Intelligent meteorological sensor automatic checking system and method based on Internet of Things

Abstract

The invention discloses an intelligent meteorological sensor automatic checking system and method based on the Internet of Things, and relates to the technical field of meteorological monitoring, and the system comprises a meteorological sensor test module, a meteorological data transmission module and an automatic checking module. According to the invention, environment testing, apparent data testing and comprehensive environment and apparent data testing are carried out on the meteorological sensor, so that each calibration interval and each calibration factor of the target meteorological sensor under different conditions are obtained, the meteorological data collected by the target meteorological sensor are calibrated in a targeted manner, the accuracy of the meteorological data is ensured, and the accuracy of the meteorological data is improved. Meanwhile, the intelligent wireless networking is built, the meteorological data is transmitted to the main control equipment through the intelligent wireless networking, the main control equipment calibrates the meteorological data device based on the test result of the meteorological sensor, and compared with a traditional wired network, the intelligent wireless networking does not need to lay a large number of cables and build complex communication infrastructures, and the system is convenient to use. And the construction cost is reduced.

Description

Technical Field

[0001] This application relates to the technical field of meteorological monitoring, and specifically relates to an intelligent meteorological sensor automatic verification system and method based on the Internet of Things. Background Art

[0002] During the operation of meteorological sensors, their vanes may be affected by various external factors, which may lead to deviations in the collected meteorological data. By obtaining the calibration intervals and calibration factors of meteorological sensors under the influence of various external factors through testing, and then calibrating the meteorological sensors, the accuracy and reliability of meteorological sensors can be improved. Therefore, this application proposes an intelligent meteorological sensor automatic verification system and method based on the Internet of Things.

[0003] An existing technology, such as a meteorological environment data real-time monitoring system disclosed in the invention patent application with the publication number CN113267833A, is composed of a sensor module, a data acquisition and storage module, a monitoring computer, a wireless transceiver module, a power management module, etc.; the sensor module is used to convert physical meteorological signals into standard electrical signals; the sensor module is composed of a solar radiation sensor, an atmospheric pressure sensor, a temperature and humidity sensor, a rainfall sensor, a black and white board temperature sensor, a sunshine duration sensor, and a wind speed and direction sensor; the data acquisition and storage module is used to collect sensor electrical signals and save the collected meteorological information, and under the support of control software, real-time monitor the data.

[0004] Regarding the above solution, there are the following technical problems: 1. The current technology mainly collects and monitors meteorological environment data through each module, without considering that due to the change of weather phenomena in the monitoring area, the meteorological data may change greatly, which may affect the functions of each sensor, resulting in deviations in the collected meteorological data. The neglect of this aspect in the current technology will lead to the lack of accuracy and reliability of the monitored meteorological data.

[0005] 2. The current technology does not consider that meteorological sensors may be interfered by insects or birds during operation. Since meteorological sensors are exposed to the air for a long time, insects and birds may lay eggs, build nests or stay on the surface of meteorological sensors, etc., which may affect the functions of meteorological sensors. If this problem is not solved in the current technology, it may lead to large deviations in the monitored meteorological data. Summary of the Invention

[0006] The purpose of this application is to provide an intelligent target meteorological sensor automatic verification system and method based on the Internet of Things, which solves the problems existing in the background art.

[0007] To solve the above technical problems, the present application adopts the following technical solutions: In the first aspect, the present application provides an automated verification system for intelligent target meteorological sensors based on the Internet of Things, including: A meteorological sensor testing module: used to conduct environmental testing, apparent data testing, and comprehensive environmental and apparent data testing on the target meteorological sensor, and then transmit the test results to the main control device through the communication node device.

[0008] A meteorological data transmission module: used to build an intelligent wireless network, and then transmit the meteorological data and apparent data of the target meteorological sensor through the intelligent wireless network.

[0009] An automated verification module: used to determine whether the target meteorological sensor needs to be calibrated based on the meteorological phenomena of the current meteorological station and the apparent data of the target meteorological sensor, and judge whether the target meteorological sensor is working properly based on the calibration results.

[0010] In the second aspect, the present application provides an automated verification method for intelligent target meteorological sensors based on the Internet of Things, including: Step 1, meteorological sensor testing: used to conduct environmental testing, apparent data testing, and comprehensive environmental and apparent data testing on the target meteorological sensor, and then transmit the test results to the main control device through the communication node device.

[0011] Step 2, meteorological data transmission: used to build an intelligent wireless network, and then transmit the meteorological data and apparent data of the target meteorological sensor through the intelligent wireless network.

[0012] Step 3, automated verification: used to determine whether the target meteorological sensor needs to be calibrated based on the meteorological phenomena of the current meteorological station and the apparent data of the target meteorological sensor, and judge whether the target meteorological sensor is working properly based on the calibration results.

[0013] The beneficial effects of the present application are as follows: 1. Through environmental testing, apparent data testing, and comprehensive environmental and apparent data testing of the meteorological sensor, the present application obtains the calibration intervals and calibration factors of the target meteorological sensor in different situations, thereby calibrating the meteorological data collected by the target meteorological sensor in a targeted manner, ensuring the accuracy of the meteorological data. At the same time, an intelligent wireless network is built, and the meteorological data is transmitted to the main control device through the intelligent wireless network. The main control device calibrates the meteorological data device based on the test results of the meteorological sensor. Compared with the traditional wired network, the intelligent wireless network does not require laying a large number of cables and building complex communication infrastructure, reducing the construction cost.

[0014] 2. Through environmental testing, apparent data testing, and comprehensive environmental and apparent data testing on the target meteorological sensor, the calibration intervals and calibration factors of the target sensor in various situations are obtained. Through testing, not only the calibration intervals and calibration factors of the target meteorological sensor under single environmental changes are obtained, but also the calibration intervals and calibration factors of the target sensor in complex environments such as various weather phenomena and various apparent data are obtained, enabling targeted correction of meteorological data, thus ensuring the accuracy of the data and providing a strong data basis for fields such as meteorological research and environmental monitoring.

[0015] 3. By building an intelligent wireless network and transmitting the meteorological data and apparent data of the target meteorological sensor through the intelligent wireless network, the intelligent wireless network gets rid of the limitations of traditional wired network cabling. Compared with the traditional wired network, the intelligent wireless network does not require laying a large number of cables and building complex communication infrastructure, greatly reducing the construction cost. Moreover, the meteorological sensors can be installed more flexibly in various complex environments, greatly reducing the installation cost and difficulty, shortening the installation cycle, and having strong scalability. It can also be more conveniently integrated with other meteorological monitoring systems, environmental monitoring systems, and related business application systems to achieve data sharing and interaction.

[0016] 4. By judging whether the meteorological data of the target meteorological sensor needs to be calibrated based on the meteorological phenomena of the current meteorological station and the apparent data of the target meteorological sensor, and judging whether the target meteorological sensor is working properly based on the calibration result, the measurement error of the meteorological sensor is corrected in a timely manner to ensure the accuracy of the meteorological data, and the working state of the meteorological sensor is judged in a timely manner, greatly avoiding errors in meteorological data. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0018] Figure 1 It is a schematic diagram of the system structure connection of the present application.

[0019] Figure 2 It is a schematic diagram of the flow of the method implementation steps of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0020] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present application without creative efforts belong to the scope of protection of the present application.

[0021] Referring to Figure 1 As shown, the present application provides an intelligent target meteorological sensor automatic verification system based on the Internet of Things in the first aspect, including the following modules: Meteorological sensor test module: used to perform environmental tests, apparent data tests, and comprehensive environmental and apparent data tests on the target meteorological sensor, and then transmit the test results to the main control device through the communication node device.

[0022] In a specific example, the target meteorological sensor test module includes: Target meteorological sensor environmental test unit: used to perform environmental tests on the target meteorological sensor, and then analyze and obtain the calibration interval and calibration factor of the meteorological data collected by the target meteorological sensor in each environment, so as to establish the deviation relationship between meteorological phenomena and meteorological data.

[0023] It should be noted that the environmental test is to test the calibration interval and calibration factor of the meteorological data collected by the target meteorological sensor under various meteorological phenomena.

[0024] Target meteorological sensor apparent data test unit: used to perform apparent data tests on the target meteorological sensor, and then analyze and obtain the calibration interval and calibration factor of the meteorological data collected by the target meteorological sensor under the influence of each apparent data, so as to establish the deviation relationship between the apparent data of the target meteorological sensor and meteorological data.

[0025] It should be noted that the apparent data test is to test the calibration interval and calibration factor of the target meteorological sensor caused by the behaviors of insects and birds nesting, laying eggs, and gnawing on the surface of the target meteorological sensor. The apparent data includes the pressure and foreign object area on the surface of the target meteorological sensor caused by insects and birds.

[0026] Target meteorological sensor environmental and apparent data comprehensive test unit: used to perform environmental and apparent data tests on the target meteorological sensor, and then analyze and obtain the calibration interval and calibration factor of the meteorological data collected by the target meteorological sensor under the influence of each meteorological phenomenon and each apparent data, so as to establish the deviation relationship between the meteorological phenomenon and apparent data of the target meteorological sensor and meteorological data.

[0027] It should be noted that the meteorological data includes temperature, humidity, etc., the apparent data includes the weight and area of foreign objects on the surface of the target meteorological sensor, where the foreign objects on the target meteorological sensor include insects, birds, bird eggs, bird droppings, etc., and the meteorological phenomena include sand and dust, lightning, rainfall, etc.

[0028] In a specific example, the target meteorological sensor is subjected to environmental testing, and then the calibration intervals and calibration factors of the meteorological data collected by the target meteorological sensor in each environment are analyzed, so as to establish the deviation relationship between meteorological phenomena and meteorological data. The specific process is as follows: S1. Set up each test chamber in the laboratory to obtain each test group. Set the initial test environments of each test chamber to be the same. After installing each meteorological sensor in each test chamber, start the test.

[0029] It should be noted that setting the initial test environments of each test chamber to be the same means setting the initial meteorological data in each test chamber to be the same.

[0030] It should be noted that the models, functions, etc. of the meteorological sensors in each test chamber are exactly the same as those of the target sensor.

[0031] S2. Record the meteorological data of each test chamber as each standard meteorological data. Simulate each meteorological phenomenon in each test chamber, and at the same time gradually change each standard meteorological data. Collect the meteorological data of each test chamber under each meteorological phenomenon and each standard meteorological data through each meteorological sensor, and compare them with the corresponding standard meteorological data respectively, so as to obtain the calibration intervals and calibration factors of the target meteorological sensor under each meteorological phenomenon.

[0032] S3. Repeat the experiment multiple times to obtain the calibration intervals and calibration factors of the target meteorological sensor under each meteorological phenomenon. Record the averages of the calibration intervals and calibration factors of the target meteorological sensor under a certain meteorological phenomenon as the calibration interval and calibration factor of the target meteorological sensor under this meteorological phenomenon respectively. Based on this, analyze and obtain the calibration intervals and calibration factors of the target meteorological sensor under each meteorological phenomenon.

[0033] S4. Establish the deviation relationship between meteorological phenomena and meteorological data based on the calibration intervals and calibration factors of the target meteorological sensor under each meteorological phenomenon.

[0034] In a specific example, the target meteorological sensor is subjected to apparent data testing, and then the calibration intervals and calibration factors of the meteorological data collected by the target meteorological sensor under the influence of each apparent data are analyzed, so as to establish the deviation relationship between the apparent data and the meteorological data of the target meteorological sensor. The specific testing process is as follows: A1. Set the initial test environment of the laboratory based on the environment of the meteorological station where the target meteorological sensor is located. After the setting is completed, start the test.

[0035] A2. Record the meteorological data in the laboratory as standard meteorological data. Gradually change the apparent data of the meteorological sensor, and at the same time gradually change the standard meteorological data in the laboratory. Collect the meteorological data of each test chamber under each apparent data through the meteorological sensor, and compare them with the corresponding standard meteorological data respectively, so as to obtain the calibration interval and calibration factor of the target meteorological sensor under each apparent data.

[0036] A3. Repeat the experiment multiple times, and then obtain the calibration intervals and calibration factors of the target meteorological sensor under each apparent data. Denote the average values of the calibration intervals and calibration factors of the target meteorological sensor under a certain apparent data as the calibration interval and calibration factor of the target meteorological sensor under this apparent data. Similarly, the calibration intervals and calibration factors of the target meteorological sensor under each apparent data can be analyzed and obtained.

[0037] A4. Establish the deviation relationship between the apparent data and the meteorological data based on the calibration intervals and calibration factors of the target meteorological sensor under each apparent data.

[0038] In a specific example, the environmental and apparent data of the target meteorological sensor are tested, and then the calibration intervals and calibration factors of the meteorological data collected by the target meteorological sensor under the influence of various meteorological phenomena and various apparent data are analyzed, so as to establish the deviation relationship between the meteorological phenomena and apparent data of the target meteorological sensor and the meteorological data. The specific process is as follows: C1. Set up each test chamber in the laboratory, and then obtain each test group. Set the initial test environment of each test chamber to be the same. After installing each meteorological sensor in each test chamber, start the test.

[0039] C2. Record the meteorological data of each test chamber as each standard meteorological data. Simulate various meteorological phenomena in each test chamber, and at the same time gradually change the apparent data of each meteorological sensor and the standard meteorological data of each test chamber. Collect the meteorological data of each test chamber through each meteorological sensor, and compare them with the corresponding standard meteorological data respectively, so as to obtain the calibration intervals and calibration factors of the target meteorological sensor under various meteorological phenomena and various apparent data.

[0040] C3. Repeat the experiment multiple times, and then obtain the calibration intervals and calibration factors of the target meteorological sensor under various meteorological phenomena and various apparent data. Denote the average values of the calibration intervals and calibration factors of the target meteorological sensor under a certain meteorological phenomenon and a certain apparent data as the calibration interval and calibration factor of the target meteorological sensor under this meteorological phenomenon and this apparent data. Based on this, the calibration intervals and calibration factors of the target meteorological sensor under various meteorological phenomena and various apparent data can be analyzed and obtained.

[0041] C4. Establish the deviation relationship among meteorological phenomenon - apparent data - meteorological data based on the calibration intervals and calibration factors of the target meteorological sensor under various meteorological phenomena and various apparent data.

[0042] It should be noted that the deviation relationships between the meteorological phenomena and meteorological data, between the apparent data and meteorological data, and among meteorological phenomena - apparent data - meteorological data of the meteorological sensor will vary due to different models of the meteorological sensor, which will not be elaborated one by one here.

[0043] Meteorological data transmission module: It is used to build an intelligent wireless network, and then transmit the meteorological data and apparent data of the target meteorological sensor through the intelligent wireless network.

[0044] In a specific example, the construction of the intelligent wireless network is as follows: The intelligent wireless network includes communication node devices and a main control device. The target meteorological sensor is connected to the communication node device through a serial port. The communication node device and the main control device use radio frequency signals to achieve long-distance transmission. The main control device is connected to multiple communication node devices at the same time to achieve intelligent networking and support remote parameter setting.

[0045] Among them, the communication node device is a handheld miniaturized device, which has two on-site communication ports, one RS232 port and one RS232 / 485 multiplexed port, and can be connected to two different devices at the same time; it has the function of long-distance data transmission of LaRa radio frequency signals, and is equipped with a rechargeable battery of 3.6V / 1.5AH, and uses an independent battery box for easy battery replacement.

[0046] It should be noted that the communication node device can be used to connect meteorological sensors and data acquisition devices, and the data acquisition devices include camera devices for collecting the apparent data of meteorological sensors, etc.

[0047] Among them, the main control device is a portable device, which is connected to the upper computer software through an RS232 serial port or WIFI signal, accepts the instructions of the upper computer software, and commands one or more communication node devices of the weather station to read the meteorological data of on-site meteorological sensors. It has three RS232 ports, one of which is an RS485 port connected to the upper computer; one is used for external device power supply; one is used for external power supply and charging power supply; and it is equipped with a rechargeable battery of 12V / 5AH and uses an independent battery box for easy battery replacement. At the same time, it is equipped with a touch control screen for on-site operation and information display.

[0048] It should be noted that at the observation site, according to the number of meteorological data to be tested or verified, an appropriate number of communication node devices are selected. Each node device is connected to the meteorological sensor to be tested or verified and the comparison meteorological sensor at the same time. After being intelligently networked with the main control device, the meteorological data to be verified is read in real time under the command of the upper computer software.

[0049] In a specific example, the process of transmitting the meteorological data and apparent data of the target meteorological sensor through intelligent wireless networking is as follows: Install a pressure sensor at the sensor of the target meteorological sensor in the meteorological station, collect the foreign object pressure received by the target meteorological sensor at a preset frequency through the pressure sensor, and at the same time collect the surface image of the target meteorological sensor at a preset frequency through the imaging device in the meteorological station. Then, transmit the meteorological data and apparent data of the target meteorological sensor to the main control device through the communication node device in the intelligent networking.

[0050] It should be noted that the preset frequency is set by relevant staff themselves.

[0051] Automated verification module: used to determine whether the target meteorological sensor needs to be calibrated based on the meteorological phenomena of the current meteorological station and the apparent data of the target meteorological sensor, and judge whether the target meteorological sensor is working properly based on the calibration result.

[0052] In a specific example, the process of determining whether the target meteorological sensor needs to be calibrated based on the meteorological phenomena of the current meteorological station and the apparent data of the target meteorological sensor is as follows: Obtain the meteorological phenomena of the area where the current meteorological station is located from the meteorological center, match the current meteorological phenomena with the meteorological phenomena - meteorological data deviation relationship, and accordingly judge whether the meteorological data needs to be calibrated under the current meteorological phenomena.

[0053] It should be noted that when matching the current meteorological phenomena with the meteorological phenomena - meteorological data deviation relationship and accordingly judging whether the meteorological data needs to be calibrated, for example, when the meteorological phenomenon in the meteorological phenomena - meteorological data deviation relationship is cloudy, the meteorological data has no deviation, and the meteorological phenomenon of the current meteorological station is cloudy, it is judged that there is no need to calibrate the meteorological data.

[0054] If there is no need to calibrate the meteorological data under the current meteorological phenomena, then match the apparent data of the target meteorological sensor with the apparent data - meteorological data deviation relationship, obtain the calibration interval corresponding to the current apparent data accordingly, and then match the current meteorological data with the calibration interval. When the current meteorological data belongs to the calibration interval, there is no need to calibrate the current meteorological data. When the meteorological data does not belong to the calibration interval, calibrate the current meteorological data based on the calibration factor corresponding to the current apparent data.

[0055] If it is necessary to calibrate meteorological data under the current meteorological phenomenon, the meteorological phenomenon of the current meteorological station and the apparent data of the target meteorological sensor are matched with the meteorological phenomenon-apparent data-meteorological data deviation value, so as to obtain the calibration interval corresponding to the current meteorological phenomenon and apparent data, and then the current meteorological data is compared with the calibration interval. When the meteorological data belongs to the calibration interval, there is no need to calibrate the current meteorological data. When the meteorological data belongs to the calibration interval, the current meteorological data is calibrated based on the calibration factor corresponding to the current meteorological phenomenon and apparent data.

[0056] In a specific example, the process of determining whether the target meteorological sensor is working properly is as follows: Denote the meteorological data after calibrating the target meteorological sensor as target meteorological data, obtain the same type of meteorological sensor closest to the target meteorological sensor, and then obtain the same type of meteorological data collected by the same type of meteorological sensor. After calibrating the same type of meteorological data, compare it with the target meteorological data. If the data difference between the target meteorological data and the same type of meteorological data is within the set meteorological data difference range, it indicates that the calibration of the target meteorological sensor is normal; otherwise, it indicates that the calibration of the target meteorological sensor is abnormal, and a warning prompt is given to the staff when the calibration is abnormal.

[0057] It should be noted that the meteorological data differences are all set by relevant staff according to the historical collection situation of meteorological data. Among them, the lower the meteorological data difference, the higher the calibration effect requirement for the target sensor. For example, the temperature difference can be set to 0.5 - 0.1 °C, the humidity difference to 5% - 10% RH, the wind speed difference to 0.5 - 1 m / s, and the air pressure difference to 1 - 5 hPa, etc.

[0058] Refer to Figure 2 As shown, in the second aspect of the present application, an automated verification method for an intelligent target meteorological sensor based on the Internet of Things is provided, including the steps: Step 1, meteorological sensor testing: used to conduct environmental testing, apparent data testing, and comprehensive environmental and apparent data testing on the target meteorological sensor, and then transmit the test results to the main control device through the communication node device.

[0059] Step 2, meteorological data transmission: used to build an intelligent wireless network, and then transmit the meteorological data and apparent data of the target meteorological sensor through the intelligent wireless network.

[0060] Step 3, automated verification: used to determine whether it is necessary to calibrate the target meteorological sensor according to the meteorological phenomenon of the current meteorological station and the apparent data of the target meteorological sensor, and judge whether the target meteorological sensor is working properly based on the calibration result.

[0061] This application conducts environmental tests, apparent data tests, and comprehensive environmental and apparent data tests on meteorological sensors, and then obtains the calibration intervals and calibration factors of the target meteorological sensors under different conditions, so as to calibrate the meteorological data collected by the target meteorological sensors specifically, ensuring the accuracy of the meteorological data. At the same time, an intelligent wireless network is built, and the meteorological data is transmitted to the main control device through the intelligent wireless network. The main control device calibrates the meteorological data device based on the test results of the meteorological sensors. Compared with the traditional wired network, the intelligent wireless network does not require laying a large number of cables and building complex communication infrastructures, reducing the construction cost.

[0062] The above content is only an example and illustration of the concept of this application. Those skilled in the art of this technology can make various modifications or supplements to the described specific embodiments or use similar methods to replace them. As long as they do not deviate from the concept of the invention or exceed the scope defined by this application, they should all fall within the protection scope of this application.

Claims

1. An intelligent meteorological sensor automatic verification system based on the Internet of Things, characterized in that Including: Meteorological sensor test module: Used to conduct environmental tests, apparent data tests, and comprehensive environmental and apparent data tests on the target meteorological sensor, and then transmit the test results to the main control device through the communication node device; Meteorological data transmission module: Used to build an intelligent wireless network, and then transmit the meteorological data and apparent data of the target meteorological sensor through the intelligent wireless network; Automation verification module: Used to determine whether the target meteorological sensor needs to be calibrated based on the meteorological phenomena of the current meteorological station and the apparent data of the target meteorological sensor, and judge whether the target meteorological sensor is working properly based on the calibration results.

2. The automated verification system for an intelligent meteorological sensor based on the Internet of Things according to claim 1, wherein The target meteorological sensor test module includes: Target meteorological sensor environmental test unit: Used to conduct environmental tests on the target meteorological sensor, and then analyze the calibration intervals and calibration factors of the meteorological data collected by the target meteorological sensor in each environment, so as to establish the deviation relationship between meteorological phenomena and meteorological data; Target meteorological sensor apparent data test unit: Used to conduct apparent data tests on the target meteorological sensor, and then analyze the calibration intervals and calibration factors of the meteorological data collected by the target meteorological sensor under the influence of each apparent data, so as to establish the deviation relationship between the apparent data of the target meteorological sensor and meteorological data; Target meteorological sensor environmental and apparent data comprehensive test unit: Used to conduct environmental and apparent data tests on the target meteorological sensor, and then analyze the calibration intervals and calibration factors of the meteorological data collected by the target meteorological sensor under the influence of each meteorological phenomenon and each apparent data, so as to establish the deviation relationship between the meteorological phenomena and apparent data of the target meteorological sensor and meteorological data.

3. An intelligent meteorological sensor automated verification system based on the Internet of Things according to claim 2, characterized in that, The process of conducting environmental tests on the target meteorological sensor, and then analyzing the calibration intervals and calibration factors of the meteorological data collected by the target meteorological sensor in each environment, so as to establish the deviation relationship between meteorological phenomena and meteorological data is as follows: S1. Set up each test chamber in the laboratory to obtain each test group. Set the initial test environment of each test chamber to be the same. After installing each meteorological sensor in each test chamber, start the test; S2. Record the meteorological data of each test chamber as each standard meteorological data. Simulate each meteorological phenomenon in each test chamber, and gradually change each standard meteorological data at the same time. Collect the meteorological data of each test chamber under each meteorological phenomenon and each standard meteorological data through each meteorological sensor, and compare them with the corresponding standard meteorological data respectively, so as to obtain the calibration intervals and calibration factors of the target meteorological sensor under each meteorological phenomenon; S3. Repeat the experiment multiple times to obtain the calibration intervals and calibration factors of the target meteorological sensor under each meteorological phenomenon. Denote the average values of the calibration intervals and calibration factors of the target meteorological sensor under a certain meteorological phenomenon as the calibration interval and calibration factor of the target meteorological sensor under this meteorological phenomenon, and analyze the calibration intervals and calibration factors of the target meteorological sensor under each meteorological phenomenon accordingly; S4. Establish the deviation relationship between meteorological phenomena and meteorological data based on the calibration intervals and calibration factors of the target meteorological sensor under each meteorological phenomenon.

4. An intelligent meteorological sensor automatic verification system based on the Internet of Things according to claim 2, characterized in that, Perform apparent data tests on the target meteorological sensor, and then analyze to obtain the calibration intervals and calibration factors of the meteorological data collected by the target meteorological sensor under the influence of various apparent data, thereby establishing the deviation relationship between the apparent data and meteorological data of the target meteorological sensor. The specific test process is as follows: A1. Based on the environment of the meteorological station where the target meteorological sensor is located, set the initial test environment of the laboratory. After the setting is completed, start the test; A2. Record the meteorological data in the laboratory as standard meteorological data. Gradually change the apparent data of the meteorological sensor and at the same time gradually change the standard meteorological data in the laboratory. Collect the meteorological data of each test chamber under each apparent data through the meteorological sensor, and compare them with the corresponding standard meteorological data respectively, so as to obtain the calibration intervals and calibration factors of the target meteorological sensor under each apparent data; A3. Repeat the experiment multiple times, and then obtain the calibration intervals and calibration factors of the target meteorological sensor under each apparent data. Denote the average values of the calibration intervals and calibration factors of the target meteorological sensor under a certain apparent data as the calibration interval and calibration factor of the target meteorological sensor under this apparent data. Similarly, the calibration intervals and calibration factors of the target meteorological sensor under each apparent data can be analyzed; A4. Based on the calibration intervals and calibration factors of the target meteorological sensor under each apparent data, establish the deviation relationship between the apparent data and meteorological data.

5. The automated verification system for an intelligent meteorological sensor based on the Internet of Things according to claim 3, characterized in that, Perform environmental and apparent data tests on the target meteorological sensor, and then analyze to obtain the calibration intervals and calibration factors of the meteorological data collected by the target meteorological sensor under the influence of various meteorological phenomena and various apparent data, thereby establishing the deviation relationship between the meteorological phenomena and apparent data and meteorological data of the target meteorological sensor. The specific process is as follows: C1. Set up each test chamber in the laboratory to obtain each test group. Set the initial test environments of each test chamber to be the same. After installing each meteorological sensor in each test chamber, start the test; C2. Record the meteorological data of each test chamber as each standard meteorological data. Simulate various meteorological phenomena in each test chamber, and at the same time gradually change the apparent data of each meteorological sensor and the standard meteorological data of each test chamber. Collect the meteorological data of each test chamber through each meteorological sensor, and compare them with the corresponding standard meteorological data respectively, so as to obtain the calibration intervals and calibration factors of the target meteorological sensor under various meteorological phenomena and various apparent data; C3. Repeat the experiment multiple times, and then obtain the calibration intervals and calibration factors of the target meteorological sensor under various meteorological phenomena and various apparent data. Denote the average values of the calibration intervals and calibration factors of the target meteorological sensor under a certain meteorological phenomenon and a certain apparent data as the calibration interval and calibration factor of the target meteorological sensor under this meteorological phenomenon and this apparent data. Based on this, the calibration intervals and calibration factors of the target meteorological sensor under various meteorological phenomena and various apparent data can be analyzed; C4. Based on the calibration intervals and calibration factors of the target meteorological sensor under various meteorological phenomena and various apparent data, establish the deviation relationship among meteorological phenomenon - apparent data - meteorological data.

6. The automated verification system for an intelligent meteorological sensor based on the Internet of Things according to claim 5, characterized in that, The construction of the intelligent wireless network is as follows: The intelligent wireless networking includes communication node devices and a master control device. The target meteorological sensor is connected to the communication node device through a serial port. The communication node device and the master control device use radio frequency signals to achieve long-distance transmission. The master control device connects to multiple communication node devices simultaneously to achieve intelligent networking and supports remote parameter setting; Among them, the communication node device is a handheld miniaturized device with two on-site communication ports, one RS232 port and one RS232 / 485 multiplexed port, which can be connected to two different devices simultaneously; it has the function of long-distance data transmission of LaRa radio frequency signals, and is equipped with a rechargeable battery of 3.6V / 1.5AH and uses an independent battery box for easy battery replacement; Among them, the master control device is a portable device that connects to the upper computer software through the RS232 serial port or WIFI signal, accepts the instructions of the upper computer software, and commands one or more communication node devices of the meteorological station to read the meteorological data of the on-site meteorological sensor. It has three RS232 ports, one of which is an RS485 port connected to the upper computer; one is used for external device power supply; one is used for external power supply and charging power supply; and it is equipped with a rechargeable battery of 12V / 5AH and uses an independent battery box for easy battery replacement. At the same time, it is equipped with a touch control screen for on-site operation and information display.

7. An intelligent meteorological sensor automatic verification system based on the Internet of Things according to claim 6, characterized in that The meteorological data and apparent data of the target meteorological sensor are transmitted through the intelligent wireless networking, and the specific process is as follows: Install a pressure sensor at the sensor of the target meteorological sensor in the meteorological station. The pressure sensor collects the foreign object pressure received by the target meteorological sensor at a preset frequency. At the same time, the imaging device of the meteorological station collects the surface image of the target meteorological sensor at a preset frequency. Then, the meteorological data and apparent data of the target meteorological sensor are transmitted to the master control device through the communication node device in the intelligent networking.

8. An intelligent meteorological sensor automated verification system based on the Internet of Things according to claim 7, characterized in that, According to the meteorological phenomenon of the current meteorological station and the apparent data of the target meteorological sensor, it is judged whether the target meteorological sensor needs to be calibrated, and the specific process is as follows: Obtain the meteorological phenomenon of the area where the current meteorological station is located from the meteorological center, match the current meteorological phenomenon with the meteorological phenomenon - meteorological data deviation relationship, and judge whether the meteorological data needs to be calibrated under the current meteorological phenomenon accordingly; If the meteorological data does not need to be calibrated under the current meteorological phenomenon, the apparent data of the target meteorological sensor is matched with the apparent data - meteorological data deviation relationship, and the calibration interval corresponding to the current apparent data is obtained accordingly. Then, the current meteorological data is matched with the calibration interval. When the current meteorological data belongs to the calibration interval, the current meteorological data does not need to be calibrated. When the meteorological data does not belong to the calibration interval, the current meteorological data is calibrated based on the calibration factor corresponding to the current apparent data; If it is necessary to calibrate meteorological data under the current meteorological phenomenon, the meteorological phenomenon of the current meteorological station and the apparent data of the target meteorological sensor are matched with the meteorological phenomenon-apparent data-meteorological data deviation value, so as to obtain the calibration interval corresponding to the current meteorological phenomenon and apparent data. Then, the current meteorological data is compared with the calibration interval. When the meteorological data belongs to the calibration interval, there is no need to calibrate the current meteorological data. When the meteorological data belongs to the calibration interval, the current meteorological data is calibrated based on the calibration factor corresponding to the current meteorological phenomenon and apparent data.

9. An intelligent meteorological sensor automated verification system based on the Internet of Things according to claim 8, characterized in that, The specific process of judging whether the target meteorological sensor is working properly is as follows: Record the meteorological data after calibrating the target meteorological sensor as the target meteorological data. Obtain the same type of meteorological sensor closest to the target meteorological sensor, and then obtain the same type of meteorological data collected by the same type of meteorological sensor. Compare the calibrated same type of meteorological data with the target meteorological data. If the data difference between the target meteorological data and the same type of meteorological data is within the set meteorological data difference range, it indicates that the calibration of the target meteorological sensor is normal; otherwise, it indicates that the calibration of the target meteorological sensor is abnormal, and a warning prompt is given to the staff when the calibration is abnormal.

10. An automated verification method for an Internet of Things-based intelligent meteorological sensor, which is executed by the automated verification system for an Internet of Things-based intelligent meteorological sensor according to any one of claims 1-9, characterized in that, It includes: Step 1, meteorological sensor testing: used to conduct environmental testing, apparent data testing and comprehensive environmental and apparent data testing on the target meteorological sensor, and then transmit the test results to the main control device through the communication node device; Step 2, meteorological data transmission: used to build an intelligent wireless network, and then transmit the meteorological data and apparent data of the target meteorological sensor through the intelligent wireless network; Step 3, automatic verification: used to judge whether it is necessary to calibrate the target meteorological sensor according to the meteorological phenomenon of the current meteorological station and the apparent data of the target meteorological sensor, and judge whether the target meteorological sensor is working properly based on the calibration result.

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