Distribution network personal safety early warning system and method

Abstract

The invention relates to a distribution network personal safety early warning system and method, and the system comprises a data collection unit which is used for collecting environment data and personnel position data corresponding to a target region in a distribution network; the central processing unit is in communication connection with the data acquisition unit and is used for performing decision analysis processing on the environment data and the personnel position data to obtain early warning information and sending the early warning information to the early warning unit; and the early warning unit is in communication connection with the central processing unit and is used for carrying out early warning on an operator corresponding to the early warning information according to the early warning information. According to the distribution network personal safety early warning system provided by the embodiment of the invention, potential dangers can be identified in time, early warning can be carried out on emergencies, accurate and reliable early warning information can be generated, early warning can be carried out in multiple forms through the early warning unit in time, it is ensured that an operator can make a response quickly, and the early warning reliability is improved.

Description

Technical Field

[0001] The present application relates to the field of electric power technology, and in particular to a distribution network personal safety early warning system and method. Background Art

[0002] The distribution network environment usually involves high voltage electricity, complex lines, equipment operation, construction operations and other scenarios, with safety risks such as electric shock, equipment failure, and fire. In order to meet the high requirements for the personal safety of operators in modern distribution network operation scenarios, it is necessary to monitor the distribution network environment in real time and issue early warnings in time when there are risks to personal safety.

[0003] The distribution network personal safety early warning system in traditional technology mostly relies on manual monitoring and simple equipment alarms. Due to the complex distribution network environment, it is difficult for operators to remain highly vigilant at all times, especially in special circumstances such as bad weather or at night. The efficiency and accuracy of manual supervision will be greatly reduced. In addition, the early warning system in traditional technology can usually only monitor a single risk factor and cannot cope with diverse application scenarios, resulting in low early warning reliability. Summary of the invention

[0004] Based on this, it is necessary to provide a distribution network personal safety warning system and method that can improve the reliability of warning in response to the above technical problems.

[0005] In a first aspect, the present application provides a distribution network personal safety early warning system, the system comprising:

[0006] A data collection unit, used to collect environmental data and personnel location data corresponding to the target area in the distribution network;

[0007] The central processing unit is connected to the data acquisition unit for making decisions and analyzing the environmental data and the personnel location data, obtaining early warning information, and sending the early warning information to the early warning unit;

[0008] The early warning unit is connected to the central processing unit for providing early warning to the operator corresponding to the early warning information according to the early warning information.

[0009] In one embodiment, a central processing unit in a distribution network personal safety early warning system is provided, comprising:

[0010] The data processing module is connected to the data acquisition unit for performing abnormal detection and processing on the environmental data and personnel location data to obtain risk information;

[0011] The decision module communicates with the data processing module and is connected to the early warning unit, and is used to generate early warning information based on the risk information and send the early warning information to the early warning unit.

[0012] In one of the embodiments, the central processing unit in the provided distribution network personal safety warning system also includes: a data storage module, connected to the data processing module, for storing environmental data and personnel location data.

[0013] In one embodiment, the distribution network personal safety early warning system provided further includes:

[0014] The feedback unit is connected to the central processing unit and is used to send feedback information to the central processing unit so that the central processing unit can generate early warning information based on the feedback information.

[0015] In one embodiment, the distribution network personal safety early warning system provided further includes:

[0016] The communication unit is respectively connected to the data acquisition unit and the central processing unit for communication, and is used for receiving the environmental data and the personnel position data, and transmitting the environmental data and the personnel position data to the central processing unit.

[0017] In one of the embodiments, the data acquisition unit in the distribution network personal safety early warning system provided includes: a temperature sensor, a humidity sensor, an air pressure sensor, an electromagnetic field sensor and an equipment sensor.

[0018] In one of the embodiments, the warning modes of the warning unit in the distribution network personal safety warning system provided include sound and light alarm, SMS notification and mobile application push.

[0019] In a second aspect, the present application further provides a distribution network personal safety warning method, which is applied to a central processing unit in a distribution network personal safety warning system as in the first aspect, and the method comprises:

[0020] Obtain environmental data and personnel location data corresponding to the target area in the distribution network;

[0021] Decision-making analysis and processing are performed on environmental data and personnel location data to obtain warning information, and the warning information is sent to the warning unit, so that the warning unit can issue a warning to the operator corresponding to the warning information based on the warning information.

[0022] In one embodiment, the process of performing decision analysis and processing on environmental data and personnel location data to obtain warning information in the distribution network personal safety warning method provided includes:

[0023] The environmental data and personnel location data are input into a pre-trained target decision analysis model to obtain early warning information. The target decision analysis model is obtained by training the initial decision analysis model based on machine learning and the historical environmental data and historical personnel location data corresponding to the environmental data and personnel location data in the historical time interval.

[0024] In one embodiment, the provided distribution network personal safety early warning method further includes:

[0025] receiving feedback information sent by the feedback unit;

[0026] Generate early warning information based on feedback information.

[0027] The above-mentioned distribution network personal safety warning system and method, one aspect of the distribution network personal safety warning system includes: a data acquisition unit, used to collect environmental data and personnel location data corresponding to the target area in the distribution network; a central processing unit, which is communicated with the data acquisition unit, and is used to perform decision analysis and processing on the environmental data and personnel location data, obtain warning information, and send the warning information to the warning unit; the warning unit, which is communicated with the central processing unit, and is used to issue a warning to the operator corresponding to the warning information based on the warning information. In this way, by real-time monitoring of environmental data and personnel positions in the target area of ​​the distribution network, potential dangers such as high-voltage electric shock, leakage, mechanical risks, etc. can be identified in time, emergency situations can be warned, accurate and reliable warning information can be generated, and warnings can be issued in a timely manner through the warning unit in various forms to ensure that operators can respond quickly and reduce the occurrence of safety accidents, thereby improving personal safety protection; the central processing unit automatically analyzes environmental data and personnel location data, and quickly generates warning information to avoid the inefficiency and subjective misjudgment of traditional manual monitoring, thereby improving work efficiency; the data acquisition unit and the central processing unit realize intelligent analysis of the distribution network operation status, which can provide more accurate and comprehensive risk assessments; historical data can be accumulated to provide a scientific basis for subsequent safety optimization, thereby improving the reliability of the distribution network personal safety warning method. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the related technologies, the drawings required for use in the embodiments or the related technical descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0029] Figure 1 It is a structural block diagram of a distribution network personal safety early warning system in one embodiment;

[0030] Figure 2 A schematic diagram of a flow chart of a personal safety early warning method for a distribution network in an embodiment;

[0031] Figure 3 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0032] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0033] The application scenarios of the distribution network personal safety warning system and the distribution network personal safety warning method provided in the embodiments of the present application may include but are not limited to substations, power plants and high-voltage transmission lines.

[0034] In an exemplary embodiment, Figure 1 As shown, a distribution network personal safety early warning system is provided, and the system includes: a data acquisition unit, which is used to collect environmental data and personnel location data corresponding to the target area in the distribution network; a central processing unit, which is communicated with the data acquisition unit, and is used to perform decision analysis and processing on the environmental data and personnel location data, obtain early warning information, and send the early warning information to the early warning unit; the early warning unit, which is communicated with the central processing unit, and is used to issue an early warning to the operator corresponding to the early warning information based on the early warning information.

[0035] The data collection unit is used to collect environmental data and personnel location data through a variety of sensors. The sensors are deployed in each monitoring area of ​​the distribution network, and the target area is one of the monitoring areas.

[0036] In a possible implementation, the data acquisition unit includes: a temperature sensor, a humidity sensor, an air pressure sensor, an electromagnetic field sensor, and an equipment sensor, which are respectively used to collect data on the temperature, humidity, air pressure, electromagnetic field strength, and equipment operation status of the target area to obtain environmental data corresponding to the target area. The data acquisition unit also includes a locator, which can be carried by the operator to collect personnel location data. Optionally, the temperature sensor can be a thermistor-based temperature sensor or an infrared sensor; the humidity sensor can be a capacitive or resistive humidity sensor; the air pressure sensor can be a MEMS (Micro-Electro-Mechanical System) air pressure sensor; the electromagnetic field sensor can be a Hall sensor or an electromagnetic induction sensor; the equipment sensor can be a vibration sensor or an acoustic sensor. The locator can be an RFID (Radio Frequency Identification) sensor, a UWB (Ultra Wide Band) locator, or a GPS (Global Positioning System) locator, through which the three-dimensional position information of the operator carrying the locator can be accurately determined. Using various sensors, the environmental data of the target area can be monitored in real time and the environmental changes in the target area can be tracked. In this embodiment, by integrating a data acquisition unit with multiple sensors, key parameters such as temperature, humidity, air pressure, electromagnetic field strength and equipment operating status in the target area of ​​the distribution network can be monitored in real time, and combined with personnel location data, comprehensive security protection can be provided to effectively reduce safety hazards.

[0037] In one possible implementation, the central processing unit includes: a data processing module, which is communicated with the data acquisition unit and is used to perform anomaly detection and processing on environmental data and personnel location data to obtain risk information; a decision module, which is communicated with the data processing module and is connected to the early warning unit, and is used to generate early warning information based on the risk information and send the early warning information to the early warning unit.

[0038] Among them, the process of anomaly detection processing may include: preprocessing environmental data and personnel location data to obtain target monitoring data; based on a preset decision analysis model, performing risk decision processing on the target monitoring data to obtain risk information corresponding to the target monitoring data.

[0039] Exemplarily, the preprocessing process may include: cleaning the environmental data and personnel location data, removing abnormal data points, such as erroneous values ​​caused by sudden noise; using interpolation or a prediction model based on historical data to repair missing data. Another exemplary process may also include: standardizing the environmental data and personnel location data, converting data from different sources and units into a unified format and unit for subsequent analysis.

[0040] Exemplarily, the process of risk decision processing may include: comparing the target monitoring data with the historical monitoring data, analyzing the changing trend of the target monitoring data compared with the historical monitoring data, if the changing trend is within a reasonable range, then the risk information is that the changing trend is normal; if the changing trend exceeds a reasonable range, then the risk information is that the changing trend is abnormal.

[0041] As another example, the risk decision-making process also includes: compliance matching processing of the target monitoring data based on a preset safety interval. For example, the temperature, humidity, air pressure, and electromagnetic field data in the target monitoring data meet the normal operating requirements of the distribution network target area, that is, they are within the safety interval. Then the risk information is that the operating status is normal; if the target monitoring data exceeds the safety interval, then the risk information is that a certain data in the target monitoring data is abnormal, or the operating status of the equipment corresponding to a certain data is abnormal. At this time, the risk information may also include the degree of deviation of the data from the safety interval.

[0042] As another example, the process of risk decision processing may also include: for the data related to the environment in the target monitoring data, using a machine learning algorithm, such as a support vector machine or a deep learning model, to detect whether the target monitoring data is in an abnormal mode. For the data related to the location of personnel in the target monitoring data, using a decision model such as a decision tree to determine whether they are close to a high-risk area, such as judging that a person is close to high-voltage equipment or a high electromagnetic field area based on the personnel location data and the magnetic field strength, or judging that the insulation layer of the equipment is damaged based on the humidity and temperature, then the risk information is that the person corresponding to the personnel location data has a safety risk, and the decision module needs to immediately generate warning information.

[0043] As another example, the decision analysis model can also be a risk prediction model based on time series analysis, neural network or particle filtering algorithm. The risk decision processing process can also include: training the risk prediction model using historical monitoring data corresponding to the target monitoring data in the historical time interval; inputting the target monitoring data into the trained risk prediction model to obtain the changing trend of temperature, humidity or equipment operating status, so as to identify potential equipment failures or environmental deterioration, or predict the activity trajectory of personnel to determine whether they are likely to enter a dangerous area, and using the changing trend or prediction result output by the risk prediction model as risk information.

[0044] In one possible implementation, the process of generating early warning information by the decision module may include: classifying the risk information generated by the data processing module into risk levels to obtain different risk levels, such as low, medium, and high; generating early warning information based on the risk information and risk levels. Exemplarily, the early warning information may include a forecast report, for example: a certain device may overheat within 24 hours, or the humidity in a certain area may increase, which may lead to the risk of leakage, and is displayed in an early warning manner such as SMS notification or mobile application push. In this implementation, through automated monitoring and real-time data analysis, even under special conditions such as bad weather or at night, the efficiency and accuracy of on-site supervision of target areas in the distribution network can be significantly improved, effectively making up for the shortcomings of manual supervision.

[0045] In a possible implementation, the warning methods of the early warning unit include sound and light alarms, SMS notifications, and mobile application push notifications. The early warning information may include early warning methods, and for different early warning methods, the decision module sends the early warning information to different early warning modules in the early warning unit. Exemplarily, based on the magnetic field strength information in the environmental data, risk information that the equipment has an overheating risk is obtained, and if the early warning method in the early warning information generated based on the risk information is sound and light alarm, the early warning information is sent to the sound and light alarm module of the early warning unit, so that the sound and light alarm module of the early warning unit can make an sound and light alarm based on the early warning information.

[0046] As another example, based on the humidity in the substation and the temperature data on the surface of the equipment in the environmental data, the central processing unit obtains the risk information that the equipment is overheating. If the warning method in the warning information generated based on the risk information is sound and light alarm and SMS notification, the warning information is sent to the sound and light alarm module and SMS notification module of the warning unit, so that the sound and light alarm module and SMS notification module of the warning unit respectively perform sound and light alarm and SMS notification based on the warning information, so as to avoid the situation that the on-site personnel may not be able to check the SMS in time and miss the warning, or for those who work in a high-noise environment, the sound and light alarm may not attract enough attention, so that the on-site personnel miss the warning. In this embodiment, warnings are issued through a variety of warning methods to ensure that the warning information can be conveyed to relevant personnel in a timely and accurate manner, improve the ability to respond to emergencies, and thus expand the scene adaptability and reliability of the distribution network personal safety warning system.

[0047] In another exemplary embodiment, the data acquisition unit also includes a wind speed sensor and an ultraviolet sensor, and the environmental data also includes wind speed data. Based on the wind speed data, the central processing unit obtains risk information that exceeds the operational safety standard, and if the warning method in the warning information generated based on the risk information is an audible and visual alarm, the warning information is sent to the audible and visual alarm module of the warning unit, and the warning unit issues an early warning based on the warning information.

[0048] In a possible implementation, the central processing unit further includes a data storage unit connected to the data processing module and used for storing environmental data and personnel location data.

[0049] Exemplarily, the central processing unit may be a central processing unit (CPU), a microcontroller unit (MCU), or a programmable logic controller (PLC).

[0050] In a possible implementation, the provided system further includes a feedback unit connected to the central processing unit and configured to send feedback information to the central processing unit so that the central processing unit can generate warning information based on the feedback information.

[0051] The feedback unit is used to receive feedback information from on-site personnel and transmit the feedback information to the central processing unit. The feedback unit may include an input device, which is composed of a button, a touch screen, and a voice recognition device. On-site personnel can input feedback information through the input device, and the feedback information includes confirmation of receipt of the warning, description of the on-site situation, and emergency help. In this embodiment, through the feedback unit, on-site personnel are allowed to promptly feedback the on-site situation to the central processing unit, so as to adjust the warning strategy according to the actual situation, optimize the system performance, and further improve the accuracy and timeliness of the warning.

[0052] In a possible implementation, the provided system further includes a communication unit, which is respectively connected to the data acquisition unit and the central processing unit for receiving environmental data and personnel location data, and transmitting the environmental data and personnel location data to the central processing unit. The communication unit may be connected to the data acquisition unit and the central processing unit by wired connection or wireless connection. Optionally, the communication unit may communicate with the data acquisition unit and the central processing unit based on a variety of communication protocols, and the communication protocols may include LoRa (Long Range Radio), Zigbee, Wi-Fi and 4G / 5G, which can ensure communication reliability and stability in different environments, and ensure reliable transmission of environmental data and personnel location data in a complex distribution network environment.

[0053] The above-mentioned distribution network personal safety early warning system includes: a data acquisition unit, which is used to collect environmental data and personnel location data corresponding to the target area in the distribution network; a central processing unit, which is communicated with the data acquisition unit, and is used to perform decision-making analysis and processing on the environmental data and personnel location data, obtain early warning information, and send the early warning information to the early warning unit; an early warning unit, which is communicated with the central processing unit, and is used to issue an early warning to the operator corresponding to the early warning information based on the early warning information. In this embodiment, by real-time monitoring of environmental data and personnel positions in the target area of ​​the distribution network, potential dangers such as high-voltage electric shock, leakage, mechanical risks, etc. can be identified in time, emergency situations can be warned, accurate and reliable warning information can be generated, and warnings can be issued in a timely manner through the warning unit in various forms to ensure that operators can respond quickly and reduce the occurrence of safety accidents, thereby improving personal safety protection; the central processing unit automatically analyzes environmental data and personnel position data, and quickly generates warning information to avoid the inefficiency and subjective misjudgment of traditional manual monitoring, thereby improving work efficiency; the data acquisition unit and the central processing unit realize intelligent analysis of the distribution network operation status, and can provide more accurate and comprehensive risk assessments; historical data can be accumulated to provide a scientific basis for subsequent safety optimization, thereby improving the reliability of the distribution network personal safety warning method.

[0054] In an exemplary embodiment, Figure 2 As shown, a distribution network personal safety warning method is provided, which is applied to the central processing unit in the distribution network personal safety warning system in the above embodiment, and the method includes the following steps 202 to 204. Among them:

[0055] Step 202: Acquire environmental data and personnel location data corresponding to a target area in the distribution network.

[0056] Step 204, decision analysis is performed on the environmental data and personnel location data to obtain warning information, and the warning information is sent to the warning unit, so that the warning unit can issue a warning to the operator corresponding to the warning information based on the warning information.

[0057] In a possible implementation, step 204 may further include: inputting environmental data and personnel location data into a pre-trained target decision analysis model to obtain early warning information, wherein the target decision analysis model is obtained by training an initial decision analysis model based on machine learning and historical environmental data and historical personnel location data corresponding to environmental data and personnel location data within a historical time interval.

[0058] In a possible implementation, the provided method further includes: receiving feedback information sent by a feedback unit; and generating early warning information according to the feedback information.

[0059] For the above-mentioned limitation on the distribution network personal safety early warning method, please refer to the description of the distribution network personal safety early warning system in the above-mentioned embodiment.

[0060] In the above-mentioned distribution network personal safety early warning method, by obtaining the environmental data and personnel location data corresponding to the target area in the distribution network; decision-making analysis and processing are performed on the environmental data and personnel location data to obtain early warning information, and the early warning information is sent to the early warning unit, so that the early warning unit can warn the operator corresponding to the early warning information according to the early warning information. In this way, by real-time monitoring of the environmental data and personnel location of the distribution network target area, potential dangers such as high-voltage electric shock, leakage, mechanical risks, etc. can be identified in time, and emergency situations can be warned, and accurate and reliable early warning information can be generated, and early warnings can be issued in various forms through the early warning unit in time to ensure that the operator can respond quickly and reduce the occurrence of safety accidents, thereby improving personal safety protection; the central processing unit automatically analyzes the environmental data and personnel location data, quickly generates early warning information, avoids the inefficiency and subjective misjudgment of traditional manual monitoring, and thus improves work efficiency; the data acquisition unit and the central processing unit realize intelligent analysis of the distribution network operation status, and can provide more accurate and comprehensive risk assessment; historical data can be accumulated to provide a scientific basis for subsequent safety optimization, thereby improving the reliability of the distribution network personal safety early warning method.

[0061] It should be understood that, although the steps in the flowcharts involved in the above embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above embodiments may include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0062] In an exemplary embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as shown in FIG. Figure 3As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store environmental data and personnel location data. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a distribution network personal safety early warning method is implemented.

[0063] Those skilled in the art will understand that Figure 3 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0064] In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the following steps when executing the computer program: obtaining environmental data and personnel location data corresponding to a target area in a distribution network; performing decision analysis and processing on the environmental data and personnel location data to obtain early warning information, and sending the early warning information to an early warning unit, so that the early warning unit can issue an early warning to an operator corresponding to the early warning information based on the early warning information.

[0065] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented: obtaining environmental data and personnel location data corresponding to a target area in a distribution network;

[0066] Decision-making analysis and processing are performed on environmental data and personnel location data to obtain warning information, and the warning information is sent to the warning unit, so that the warning unit can issue a warning to the operator corresponding to the warning information based on the warning information.

[0067] In one embodiment, a computer program product is provided, including a computer program, which, when executed by a processor, implements the following steps: obtaining environmental data and personnel location data corresponding to a target area in a distribution network; performing decision analysis and processing on the environmental data and personnel location data to obtain early warning information, and sending the early warning information to an early warning unit, so that the early warning unit can issue an early warning to an operator corresponding to the early warning information based on the early warning information.

[0068] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0069] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0070] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0071] The above embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A distribution network personal safety early warning system, characterized in that: The system comprises: A data collection unit, used to collect environmental data and personnel location data corresponding to the target area in the distribution network; A central processing unit, which is in communication with the data acquisition unit, is used to perform decision analysis on the environmental data and the personnel location data to obtain warning information, and send the warning information to the warning unit; The early warning unit is in communication with the central processing unit, and is used to issue an early warning to an operator corresponding to the early warning information according to the early warning information.

2. The system according to claim 1, characterized in that The central processing unit comprises: A data processing module, which is in communication with the data acquisition unit and is used to perform abnormality detection processing on the environmental data and the personnel location data to obtain risk information; A decision module, which communicates with the data processing module and is connected to the early warning unit, is used to generate the early warning information based on the risk information and send the early warning information to the early warning unit.

3. The system according to claim 2, characterized in that The central processing unit also includes: a data storage module, connected to the data processing module, and used to store the environmental data and the personnel location data.

4. The system according to claim 1, characterized in that The system further comprises: A feedback unit is connected to the central processing unit and is used to send feedback information to the central processing unit so that the central processing unit can generate the warning information based on the feedback information.

5. The system according to claim 1, characterized in that The system further comprises: The communication unit is respectively connected to the data acquisition unit and the central processing unit for receiving the environmental data and the personnel position data, and transmitting the environmental data and the personnel position data to the central processing unit.

6. The system according to claim 1, characterized in that The data acquisition unit includes: a temperature sensor, a humidity sensor, an air pressure sensor, an electromagnetic field sensor and an equipment sensor.

7. The system according to claim 1, characterized in that The warning modes of the warning unit include sound and light alarm, SMS notification and mobile application push.

8. A distribution network personal safety early warning method, characterized in that: The method is applied to a central processing unit in a distribution network personal safety early warning system according to any one of claims 1 to 7, and the method comprises: Obtain environmental data and personnel location data corresponding to the target area in the distribution network; The environmental data and the personnel location data are subjected to decision analysis and processing to obtain warning information, and the warning information is sent to the warning unit, so that the warning unit can issue a warning to the operator corresponding to the warning information based on the warning information.

9. The method according to claim 8, characterized in that The performing decision analysis on the environmental data and the personnel location data to obtain early warning information includes: The environmental data and the personnel location data are input into a pre-trained target decision analysis model to obtain the early warning information. The target decision analysis model is obtained by training an initial decision analysis model based on machine learning and historical environmental data and historical personnel location data corresponding to the environmental data and the personnel location data within a historical time interval.

10. The method according to claim 8, characterized in that The method further comprises: receiving feedback information sent by the feedback unit; The early warning information is generated according to the feedback information.

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