Flood monitoring equipment and method and transformer substation

Abstract

The invention discloses flood monitoring equipment, a flood monitoring method and a transformer substation. The equipment comprises a sensor unit, a data processing unit, a power supply unit and a fixing support, the fixing support is used for fixing the flood monitoring equipment, and the power supply unit is used for providing power for the sensor unit and the data processing unit; the sensor unit is used for acquiring environmental data of the transformer substation in real time and transmitting the acquired environmental data to the data processing unit; and the data processing unit is used for processing the environmental data by adopting a built-in AI algorithm to obtain the potential flood risk of the transformer substation. According to the invention, the technical problems of low monitoring precision, poor real-time performance and unstable data transmission caused by the risk monitoring of flood disasters depending on manual observation and simple water level monitoring equipment are solved.

Description

Technical Field

[0001] The present invention relates to the field of electric power, and in particular to flood monitoring equipment, method and substation. Background Art

[0002] Flood disasters have a serious impact on power infrastructure, especially substations. In order to reduce the impact of flood disasters on substations, it is necessary to monitor the risks of flood disasters and issue early warnings to substations to avoid power supply interruptions caused by substation shutdowns. However, the existing technology mainly relies on manual observation and simple water level monitoring equipment to monitor the risks of flood disasters, which has problems such as low monitoring accuracy, poor real-time performance, and unstable data transmission.

[0003] To address the above-mentioned problems, no effective solution has been proposed yet. Summary of the invention

[0004] The embodiments of the present invention provide a flood monitoring device, method and substation to at least solve the technical problems of low monitoring accuracy, poor real-time performance and unstable data transmission caused by relying on manual observation and simple water level monitoring equipment to monitor the risk of flood disasters.

[0005] According to one aspect of an embodiment of the present invention, there is provided a flood monitoring device, comprising: a sensor unit, a data processing unit, a power supply unit and a fixed bracket, wherein the fixed bracket is used to fix the flood monitoring device, and the power supply unit is used to provide power to the sensor unit and the data processing unit; the sensor unit is used to collect environmental data of a substation in real time, and transmit the collected environmental data to the data processing unit; the data processing unit uses a built-in AI algorithm to process the environmental data to obtain a potential flood risk of the substation.

[0006] Optionally, the fixed bracket is a pole, and the pole is used to be fixed on the ground, wherein the sensor unit includes a rain gauge, a temperature and humidity sensor, an atmospheric pressure sensor, a wind direction sensor, a wind speed sensor and a camera installed above the pole, and the sensor unit also includes an electronic water gauge installed below the pole, and the electronic water gauge and the camera are jointly used to monitor the water level of the substation; the data processing unit includes a processor and a memory installed in a control box, and the control box is installed above the pole, and the power supply unit is also installed above the pole.

[0007] Optionally, the rain gauge is a tipping bucket rain gauge, the temperature and humidity sensor and the atmospheric pressure sensor are louvered box all-in-one sensors, and the camera is a dome camera.

[0008] Optionally, the fixed bracket is a tripod, on which the sensor unit, the data processing unit and the power supply unit are fixed, wherein the sensor unit includes an all-in-one waterlogging monitoring machine, the all-in-one waterlogging monitoring machine includes a capacitive sensor and a pressure sensor, the pressure sensor is used to measure the water level based on the sensed pressure, and the capacitive sensor is used to calibrate the water level measured by the pressure sensor.

[0009] Optionally, the flood monitoring device also includes: a communication unit, wherein the communication unit is used to obtain monitoring tasks sent by a remote monitoring center, obtain model update parameters for data processing from the remote monitoring center; and the data processing unit is used to upload processed data to the remote monitoring center.

[0010] According to another aspect of an embodiment of the present invention, a method for flood monitoring using the flood monitoring device is provided, including: using the sensor unit to obtain the environmental data of the substation; controlling the sensor unit to transmit the environmental data to the data processing unit; using the data processing unit to clean the environmental data to obtain cleaned environmental data; using the data processing unit based on an AI algorithm and using the cleaned environmental data to predict flood risks for the substation to obtain potential flood risks of the substation.

[0011] Optionally, the use of the data processing unit to clean the environmental data to obtain cleaned environmental data includes: using a digital filtering algorithm to detect noise in the environmental data, removing the detected noise, and obtaining denoised environmental data; using a clustering algorithm to detect abnormal data in the denoised environmental data, eliminating the abnormal data, and obtaining environmental data after eliminating the abnormal data; using a neural network model to detect data missing bits in the environmental data after eliminating the abnormal data, and interpolating corresponding data at the data missing bits to obtain the cleaned environmental data.

[0012] Optionally, the data processing unit adopts the cleaned environmental data based on the AI ​​algorithm to predict the flood risk of the substation to obtain the potential flood risk of the substation, including: obtaining historical environmental data for a predetermined time period before the current moment; adopting the AI ​​algorithm to predict the flood risk trend of the substation based on the historical environmental data and the cleaned environmental data to obtain the potential flood risk of the substation.

[0013] Optionally, after using the data processing unit to clean the environmental data to obtain the cleaned environmental data, it also includes: packaging the cleaned environmental data to obtain packaged environmental data; encrypting the packaged environmental data to obtain encrypted environmental data; sending the encrypted environmental data to the remote monitoring center, wherein the remote monitoring center is used to determine the final potential flood risk of the substation based on the encrypted environmental data corresponding to the substation and the environmental data of other substations.

[0014] According to another aspect of the present invention, there is provided a substation, comprising: a substation device, and the flood monitoring device.

[0015] In the embodiment of the present invention, an AI algorithm is integrated with fixed flood monitoring technology. Through the efficient collaboration of a high-precision sensor group and the accurate analysis of sensor data by the AI ​​algorithm, comprehensive capture of the environmental data of the substation and accurate monitoring of the flood risk of the substation based on the environmental data of the substation are achieved, thereby achieving the technical effect of accurately warning of flood disasters in the area where the substation is located, and further solving the technical problems of low monitoring accuracy, poor real-time performance and unstable data transmission caused by relying on manual observation and simple water level monitoring equipment for risk monitoring of flood disasters. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0017] Figure 1 is a schematic diagram of a flood monitoring device according to an embodiment of the present invention;

[0018] Figure 2 is a flow chart of a method for performing flood monitoring using the above-mentioned flood monitoring device according to an embodiment of the present invention;

[0019] Figure 3 is a schematic diagram of a fixed flood precision monitoring device based on an AI algorithm according to an optional implementation mode of the present invention;

[0020] Figure 4 It is a schematic diagram of a fixed flood precision monitoring method based on AI algorithm according to an optional implementation mode of the present invention. DETAILED DESCRIPTION

[0021] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0022] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0023] First, some nouns or terms that appear in the description of the embodiments of the present application are subject to the following explanations:

[0024] Density-Based Spatial Clustering ofApplications with Noise (DBSCAN): It is a density-based clustering algorithm that is mainly used to discover clusters of arbitrary shapes and can identify noise points in the data set. Unlike ordinary clustering algorithms, DBSCAN does not require the number of clusters to be specified in advance, but automatically determines the cluster boundaries based on the local density distribution of data points. The key concepts of the DBSCAN algorithm are: neighborhood. For each P in the data set, the concept of neighborhood refers to all points within the neighborhood radius ε, including P itself; core point. If a point's neighborhood contains at least the minimum number of points (MinPts) points (including itself), then the point is considered a core point. The clustering process of DBSCAN mainly includes: selecting an unvisited point in the data set as the starting point and finding all points in its neighborhood. If the number of points in the neighborhood is less than MinPts, the point is marked as a noise point; otherwise, the point is marked as a core point and clustering begins. Add all the boundary points in the neighborhood of the core point to the same cluster, and recursively perform the same process on the neighborhoods of these boundary points until no new points can be added to the cluster. Repeat the above process until all points have been visited and classified as a cluster or noise point.

[0025] Convolutional Neural Network (CNN): A deep learning model specifically designed to process data with grid-structured inputs. CNN has achieved remarkable results in the field of computer vision, especially in tasks such as image recognition, object detection, and image classification. The main components of CNN include: Convolutional layer, which is the core part of CNN. It performs convolution operations by sliding one or more convolution kernels on the input data to detect local features in the input. Convolutional layers can capture local correlations in space and are also translation invariant, which means that CNN can detect these features even if the positions of the input features in the image change. Activation function, nonlinear activation functions are usually applied after convolutional layers to increase the nonlinear expression ability of the network and help the model learn more complex features. Pooling layer, which usually follows the convolutional layer, is used to reduce the spatial size of the feature map, reduce the amount of calculation and the number of parameters, while maintaining important feature information. Common pooling operations include maximum pooling and average pooling. Fully connected layer, usually located at the end of CNN, is used to map the features extracted by the convolutional layer and pooling layer to the classification label and convert them into probability distributions of each category. Through end-to-end learning, CNN can automatically learn the features in the image during training and adjust the weights of the convolution kernel to achieve efficient processing of specific tasks.

[0026] Bidirectional Long Short-Term Memory (BiLSTM): It is a variant of Long Short-Term Memory (LSTM), mainly used for sequence data processing, especially in natural language processing tasks. LSTM is a recurrent neural network that adds gating mechanisms (such as input gate, forget gate, and output gate) to solve the problem of long-term dependency, that is, it can effectively remember and utilize the information in the sequence when processing long sequences. However, traditional LSTM networks can only process sequences sequentially, that is, read information from front to back, which may not be comprehensive in some cases, because future information in the sequence may also have an important impact on the understanding of the current time step. To solve this problem, BiLSTM was introduced, which combines two directional LSTM units, forward LSTM and reverse LSTM. BiLSTM fuses the hidden states of the forward and reverse LSTM at each time step (usually by splicing), so that the complete context information, including past and future context, can be utilized when processing each element in the sequence. This bidirectional information flow can enhance the model’s understanding of sequence semantics and improve prediction and classification accuracy, especially when processing natural language, audio signals, and other time series data.

[0027] Advanced Encryption Standard (AES): is a symmetric encryption algorithm that can be used for data encryption and protection. The AES encryption standard supports key lengths of 128, 192, and 256 bits, corresponding to AES-128, AES-192, and AES-256, respectively. The encryption process of AES mainly includes the following steps: Key expansion, using an algorithm to expand the original key into a series of subkeys, which will be used in subsequent encryption and decryption processes. Initial round, the plaintext is XORed with the first subkey to generate a data block that has been preliminarily processed. Multi-round processing, multiple rounds of fixed operations are performed, including byte substitution, row shift, column mixing, and round key addition. The final round is similar to the multi-round processing, but does not include the column mixing operation, and only includes byte substitution, row shift, and round key addition. Output, the data block after multiple rounds of encryption processing is the ciphertext, which can be securely transmitted in the encrypted channel. The decryption process of AES is the opposite of the encryption process. It uses the same subkey, but the order of operations and the form of certain operations (such as the inverse operation of byte substitution) are adjusted to restore the original plaintext data. The AES encryption standard is suitable for various data encryption needs due to its efficiency, security and flexibility, including network communication, data storage, file encryption and other scenarios. It can provide strong encryption protection while maintaining relatively high efficiency in the encryption and decryption process, and is one of the most popular data encryption algorithms today.

[0028] In the related art, rainstorms and floods may occur frequently, often causing substations (rooms) to be invaded by floods and causing power outages. Rainstorms and floods not only cause the substation (room) to shut down and equipment and facilities to be directly damaged, but more seriously, the substation (room) shutdown causes the interruption of power supply services, which further spreads the flood disaster chain. However, for a long time, due to information barriers and technical barriers, the flood disaster risks faced by substations (rooms) have not been fully understood. At present, the related art mainly relies on manual observation and simple water level monitoring equipment in flood monitoring, and there are problems such as low monitoring accuracy, poor real-time performance, and unstable data transmission. In order to improve the accuracy and real-time performance of flood monitoring and reduce the losses caused by flood disasters, an intelligent, fixed, and accurate flood monitoring device is provided in an embodiment of the present invention.

[0029] According to an embodiment of the present invention, an embodiment of a flood monitoring device is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0030] Figure 1 is a schematic diagram of a flood monitoring device according to an embodiment of the present invention. Figure 1 As shown, the device includes the following parts: a sensor unit 102 , a data processing unit 104 , a power supply unit 106 and a fixing bracket 108 .

[0031] As an optional embodiment, the flood monitoring device is used to monitor the environmental data of the substation, so the flood monitoring device can be placed near the substation. Since the flood situation of the substation is monitored, the flood monitoring device can be placed at a lower level of the substation, so that when the collected data is used to monitor the flood situation of the substation, the monitoring result obtained is more accurate. Among them, the fixed bracket is used to fix the flood monitoring device, that is, the fixed bracket can be placed at the lowest point of the substation. The power supply unit is used to provide power for the sensor unit and the data processing unit; the sensor unit is used to collect the environmental data of the substation in real time and transmit the collected environmental data to the data processing unit; the data processing unit uses the built-in AI algorithm to process the environmental data to obtain the potential flood risk of the substation. Among them, the above-mentioned fixed bracket can be used to fix the equipment at a specified position, including the sensor unit, the data processing unit and the power supply unit, so that the sensor unit, the data processing unit and the power supply unit can normally monitor, process and transmit data even under severe weather conditions, thereby ensuring the stable operation of the equipment.

[0032] The power supply unit can use a variety of power supplies to power the sensor unit and the data processing unit. For example, 220V power supply is suitable for scenes with stable power grid power supply. This power supply mode can provide stable and sufficient power to ensure that the equipment is always running, but backup power supply support is required when the power grid fails. For another example, solar power supply is suitable for outdoor scenes with abundant sunshine. Solar panels can be used to convert solar energy into electrical energy to power the equipment, which can reduce dependence on the external power grid and realize the use of green energy. For another example, battery power supply, a large-capacity battery can meet the continuous working requirements of the equipment without external power supply (such as power grid interruption, insufficient solar energy). In addition, multiple power supply modes can be used in combination to power the sensor unit and the data processing unit, for example, a combination of 220V power supply and battery power supply, and another example, a combination of solar power supply and battery power supply. By combining multiple power supply modes, the stability and flexibility of the power supply can be improved, thereby adapting to various environmental conditions and ensuring that the equipment can operate stably under any circumstances.

[0033] As an optional embodiment, the fixed bracket can adopt different bracket modes according to the different positions where the flood monitoring equipment is placed. For example, when the flood monitoring equipment is placed on the ground, the fixed bracket can be a pole, which is used to be fixed on the ground, wherein the sensor unit includes a rain gauge, a temperature and humidity sensor, an atmospheric pressure sensor, a wind direction sensor, a wind speed sensor and a camera installed above the pole, and the sensor unit also includes an electronic water gauge installed below the pole, and the electronic water gauge and the camera are used to monitor the water level of the substation; the data processing unit includes a processor and a memory installed in a control box, and the control box is installed above the pole, and a power supply unit is also installed above the pole. By fixing the fixed bracket on the ground, the sensor unit, the data processing unit and the power supply unit fixed on the fixed bracket can be placed in a working environment similar to that of the substation, so that the environmental data of the substation can be accurately collected. In addition, there can be more sensors fixed on the bracket on the ground, so that the information that can be collected is also richer, and thus accurate flood disaster warning can be carried out. The sensor unit may include multiple types of sensors, and the sensors are installed at appropriate positions on the fixed bracket according to the data types collected by the sensor. By analyzing the multiple types of environmental data collected by the multiple types of sensors, the environmental data of the substation can be monitored from multiple dimensions to achieve all-round monitoring, so as to more accurately grasp the weather and water level changes around the substation, which is important for preventing flood disasters. The data processing unit is installed in the control box, which can provide a layer of protection for the data processing unit to prevent severe weather such as heavy rain and lightning from affecting the normal operation of the data processing unit.

[0034] As an optional embodiment, the sensor unit may include the following sensors: the rain gauge is a tipping bucket rain gauge, the temperature and humidity sensor and the atmospheric pressure sensor are louvered box type all-in-one sensors, and the camera is a ball camera. Among them, the tipping bucket rain gauge calculates rainfall by tilting and resetting the tipping bucket. When the rainwater accumulation reaches a certain amount, the tipping bucket will tilt, and the rainfall will be recorded through the internal mechanism. Then the tipping bucket will reset and start the next round of measurement. It has a simple design and is easy to maintain, and can provide continuous rainfall data. The louvered box type all-in-one sensor is a louvered box type temperature and humidity sensor and an atmospheric pressure sensor combined into an all-in-one sensor, which can simultaneously monitor environmental parameters such as temperature, humidity and atmospheric pressure. In addition, the louvered box design can effectively prevent direct sunlight and ground reflection, avoid environmental factors from interfering with sensor readings, and ensure the accuracy of measurement. The ball camera is a surveillance camera with a 360-degree panoramic view that can provide all-round video surveillance. The ball camera also has an intelligent zoom function that can clearly capture details of different distances, thereby monitoring rising water levels, expansion of waterlogged areas, and any possible environmental anomalies, such as personnel activities, facility damage, etc.

[0035] As an optional embodiment, when the substation is an indoor substation or a semi-indoor substation, the flood monitoring device is placed indoors or in a closed area with a small space. The fixed bracket can be a tripod, on which a sensor unit, a data processing unit and a power supply unit are fixed, wherein the sensor unit includes an integrated waterlogging monitoring machine, and the integrated waterlogging monitoring machine includes a capacitive sensor and a pressure sensor. The pressure sensor is used to measure the water level based on the sensed pressure, and the capacitive sensor is used to calibrate the water level measured by the pressure sensor. The structure of the tripod utilizes the stability of the triangle, so that the fixed bracket can provide a more stable support for the flood monitoring device. The sensor unit also includes a design of an integrated waterlogging monitoring machine, which can not only monitor waterlogging, but also correct the error of water level measurement, thereby improving the accuracy of monitoring. When part or all of the integrated waterlogging monitoring machine is immersed in water, water, as a substance with a high dielectric constant, will change the capacitance value between the sensor electrodes. The capacitive sensor can quickly respond to water level changes in the case of non-contact measurement, reducing mechanical wear and maintenance requirements. In addition, the device starts to trigger measurement when it starts to be immersed in water, so that even a small amount of accumulated water can be monitored in time. After the device is completely submerged in water, the sensitive elements inside the pressure sensor can sense the change in water pressure and calculate the depth of the water. It is more stable in deep water or high water pressure conditions and has a wider measurement range. The all-in-one waterlogging monitoring device combines capacitive sensors and pressure sensors to accurately measure water levels in environments with both small and large amounts of water.

[0036] As an optional embodiment, the flood monitoring device also includes: a communication unit, wherein the communication unit is used to obtain the monitoring tasks sent by the remote monitoring center and obtain the model update parameters for data processing from the remote monitoring center; and the data processing unit is used to upload the processed data to the remote monitoring center. Through wireless communication technology, the flood monitoring device can interact with the remote monitoring center in real time, not only can it upload monitoring data in a timely manner, and the remote monitoring center can predict flood disasters based on the monitoring data, but it can also receive the model update parameters for data processing, and realize the prediction of flood disasters at the flood monitoring device end, that is, the substation. By establishing communication between the flood monitoring device and the remote monitoring center through the communication unit, it is also possible to combine the predictions of the flood disasters by the two to obtain the final prediction results, thereby improving the accuracy of risk prediction.

[0037] It should be noted that, by using the communication unit, the flood monitoring device can not only upload the processed data to the remote monitoring center, but also obtain the required data from the remote monitoring center. For example, the flood monitoring device can obtain the model update parameters used for model training of the flood monitoring device from the remote monitoring center, and can obtain the flood prediction results obtained by the remote monitoring center based on the data obtained from each flood monitoring device. Among them, after the flood monitoring device receives the flood prediction results transmitted by the remote monitoring center, it can obtain the final flood monitoring results based on the monitoring results calculated based on the data collected by itself and the flood prediction results transmitted by the remote monitoring center. For example, the flood prediction results transmitted by the remote monitoring center can be used to correct and revise the monitoring results calculated by the flood monitoring device.

[0038] According to an embodiment of the present invention, an embodiment of a method for performing flood monitoring using the above-mentioned flood monitoring device is provided. Figure 2 FIG. 1 is a flow chart of a method for performing flood monitoring using the flood monitoring device according to an embodiment of the present invention. Figure 2 As shown, the method comprises the following steps:

[0039] Step S202: using a sensor unit to obtain environmental data of the substation.

[0040] As an optional embodiment, the execution subject of the method of this embodiment may be a device for flood monitoring, and the above-mentioned device may be used for collecting, processing and transmitting environmental data of a substation.

[0041] As an optional embodiment, when using a sensor unit to obtain environmental data of a substation, multiple types of sensors can be used to collect multiple types of environmental data to achieve all-round monitoring of the substation. For example, a rainfall sensor, a temperature and humidity sensor, an atmospheric pressure sensor, a wind speed and direction sensor, a video device, a water level sensor, etc. can be used to collect environmental data.

[0042] Step S204: Control the sensor unit to transmit the environmental data to the data processing unit.

[0043] As an optional embodiment, the control sensor unit transmits the environmental data to the data processing unit, which can not only realize the collection of environmental data of the substation, but also immediately process and analyze the environmental data to quickly obtain flood disaster prediction results.

[0044] Step S206: clean the environmental data using a data processing unit to obtain cleaned environmental data.

[0045] As an optional embodiment, when the data processing unit is used to clean the environmental data, multiple cleaning operations can be performed. For example, a digital filtering algorithm is used to detect the noise in the environmental data, remove the noise, and obtain the denoised environmental data; a clustering algorithm is used to detect the abnormal data in the denoised environmental data, remove the abnormal data, and obtain the environmental data after the abnormal data is removed; a neural network model is used to detect the data missing bits in the environmental data after the abnormal data is removed, and the corresponding data is interpolated at the data missing bits to obtain the cleaned environmental data. By using a variety of AI algorithms to denoise, remove outliers, and interpolate missing values ​​for environmental data, not only can the data quality be effectively improved, but also the processing efficiency is high. It can effectively reduce data errors caused by environmental interference or equipment failure, especially for substations working in various complex environments, and can ensure the accuracy of flood risk prediction.

[0046] Step S208, using the data processing unit based on the AI ​​algorithm and the cleaned environmental data to predict the flood risk of the substation, and obtain the potential flood risk of the substation.

[0047] As an optional embodiment, when a data processing unit is used to predict the flood risk of a substation based on the cleaned environmental data based on an AI algorithm, the prediction can be made based only on the real-time cleaned environmental data, or it can be made based on a combination of historical environmental data and real-time environmental data. By combining historical environmental data with real-time environmental data, the AI ​​algorithm can learn more information about the surrounding environment of the substation, thereby making more accurate judgments. Specifically, historical environmental data for a predetermined time period before the current moment can be obtained; an AI algorithm is used to predict the flood risk trend of the substation based on the historical environmental data and the cleaned environmental data, and the potential flood risk of the substation is obtained. By combining the historical data and real-time data of the substation, the AI ​​algorithm can more accurately predict the potential flood risk of the substation, provide a scientific basis for the flood prevention and control management of the substation, and especially in flood-prone seasons, can provide early warnings and reduce the losses of power facilities in the substation.

[0048] As an optional embodiment, after using a data processing unit to clean the environmental data and obtain the cleaned environmental data, the cleaned environmental data can also be encapsulated to obtain encapsulated environmental data; the encapsulated environmental data is encrypted to obtain encrypted environmental data; the encrypted environmental data is sent to the remote monitoring center, and the remote monitoring center determines the final potential flood risk of the substation based on the encrypted environmental data corresponding to the substation and the environmental data of other substations. By sending the environmental data of the substation to the remote monitoring center, the remote monitoring center can combine the data of multiple substations in a certain area, use larger-scale processors and more complex AI algorithms, and obtain more accurate flood risk predictions. Data encapsulation and encryption can protect the security of data and prevent data from being tampered with or stolen during transmission. It is suitable for power systems with high requirements for data security to ensure the integrity and confidentiality of monitoring data.

[0049] Through the above steps, intelligent monitoring and early warning of substation flood risks can be achieved, effectively preventing and reducing the impact of flood disasters on power facilities, and ensuring the safe and stable operation of the power system. At the same time, the modular design of the equipment and the integration of the communication unit make the monitoring system easy to deploy and maintain, enhance the flexibility and reliability of the system, and bring significant efficiency improvements and cost savings to the flood prevention work of the power industry. Especially in extreme weather conditions, it can still stably achieve intelligent monitoring and early warning of substation flood risks.

[0050] In combination with the above embodiment and the optional embodiment, an optional implementation is provided. In this optional implementation, a fixed flood precision monitoring device based on an AI algorithm is proposed, aiming to solve the problems of low flood monitoring accuracy and poor real-time performance in related technologies. Figure 3 is a schematic diagram of a fixed flood precision monitoring device based on an AI algorithm according to an optional implementation mode of the present invention, such as Figure 3 shown.

[0051] The device comprises a sensor unit, a data processing unit, a communication unit, a power supply unit and a fixing bracket.

[0052] The sensor unit includes a rainfall sensor, a temperature and humidity sensor, an atmospheric pressure sensor, a wind speed and direction sensor, a video device, and a water level sensor, which are used to collect environmental data such as water level, rainfall, and flow rate in real time.

[0053] Among them, the rainfall sensor can be a tipping bucket rain gauge, the tipping bucket can be of three-dimensional streamlined design, and is designed with a drooping arc-shaped guide tip, which has a beautiful and smooth shape, better water-turning performance and is easy to clean and maintain.

[0054] Among them, the temperature and humidity sensor and the atmospheric pressure sensor can use a louvered box type all-in-one sensor. The function of the louvered box is to prevent the direct radiation of the sun to the instrument and the back radiation of the ground to the instrument, protect the instrument from strong winds, rain, snow, etc., and allow the sensor part to have proper ventilation, so that it can truly sense changes in the external air temperature, humidity, atmospheric pressure and other environments.

[0055] Among them, the wind speed and direction sensor can be a device used to measure wind speed and wind direction. The wind speed and direction sensor can use a polycarbonate shell heat-resistant and wind-resistant sensor with a polycarbonate shell. This material exhibits excellent temperature resistance and can withstand both high and low temperatures. The material has no deformation and the strength is stable. As an excellent thermoplastic engineering plastic, it can resist weathering for a long time, has outstanding impact resistance, exhibits good creep resistance, and ensures dimensional stability.

[0056] Among them, the video equipment camera can choose a ball camera, which uses a 4-megapixel camera and intelligent zoom 360° panoramic monitoring without blind spots. It can monitor both the water level and the waterlogged area.

[0057] Among them, in the scenario of outdoor substations on the ground, the water level sensor selects a combination of water level video recognition equipment and electronic water gauge to monitor the water level. In semi-underground substations (rooms), underground substations (rooms) or places with small spaces, an integrated waterlogging monitoring machine is selected. The integrated waterlogging monitoring machine adopts a capacitance and pressure dual sensor working mode. The pressure sensor data is calibrated through the capacitive sensor measurement data to ensure the accuracy of the water level data. When the device begins to be immersed in water, the capacitive sensor begins to trigger for measurement. When the device is completely immersed in water, it mainly relies on the pressure sensor for measurement. The integrated waterlogging monitoring machine adopts a contactless isolation measurement method, which effectively eliminates the influence of accumulated water pollutants, silt, etc. on the measurement.

[0058] The electronic water gauge uses an advanced processor chip as a controller. It measures the water level of the electrode to obtain water level data. It has extremely high accuracy and strong anti-interference ability. The electronic water gauge adopts advanced production technology and uses stainless steel as a protective shell. It has excellent protection performance and anti-interference ability. Since the sampling accuracy is independent of the water gauge length of the equipment, it can maintain extremely high measurement accuracy in any application environment, with a measurement accuracy of 1cm. It can be used to monitor water levels in water conservancy projects such as rivers, lakes, reservoirs, hydropower stations, irrigation areas and water transfer. It can also be used to monitor water levels in municipal projects such as tap water, urban sewage treatment, and urban road waterlogging.

[0059] The data processing unit includes a microprocessor and a memory, and is used to receive, process and store the data collected by the sensor unit.

[0060] Among them, the data processing unit has a variety of communication interfaces, including RS485, TCP, LORA, 4G, satellite expansion communication, etc., and must also have the function of processing video.

[0061] The microprocessor uses a high-performance, low-power microprocessor with fast data processing capabilities, which can realize data fusion and analysis of multiple sensors. It mainly stores, displays, alarms and transmits information such as water level, rainfall, wind speed, and weather, senses and fuses multi-source heterogeneous information such as water level, rainfall, wind speed, and weather in substations, and uploads it to the application center in real time through the Internet of Things technology.

[0062] Among them, the memory provides a large-capacity storage space for storing historical monitoring data and system operation logs, which is convenient for subsequent data analysis and troubleshooting.

[0063] The communication unit provides a communication mode combining multiple communication means for the flood precision monitoring equipment, including internal communication network, 4G wireless communication and satellite communication, etc., to ensure information transmission under different circumstances. It includes a wireless communication module for transmitting processed data to the remote monitoring center.

[0064] Among them, in normal mode, the communication unit uses the internal network to transmit information, for example, when the substation has an internal network; when the substation does not have an internal network, a combination of 4G communication and the internal network is used to transmit information.

[0065] In emergency mode, when both the internal network and 4G communication fail, satellite communication is used for emergency communication. Beidou short message 4G full network transmission terminal is selected to realize emergency communication.

[0066] The power supply unit can use different power supply modules in different scenarios. In the outdoor substation scenario, when there is 220V power supply, you can choose to use the power supply method that combines the existing 220V power supply in the station room with the energy storage battery to power the equipment to ensure the safety of the equipment power supply. After the 220V power supply is interrupted, the built-in energy storage battery of the equipment can ensure the normal use of the equipment for 3 days. In the outdoor substation scenario, when there is no 220V power supply, you can choose to use the power supply method that combines solar energy and energy storage batteries to power the equipment to ensure the safety of the equipment power supply. After the solar power supply is interrupted, the built-in energy storage battery of the equipment can ensure the normal use of the equipment for 3 days.

[0067] In the above-ground indoor substation (room) or underground substation (room) scenario, you can choose to use the existing 220V power supply in the station room combined with the energy storage battery to power the equipment to ensure the safety of the equipment power supply. After the 220V power supply is interrupted, the built-in energy storage battery of the equipment can ensure the normal use of the equipment for 3 days.

[0068] In scenarios where it is inconvenient to use 220V and solar power supply, the device can be powered by its own battery. The built-in battery self-powered mode can work continuously for more than 1 year on a single charge.

[0069] Among them, the solar panel uses a high-efficiency solar panel, which can provide a certain amount of power for the equipment even in rainy weather.

[0070] Among them, the energy storage battery is equipped with a large-capacity energy storage battery to ensure that the equipment can still operate normally under continuous rainy or night conditions.

[0071] The fixed bracket is used to fix the equipment in the specified position to ensure stable operation of the equipment. The fixed bracket is made of high-strength, corrosion-resistant materials and is suitable for various harsh environments. The bracket is designed as a detachable structure, which is convenient for quick installation and disassembly in complex terrain.

[0072] In summary, the sensor unit is responsible for real-time collection of multi-dimensional data, including water level sensors that monitor water levels through ultrasonic pulses or water pressure changes, tipping bucket rain gauges that calculate rainfall, flow rate sensors that measure water flow speed, and temperature and humidity sensors and atmospheric pressure sensors that collect environmental parameters. In addition, high-definition cameras perform video monitoring, and wind speed and direction sensors measure wind speed and direction to ensure that comprehensive and accurate flood monitoring data is obtained. After receiving the sensor data, the data processing unit performs signal conversion, digital filtering, and data fusion to eliminate noise and improve data quality. Subsequently, through in-depth analysis of the fused data, trend analysis, threshold judgment, and pattern recognition are performed to identify potential flood risks and generate early warning information. At the same time, a large-capacity memory records historical monitoring data and system operation logs to provide support for subsequent analysis and maintenance. The communication unit encapsulates the processed data into data packets containing necessary information and uses the AES encryption standard to ensure transmission security. The data packets are sent to the remote monitoring center through a variety of communication methods (such as RS485, TCP, LORA, 4G, and satellite communication) to achieve reliable data transmission. In normal mode, the internal network or 4G communication is used first, and in emergency mode, the Beidou short message 4G full network transmission terminal is enabled to ensure the stability and security of data transmission. The power supply unit selects the appropriate power supply method according to different scenarios, such as 220V power supply + energy storage battery, solar energy + energy storage battery or the device's own battery. The solar panel is equipped with MPPT technology to improve energy conversion efficiency. The energy storage battery powers the device when the power supply is insufficient, and is equipped with a battery management system to monitor the battery status, balance charging and discharging, and prevent overcharging and over-discharging. The power supply unit provides stable power for the entire system to ensure continuous and efficient operation of the equipment.

[0073] By using the above-mentioned fixed flood precision monitoring equipment based on AI algorithm, when the water level, rainfall or flow rate is detected to exceed the set threshold, the equipment can automatically trigger the early warning system and notify relevant personnel through sound and light alarms or text messages.

[0074] The above-mentioned fixed flood precision monitoring equipment based on AI algorithm can also use big data and artificial intelligence technology to conduct in-depth analysis of historical monitoring data, predict flood disaster trends, and provide a scientific basis for flood control decisions.

[0075] In this optional implementation, a fixed flood precision monitoring method based on AI algorithm is proposed. Figure 4 is a schematic diagram of a fixed flood precision monitoring method based on an AI algorithm according to an optional implementation mode of the present invention, such as Figure 4 As shown, the method includes the following processing.

[0076] S0, system architecture construction, first design the middle platform bridge data system, which is responsible for real-time reception, processing, storage and analysis of station data, following the data processing process: receiving sensor data, decoding raw data into a readable format, and storing it in the database. At the same time, deploy the AI ​​algorithm management platform, which covers model selection and deployment, parameter debugging to optimize performance, model testing and verification, and model upgrade and distribution to monitoring sites to ensure the effectiveness and continuous optimization of the AI ​​model.

[0077] S1, sensor units are used to collect water level, rainfall and flow rate data in real time. During the sensor deployment phase, various sensors such as water level, rainfall, and flow rate sensors are installed to collect hydrological data in real time.

[0078] S2, using the data processing unit to process the collected data in real time. During the data reception and conversion process, the microprocessor converts the electrical signals collected by the sensor into digital signals for further processing. Subsequently, a digital filtering algorithm (such as sliding mean filtering) is used to remove signal noise and improve data quality. The calculation formula of the sliding mean filtering algorithm is as follows:

[0079]

[0080] Where y[n] is the output signal after filtering. N is the size of the sliding window. x[ni] is the original signal.

[0081] Among them, the application of AI algorithms includes the deployment of multiple models, such as water level recognition, water accumulation area recognition, personnel intrusion recognition, fireworks recognition, personnel off-duty monitoring and face recognition, to achieve accurate hydrological monitoring and safety management.

[0082] Next, data cleaning and optimization are performed. Clustering algorithms such as DBSCAN are used to detect and remove abnormal data. Among them, the key parameters of DBSCAN are: ε (neighborhood radius): determine the neighborhood around a point; MinPts (minimum number of points): define the minimum number of neighborhood points of a core point.

[0083] The CNN-BiLSTM-Attention model is used to interpolate missing data. The convolutional layer formula is:

[0084]

[0085] Where w is the convolution kernel weight, b is the bias, and σ is the activation function.

[0086] The formula of BiLSTM is as follows:

[0087]

[0088] In the formula, is the forward hidden state, is the reverse hidden state.

[0089] S3, data analysis and early warning judgment. The microprocessor integrates, analyzes and judges the trends of the collected multi-source data, and uses AI algorithms to accurately warn of potential flood risks, providing timely and accurate information support for flood prevention and disaster reduction.

[0090] S4, the communication unit prepares for data transmission. The processed data is encapsulated into data packets containing necessary information, and encryption standards such as AES are used to ensure transmission security.

[0091] S5, the communication unit transmits data to the remote monitoring center. Finally, the data packet is sent to the remote monitoring center through the wireless communication module to achieve reliable data transmission and storage.

[0092] By innovatively integrating AI algorithms with fixed flood monitoring technology, and relying on the efficient collaboration of high-precision sensor groups, the accurate capture and monitoring of flood-related data can be achieved, greatly enhancing the reliability of the flood warning system. Its advanced real-time data transmission mechanism ensures that the flood control command center can quickly and accurately obtain disaster information, so as to respond in a timely manner, significantly reduce the losses caused by disasters, and achieve rapid rescue in emergency situations, greatly improving rescue efficiency. The fixed layout strategy of the equipment effectively achieves full coverage of key areas, establishes a robust regional monitoring network, and provides strong support for regional joint prevention and control. By adopting a composite energy system of solar power supply and energy storage batteries, the equipment can still maintain stable operation under extreme climatic conditions, ensuring the continuity and integrity of monitoring data. The structural design of the equipment is simple and modular, which not only reduces the complexity and cost of maintenance and prolongs the service life, but also makes the operation easier. Even non-professionals can easily get started, greatly improving the popularity and practical value of the equipment.

[0093] In combination with the above-mentioned embodiment and the optional embodiment, an optional embodiment of a flood monitoring system for an above-ground outdoor substation is provided.

[0094] In order to effectively monitor flooding conditions at a certain outdoor substation, the following fixed flood monitoring solution is implemented:

[0095] 1. Monitoring site selection and bracket installation.

[0096] In the low-lying area of ​​the substation, a suitable monitoring point is selected, which can representatively reflect the flooding conditions in the substation area. In addition, based on the determined flooding conditions, the lowest position for placing the power equipment inside the substation can be effectively determined so that the power equipment will not suffer from flooding disasters.

[0097] At the selected location, a stable pole support is installed to ensure that it can withstand strong winds and corrosion and can be firmly fixed to the ground. The design of the support takes into account the needs of solar radiation to ensure energy supply.

[0098] 2.Sensor unit and smart terminal installation.

[0099] Rain gauges, temperature and humidity sensors, atmospheric pressure sensors, wind direction sensors, wind speed sensors and cameras are installed on the poles to collect environmental data in real time.

[0100] An electronic water gauge is installed below the pole to accurately monitor water level changes.

[0101] A monitoring intelligent terminal is installed in the control box of the pole, which is connected to the sensor through RS485 and LoRa communication methods to collect data in real time. It also uses the built-in AI algorithm to process video data and extract water level and water accumulation area information.

[0102] 3. Data processing and communication unit installation.

[0103] The monitoring intelligent terminal transmits the processed data to the application platform and operation and maintenance platform via 4G communication.

[0104] The application platform is responsible for data storage, query, visualization, statistical analysis, early warning and alarm functions.

[0105] The operation and maintenance platform is used to monitor and maintain monitoring equipment to ensure stable operation of the system.

[0106] 4. Power supply unit installation and line connection.

[0107] Solar panels and energy storage batteries are installed on the bracket, with the panels facing the direction of sufficient sunlight to maximize energy collection efficiency.

[0108] According to the design drawings, correctly connect the lines between the sensor unit, data processing unit, communication unit and power supply unit, and perform insulation treatment to ensure reliable connection.

[0109] 5. Equipment configuration and calibration.

[0110] After the device is started, initial configuration and calibration are performed, including setting monitoring parameters, alarm thresholds, and data transmission frequency, etc., to ensure the accuracy of the sensor output data.

[0111] 6. Normal operation and data transmission.

[0112] After the equipment enters normal operation, it starts to collect water level, rainfall and flow rate data in real time. The data processing unit processes the data and sends the data to the remote monitoring center through the communication unit. The power supply unit provides continuous and stable power to the equipment to ensure stable operation of the equipment under all-weather conditions.

[0113] Through the above implementation steps, the flood situation in the substation area can be effectively monitored, providing important technical support for flood prevention and disaster reduction.

[0114] According to an embodiment of the present invention, a substation is provided, comprising: a substation device and a flood monitoring device, wherein the substation device may be one or more, and the one or more substation devices are located in the substation.

[0115] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0116] In the above embodiments of the present invention, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0117] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of the units can be a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0118] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0119] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0120] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk and other media that can store program codes.

[0121] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A flood monitoring device, characterized in that: include: A sensor unit, a data processing unit, a power supply unit and a fixing bracket, wherein the fixing bracket is used to fix the flood monitoring device, and the power supply unit is used to provide power for the sensor unit and the data processing unit; The sensor unit is used to collect environmental data of the substation in real time and transmit the collected environmental data to the data processing unit; The data processing unit uses a built-in AI algorithm to process the environmental data to obtain the potential flood risk of the substation.

2. The flood monitoring device according to claim 1, characterized in that: The fixing bracket is a vertical pole, and the vertical pole is used to be fixed on the ground, wherein: The sensor unit includes a rain gauge, a temperature and humidity sensor, an atmospheric pressure sensor, a wind direction sensor, a wind speed sensor and a camera installed above the pole, and the sensor unit also includes an electronic water gauge installed below the pole, and the electronic water gauge and the camera are used together to monitor the water level of the substation; The data processing unit includes a processor and a memory installed in a control box. The control box is installed above the vertical pole. The power supply unit is also installed above the vertical pole.

3. The flood monitoring device according to claim 2, characterized in that: The rain gauge is a tipping bucket rain gauge, the temperature and humidity sensor and the atmospheric pressure sensor are shutter box type all-in-one sensors, and the camera is a ball camera.

4. The flood monitoring device according to claim 1, characterized in that: The fixed bracket is a tripod, on which the sensor unit, the data processing unit and the power supply unit are fixed, wherein the sensor unit includes an all-in-one waterlogging monitoring machine, and the all-in-one waterlogging monitoring machine includes a capacitive sensor and a pressure sensor, the pressure sensor is used to measure the water level based on the sensed pressure, and the capacitive sensor is used to calibrate the water level measured by the pressure sensor.

5. The flood monitoring device according to any one of claims 1 to 4, characterized in that: The flood monitoring device also includes: a communication unit, wherein the communication unit is used to obtain monitoring tasks sent by a remote monitoring center, obtain model update parameters for data processing from the remote monitoring center; and the data processing unit is used to upload processed data to the remote monitoring center.

6. A method for flood monitoring using the flood monitoring device according to any one of claims 1 to 5, characterized in that: include: Acquiring the environmental data of the substation using the sensor unit; Controlling the sensor unit to transmit the environmental data to the data processing unit; Using the data processing unit to clean the environmental data to obtain cleaned environmental data; The data processing unit is used to predict the flood risk of the substation based on the AI ​​algorithm and the cleaned environmental data to obtain the potential flood risk of the substation.

7. The method according to claim 6, characterized in that The step of using the data processing unit to clean the environmental data to obtain cleaned environmental data includes: Using a digital filtering algorithm to detect noise in the environmental data, removing the detected noise, and obtaining denoised environmental data; Using a clustering algorithm to detect abnormal data in the denoised environmental data, removing the abnormal data, and obtaining environmental data after removing the abnormal data; A neural network model is used to detect data missing bits in the environmental data after the abnormal data is removed, and corresponding data is interpolated at the data missing bits to obtain the cleaned environmental data.

8. The method according to claim 6, characterized in that The data processing unit uses the cleaned environmental data based on the AI ​​algorithm to predict the flood risk of the substation to obtain the potential flood risk of the substation, including: Obtain historical environmental data for a predetermined period of time before the current moment; The AI ​​algorithm is used to predict the flood risk trend of the substation based on the historical environmental data and the cleaned environmental data to obtain the potential flood risk of the substation.

9. The method according to claim 6, characterized in that After the environmental data is cleaned by the data processing unit to obtain the cleaned environmental data, the method further includes: Encapsulating the cleaned environmental data to obtain encapsulated environmental data; Encrypting the packaged environmental data to obtain encrypted environmental data; The encrypted environmental data is sent to the remote monitoring center, wherein the remote monitoring center is used to determine the final potential flood risk of the substation based on the encrypted environmental data corresponding to the substation and environmental data of other substations.

10. A substation, characterized in that: include: A power transformation device, and the flood monitoring device as claimed in any one of claims 1 to 5.

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