High-voltage electrical equipment monitoring Internet of Things platform based on multiple IEDs

Abstract

The invention provides a high-voltage electrical equipment monitoring Internet of Things platform based on a multi-element IED, which comprises a monitoring Internet of Things system and monitoring equipment, the monitoring equipment comprises a multi-element IED and a physical sensor, the multi-element IED comprises an acquisition unit and a parallel computing device, and the physical sensor comprises a digital quantity sensor and an analog quantity sensor. The analog quantity sensors with the same configuration are connected to the same acquisition unit, only the physical sensors need to be inserted into the interfaces of the corresponding acquisition unit and the parallel computing equipment, and compared with the prior art, monitoring of a plurality of indexes can be carried out at the same time. The parallel computing device can process the operation parameters of the multiple physical sensors in a unified mode, and the phenomenon that in the prior art, data self-isolated islands are formed among all systems is avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of the Internet of Things, and particularly relates to an Internet of Things platform for monitoring high-voltage electrical equipment based on multiple IEDs. Background Art

[0002] With the continuous improvement of the intelligence level of high-voltage electrical equipment, high-voltage electrical equipment is usually equipped with multiple sets of electrical on-line monitoring platforms such as SF6, main transformer high-voltage bushings, main transformer oil chromatography, GIS partial discharge, and cable insulation monitoring. These electrical on-line monitoring systems usually use sensors for monitoring and finally display on the upper computers of their respective systems.

[0003] Since the existing electrical on-line monitoring platforms are always custom-developed based on a certain monitoring index or multiple monitoring indexes, the functions of each system are single, and the data between each system forms its own isolated island. Summary of the Invention

[0004] In view of this, the present invention provides an Internet of Things platform for monitoring high-voltage electrical equipment based on multiple IEDs to solve the problems.

[0005] The present invention provides an Internet of Things platform for monitoring high-voltage electrical equipment based on multiple IEDs, including an Internet of Things monitoring system and monitoring devices. The monitoring devices include multiple IEDs and physical sensors. Among them, the multiple IEDs include an acquisition unit and a parallel computing device, and the physical sensors include digital sensors and analog sensors;

[0006] The acquisition unit is divided into an analog acquisition unit group and a digital acquisition unit group. Among them, the analog sensors are connected to the parallel computing device through the analog acquisition unit group, and the digital sensors are connected to the parallel computing device;

[0007] The acquisition units in the analog acquisition unit group are configured through an analog acquisition unit strategy:

[0008] According to the configuration of the analog sensors, analog acquisition units that meet the performance requirements of the analog sensors are selected, and the configurations of the analog sensors connected to the same acquisition unit are the same;

[0009] The physical sensors are respectively connected to the interfaces of the acquisition unit and the parallel computing device in a plug-and-play manner, and the Internet of Things monitoring system respectively defines the data types of the acquisition unit and the parallel computing device interfaces.

[0010] Further, the Internet of Things monitoring system performs parameter modeling on the physical sensors to obtain corresponding sensor models.

[0011] Further, pulse sensors are connected to the parallel computing device through the digital acquisition unit group;

[0012] The digital quantity acquisition units in the digital quantity acquisition unit group are configured through the digital quantity acquisition unit strategy:

[0013] According to the configuration of the pulse type sensor, select the digital quantity acquisition unit that meets the performance requirements of the pulse type sensor, and the configurations of the pulse type sensors connected to the same acquisition unit are the same.

[0014] Further, the analog quantity acquisition unit strategy adopts the strategy function F( , b), and the strategy function F( , b) is:

[0015] F( , b) = ( , , );

[0016] Among them, = k ×

[0017] = × b

[0018] = / η

[0019] Among them, : Sensor sampling rate, unit Hz;

[0020] b: Number of bits of data generated by each sensor sampling, unit bit;

[0021] : CPU main frequency required by the acquisition unit, which is the computing power required to process sensor data, unit Hz;

[0022] : Data transmission rate, which is the rate at which data is transmitted from the acquisition unit to the storage or parallel computing device, unit bps;

[0023] : Pin data processing speed, which is the speed at which the data interface of the acquisition unit processes data, unit bps;

[0024] Transmission rate calculation formula:

[0025] = × b

[0026] Among them, sample times per second, generate b bits of data for each sampling, and the total amount of data transmitted per second is bps;

[0027] CPU main frequency calculation formula:

[0028] = k ×

[0029] where k is the number of CPU cycles required for each sampling and depends on the complexity of data processing; is the sampling rate, with the unit of Hz;

[0030] Pin data processing speed calculation formula:

[0031] = / η

[0032] where is the total transmission rate; η is the transmission efficiency.

[0033] Furthermore, between the acquisition unit and the parallel computing device, or between the digital quantity sensor and the parallel computing device, data is transmitted through a communication protocol, and the communication protocol includes one or more of TCP / UDP, MODBUS, MQTT, and IEC61850.

[0034] Furthermore, nodes are provided in the physical sensor, the acquisition unit, and the parallel computing device, and the monitoring Internet of Things system defines the standard interfaces for data access and output of each node.

[0035] Furthermore, the monitoring Internet of Things system records the input and output data of each node, forms a complete data processing link, monitors the operating status of each node in real time, and triggers an alarm when an abnormality or failure occurs.

[0036] Furthermore, the monitoring Internet of Things system includes:

[0037] An acquisition component, used to access the physical sensor and perform signal sampling and oscillogram recording on the physical sensor;

[0038] A function component, used to process the physical sensor signals sampled and recorded by the acquisition unit;

[0039] A network component, used to distribute and report the physical sensor signals;

[0040] A storage component, used to store the physical sensor signals.

[0041] Furthermore, the monitoring Internet of Things system further includes:

[0042] A process choreography component, used to choreograph the acquisition component, the function component, the network component, and the storage component through a graphical user interface.

[0043] Further, it also includes a usage method of the Internet of Things platform for monitoring high-voltage electrical equipment based on multiple IEDs, including the following steps:

[0044] Select an IED based on the communication protocol of the physical sensor and complete the wiring;

[0045] Select or add a sensor model on the graphical interaction interface;

[0046] Use the graphical interaction interface for process choreography;

[0047] View the operating status and signal output of the node.

[0048] Beneficial effects:

[0049] According to the configuration of the analog sensors, this application selects an analog acquisition unit that meets the performance requirements of the analog sensors, and the configurations of the analog sensors connected to the same acquisition unit are the same. The physical sensors are respectively connected to the interfaces of the acquisition unit and the parallel computing device in a plug-and-play manner, and the monitoring Internet of Things system defines the data types of the acquisition unit and the parallel computing device interface respectively. When in use, analog sensors with the same configuration are connected to the same acquisition unit, and only need to insert the physical sensors into the corresponding interfaces of the acquisition unit and the parallel computing device. Compared with the prior art, this application can monitor multiple indicators simultaneously. The parallel computing device can uniformly process the operating parameters of multiple physical sensors, avoiding the problem that the data of each system forms an isolated island in the prior art. Description of the drawings

[0050] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following will briefly introduce the drawings required for use in the description of the specific embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0051] Figure 1 It is the connection diagram of the monitoring device in the embodiment of the present invention;

[0052] Figure 2 It is the structural schematic diagram of the embodiment of the present invention;

[0053] Figure 3 It is the schematic diagram of the graphical interaction interface in the embodiment of the present invention. Specific embodiments

[0054] To make the objectives, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0055] The embodiments of the present invention will be described below with reference to Figures 1 to 3 .

[0056] The present invention provides an Internet of Things platform for monitoring high-voltage electrical equipment based on multiple IEDs, including a monitoring Internet of Things system and monitoring devices. The monitoring devices include multiple IEDs and physical sensors. Among them, the multiple IEDs include an acquisition unit and a parallel computing device, and the physical sensors include digital quantity sensors and analog quantity sensors.

[0057] The acquisition unit is divided into an analog quantity acquisition unit group and a digital quantity acquisition unit group. Among them, the analog quantity sensors are connected to the parallel computing device through the analog quantity acquisition unit group, and the digital quantity sensors are connected to the parallel computing device.

[0058] The acquisition units in the analog quantity acquisition unit group are configured through an analog quantity acquisition unit strategy:

[0059] According to the configuration of the analog quantity sensors, analog quantity acquisition units that meet the performance requirements of the analog quantity sensors are selected, and the configurations of the analog quantity sensors connected to the same acquisition unit are the same.

[0060] The physical sensors are respectively connected to the interfaces of the acquisition unit and the parallel computing device in a pluggable manner, and the monitoring Internet of Things system defines the data types of the interfaces of the acquisition unit and the parallel computing device respectively. Acquisition units with different configurations can be connected to analog quantity sensors with different configurations, and acquisition units with the same configuration can be connected to analog quantity sensors with the same configuration, making the Internet of Things platform for monitoring high-voltage electrical equipment of the present application have better compatibility than the prior art.

[0061] According to the configuration of the analog sensor, this application selects an analog acquisition unit that meets the performance requirements of the analog sensor, and the configurations of the analog sensors connected to the same acquisition unit are the same. The physical sensors are respectively connected to the interfaces of the acquisition unit and the parallel computing device in a plug-and-play manner, and the monitoring Internet of Things system defines the data types of the acquisition unit and the parallel computing device interface respectively. When in use, analog sensors of the same configuration are connected to the same acquisition unit, and only need to insert the physical sensors into the corresponding interfaces of the acquisition unit and the parallel computing device. Compared with the prior art, this application can monitor multiple indicators simultaneously. The parallel computing device can uniformly process the operating parameters of multiple physical sensors, avoiding the problem that the data of each system forms an isolated island in the prior art.

[0062] It should be noted that: Digital sensors and analog sensors have great differences in data types, signal processing, and transmission methods. It is precisely these differences that result in the fact that the data transmission of digital sensors does not require an acquisition unit, while analog sensors need an acquisition unit to be connected to a parallel computing device. Specifically, digital sensors usually output digital signals, that is, there are only two possible states, such as "on / off" or "1 / 0", which usually represent "switching quantity" data (such as whether the temperature exceeds a certain threshold, whether the door is open or closed, etc.). The advantage of digital signals is that they are simple and easy to understand, and can directly send data to the parallel computing device through serial communication (such as RS-232, RS-485), Ethernet, or even wireless protocols (such as Wi-Fi, ZigBee, etc.), usually without complex signal processing and conversion. Therefore, digital sensors can be directly connected to the parallel computing device. Analog sensors output continuous signals, such as temperature, pressure, humidity, light intensity, etc. These values are continuously changing values within a range, usually output in the form of voltage or current signals, such as 0-10V or 4-20mA current signals. The characteristic of analog signals is continuity, and they need to be converted, processed, amplified, or digitized in a specific way to be recognized and further processed by the parallel computing device. Therefore, analog sensors need to use an acquisition unit to perform signal conversion and processing, and then transmit the processed data to the parallel computing device.

[0063] The output signal of the digital sensor is a simple binary signal, usually without conversion, and can be directly sent to the parallel computing device through a suitable communication interface (such as a serial port, I / O interface, or network interface). The processing of these signals is relatively simple, and it is only necessary to directly judge their high-level or low-level states.

[0064] The signals of analog sensors are continuous voltage or current signals, which usually need to be converted through analog-to-digital conversion (ADC) into digital signals so that parallel computing devices can process and analyze them. The role of the acquisition unit is to convert the analog signals into digital signals through the internal analog-to-digital converter (ADC), and then transmit the data to the parallel computing device through appropriate protocols and interfaces.

[0065] The signals output by analog sensors usually need signal conditioning, that is, amplification or noise filtering. For example, a temperature sensor may output weak current or voltage signals, and these signals may need to be amplified, filtered, or otherwise processed to obtain accurate readings. The acquisition unit is responsible for processing these signals, including amplification, filtering, analog-to-digital conversion, data formatting, etc.

[0066] Since the output of digital sensors has only two states of "on" or "off", the signals themselves usually do not require additional processing or conversion.

[0067] The output of digital sensors is usually discrete (digital), such as simple high and low level signals or pulses, which are directly transmitted through serial ports, parallel ports, or simple digital interfaces. Even when sending data through network protocols (such as Modbus, MQTT, etc.), digital sensors can directly communicate with parallel computing devices through simple switch signals and protocol transmissions.

[0068] The signals of analog sensors need to be converted into digital signals and then sent to parallel computing devices through some protocols (such as Modbus RTU, Modbus TCP, CAN bus, I2C, etc.). The role of the acquisition unit is to collect the analog signals of the sensors and convert them into a data format that can be transmitted through these communication protocols.

[0069] The functions of the acquisition unit include: Analog-to-digital conversion (ADC): Convert the continuous electrical signals of analog sensors into digital signals. Signal processing: Such as amplification, filtering, calibration, average value calculation, etc., to improve the accuracy and reliability of the data. Protocol conversion: Format the acquired digital data according to specific protocols (such as Modbus, TCP / IP, MQTT, etc.) and then transmit it to the parallel computing device. Data aggregation and management: When multiple sensors are connected to the same acquisition unit, the acquisition unit is responsible for managing the data of multiple sensors and uploading it to the parallel computing device.

[0070] Since the signals of digital sensors are simple and usually only have "on" and "off" states, complex data processing, conversion, or signal conditioning like that for analog signals is not required. Therefore, digital sensors can communicate directly with parallel computing devices through simple interfaces. They exchange data with parallel computing devices through standard digital input ports (such as digital input modules) or communication protocols (such as Modbus RTU / TCP).

[0071] As can be seen from the above, digital sensors output digital on-off data with simple signals and can be directly transmitted to parallel computing devices through digital interfaces or communication protocols without the need for additional acquisition units for signal conversion and conditioning. Analog sensors output continuous signals and usually require signal conversion (analog-to-digital conversion), amplification, conditioning, etc. through an acquisition unit to convert the data into a digital format that can be processed by parallel computing devices. Therefore, analog sensors need an acquisition unit to achieve signal conversion and data processing, while digital sensors can be directly connected to parallel computing devices for data transmission.

[0072] It should be noted that pulse sensors (such as flow meters, rotational speed sensors, counters, etc.) output a series of pulse signals, and their signal types are usually discrete digital signals. The number and frequency of these pulses represent changes in the measured physical quantity (for example, rotational speed, flow rate, etc.). However, compared with other digital sensors, the data processing and transmission requirements for pulse signals are more complex, so pulse sensors usually need to be connected to parallel computing devices through an acquisition unit.

[0073] Specifically, pulse sensors need an acquisition unit to connect to parallel computing devices mainly because: Pulse signals need to be counted and accumulated to be converted into available physical quantities (such as flow rate, rotational speed, etc.). Pulse signals usually require frequency conversion, noise reduction, and data integration. The acquisition unit is responsible for converting pulse signals into digital signals and transmitting data according to specific protocols (such as Modbus, CAN, etc.). The acquisition unit can implement functions such as signal filtering, real-time data acquisition, and multi-device data aggregation. Therefore, as an intermediary, the acquisition unit plays the role of signal processing, data conversion, protocol adaptation, and aggregation and forwarding to ensure that the data of pulse sensors can be effectively and accurately transmitted to parallel computing devices.

[0074] Furthermore, the monitoring IoT system models the parameters of the physical sensor to obtain the corresponding sensor model.

[0075] Furthermore, the pulse sensor is connected to the parallel computing device through a digital acquisition unit group;

[0076] The digital acquisition units within the digital acquisition unit group are configured through digital acquisition unit strategies:

[0077] According to the configuration of the pulse-type sensor, a digital acquisition unit that meets the performance requirements of the pulse-type sensor is selected, and the configurations of the pulse-type sensors connected to the same acquisition unit are the same.

[0078] Furthermore, the analog acquisition unit strategy adopts the strategy function F( , b), and the strategy function F( , b) is:

[0079] F( , b) = ( , , );

[0080] Among them, = k ×

[0081] = × b

[0082] = / η

[0083] Among them, : Sensor sampling rate, unit Hz;

[0084] b: Number of bits of data generated by each sensor sampling, unit bit;

[0085] : CPU main frequency required by the acquisition unit, which is the computing power required to process sensor data, unit Hz;

[0086] : Data transmission rate, which is the rate at which data is transmitted from the acquisition unit to the storage or parallel computing device, unit bps;

[0087] : Pin data processing speed, which is the speed at which the data interface of the acquisition unit processes data, unit bps;

[0088] Transmission rate calculation formula:

[0089] = × b

[0090] Among them, the number of samples per second is times, and each sampling generates b bits of data. The total amount of data transmitted per second is bps;

[0091] CPU main frequency calculation formula:

[0092] = k ×

[0093] where k is the number of CPU cycles required for each sampling and depends on the complexity of data processing; is the sampling rate, with the unit of Hz;

[0094] Calculation formula for the pin data processing speed:

[0095] = / η

[0096] where is the total transmission rate; η is the transmission efficiency.

[0097] The function F( , b) describes that under different sampling rates and data bits, the required CPU main frequency increases linearly with the sampling rate. The transmission rate increases linearly with the product of the sampling rate and the data bits. The pin data processing speed is jointly affected by the transmission rate and the transmission efficiency. It is used to evaluate the performance requirements of the acquisition unit under different sensor configurations and helps to select an acquisition unit with an appropriate CPU main frequency, communication rate, and interface speed.

[0098] Furthermore, between the acquisition unit and the parallel computing device, or between the digital quantity sensor and the parallel computing device, data is transmitted through a communication protocol, and the communication protocol includes one or more of TCP / UDP, MODBUS, MQTT, and IEC61850.

[0099] Furthermore, nodes are set in the physical sensor, the acquisition unit, and the parallel computing device, and the monitoring Internet of Things system defines the standard interfaces for data access and output of each node.

[0100] Furthermore, the monitoring Internet of Things system records the input and output data of each node, forms a complete data processing link, monitors the operating status of each node in real time, and triggers an alarm when an anomaly or failure occurs.

[0101] The monitoring Internet of Things system defines the nodes for link tracing by introducing a link tracing library or middleware (such as OpenTelemetry, Jaeger, etc.). Each node is usually defined by the following steps:

[0102] Initialize the link tracing context and generate a trace ID and a span ID.

[0103] Record the information of the node, including the start time, end time, status, tags, and logs, etc.

[0104] Transfer context information and pass the trace ID and span ID during cross-service calls.

[0105] End node, record the end information of the node and send it to the link tracing server.

[0106] The definition and data collection of nodes are usually completed through an automated link tracing library. The developers of the service can enable link tracing by adding relevant code at key positions.

[0107] The monitoring IoT system defines and traces the nodes in the link by integrating a link tracing library (such as OpenTelemetry, Jaeger, Zipkin). Each node represents the request processing process of a service or module. The creation, recording, context transfer, end, and collection of status information of the nodes are automatically performed with the help of the link tracing library.

[0108] Furthermore, the monitoring IoT system includes:

[0109] An acquisition component for accessing the physical sensor and performing signal sampling and oscillogram recording on the physical sensor;

[0110] A function component for processing the physical sensor signals sampled and recorded by the acquisition unit;

[0111] A network component for distributing and reporting the physical sensor signals;

[0112] A storage component for storing the physical sensor signals.

[0113] Furthermore, the monitoring IoT system further includes:

[0114] A process orchestration component for orchestrating the processes of the acquisition component, function component, network component, and storage component through a graphical user interface.

[0115] Furthermore, it also includes a usage method of the high-voltage electrical equipment monitoring IoT platform based on multiple IEDs, including the following steps:

[0116] Select the IED based on the communication protocol of the physical sensor and complete the wiring;

[0117] Select or add a sensor model on the graphical user interface; when a physical sensor intervenes in an incorrect acquisition unit or parallel computing device interface, for example, when a temperature sensor is connected to an interface defined as collecting pressure sensor signals on the acquisition unit, the present application can change the sensor model on the graphical user interface so that the sensor model displays the correct data.

[0118] Orchestrate processes using the described graphical user interface; optimize script components so that scripts are no longer required in process orchestration.

[0119] View the running status and signal output of the node.

[0120] Although embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the present invention, and such modifications and variations fall within the scope defined by the appended claims.

Claims

1. A high-voltage electrical equipment monitoring Internet of Things platform based on multiple IEDs, characterized in that: It includes a monitoring Internet of Things system and a monitoring device, wherein the monitoring device includes a multi-element IED and a physical sensor, wherein the multi-element IED includes a collection unit and a parallel computing device, and the physical sensor includes a digital quantity sensor and an analog quantity sensor; The acquisition unit is divided into an analog quantity acquisition unit group and a digital quantity acquisition unit group, wherein the analog quantity sensor is connected to the parallel computing device through the analog quantity acquisition unit group, and the digital quantity sensor is connected to the parallel computing device; The acquisition units in the analog acquisition unit group are configured by analog acquisition unit strategy: According to the configuration of the analog sensor, select an analog acquisition unit that meets the performance requirements of the analog sensor, and the analog sensors connected to the same acquisition unit have the same configuration; The physical sensor is connected to the interfaces of the acquisition unit and the parallel computing device respectively by plugging and unplugging, and the monitoring Internet of Things system defines the data types of the acquisition unit and the parallel computing device interface respectively.

2. The high-voltage electrical equipment monitoring Internet of Things platform based on multiple IEDs according to claim 1 is characterized in that: The monitoring Internet of Things system performs parameter modeling on the physical sensor to obtain a corresponding sensor model.

3. The high-voltage electrical equipment monitoring Internet of Things platform based on multiple IEDs according to claim 1 is characterized in that: The pulse sensor is connected to the parallel computing device via a digital quantity acquisition unit group; The digital quantity acquisition units in the digital quantity acquisition unit group are configured by the digital quantity acquisition unit strategy: According to the configuration of the pulse type sensor, a digital quantity acquisition unit that meets the performance requirements of the pulse type sensor is selected, and the configuration of the pulse type sensors connected to the same acquisition unit is the same.

4. The high-voltage electrical equipment monitoring Internet of Things platform based on multiple IEDs according to claim 1 is characterized in that: The analog quantity acquisition unit strategy adopts the strategy function F( ,b), the strategy function F( ,b) is: F( ,b)=( , , ); in, =k× = ×b = / or in, : sensor sampling rate, unit Hz; b: the number of data bits generated by the sensor each time it samples, in bits; : The CPU main frequency required by the acquisition unit, which is the computing power required to process sensor data, in Hz; : Data transmission rate, which is the rate at which data is transmitted from the acquisition unit to the storage or parallel computing device, in bps; : Pin data processing speed, which is the speed at which the data interface of the acquisition unit processes data, in bps; Transmission rate calculation formula: = ×b Among them, samples per second times, each sampling generates b bits of data, and the total amount of data transmitted per second is bps; CPU main frequency calculation formula: =k× Where k is the number of CPU cycles required for each sampling and depends on the complexity of data processing; is the sampling rate in Hz; Pin data processing speed calculation formula: = / or in, is the total transmission rate; η is the transmission efficiency.

5. The high-voltage electrical equipment monitoring Internet of Things platform based on multiple IEDs according to claim 3 is characterized in that: The acquisition unit and the parallel computing device, or the digital quantity sensor and the parallel computing device, are transmitted via a communication protocol, and the communication protocol includes one or more of TCP / UDP, MODBUS, MQTT and IEC61850.

6. The high-voltage electrical equipment monitoring Internet of Things platform based on multiple IEDs according to claim 1 is characterized in that: Nodes are provided in the physical sensor, the acquisition unit and the parallel computing device, and the monitoring Internet of Things system defines a standard interface for data access and output of each node.

7. The high-voltage electrical equipment monitoring Internet of Things platform based on multiple IEDs according to claim 6 is characterized in that: The monitoring Internet of Things system records the input and output data of each node, forms a complete data processing link, monitors the operating status of each node in real time, and triggers an alarm when an abnormality or failure occurs.

8. The high-voltage electrical equipment monitoring Internet of Things platform based on multiple IEDs according to claim 7 is characterized in that: The monitoring Internet of Things system includes: A collection component, used to access the physical sensor and perform signal sampling and waveform recording on the physical sensor; Functional components for processing the physical sensor signals sampled and recorded by the acquisition unit; Network components for distributing and reporting physical sensor signals; The storage component is used to store the physical sensor signal.

9. The high-voltage electrical equipment monitoring Internet of Things platform based on multiple IEDs according to claim 8 is characterized in that: The monitoring Internet of Things system also includes: The process orchestration component is used to orchestrate the processes of the collection components, functional components, network components and storage components through a graphical interactive interface.

10. The high-voltage electrical equipment monitoring Internet of Things platform based on multiple IEDs according to claim 9 is characterized in that: Also included is a method for using a high-voltage electrical equipment monitoring IoT platform based on a multi-IED, including the following steps: Selecting an IED based on the communication protocol of the physical sensor and completing wiring; Select or add a sensor model on the graphical interactive interface; Use the graphical interactive interface to perform process orchestration; Check the running status and signal output of the node.

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