of hierarchical response strategies, early warning information is pushed to the management platform in real time, significantly improving the intelligence and unmanned level of electrical safety management at construction sites.

[0032] As stated above, this case protects a method and monitoring system for intelligent early warning of substations based on infrared imaging. All technical solutions that are the same as or similar to those in this case should be considered to fall within the scope of protection of this case.

Claims

1. A power transformation cabinet intelligent early warning method based on infrared imaging, characterized in that, The method comprises the following steps: Collecting the infrared thermal images of the power distribution cabinets at different levels in the construction site through the fixed and mobile infrared temperature measuring devices; Performing real-time analysis on the infrared thermal images in the edge computing unit, and identifying the temperature abnormal area in combination with the preset fault thermal feature library; Based on the temperature value, temperature rise rate, duration and equipment type of the abnormal area, a multi-dimensional risk assessment model is constructed to output the short circuit risk level; Push the risk level information to the early warning platform, and trigger the visual alarm and hierarchical response strategy.

2. The infrared imaging-based intelligent early warning method for power transformation cabinets according to claim 1, characterized in that, The power distribution cabinets are divided into high-risk and low-risk categories according to voltage level, load characteristics and installation location; The high-risk category includes high-voltage power distribution cabinets, box-type substations and main transformers, and is monitored by fixed and mobile temperature measuring devices; The low-risk category includes low-voltage distribution cabinets and terminal distribution boxes, and only fixed or periodic mobile temperature measuring is configured.

3. The infrared imaging-based intelligent early warning method for power transformation cabinets according to claim 2, characterized in that, The fixed temperature measuring device covers the key heating parts of the high-risk power distribution cabinet, including the bus connection point, the movable and static contact of the circuit breaker and the cable terminal.

4. The infrared imaging-based intelligent early warning method for power transformation cabinets according to claim 3, characterized in that, After receiving continuous abnormal alarms from the fixed temperature measuring device, the edge computing unit generates an emergency inspection task for the mobile temperature measuring device to perform high-resolution thermal imaging review on the corresponding power distribution cabinet.

5. The infrared imaging-based intelligent early warning method for power transformation cabinets according to claim 2, characterized in that, The regular inspection cycle of the mobile temperature measuring device is dynamically adjusted according to the risk category of the equipment, with high-risk equipment inspected once a week and low-risk equipment inspected once a quarter; When the ambient temperature exceeds the threshold or the overall load of the construction site rises, the inspection cycle is automatically shortened.

6. The infrared imaging-based intelligent early warning method for power transformation cabinets according to claim 1, characterized in that, The fault thermal feature library stores the normal thermal distribution patterns of various power distribution cabinets under different working conditions, as well as the abnormal thermal feature vectors corresponding to poor contact, three-phase imbalance and harmonic overload; The edge computing unit compares the real-time thermal image with the feature vector through a similarity matching algorithm and outputs the abnormal matching degree.

7. The infrared imaging-based intelligent early warning method for power transformation cabinets according to claim 6, characterized in that, The multi-dimensional risk assessment model further introduces the service life of the equipment, historical maintenance records and current environmental temperature and humidity to perform weighted calculation on the short circuit risk level.

8. A power transformer cabinet monitoring system based on infrared imaging, characterized by The method can be implemented as described in any one of claims 1 to 7, comprising: A multi-modal infrared perception unit, including a fixed-point thermal imager installed on high-risk power distribution cabinets and a mobile infrared inspection device; An edge intelligent analysis unit deployed locally at the construction site for receiving thermal images and performing abnormal identification and risk assessment; An early warning and management platform for displaying thermal images, alarm information and generating electronic acceptance reports; The mobile infrared inspection device is integrated into a track robot or a drone platform, supporting autonomous navigation and obstacle avoidance in complex construction site environments.

9. The infrared imaging-based electrical cabinet monitoring system of claim 8, wherein, The early warning and management platform generates a device temperature trend graph based on multiple detection data, predicts the short circuit risk probability in a preset future time based on the trend slope, and generates preventive maintenance recommendations.

10. The infrared imaging-based electrical cabinet monitoring system of claim 8, wherein, ​

Images