Intelligent power distribution cabinet system and control method

Abstract

The invention discloses an intelligent power distribution cabinet system and a control method, and the method comprises the steps: firstly, a power distribution cabinet obtains detection parameters, such as current, voltage, temperature and smoke, through a sensor, and compares the detection parameters with set parameters, so as to determine a fault type; secondly, the power distribution cabinet obtains an internal image through a camera, and the detection data, the fault type, the internal image and the number of the power distribution cabinet are packaged into a data packet to be uploaded to a cloud server; and the cloud server identifies the number of the power distribution cabinet in the data packet, generates a maintenance task according to the fault type, and associates the data packet to the maintenance task. Furthermore, the cloud server calculates the proportion value of the maintenance task according to the grade of the power distribution cabinet and the severity of the fault type, and updates the maintenance task table according to the proportion value, so that the console arranges maintenance workers to maintain the power distribution cabinet according to the task table. Through intelligent fault detection and maintenance task management, the operation and maintenance efficiency of the power distribution cabinet is improved, and stable operation of a power system is guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of power distribution cabinets, and in particular to an intelligent power distribution cabinet system and a control method. Background Art

[0002] Safety distribution cabinets are electrical equipment used to distribute, control, protect, and monitor electrical energy. They play a vital role in industrial, commercial, and residential applications. However, due to the complexity of power systems and human error, power accidents frequently occur, posing a serious threat to life and property. To improve the safety of distribution cabinets and reduce the incidence of power accidents, safety distribution cabinets based on intelligent monitoring have emerged. However, when multiple distribution cabinets fail, it is difficult to rationally allocate maintenance resources based on the severity of the failure and the importance of the distribution cabinets, which can result in critical equipment not receiving timely repairs. Summary of the Invention

[0003] To solve the problem of being unable to rationally arrange maintenance resources when multiple distribution cabinets fail, the present invention provides an intelligent distribution cabinet system and control method. The specific technical solutions of the present invention are as follows:

[0004] A control method for an intelligent power distribution cabinet system, the control method comprising the following steps:

[0005] The distribution cabinet obtains detection parameters in the distribution cabinet through sensors, and compares the obtained detection parameters with set parameters to determine the fault type of the distribution cabinet;

[0006] The PDC uses a camera to capture its own internal image, then packages the detection data, fault type, internal image, and PDC number into a data package and uploads it to the cloud server.

[0007] The cloud server identifies the distribution cabinet number in the data packet, generates a maintenance task based on the fault type in the data packet, and adds the data packet to the maintenance task;

[0008] The cloud server determines the proportion of the current maintenance task according to the level and fault type of the distribution cabinet, then updates the maintenance task table according to the proportion of the maintenance task, and sends the maintenance task table to the console, so that the console arranges maintenance workers to repair the distribution cabinet according to the maintenance task table.

[0009] Furthermore, the sensors include but are not limited to current sensors, voltage sensors, temperature sensors and smoke sensors. The detection parameters acquired by the sensors include current parameters, voltage parameters, temperature parameters and smoke parameters. The fault types include overload, short circuit, leakage, fire and continuous high temperature.

[0010] When the current parameter is greater than the first set current value, the power distribution cabinet determines that it is in a short-circuit state;

[0011] When the power distribution cabinet maintains a current parameter higher than the second set current value for a time period greater than the first set time period, the power distribution cabinet determines that it is in an overload state;

[0012] When the voltage parameter is greater than the first set voltage value, the power distribution cabinet determines that it is in a leakage state;

[0013] When the temperature parameter is greater than the first set temperature value and the smoke parameter is greater than the set smoke value, the power distribution cabinet determines that it is in a fire state;

[0014] When the power distribution cabinet maintains a temperature parameter greater than a second set temperature value and a smoke parameter not higher than a set smoke value for a time greater than a second set time, the power distribution cabinet determines that it is in a high temperature state;

[0015] The first set current value is greater than the second set current value, and the first set temperature is greater than the second set temperature.

[0016] Furthermore, the power distribution cabinet adjusts the speed of its own cooling fan according to the temperature parameters;

[0017] When the power distribution cabinet detects that the temperature parameter is greater than the second set temperature value and the smoke parameter is less than or equal to the set smoke value, the power distribution cabinet starts timing and adjusts the speed of its own cooling fan to the highest;

[0018] When the timing time of the power distribution cabinet is greater than the second set time, the power distribution cabinet determines that it is in a continuous high temperature state;

[0019] If the temperature parameter of the power distribution cabinet is greater than the first set temperature value and the smoke parameter is greater than the set smoke value during timing, the power distribution cabinet determines that it is in a fire state and releases carbon dioxide gas to extinguish the fire.

[0020] Furthermore, the cloud server generates a maintenance task based on the fault type in the data packet, including the following steps:

[0021] The cloud server records the receiving time of the received data packet and then uses the receiving time as the task start time of the maintenance task;

[0022] The cloud server adds the fault type, distribution cabinet number, and task start time to the maintenance task content and attaches the data packet to the maintenance task.

[0023] When the cloud server generates a maintenance task, it will no longer receive data uploaded by the distribution cabinet until the maintenance task is completed.

[0024] Furthermore, the cloud server determines the weight of the current maintenance task according to the level and fault type of the power distribution cabinet, and then updates the maintenance task table according to the weight of the maintenance task, including the following steps:

[0025] The cloud server pre-sets the level of the distribution cabinet. The higher the level, the higher the weight. The distribution cabinets are then numbered from high to low according to their weight.

[0026] The cloud server pre-sets the proportion of fault types of the power distribution cabinet. The fault types are arranged in descending order according to the proportion value: fire, leakage, short circuit, overload and continuous high temperature;

[0027] The cloud server uses the sum of the proportion value of the fault type in the maintenance task and the proportion value corresponding to the number of the distribution cabinet as the proportion value of the maintenance task;

[0028] The cloud server sorts the maintenance tasks from high to low according to their weight values ​​and generates a maintenance task table.

[0029] Furthermore, every time the cloud server obtains a new maintenance task, it reorders the maintenance task table to update the maintenance task table;

[0030] Every time the cloud server updates the maintenance task list, it sends the new maintenance task list to the console.

[0031] Furthermore, after receiving the maintenance task list, the console will add the maintenance tasks in the maintenance task list to the task list to be assigned;

[0032] The console will send the maintenance tasks in the task list to be assigned to the maintenance personnel's mobile device in sequence, so that the maintenance personnel can repair the corresponding distribution cabinet according to the maintenance tasks in the mobile device;

[0033] The console receives a task completion signal from the mobile device after it completes the maintenance task, and sends the task completion signal to the cloud server;

[0034] The cloud server will remove the completed maintenance tasks from the maintenance task list.

[0035] Furthermore, when the control console receives a maintenance task, it first traverses the maintenance task table and determines the newly received maintenance task based on the number of the distribution cabinet in the maintenance task table;

[0036] The console adds the newly received maintenance tasks to the task list to be assigned, and arranges the maintenance tasks from high to low according to their weight.

[0037] The console distributes the maintenance tasks to the maintenance personnel's mobile devices according to the arrangement order, and removes the distributed maintenance tasks from the to-be-assigned task list.

[0038] Furthermore, the cloud server records the time of receiving the task completion signal uploaded by the receiving console and uses the time as the task completion time;

[0039] The cloud server generates a maintenance log for the distribution cabinet based on the completed maintenance tasks stored for the distribution cabinet. This log includes the start and completion time of each maintenance task, as well as the fault type. This maintenance log generation mechanism provides detailed historical data for the distribution cabinet's operation and maintenance management, facilitating fault analysis and equipment maintenance. The cloud server also counts the number of fault types encountered and ranks them accordingly. This fault statistics mechanism provides data support for the distribution cabinet's operation and maintenance management, facilitating the identification of potential equipment problems and the implementation of preventive measures.

[0040] A smart distribution cabinet system, which executes the above-mentioned control method of the smart distribution cabinet system. The smart distribution cabinet system includes a console, a cloud server and several distribution cabinets. The cloud server is communicated with the console and the distribution cabinets respectively. Through the system architecture of one cloud server corresponding to multiple distribution cabinets, intelligent monitoring and management of the distribution cabinets are realized, the operating reliability of the distribution cabinets is improved, the operation and maintenance costs are reduced, and the overall operation and maintenance efficiency is improved.

[0041] Compared with the existing technology, the beneficial effects of the present invention are:

[0042] 1. Real-time monitoring and fault diagnosis: The distribution cabinet uses sensors to acquire detection parameters in real time and compares them with set parameters, enabling rapid and accurate identification of fault types. Compared to traditional manual inspections, this method enables real-time monitoring of the distribution cabinet's operating status, enabling timely detection of faults and significantly improving the efficiency and accuracy of fault diagnosis. The distribution cabinet uses cameras to capture internal images, further enriching the data sources for fault diagnosis and providing maintenance personnel with more intuitive fault information, enabling more precise identification of the cause and location of the fault.

[0043] 2. Intelligent Fault Handling and Resource Management: The PDC packages detection data, fault type, internal image, and number into data packets and uploads them to the cloud server, enabling remote transmission and centralized management of fault information. The cloud server can quickly identify the PDC number, generate a maintenance task based on the fault type, and add the data packet to the maintenance task, thus achieving automated and information-based fault handling. The cloud server determines the weight of the maintenance task based on the PDC level and fault type, and updates the maintenance task table accordingly, allowing the control console to rationally schedule maintenance workers according to the maintenance task table. This method can rationally allocate maintenance resources based on the severity of the fault and the importance of the equipment, prioritize critical faults, improve maintenance efficiency, and reduce equipment downtime.

[0044] 3. Improve system reliability and safety: Real-time monitoring and rapid fault handling can promptly eliminate potential faults, reduce power outages caused by faults, and improve the reliability and stability of the power distribution system. The cloud server's centralized management and analysis of fault information helps accumulate fault data, providing reference for subsequent equipment maintenance and improvements, further improving the safety and reliability of the power distribution system. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 The figure is a flow chart of a control method of an intelligent power distribution cabinet system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0046] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements with the same or similar functions.

[0047] In the description of the present invention, it should be noted that, for directional words, such as the terms "center", "horizontal", "longitudinal", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", "clockwise", "counterclockwise" and so on, indicating directions and positional relationships, are based on the directions or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and cannot be understood as limiting the specific scope of protection of the present invention.

[0048] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features. Therefore, the terms "first" and "second" may explicitly or implicitly include one or more of these features. Throughout the description of the present invention, "at least" means one or more than one, unless otherwise specifically defined.

[0049] In the present invention, unless otherwise specified or limited, the terms "assemble," "connect," and "connect" should be understood in a broad sense. For example, they may refer to fixed connection, detachable connection, or integral connection; mechanical connection; direct connection, connection through an intermediate medium, or internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on specific circumstances.

[0050] In the present invention, unless otherwise specified or limited, a first feature being "above" or "below" a second feature may include the first and second features being in direct contact, or may include the first and second features being in contact not directly but through another feature therebetween. Furthermore, a first feature being "above," "below," and "above" a second feature may include the first feature being directly above or obliquely above the second feature, or may simply mean that the first feature is higher in level than the second feature. A first feature being "above," "below," and "below" a second feature may include the first feature being directly below or obliquely below the second feature, or may simply mean that the first feature is lower in level than the second feature.

[0051] The following description of the embodiments of the present invention is provided in conjunction with the accompanying drawings to further describe the specific embodiments of the present invention so that the technical solutions and beneficial effects of the present invention will be more clearly understood. The following description of the embodiments with reference to the accompanying drawings is illustrative and intended to explain the present invention, but is not to be construed as limiting the present invention.

[0052] like Figure 1 As shown, a control method for an intelligent power distribution cabinet system is provided. This control method uses advanced sensor technology and intelligent algorithms to achieve real-time monitoring and fault diagnosis of the power distribution cabinet. The control method includes the following steps:

[0053] The PDC uses high-precision sensors to acquire detection parameters within the PDC and accurately compares these parameters with pre-set parameters to determine the type of fault. This process enables rapid and accurate fault identification, significantly improving PDC operation and maintenance efficiency and reducing troubleshooting time.

[0054] The distribution cabinet uses a high-definition camera to capture internal images of itself. The camera then packages the detection data, fault type, internal image, and distribution cabinet number into a data package and uploads it to the cloud server. This data integration and upload method allows maintenance personnel to remotely view the detailed status of the distribution cabinet, improving the timeliness and accuracy of maintenance. The distribution cabinet not only obtains detection parameters through sensors but also uses cameras to capture internal image information. These images can intuitively display the equipment status and fault conditions within the distribution cabinet, making it easier for maintenance personnel to understand the internal situation based on the images and improving maintenance efficiency. When the distribution cabinet's sliding door is closed, the interior is relatively dark, providing light for the camera, allowing it to capture clearer images.

[0055] The cloud server identifies the distribution cabinet number in the data packet, generates a maintenance task based on the fault type in the data packet, and adds the data packet to the maintenance task list. Through its intelligent task generation mechanism, the cloud server can quickly respond to faults and ensure timely delivery of maintenance tasks.

[0056] The cloud server determines the current maintenance task's weight based on the PDU's level and fault type. It then updates the maintenance task list based on the weight and sends it to the control console, which then schedules maintenance workers to repair the PDU. This system effectively allocates maintenance resources based on the severity of the fault and the importance of the PDU, optimizing the maintenance process and improving maintenance resource allocation efficiency by at least 30%.

[0057] In one embodiment, the sensors include but are not limited to current sensors, voltage sensors, temperature sensors, and smoke sensors. The detection parameters acquired by the sensors include current parameters, voltage parameters, temperature parameters, and smoke parameters. The fault types include overload, short circuit, leakage, fire, and sustained high temperature. The combination of these sensors can comprehensively cover the operating status of the power distribution cabinet, ensuring that no faults are missed.

[0058] When the current parameter exceeds the first set current value, the distribution cabinet determines that it is in a short-circuit state. When a short circuit occurs, the current in the distribution cabinet increases dramatically and the action is rapid, typically in milliseconds. The ammeter reading increases dramatically and instantaneously, far exceeding the rated current of the circuit breaker and even the ammeter's range. For example, a normal current of 100A may increase to 500A or even higher during a short circuit. In this case, the first set current value can be set to 150A, 200A, or 250A. This rapid detection mechanism enables timely detection of short-circuit faults, preventing equipment damage and safety accidents caused by short circuits.

[0059] When the power distribution cabinet maintains a current parameter higher than the second set current value for a time longer than the first set time, the power distribution cabinet determines that it is in an overload state. When the power distribution cabinet is overloaded, the action time is relatively long, usually between a few seconds and a few minutes. The ammeter reading will gradually increase and exceed the rated current value of the circuit breaker, but it will not increase sharply in an instant. For example, the normal current is 100A, and the current may gradually increase to 120A when overloaded. At this time, the second set current value can be set to 110A, and the first set time is 1 minute. Therefore, the power distribution cabinet will maintain the state of increasing current for a certain period of time. Through the dual judgment of time and current value, it is possible to accurately distinguish between overload and instantaneous current fluctuations, thereby improving the accuracy of fault judgment.

[0060] When the voltage parameter exceeds the first set voltage value, the distribution cabinet determines that it is in a leakage state. Leakage is determined by the voltage of the distribution cabinet, primarily based on abnormal voltage changes or voltage distribution to infer the presence of a leakage path. The distribution cabinet measures the voltage between the neutral line and ground to determine whether the distribution cabinet is leaking. The voltage between the neutral line (N) and ground is measured. Under normal circumstances, the neutral line-to-ground voltage should be close to 0V. If the neutral line-to-ground voltage increases significantly, exceeding the first set voltage value (5V), leakage may be present, causing the neutral line to be energized. This voltage monitoring mechanism can promptly detect leakage faults and ensure the safety of personnel and equipment.

[0061] When the temperature parameter exceeds the first set temperature value and the smoke parameter exceeds the set smoke value, the distribution cabinet determines that it is on fire. The temperature sensor determines whether a fire has occurred by monitoring temperature changes inside the distribution cabinet. When the internal temperature of the distribution cabinet exceeds a preset threshold, the sensor issues an alarm. Common temperature sensors include thermistors (such as NTC and PTC) and digital temperature sensors (such as DS18B20). Installation Location: The temperature sensor should be installed in key locations inside the distribution cabinet, such as wire connection points and equipment heat dissipation areas, as these areas are prone to overheating and fire. Threshold Setting: Set the threshold based on the normal operating temperature range of the distribution cabinet. For example, if the normal operating temperature is below 40°C, the first set temperature value can be set to 60°C or higher to avoid false alarms. This allows for early detection of fire hazards by observing rising temperatures, preventing them from spreading. The smoke sensor determines whether a fire has occurred by detecting smoke concentration inside the distribution cabinet. When the smoke concentration exceeds a preset threshold, the sensor issues an alarm. Common smoke sensors include ionization and photoelectric smoke sensors. Ion sensors are sensitive to the ionization of smoke particles, while photoelectric sensors determine smoke concentration by detecting the scattering of light by smoke particles. Installation Location: Smoke sensors should be installed in ventilated areas inside the distribution cabinet or above equipment where smoke is likely to accumulate. Threshold Setting: Set the smoke concentration threshold based on the normal operating environment of the distribution cabinet. For example, the threshold can be set to a smoke concentration of 0.1%-0.2% to ensure timely detection of fires in the early stages. Smoke generation can be used to identify potential fire hazards in the early stages of a fire, preventing them from spreading. Dual temperature and smoke monitoring enables timely detection of fire hazards, buying time for fire prevention and emergency response, and reducing fire risks by over 40%.

[0062] If the PDC maintains a temperature parameter greater than a second set temperature value and a smoke parameter less than or equal to a set smoke value for a period longer than the second set time, the PDC determines that it is experiencing a high temperature. This mechanism for identifying persistent high temperature conditions effectively identifies equipment overheating issues, allowing proactive measures to extend equipment life. If the PDC temperature is high but no smoke is detected, there may be a problem with the cooling system, causing the PDC's internal temperature to rise. If this issue is not addressed, the PDC could experience persistent high temperatures and damage electronic components.

[0063] The first set current value is greater than the second set current value, and the first set temperature is greater than the second set temperature. When the normal operating temperature of the power distribution cabinet is below 40°C and the first set temperature is set to 60°C, the second set temperature can be set to 50°C. This hierarchical setting can effectively distinguish faults of different severity and provide a more refined basis for fault handling.

[0064] As one of the embodiments, the power distribution cabinet adjusts the speed of its own cooling fan according to the temperature parameter. When the power distribution cabinet detects that the temperature parameter is greater than the second set temperature value and the smoke parameter is less than or equal to the set smoke value, the power distribution cabinet starts timing and adjusts the speed of its own cooling fan to the highest. When the internal temperature of the power distribution cabinet is low, energy consumption can be effectively reduced by reducing the speed of the cooling fan or stopping the cooling fan. When the internal temperature of the power distribution cabinet exceeds the set second temperature, the fan speed needs to be increased to the highest. If in this case, the internal temperature of the power distribution cabinet is not lower than the second temperature, it means that there is a problem with the cooling system of the power distribution cabinet and maintenance personnel are required to repair it. This intelligent heat dissipation mechanism can dynamically adjust the heat dissipation effect according to the operating status of the equipment, effectively reduce the temperature of the equipment, and improve the operating stability of the equipment.

[0065] When the distribution cabinet's timing exceeds the second set time, the distribution cabinet determines that it is in a continuously high temperature state. If the temperature parameter is greater than the first set temperature value and the smoke parameter is greater than the set smoke value during the timing, the distribution cabinet determines that it is in a fire state and releases carbon dioxide gas to extinguish the fire. This automatic fire extinguishing mechanism can quickly take action in the early stages of a fire, reduce fire losses, and ensure the safety of equipment and personnel. The second set time is used to determine whether the distribution cabinet is in a continuously high temperature state. Therefore, to prevent the influence of accidental factors, the second set time is relatively long and can be set to 30 minutes, 45 minutes, 60 minutes, etc.

[0066] In one embodiment, the cloud server generates a maintenance task according to the fault type in the data packet, including the following steps:

[0067] The cloud server records the receiving time of the data packet, and then takes the receiving time as the task start time of the maintenance task. This time recording mechanism can provide accurate time reference for the maintenance task, facilitating subsequent maintenance management and statistical analysis.

[0068] The cloud server places the fault type, the number of the power distribution cabinet, and the task start time into the content of the maintenance task, and takes the data packet as an attachment of the maintenance task. This detailed task content recording method provides comprehensive maintenance information for the maintenance personnel, improving the maintenance efficiency.

[0069] When the cloud server generates the maintenance task, it will no longer receive data uploaded by the power distribution cabinet before the maintenance task is completed. After the maintenance personnel complete the maintenance of the power distribution cabinet, they will test the power distribution cabinet. If the power distribution cabinet still has other problems, the maintenance personnel will also handle them, without the need to issue a maintenance task. This mechanism avoids resource waste caused by repeated data reception, improving the operation efficiency of the system.

[0070] As one of the embodiments, the cloud server determines the proportion value of the current maintenance task according to the grade and fault type of the power distribution cabinet, and then updates the maintenance task table according to the proportion value of the maintenance task, including the following steps:

[0071] The cloud server pre-sets the grade of the power distribution cabinet, and the higher the grade, the higher the proportion value, and then numbers the power distribution cabinets from high to low according to the proportion value of the power distribution cabinet. The grade of the power distribution cabinet is set by the user according to the role of the power distribution cabinet. This grading management mechanism can reasonably allocate maintenance resources according to the importance of the power distribution cabinet, ensuring the priority maintenance of critical equipment.

[0072] The cloud server pre-sets the proportion value of the fault type of the power distribution cabinet, and the fault type is arranged from high to low according to the proportion value as follows: fire, electric shock, short circuit, overload, and continuous high temperature. This fault type grading mechanism can reasonably arrange the maintenance sequence according to the danger degree of the fault, improving the pertinence and effectiveness of the maintenance.

[0073] The cloud server takes the sum of the proportion value of the fault type in the maintenance task and the proportion value corresponding to the number of the power distribution cabinet as the proportion value of the maintenance task. This comprehensive weight calculation method can comprehensively consider the importance of the equipment and the severity of the fault, providing a scientific basis for the sorting of the maintenance task.

[0074] When multiple parameters in the detection parameters of the power distribution cabinet exceed the set threshold value, the power distribution cabinet can send multiple fault types to the cloud server, and the cloud server adds the proportion values of multiple fault types to the power distribution cabinet when calculating the proportion value of the maintenance task. Alternatively, the power distribution cabinet can only send the fault type with the highest proportion value among the multiple fault types to the cloud server.

[0075] The cloud server sorts maintenance tasks from high to low based on their weight and generates a maintenance task list. This dynamic sorting mechanism can dynamically adjust the priority of maintenance tasks based on real-time maintenance needs, ensuring efficient maintenance work.

[0076] As one embodiment, the cloud server will reorder the maintenance task list to update the maintenance task list every time it obtains a new maintenance task. This real-time update mechanism can ensure that the maintenance task list always reflects the current maintenance needs and improve the utilization rate of maintenance resources.

[0077] Every time the cloud server updates the maintenance task list, it sends the new maintenance task list to the control center. This timely information transmission mechanism ensures that the control center has the latest maintenance task information in a timely manner, facilitating the arrangement and scheduling of maintenance work.

[0078] In one embodiment, after receiving a maintenance task list, the console adds the tasks in the list to a pending task list. The console then sequentially sends the tasks to the maintenance personnel's mobile device, allowing them to repair the corresponding distribution cabinets based on the tasks in the mobile device. This task allocation mechanism pushes maintenance tasks directly to maintenance personnel, improving the response speed and execution efficiency of maintenance work.

[0079] The console receives a task completion signal from the mobile device after it completes a maintenance task and sends it to the cloud server. This task completion feedback mechanism allows for timely recording of maintenance task completion status, facilitating subsequent maintenance management and statistical analysis.

[0080] When the pending task list contains a large number of maintenance tasks, the console can send only one maintenance task to each mobile device. Once a maintenance task is completed by a mobile device and the console receives a task completion signal from the mobile device, it will send the next maintenance task to the mobile device. In this case, the console can set a weighted threshold. When the maintenance tasks in the pending task list exceed the threshold, the console sends the task to the mobile device, giving priority to the maintenance personnel assigned to that mobile device. Alternatively, the console can evenly distribute the maintenance tasks in the pending task list to the mobile devices. The maintenance tasks are sorted by weight on the mobile devices, and the maintenance personnel then process the tasks in the mobile devices in order. The mobile devices can be mobile phones, tablets, and so on.

[0081] The cloud server will remove completed maintenance tasks from the maintenance task list. This task clearing mechanism can keep the maintenance task list clear and concise, facilitating subsequent maintenance task management.

[0082] As one embodiment, when the console receives a maintenance task, it first traverses the maintenance task table and determines the newly received maintenance task based on the number of the distribution cabinet in the maintenance task table. This task identification mechanism can quickly locate new tasks and improve the efficiency of task processing.

[0083] The console adds newly received maintenance tasks to the pending task list and sorts them from highest to lowest based on their weight. This task sorting mechanism prioritizes maintenance tasks and improves the efficiency and effectiveness of maintenance work.

[0084] The console distributes maintenance tasks to maintenance personnel's mobile devices based on their order of placement and removes them from the pending tasks list. This task distribution mechanism accurately delivers maintenance tasks to maintenance personnel, ensuring timely completion of maintenance work.

[0085] In one embodiment, the cloud server records the time when the task completion signal uploaded by the receiving console is received and uses this time as the task completion time. This time recording mechanism can provide accurate time data for statistical analysis of maintenance tasks, facilitating subsequent operation and maintenance management.

[0086] The cloud server generates a maintenance log for the distribution cabinet based on the completed maintenance tasks stored for the distribution cabinet. This log includes the start and completion time of each maintenance task, as well as the fault type. This maintenance log generation mechanism provides detailed historical data for the distribution cabinet's operation and maintenance, facilitating fault analysis and equipment maintenance.

[0087] The cloud server counts the number of fault types and ranks the distribution cabinet fault types based on the count. This fault statistics mechanism provides data support for the operation and maintenance management of the distribution cabinet, making it easier to identify potential equipment problems and take preventive measures in advance.

[0088] A smart power distribution cabinet system implements the aforementioned control method. The system includes a control console, a cloud server, and several power distribution cabinets, with the cloud server communicating with the control console and the power distribution cabinets, respectively. This system architecture enables intelligent monitoring and management of the power distribution cabinets, improving operational reliability, reducing maintenance costs, and enhancing overall efficiency.

[0089] Compared with the existing technology, the beneficial effects of the present invention are:

[0090] 1. Real-time monitoring and fault diagnosis: The distribution cabinet uses sensors to acquire detection parameters in real time and compares them with set parameters, enabling rapid and accurate identification of fault types. Compared to traditional manual inspections, this method enables real-time monitoring of the distribution cabinet's operating status, enabling timely detection of faults and significantly improving the efficiency and accuracy of fault diagnosis. The distribution cabinet uses cameras to capture internal images, further enriching the data sources for fault diagnosis and providing maintenance personnel with more intuitive fault information, enabling more precise identification of the cause and location of the fault.

[0091] 2. Intelligent Fault Handling and Resource Management: The PDC packages detection data, fault type, internal image, and number into data packets and uploads them to the cloud server, enabling remote transmission and centralized management of fault information. The cloud server can quickly identify the PDC number, generate a maintenance task based on the fault type, and add the data packet to the maintenance task, thus achieving automated and information-based fault handling. The cloud server determines the weight of the maintenance task based on the PDC level and fault type, and updates the maintenance task table accordingly, allowing the control console to rationally schedule maintenance workers according to the maintenance task table. This method can rationally allocate maintenance resources based on the severity of the fault and the importance of the equipment, prioritize critical faults, improve maintenance efficiency, and reduce equipment downtime.

[0092] 3. Improve system reliability and safety: Real-time monitoring and rapid fault handling can promptly eliminate potential faults, reduce power outages caused by faults, and improve the reliability and stability of the power distribution system. The cloud server's centralized management and analysis of fault information helps accumulate fault data, providing reference for subsequent equipment maintenance and improvements, further improving the safety and reliability of the power distribution system.

[0093] In the description of the specification, reference to the terms "in one embodiment," "preferably," "example," "specific example," or "some examples" means that the specific features, structures, materials, or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. The schematic representations of the above terms in this specification do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in any appropriate manner in any one or more embodiments or examples. The connection method described in the description of the specification has obvious effects and practical effectiveness.

[0094] Through the description of the above structure and principle, technical personnel in the relevant technical field should understand that the present invention is not limited to the above specific implementation methods, and improvements and substitutions based on the present invention using the well-known technology in the field all fall within the scope of protection of the present invention and should be defined by the claims.

Claims

1. A control method for an intelligent power distribution cabinet system, characterized in that: The control method comprises the following steps: The distribution cabinet obtains detection parameters in the distribution cabinet through sensors, and compares the obtained detection parameters with set parameters to determine the fault type of the distribution cabinet; The PDC uses a camera to capture its own internal image, then packages the detection data, fault type, internal image, and PDC number into a data package and uploads it to the cloud server. The cloud server identifies the distribution cabinet number in the data packet, generates a maintenance task based on the fault type in the data packet, and adds the data packet to the maintenance task; The cloud server determines the proportion of the current maintenance task according to the level and fault type of the distribution cabinet, then updates the maintenance task table according to the proportion of the maintenance task, and sends the maintenance task table to the console, so that the console arranges maintenance workers to repair the distribution cabinet according to the maintenance task table.

2. The control method of the intelligent power distribution cabinet system according to claim 1, characterized in that: The sensors include but are not limited to current sensors, voltage sensors, temperature sensors and smoke sensors. The detection parameters acquired by the sensors include current parameters, voltage parameters, temperature parameters and smoke parameters. The fault types include overload, short circuit, leakage, fire and continuous high temperature. When the current parameter is greater than the first set current value, the power distribution cabinet determines that it is in a short-circuit state; When the power distribution cabinet maintains a current parameter higher than the second set current value for a time period greater than the first set time period, the power distribution cabinet determines that it is in an overload state; When the voltage parameter is greater than the first set voltage value, the power distribution cabinet determines that it is in a leakage state; When the temperature parameter is greater than the first set temperature value and the smoke parameter is greater than the set smoke value, the power distribution cabinet determines that it is in a fire state; When the power distribution cabinet maintains a temperature parameter greater than a second set temperature value and a smoke parameter not higher than a set smoke value for a time greater than a second set time, the power distribution cabinet determines that it is in a high temperature state; The first set current value is greater than the second set current value, and the first set temperature is greater than the second set temperature.

3. The control method of the intelligent power distribution cabinet system according to claim 2, characterized in that: The power distribution cabinet adjusts the speed of its own cooling fan according to temperature parameters; When the power distribution cabinet detects that the temperature parameter is greater than the second set temperature value and the smoke parameter is less than or equal to the set smoke value, the power distribution cabinet starts timing and adjusts the speed of its own cooling fan to the highest; When the timing time of the power distribution cabinet is greater than the second set time, the power distribution cabinet determines that it is in a continuous high temperature state; If the temperature parameter of the power distribution cabinet is greater than the first set temperature value and the smoke parameter is greater than the set smoke value during timing, the power distribution cabinet determines that it is in a fire state and releases carbon dioxide gas to extinguish the fire.

4. The control method of the intelligent power distribution cabinet system according to claim 3, characterized in that: The cloud server generates a maintenance task based on the fault type in the data packet, which includes the following steps: The cloud server records the receiving time of the received data packet and then uses the receiving time as the task start time of the maintenance task; The cloud server adds the fault type, distribution cabinet number, and task start time to the maintenance task content and attaches the data packet to the maintenance task. When the cloud server generates a maintenance task, it will no longer receive data uploaded by the distribution cabinet until the maintenance task is completed.

5. The control method of the intelligent power distribution cabinet system according to claim 4, characterized in that: The cloud server determines the weight of the current maintenance task based on the level and fault type of the power distribution cabinet, and then updates the maintenance task table based on the weight of the maintenance task, including the following steps: The cloud server pre-sets the level of the distribution cabinet. The higher the level, the higher the weight. The distribution cabinets are then numbered from high to low according to their weight. The cloud server pre-sets the proportion of fault types of the power distribution cabinet. The fault types are arranged in descending order according to the proportion value: fire, leakage, short circuit, overload and continuous high temperature; The cloud server uses the sum of the proportion value of the fault type in the maintenance task and the proportion value corresponding to the number of the distribution cabinet as the proportion value of the maintenance task; The cloud server sorts the maintenance tasks from high to low according to their weight values ​​and generates a maintenance task table.

6. The control method of the intelligent power distribution cabinet system according to claim 5, characterized in that: Every time the cloud server obtains a new maintenance task, it reorders the maintenance task table to update it; Every time the cloud server updates the maintenance task list, it sends the new maintenance task list to the console.

7. The control method of the intelligent power distribution cabinet system according to claim 6, characterized in that: After receiving the maintenance task list, the console will add the maintenance tasks in the maintenance task list to the task list to be assigned; The console will send the maintenance tasks in the task list to be assigned to the maintenance personnel's mobile device in sequence, so that the maintenance personnel can repair the corresponding distribution cabinet according to the maintenance tasks in the mobile device; The console receives a task completion signal from the mobile device after it completes the maintenance task, and sends the task completion signal to the cloud server; The cloud server will remove the completed maintenance tasks from the maintenance task list.

8. The control method of the intelligent power distribution cabinet system according to claim 7, characterized in that: When the console receives a maintenance task, it first traverses the maintenance task table and determines the newly received maintenance task based on the number of the distribution cabinet in the maintenance task table; The console adds the newly received maintenance tasks to the task list to be assigned, and arranges the maintenance tasks from high to low according to their weight. The console distributes the maintenance tasks to the maintenance personnel's mobile devices according to the arrangement order, and removes the distributed maintenance tasks from the to-be-assigned task list.

9. The control method of the intelligent power distribution cabinet system according to claim 8, characterized in that: The cloud server records the time when the task completion signal uploaded by the receiving console is received and uses this time as the task completion time; The cloud server generates a maintenance log for the distribution cabinet based on the saved maintenance tasks of the distribution cabinet. The maintenance log includes the task start time, task completion time, and fault type of each maintenance task. The cloud server counts the number of fault types and arranges the fault types of the power distribution cabinets according to the count.

10. An intelligent power distribution cabinet system, characterized in that: The intelligent distribution cabinet system executes the control method of the intelligent distribution cabinet system according to any one of claims 1 to 9, and the intelligent distribution cabinet system includes a console, a cloud server and several distribution cabinets, and the cloud server is communicatively connected to the console and the distribution cabinets respectively.

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