CN117713381A - Switch board system convenient to overhaul - Google Patents
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- CN117713381A CN117713381A CN202410122442.7A CN202410122442A CN117713381A CN 117713381 A CN117713381 A CN 117713381A CN 202410122442 A CN202410122442 A CN 202410122442A CN 117713381 A CN117713381 A CN 117713381A
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Abstract
The invention relates to the technical field of detection of power distribution cabinets, in particular to a power distribution cabinet system convenient to overhaul. Accurate fault type judgment is achieved through multi-dimensional data from inside to outside to the whole, and dependence on manual judgment is avoided. The prompt positioning module provides fault information through a visual interface. The improvement of the overhaul efficiency of the power distribution cabinet and the reduction of the dependence on the professional of personnel are realized.
Description
Technical Field
The invention relates to the technical field of power distribution cabinet detection, in particular to a power distribution cabinet system convenient to overhaul.
Background
In conventional power distribution cabinet systems, service work is often faced with difficulties in locating fault points and fault types, mainly due to the complexity of the system and the lack of effective monitoring and diagnostic tools. Often, maintenance personnel need to rely on experience and manual testing methods to identify and solve problems, which is time consuming and inefficient, and highly dependent on the expertise of the technician. In addition, manual inspection presents difficulties in identifying and locating the fine fault points. Manual service relies on experience and manual testing, which is not only inefficient, but also difficult to discover and diagnose some hidden or insignificant faults, such as minor temperature anomalies or current fluctuations. Since these detail problems are often precursors to large faults, disregarding them can lead to system failure or serious damage. Therefore, developing a power distribution cabinet system capable of accurately identifying and prompting these fine problems is a key to improving maintenance efficiency and avoiding occurrence of fault recurrence.
Disclosure of Invention
In order to solve the problems, the invention provides a power distribution cabinet system convenient to overhaul.
In order to achieve the above purpose, the invention adopts the following technical scheme:
the power distribution cabinet system convenient to overhaul comprises a cabinet internal state acquisition module, a point position state acquisition module, a current and voltage monitoring module, a central control module and a prompt positioning module, wherein the cabinet internal state acquisition module, the point position state acquisition module, the current and voltage monitoring module and the prompt positioning module are respectively connected with the central control module;
the in-cabinet state acquisition module is used for acquiring environmental data in the power distribution cabinet and sending the environmental data to the central control module;
the point position state acquisition module is used for acquiring temperature and characterization images of a plurality of point positions in the power distribution cabinet;
the current and voltage monitoring module is used for acquiring voltage and current data of each path of power supply in the power distribution cabinet and sending the voltage and current data to the central control module;
the central control module is used for judging the fault type of the power distribution cabinet according to the environment data in the power distribution cabinet, the temperature of the point location, the characterization image and the voltage and current data, and sending alarm information to the prompt positioning module;
the prompt positioning module is used for receiving the alarm information sent by the central control module and providing fault positioning prompts according to the alarm information.
Further, the power distribution cabinet internal environment data comprises temperature and humidity.
Further, the judging of the fault type of the power distribution cabinet comprises the following steps:
performing primary positioning of faults according to the voltage and current data;
performing point location matching according to the preliminary positioning result, continuously acquiring the temperature of the fault point location and the characterization image of the fault point location, and generating a preliminary judgment result according to the temperature change of the fault point location and the dynamic change of the fault point location;
and carrying out fusion analysis based on the initial judgment result and the environmental data in the power distribution cabinet to generate the fault type of the power distribution cabinet.
Further, the preliminary fault location based on the voltage and current data includes the steps of:
judging whether short circuit faults, open circuit faults and overload faults exist or not according to the change rates of the current value and the voltage value;
and carrying out preliminary positioning on faults according to the current value and the voltage value of each node.
Further, the performing the point location matching according to the preliminary positioning result includes:
extracting features of the characterization images, identifying entity parts and associating the entity parts with the parts in a preset virtual circuit diagram;
and performing point location matching according to the preliminary positioning result.
Further, the generating the initial judgment result according to the temperature change of the fault point location and the dynamic change of the fault point location includes:
performing pattern recognition on the temperature data of the fault point location based on machine learning, and recognizing a temperature abnormality pattern related to the fault;
based on the temperature anomaly mode related to the fault, analyzing and matching the characterization images of the fault points by using an edge detection algorithm to generate an initial judgment result.
Further, the fusion analysis based on the initial judgment result and the environmental data in the power distribution cabinet comprises the following steps:
judging an influence relationship by combining the initial judgment result and the environmental data in the power distribution cabinet;
and correcting the primary judgment result according to the influence relation to generate the fault type of the power distribution cabinet.
Further, the impact relationship includes an in-cabinet environment impact fault and a fault impact in-cabinet environment.
Further, the providing of the fault location prompt according to the alarm information comprises prompting the fault type, the fault position and the potential cause of the fault through a visual interface.
The invention has the beneficial effects that: according to the invention, the state acquisition module in the cabinet is used for automatically monitoring the environmental data in the power distribution cabinet and transmitting the data to the central control module, the point position state acquisition module is used for acquiring temperature and characterization images of specific points in the power distribution cabinet, the current and voltage monitoring module is used for monitoring the voltage and current data of each path of power supply in the power distribution cabinet in real time, and the central control module is used for comprehensively analyzing the data provided by all the modules, judging the fault type of the power distribution cabinet by using an algorithm and generating alarm information. Accurate fault type judgment is achieved through multi-dimensional data from inside to outside to the whole, and dependence on manual judgment is avoided.
Drawings
Fig. 1 is a schematic structural diagram of a power distribution cabinet system for easy maintenance in the present invention.
Fig. 2 is a flowchart of the steps for determining the fault type of the power distribution cabinet in the present invention.
Detailed Description
Referring to fig. 1-2, the invention relates to a power distribution cabinet system convenient to overhaul, which comprises a cabinet internal state acquisition module, a point position state acquisition module, a current and voltage monitoring module, a central control module and a prompt positioning module, wherein the cabinet internal state acquisition module, the point position state acquisition module, the current and voltage monitoring module and the prompt positioning module are respectively connected with the central control module;
the in-cabinet state acquisition module is used for acquiring environmental data in the power distribution cabinet and sending the environmental data to the central control module;
the point position state acquisition module is used for acquiring temperature and characterization images of a plurality of point positions in the power distribution cabinet;
the current and voltage monitoring module is used for acquiring voltage and current data of each path of power supply in the power distribution cabinet and sending the voltage and current data to the central control module;
the central control module is used for judging the fault type of the power distribution cabinet according to the environment data in the power distribution cabinet, the temperature of the point location, the characterization image and the voltage and current data, and sending alarm information to the prompt positioning module;
the prompt positioning module is used for receiving the alarm information sent by the central control module and providing fault positioning prompts according to the alarm information.
It should be noted that the in-cabinet status collection module includes a plurality of sensors that are located at strategic locations within the power distribution cabinet. For example, temperature sensors are used to monitor temperature changes within the cabinet, while humidity sensors are used to detect humidity levels in the air. The sensors can capture subtle environmental changes and provide accurate data support for fault prevention and timely maintenance. The data collected by the sensors is sent to the central control module periodically or continuously. The transmission of data may be accomplished through a wired connection (e.g., ethernet) or a wireless technology (e.g., wi-Fi or bluetooth). This flexible data transmission ensures that data can be reliably transmitted even in complex industrial environments. These sensors and modules are designed to be very durable and reliable in view of the harsh operating environments to which the power distribution cabinet may be subjected, such as high temperature, humidity or vibration. They generally have a high level of protection and are capable of stable operation in a variety of industrial environments.
The point location status acquisition module contains several infrared temperature sensors that are deployed near critical locations within the power distribution cabinet, such as circuit breakers, cable connectors, and other important electrical components. By precisely locating these sensors, the system can ensure that all potential hot spots are effectively monitored. One of the main advantages of infrared sensors is that they provide a contactless measurement. This means that the sensor can accurately measure its surface temperature without physical contact with the object to be measured. This is particularly important for electrical devices, as the contactless measurement reduces the risk of introducing faults or disturbances. The infrared sensor is capable of monitoring the surface temperature of the critical component in real time. Any abnormal temperature changes, such as overheating caused by overload, short circuit or other electrical problems, are rapidly detected and reported to the central control module. The point position state acquisition module further comprises a high-resolution camera which is used for capturing real-time images of key points in the power distribution cabinet. The cameras can capture images of wiring errors, physical damage or other visual faults, and provide important visual information for fault analysis and diagnosis.
The current and voltage monitoring module is used for monitoring current and voltage data, such as an input end, an output end, a branch circuit, a main circuit and the like, at key nodes of the power distribution cabinet.
The prompt locating module collects detailed information about various potential faults occurring within the power distribution cabinet, such as overloads, short circuits, temperature anomalies, or other electrical faults. May include the specific location of the failed component, recommended service paths, and necessary safety measures. In some systems, an interactive distribution cabinet layout may also be included, indicating the exact location of the fault point.
Further, the environmental data in the power distribution cabinet comprises temperature and humidity;
specifically, unlike temperature monitoring for a particular point location, intra-cabinet ambient temperature monitoring is concerned with the average temperature of the entire power distribution cabinet. For this purpose, the temperature sensors are distributed uniformly in different areas of the power distribution cabinet to comprehensively monitor the temperature distribution in the cabinet. The comprehensive monitoring mode can effectively capture any overheating phenomenon possibly occurring in the whole power distribution cabinet, and equipment damage or faults caused by overheating are prevented. Humidity monitoring is also important, particularly in controlling corrosion and condensation of electrical equipment. The humidity sensor is used for continuously tracking the air humidity level in the power distribution cabinet, so that environmental conditions are ensured to accord with the operation standard of the electrical equipment. Too high humidity may lead to corrosion of the electrical components, reduced insulation properties and even short circuits. For example, a power distribution cabinet operating in a high humidity environment may require additional drying measures to prevent damage caused by moisture.
Further, the judging of the fault type of the power distribution cabinet comprises the following steps:
performing primary positioning of faults according to the voltage and current data;
performing point location matching according to the preliminary positioning result, continuously acquiring the temperature of the fault point location and the characterization image of the fault point location, and generating a preliminary judgment result according to the temperature change of the fault point location and the dynamic change of the fault point location;
and carrying out fusion analysis based on the initial judgment result and the environmental data in the power distribution cabinet to generate the fault type of the power distribution cabinet.
Further, the preliminary fault location based on the voltage and current data includes the steps of:
judging whether short circuit faults, open circuit faults and overload faults exist or not according to the change rates of the current value and the voltage value;
and carrying out preliminary positioning on faults according to the current value and the voltage value of each node.
In some embodiments, the system continuously collects current and voltage data for each node within the power distribution cabinet. The data are captured in real time through the sensors of the current and voltage monitoring module, and the real-time electric state of each power supply in the power distribution cabinet can be reflected. The core is to analyze the rate of change of the current value and the voltage value. The system performs a time series analysis of the collected data to identify rapid changes in current and voltage, which are typically a significant indication of the occurrence of a fault. For example, a short circuit fault typically results in a sudden increase in current and a voltage drop, while an open circuit fault may appear as a sudden drop in current value to zero. If a sudden increase in current is detected while a sudden decrease in voltage is detected, the system may determine a short circuit fault. If the current at a node suddenly drops to zero while the voltage value remains unchanged, this may be an indication of a circuit break fault. When the current value of a certain node continues to be higher than the normal operating range, and with a voltage drop, the system may recognize an overload fault.
Further, the performing the point location matching according to the preliminary positioning result includes:
extracting features of the characterization images, identifying entity parts and associating the entity parts with the parts in a preset virtual circuit diagram;
and performing point location matching according to the preliminary positioning result.
In some embodiments, first, a high-definition camera in a point location status acquisition module captures a real-time image of a critical location in a power distribution cabinet. These images provide a visual representation of the components within the power distribution cabinet, providing a basis for further fault analysis. The system analyzes the captured image by applying image processing and image recognition techniques. This includes extracting key visual features from the image, such as shape, edges, color, texture, etc. These features help identify individual electrical components and devices in the image. The system then analyzes the extracted features using machine learning or deep learning algorithms to identify solid components in the image. This may include identifying specific switches, terminals, circuit breakers, etc. electrical components. The identified physical components are then matched and associated with corresponding components in a pre-set virtual circuit diagram. The virtual circuit diagram is a digital representation of the power distribution cabinet and contains the positions and connection relations of all the electrical components.
The collected current and voltage data for each node is analyzed. This includes comparing data differences between different nodes and analyzing time series changes of data on individual nodes. By this comparison, the system is able to identify nodes that are data anomalies that may be caused by faults. If the current of a node suddenly increases or decreases while the current and voltage of neighboring nodes exhibit corresponding changes, this may indicate a fault near the node. In the event of a circuit break fault, the current after the fault node may drop to zero while the previous node current remains unchanged. For overload faults, the faulty node may exhibit a continuous high current reading. By comprehensively analyzing the current and voltage data of each node, the system can perform preliminary positioning on faults. For example, if a current sustained anomaly is found at a node and a significant difference is found in comparison with the data of other nodes, the system may initially determine that a fault is occurring in the vicinity of the node.
Further, the generating the initial judgment result according to the temperature change of the fault point location and the dynamic change of the fault point location includes:
performing pattern recognition on the temperature data of the fault point location based on machine learning, and recognizing a temperature abnormality pattern related to the fault;
based on the temperature anomaly mode related to the fault, analyzing and matching the characterization images of the fault points by using an edge detection algorithm to generate an initial judgment result.
In some embodiments, first, machine learning uses a convolutional neural network CNN model, whose training begins with a large amount of historical temperature data derived from the normal operating state of the power distribution cabinet system and known fault events. During the training phase, model learning identifies different types of temperature change patterns that may include rapid rise in temperature, sustained high temperature, or irregular fluctuations. For example, a rapid rise in temperature may be associated with a short circuit, while a sustained high temperature may indicate an overload condition. In terms of feature extraction, CNN automatically extracts key features from temperature data through its multi-layer structure. These features include not only basic statistical information of the temperature, but also more complex patterns such as trends and periodicity of temperature changes. This feature of CNN makes it particularly suitable for processing temperature data, which typically have time-series characteristics and complex patterns. After training is completed, the CNN model is used for monitoring temperature data of the power distribution cabinet in real time. When the system detects abnormal temperature patterns, such as sudden and continuous increases in temperature around a certain circuit breaker, the CNN model analyzes the patterns and determines if they match a known fault type. If the model identifies a temperature pattern associated with a fault, it alerts the system. Furthermore, the CNN model is advantageous in that it can continuously learn and adapt. Over time and with the accumulation of more fault data, the model will continually adjust its parameters to improve the accuracy of fault identification. This means that the fault detection capability of the system will increase over time.
These characterization images are then processed using an edge detection algorithm. Edge detection is a commonly used image processing technique for identifying the boundaries and contours of objects in an image. In a power distribution cabinet system, edge detection may reveal the physical condition of the electrical components, such as whether the wiring is loose, whether the components are subject to signs of ablation, or whether other visible damage is present. By analyzing the edge information of these images, the system is able to identify visible changes associated with temperature anomaly patterns. For example, if temperature monitoring reveals that a certain circuit breaker is overheated, edge detection may reveal color changes or structural deformations of the circuit breaker surface, which are typical signs caused by overheating. Finally, the system combines the temperature anomaly mode and the image edge detection result to generate preliminary fault judgment. If both the temperature data and the image analysis are directed to the same fault, the system will identify the nature and location of the fault. For example, if a temperature anomaly of a component corresponds to a visible damage in its image, the system may initially determine that the fault is a physical damage caused by overheating. By the method, the power distribution cabinet system not only can identify the potential faults based on the temperature data, but also can further verify and accurately locate the faults through image analysis. The method combining various sensor data and advanced analysis technology greatly improves the accuracy and efficiency of fault diagnosis, and provides powerful support for the maintenance and management of a power distribution cabinet system.
Further, the fusion analysis based on the initial judgment result and the environmental data in the power distribution cabinet comprises the following steps:
judging an influence relationship by combining the initial judgment result and the environmental data in the power distribution cabinet;
and correcting the primary judgment result according to the influence relation to generate the fault type of the power distribution cabinet.
The impact relationship includes an in-cabinet environment impact failure and a failure impact in-cabinet environment.
It should be noted that this step integrates data from different sensors, including temperature changes at the point of failure, characterization images, and environmental data within the power distribution cabinet (such as overall temperature and humidity). For example, if the temperature at a certain fault point (such as a circuit breaker) is abnormally elevated, this may be due to internal circuit problems (such as overload). However, if the temperature of the power distribution cabinet as a whole also increases abnormally, this may indicate that environmental factors (such as insufficient heat dissipation or external high temperature environments) are also affecting the condition of this fault point. Conversely, a certain partial fault may also affect the environment within the whole cabinet. For example, an overheated electrical component may cause an increase in temperature throughout the power distribution cabinet, thereby affecting proper operation of other components. In this case, local faults may cause a wider range of system problems.
In some embodiments, the temperature data of the fault point and the environmental data (such as temperature and humidity) of the whole power distribution cabinet are firstly compared in time series. This involves looking at the environmental data changes before and after the fault occurs and the temporal correspondence to the fault point temperature anomalies. If the overall temperature within the power distribution cabinet is also rising when a fault occurs, it may be indicative that environmental factors contribute to the fault. And judging whether a direct association exists between the change mode (such as the rate and the duration of temperature rise) of the fault point temperature and the mode of overall environmental change in the power distribution cabinet or not by analyzing the change mode of the fault point temperature. For example, a slow but sustained temperature rise may indicate a long-term overheating problem, while a sudden temperature surge may indicate an abrupt failure event. After confirming the correlation of time and pattern, the system further performs causal reasoning. This involves analyzing the cause and effect of the fault occurrence and how environmental conditions may affect the development of the fault. For example, if faults occur frequently under high temperature and high humidity environmental conditions, it can be inferred that these environmental conditions may exacerbate the development of the fault. The system applies logical reasoning and preset analysis rules to determine specific relationships between faults and environmental factors. This may include expert systems or decision trees that interpret interactions between data according to specific logic and known fault models.
After the mutual influence relation between the temperature abnormality of the fault point location and the environment in the power distribution cabinet is analyzed and determined, the primarily judged fault type is adjusted based on the relevance between the environment data and the fault point location data. For example, if a single fault is originally determined to be directed to a particular component, but environmental analysis shows that the fault may be related to the high temperature environment of the power distribution cabinet as a whole, the fault type may be corrected to "electrical component fault caused by environmental conditions". And combining the corrected judgment and the comprehensive analysis result, and generating a final fault type by the system. This process may involve multiple considerations including the cause of the failure, the scope of impact, the possible consequences, and the most appropriate countermeasures. The generated fault type not only identifies the nature of the fault, but also provides detailed information about the cause of the fault and the possible solutions. This is very valuable to maintenance teams, who can make more efficient maintenance plans and precautions based on this information. The finally generated fault type is helpful for guiding maintenance decision and operation, so that stable operation and safety of the power distribution cabinet system are ensured. For example, if the fault type is directed to a heat dissipation problem of the system, maintenance teams may need to take steps to improve the ventilation of the power distribution cabinet or upgrade its cooling system.
Further, the providing of the fault location prompt according to the alarm information comprises prompting the fault type, the fault position and the potential cause of the fault through a visual interface;
in some embodiments, an alarm mechanism is triggered after a fault is detected and diagnosis of the fault type is completed. This alarm is not just a simple notification, but contains rich information to help operators understand and respond quickly to faults. These alarm messages are transmitted to the visual interface of the system. This interface is typically designed to be intuitive and understandable so that even non-professionals can quickly understand the fault condition. Specific fault types, such as "circuit breaker overheat", "cable short" etc., are displayed on the interface so that the operator can quickly identify the problem. Further, specific location information of the fault may be provided on the visual interface. This is typically accomplished by highlighting fault points on a digitized layout of the power distribution cabinet. For example, if a fault occurs on a particular circuit breaker, the location of that circuit breaker is accurately marked in the distribution cabinet layout at the interface. Information about the potential cause of the fault may also be provided on the interface. This is based on previous fault analysis procedures, not only identifying the type and location of the fault, but also inferring the underlying cause of the fault. For example, if the fault type is diagnosed as overheating of the circuit breaker due to overload, the system may prompt "potentially caused by overload" at the interface. The method for providing fault location prompt through the visual interface greatly improves the efficiency and accuracy of fault response. The operators can quickly obtain key information and make countermeasures according to the key information, so that the system downtime is reduced, and the stable operation of the power distribution system is ensured.
The above embodiments are merely illustrative of the preferred embodiments of the present invention and are not intended to limit the scope of the present invention, and various modifications and improvements made by those skilled in the art to the technical solution of the present invention should fall within the scope of protection defined by the claims of the present invention without departing from the spirit of the design of the present invention.
Claims (6)
1. The power distribution cabinet system convenient to overhaul is characterized by comprising a cabinet internal state acquisition module, a point position state acquisition module, a current and voltage monitoring module, a central control module and a prompt positioning module, wherein the cabinet internal state acquisition module, the point position state acquisition module, the current and voltage monitoring module and the prompt positioning module are respectively connected with the central control module;
the in-cabinet state acquisition module is used for acquiring environmental data in the power distribution cabinet and sending the environmental data to the central control module;
the point position state acquisition module is used for acquiring temperature and characterization images of a plurality of point positions in the power distribution cabinet;
the current and voltage monitoring module is used for acquiring voltage and current data of each path of power supply in the power distribution cabinet and sending the voltage and current data to the central control module;
the central control module is used for judging the fault type of the power distribution cabinet according to the environment data in the power distribution cabinet, the temperature of the point location, the characterization image and the voltage and current data, and sending alarm information to the prompt positioning module;
the prompt positioning module is used for receiving the alarm information sent by the central control module and providing fault positioning prompts according to the alarm information;
the environmental data in the power distribution cabinet comprises temperature and humidity;
the judging of the fault type of the power distribution cabinet comprises the following steps:
performing primary positioning of faults according to the voltage and current data;
performing point location matching according to the preliminary positioning result, continuously acquiring the temperature of the fault point location and the characterization image of the fault point location, and generating a preliminary judgment result according to the temperature change of the fault point location and the dynamic change of the fault point location;
performing fusion analysis based on the initial judgment result and the environmental data in the power distribution cabinet to generate a fault type of the power distribution cabinet;
the fusion analysis based on the initial judgment result and the environmental data in the power distribution cabinet comprises the following steps:
judging an influence relationship by combining the initial judgment result and the environmental data in the power distribution cabinet;
and correcting the primary judgment result according to the influence relation to generate the fault type of the power distribution cabinet.
2. A power distribution cabinet system for easy access according to claim 1, wherein said preliminary fault location based on voltage current data comprises the steps of:
judging whether short circuit faults, open circuit faults and overload faults exist or not according to the change rates of the current value and the voltage value;
and carrying out preliminary positioning on faults according to the current value and the voltage value of each node.
3. The electrical distribution cabinet system for easy access of claim 1, wherein the performing point location matching based on the preliminary positioning result comprises:
extracting features of the characterization images, identifying entity parts and associating the entity parts with the parts in a preset virtual circuit diagram;
and performing point location matching according to the preliminary positioning result.
4. The power distribution cabinet system for easy maintenance according to claim 1, wherein the generating the initial judgment result according to the temperature change of the fault point location and the dynamic change of the fault point location comprises:
performing pattern recognition on the temperature data of the fault point location based on machine learning, and recognizing a temperature abnormality pattern related to the fault;
based on the temperature anomaly mode related to the fault, analyzing and matching the characterization images of the fault points by using an edge detection algorithm to generate an initial judgment result.
5. A service friendly power distribution cabinet system according to claim 1 wherein said impact relationship comprises an in-cabinet environment impact fault and a fault impact in-cabinet environment.
6. The electrical distribution cabinet system for easy access of claim 1, wherein providing fault location cues based on the alarm information comprises presenting fault type, fault location, and potential cause of the fault via a visual interface.
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| CN202410122442.7A CN117713381A (en) | 2024-01-30 | 2024-01-30 | Switch board system convenient to overhaul |
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| CN113258678A (en) * | 2021-06-03 | 2021-08-13 | 长沙理工大学 | Intelligent power distribution cabinet fault first-aid repair system, method and device |
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| CN113258678A (en) * | 2021-06-03 | 2021-08-13 | 长沙理工大学 | Intelligent power distribution cabinet fault first-aid repair system, method and device |
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