Building block type ground meteorological equipment health assessment method, device and equipment and storage medium

Abstract

The embodiment of the invention provides a building block type ground meteorological equipment health assessment method, device and equipment and a storage medium, and is applied to the technical field of meteorological equipment guarantee. The method comprises the following steps: determining an evaluation target for a module based on to-be-evaluated ground meteorological equipment and an evaluation algorithm; selecting an evaluation sample based on the selection target; selecting a corresponding evaluation base set based on the evaluation target to construct a building block type evaluation algorithm; determining the evaluation probability of the building block type evaluation algorithm; and judging whether an evaluation result obtained by the building block type evaluation algorithm meets the evaluation probability or not, and outputting corresponding health conditions including health, sub-health and faults. In this way, flexible, accurate and low-cost assessment of the health state of the meteorological equipment can be realized, and a powerful guarantee is provided for accuracy and continuity of meteorological observation.

Description

Technical Field

[0001] The present disclosure relates to the field of meteorological equipment support, and particularly to a building-block type health assessment method, device, equipment and storage medium for ground meteorological equipment. Background Art

[0002] Ground meteorological observation refers to the systematic, standardized and continuous collection and recording of meteorological conditions and their change processes within a certain range of the earth's surface. Conventional observation elements include temperature, humidity, air pressure, wind direction, wind speed, rainfall, etc. Since 1998, China has started a comprehensive upgrade of ground meteorological observation equipment, aiming to achieve the automation of meteorological element observation and improve the observation efficiency and accuracy. After years of development, most ground meteorological observation equipment has achieved automatic observation, providing important basis for weather, climate, climate change, artificial weather modification, ecological meteorology and other operations, scientific research and services.

[0003] There are more than 70,000 national ground automatic meteorological observation stations (automatic stations), and the pressure of observing equipment support is increasing day by day. The stable operation of meteorological equipment is the basis and premise for doing a good job in meteorological services. Strengthening the health status assessment of meteorological equipment helps to timely discover and solve equipment failures and ensure the accuracy and continuity of meteorological observations.

[0004] The traditional health assessment module of ground meteorological equipment is usually "hard-coded" into the backend program by programmers in advance, providing users with a set of fixed assessment frameworks, which show fast and efficient characteristics for single needs. However, it is difficult for the fixed framework to cover all possible health status assessment scenarios and meet the assessment needs under different terrains, seasons and extreme events. Facing diverse extreme weather changes and the rapidly developing observation needs of ground meteorological equipment, it has low flexibility and is difficult to expand. Users cannot adjust the assessment algorithm according to their own needs or actual situations, resulting in high maintenance costs. Summary of the Invention

[0005] The present disclosure provides a method, device, equipment and storage medium for building-block type health assessment of ground meteorological equipment, which solves the problems of low flexibility and difficult adjustment of the traditional meteorological equipment health assessment framework.

[0006] According to a first aspect of the present disclosure, there is provided a building-block type health assessment method for ground meteorological equipment. The method includes:

[0007] Determining an assessment target based on the ground meteorological equipment to be evaluated and the assessment algorithm for the module;

[0008] Selecting an assessment sample based on the selected target;

[0009] Selecting a corresponding assessment basic set based on the assessment target to construct a building-block type assessment algorithm;

[0010] Determine the evaluation probability of the building block type evaluation algorithm;

[0011] Judge whether the evaluation result obtained by the building block type evaluation algorithm meets the evaluation probability, and output the corresponding health status, where the health status includes healthy, sub-healthy and faulty.

[0012] In the above-mentioned aspect and any possible implementation manner, a further implementation manner is provided. The evaluation algorithm for the module includes an acquisition system, a power supply system, a communication system, and a sensor system.

[0013] In the above-mentioned aspect and any possible implementation manner, a further implementation manner is provided. The selection targets include evaluation duration, evaluation sample conditions, and data reading time periods; the evaluation basic set includes: evaluation elements, logical operations, mathematical operations, relational comparison operations, mean value calculation, and extreme value evaluation.

[0014] In the above-mentioned aspect and any possible implementation manner, a further implementation manner is provided. The evaluation probability is the proportion of the data with the health status meeting the preset conditions screened out by the building block type evaluation algorithm in the selected evaluation samples.

[0015] In the above-mentioned aspect and any possible implementation manner, a further implementation manner is provided. The judgment of whether the evaluation result obtained by the building block type evaluation algorithm meets the evaluation probability and the output of the corresponding health status include:

[0016] If the evaluation result obtained by the building block type evaluation algorithm meets the evaluation probability, directly output the corresponding health status, and give the problem location and corresponding solution for the sub-healthy or the faulty.

[0017] In the above-mentioned aspect and any possible implementation manner, a further implementation manner is provided. The building block type evaluation algorithms are in multiple groups, and each group of evaluation algorithms corresponds to different evaluation samples and evaluation probabilities; according to the evaluation results of each group of evaluation algorithms and the logical relationship between each group of evaluation algorithms, output the corresponding health status.

[0018] According to the second aspect of the present disclosure, a building block type ground meteorological equipment health evaluation device is provided. The device includes:

[0019] A target determination module, configured to determine an evaluation target based on the ground meteorological equipment to be evaluated and the evaluation algorithm for the module;

[0020] A sample selection module, configured to select evaluation samples based on the selection target;

[0021] An algorithm construction module, configured to construct a building block type evaluation algorithm by selecting a corresponding evaluation basic set based on the evaluation target;

[0022] A probability setting module, configured to determine the evaluation probability of the building block type evaluation algorithm;

[0023] A result output module, configured to determine whether the evaluation result obtained by the building block type evaluation algorithm meets the evaluation probability, and output the corresponding health status, where the health status includes healthy, sub-healthy, and faulty.

[0024] According to a third aspect of the present disclosure, there is provided an electronic device. The electronic device includes: a memory and a processor, where a computer program is stored on the memory, and when the processor executes the program, the method described above is implemented.

[0025] According to a fourth aspect of the present disclosure, there is provided a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the method according to the first aspect and / or the second aspect of the present disclosure is implemented.

[0026] The present disclosure provides a building block type health assessment method for ground meteorological equipment, which flexibly selects and combines evaluation algorithm rules according to different requirements to evaluate the health status of the equipment. At the same time, it can also be extended and modified on the basis of existing algorithms to adapt to the changing observation instruments and observation environments, realizing flexible, accurate, and low-cost assessment of the health status of meteorological equipment, and providing a strong guarantee for the accuracy and continuity of meteorological observations.

[0027] It should be understood that the content described in the summary of the invention section is not intended to limit the key or important features of the embodiments of the present disclosure, nor is it used to limit the scope of the present disclosure. Other features of the present disclosure will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In combination with the drawings and with reference to the following detailed description, the above and other features, advantages, and aspects of the embodiments of the present disclosure will become more obvious. The drawings are used to better understand the solution and do not constitute a limitation to the present disclosure. In the drawings, the same or similar reference numerals represent the same or similar elements, where:

[0029] Figure 1 Shows a flowchart of a building block type health assessment method for ground meteorological equipment according to an embodiment of the present disclosure;

[0030] Figure 2 Shows a block diagram of a building block type health assessment device for ground meteorological equipment according to an embodiment of the present disclosure;

[0031] Figure 3 Shows a block diagram of an exemplary electronic device capable of implementing the embodiments of the present disclosure. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0032] To make the objectives, technical solutions, and advantages of the embodiments of the present disclosure clearer, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present disclosure. Apparently, the described embodiments are some, but not all, of the embodiments of the present disclosure. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present disclosure without creative efforts shall fall within the scope of protection of the present disclosure.

[0033] In addition, the term "and / or" in this document merely describes the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent three situations: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " in this document generally represents an "or" relationship between the associated objects before and after.

[0034] The present disclosure provides a modular ground meteorological equipment health assessment method, which flexibly selects and combines assessment algorithm rules according to different requirements to evaluate the health status of the equipment. The present disclosure only provides an assessment technical method, not a finished product. Users can independently select and combine assessment parameters according to the assessment target requirements to form an assessment algorithm, and formulate personalized health assessment criteria for different meteorological equipment. This assessment method can not only improve the accuracy and timeliness of the assessment, reduce the development cost, but also be widely applicable to different types of ground meteorological equipment and observation tasks, solving problems such as the traditional ground meteorological equipment health assessment architecture program being "written in stone", with low flexibility, difficult adjustment, and limited application scenarios. The modular ground meteorological equipment health assessment method has the characteristics of flexibility, accuracy, and low cost, providing strong support for meteorological equipment guarantee.

[0035] Figure 1 The flowchart of a modular ground meteorological equipment health assessment method according to an embodiment of the present disclosure is shown. As Figure 1 shown, a modular ground meteorological equipment health assessment method includes:

[0036] S101, determining an assessment target based on the ground meteorological equipment to be evaluated and the assessment algorithm for the module.

[0037] In some embodiments, taking an automatic weather station as an example, based on the model of the automatic weather station to be evaluated and the assessment algorithm for the module, clarify the logical idea of the target assessment algorithm.

[0038] The models of automatic weather stations include, but are not limited to, CAWS100, CAWSMART, DSD14, DZZ2, DZZ5, DZZ4, QML20, etc.;

[0039] The evaluation algorithm target modules include, but are not limited to, the acquisition system, power supply system, communication system, sensor system, etc. The collector system includes an AD module, a collector, and a clock; the power supply system includes a storage battery and a solar panel; the communication system includes a communication module; the sensor system includes a rainfall sensor, a wind direction sensor, a wind speed sensor, a humidity sensor, a temperature sensor, a barometric pressure sensor, etc. Select the corresponding target evaluation module from the above-mentioned acquisition system, power supply system, communication system, and sensor system according to the automatic station model.

[0040] S102, select an evaluation sample based on the selected target.

[0041] In some embodiments, an evaluation algorithm sample set is determined according to the selected target, where the selected target includes an evaluation duration, evaluation sample conditions, and data reading time.

[0042] S103, select a corresponding evaluation basis set based on the evaluation target to construct a building-block evaluation algorithm.

[0043] In some embodiments, the evaluation basis set includes: evaluation elements, logical operations, mathematical operations, relational comparison operations, mean calculation, and extreme value evaluation.

[0044] Specifically, the evaluation elements are determined by the elements stored in the selected automatic station model. One or more evaluation elements can be selected according to the evaluation target to build an evaluation algorithm. The evaluation elements include, but are not limited to, the current test time, storage time, two-minute wind direction, two-minute wind speed, ten-minute wind direction, ten-minute wind speed, maximum wind direction, maximum wind speed, instantaneous wind direction, instantaneous wind speed, extreme wind direction, extreme wind speed, air temperature, maximum temperature, minimum temperature, barometric pressure, maximum barometric pressure, minimum barometric pressure, humidity, minimum humidity, minute precipitation, hourly precipitation, rainfall sensor status, air temperature sensor status, clock status, main acquisition AD module working status, external storage card status, serial port status, motherboard temperature, solar panel charging current, solar panel charging voltage, storage battery voltage, signal strength, quality control code, presence or absence of sunshine within a minute, cumulative sunshine hours (minutes), one-minute visibility, one-minute minimum visibility, ten-minute visibility, ten-minute minimum visibility, wind direction sensor status, wind speed sensor status, humidity sensor status, barometric pressure sensor status, visibility sensor status, sunshine sensor status, sea-level barometric pressure, vapor pressure, dew point temperature, overall missing rate, element missing rate, etc.

[0045] Specifically, according to the requirements of the evaluation target, logical operations are selected for the evaluation elements by oneself to build an evaluation algorithm. The logical operations include, but are not limited to, AND, OR, NOT, XOR, etc.

[0046] Specifically, according to the requirements of the evaluation target, mathematical operations are selected for the evaluation elements by oneself to build an evaluation algorithm. The mathematical operations include, but are not limited to, addition, subtraction, multiplication, division, etc.

[0047] Specifically, according to the needs of the evaluation objective, the relationship comparison operation is selected for the evaluation element to build the evaluation algorithm by itself. The relationship comparison operation includes but is not limited to greater than (>), less than (<), greater than or equal to (≥), less than or equal to (≤), equal to (=), and not equal to (!=).

[0048] Specifically, according to the needs of the evaluation objective, the mean calculation is selected for the evaluation element to build the evaluation algorithm by itself. The mean calculation includes but is not limited to the mean of the evaluation element within the selected time period (time average) and the mean of the evaluation element within the custom kilometer range within the selected time period (space average).

[0049] Specifically, according to the needs of the evaluation objective, the extreme value evaluation is selected for the evaluation element to build the algorithm. The extreme value evaluation includes but is not limited to the maximum value, the minimum value, and the difference value.

[0050] S104. Determine the evaluation probability of the modular evaluation algorithm.

[0051] In some embodiments, the evaluation probability is the proportion of the data with the health status meeting the preset conditions screened by the modular evaluation algorithm in the selected evaluation samples, and the evaluation probability range of the algorithm can be customized according to the actual situation.

[0052] In some embodiments, by setting different evaluation probability thresholds, the performance of various evaluation elements can be determined separately, so as to provide a basis for system maintenance and fault troubleshooting.

[0053] Specifically, by setting the threshold of the evaluation probability, it can be judged whether the performance state of the evaluation element is normal. For example, when the evaluation probability of the phenomenon that the charging current of the solar panel is continuously small or the voltage of the storage battery is low exceeds the set threshold, it indicates that there are sub-health or fault problems in the system.

[0054] S105. Judge whether the evaluation result obtained by the modular evaluation algorithm meets the evaluation probability, and output the corresponding health status, where the health status includes healthy, sub-healthy, and faulty.

[0055] In some embodiments, if the evaluation result obtained by the modular evaluation algorithm meets the evaluation probability, the corresponding health status is directly output, and the problem location and the corresponding solution are given for the sub-healthy or faulty status.

[0056] In some embodiments, there are multiple groups of the modular evaluation algorithms, and each group of evaluation algorithms corresponds to different evaluation samples and evaluation probabilities; according to the evaluation results of each group of evaluation algorithms and the logical relationship between each group of evaluation algorithms, the corresponding health status is output.

[0057] The following provides a detailed description of a modular ground meteorological equipment health assessment method 100 provided by the embodiments of the present disclosure in combination with three specific embodiments, as follows:

[0058] Embodiment 1: In view of the phenomenon that the performance of solar panels often deteriorates during the long-term field operation of automatic weather stations and the batteries cannot be effectively charged, Embodiment 1 provides a modular performance assessment method for the solar panels of the DZZ2 model automatic weather station, including the following steps:

[0059] Select the DZZ2 model of the automatic weather station and the solar panel module of the power system, and clarify the assessment idea for the deterioration of the solar panel performance. Usually, the charging current of the solar panel continues to be small, and the corresponding battery ages. Due to insufficient charging, the battery voltage may be low at night.

[0060] Select Evaluation Sample 1. For the problem of low charging current of the solar panel for a long time, select the data of the previous 6000 hours (about 8 months) before the current moment, with a sampling interval of 60 minutes, covering the time period from 00:00 to 23:00.

[0061] Build an evaluation algorithm group for the low charging current of the solar panel. The algorithm rule is: solar charging current > 0 mA and solar charging current < 1000 mA.

[0062] The evaluation probability is set to 100%, indicating that the charging current during the solar panel charging is less than 1000 mA in all 6000 hours.

[0063] Through the above steps, Algorithm Group 1 is built. Then, Algorithm Group 2 is added, and it has a logical AND relationship with Algorithm Group 1.

[0064] Select Evaluation Sample 2. For the problem of the aging of the battery corresponding to the solar panel, select the data of the previous 720 hours (about 1 month) before the current moment, with a sampling interval of 60 minutes, covering the time period from 00:00 to 23:00.

[0065] Build an evaluation algorithm group for the error of the quality control code corresponding to the solar panel. The algorithm rule is: solar charging current > 400 mA and the 15th to 18th digits of the battery aging value ≤ 6.

[0066] The evaluation probability is set to be greater than 80%, indicating that when the charging current of the solar panel is greater than 400 mA in 720 hours, the battery aging data reaches more than 80%.

[0067] Through the above steps, Algorithm Group 1 and Algorithm Group 2 are built. Then, Algorithm Group 3 is added, and it has a logical AND relationship with Algorithm Group 1 and Algorithm Group 2.

[0068] Select evaluation sample three. For the problem that may cause low battery voltage at night, select the data in the 720 hours (about 1 month) before the current moment, with a sampling interval of 60 minutes, covering the time period from 21:00 to 05:00.

[0069] Build a battery voltage evaluation algorithm group. The algorithm rule: the battery voltage < 12.5V.

[0070] Set the evaluation probability to be greater than 20%, indicating that in 720 hours, the data of the battery voltage at night being less than 12.5V reaches more than 20%.

[0071] Do not add more algorithm groups.

[0072] Output the evaluation results. During 6000 hours, the charging current during the solar panel charging is less than 1000mA; and during 720 hours, when the charging current of the solar panel is greater than 400mA, the data of the quality control code battery aging reaches more than 80%; and during 720 hours, the data of the battery voltage at night being less than 12.5V reaches more than 20%. If the above conditions are met, the evaluation status is set to sub-healthy. Give the problem content: The charging current of the solar panel is continuously small and the performance has declined. There may be problems such as poor cable connection or serious panel contamination. Give the solution: Check the cables, tighten the cable connectors; wipe the panel contaminants; replace the solar panel.

[0073] Example two: For the phenomenon that the wind direction gets stuck and does not change for a long time during the long-term field operation of the automatic weather station, example two provides a building block type evaluation method for the long-term unchanged wind direction of the DZZ2 model automatic weather station, including the following steps:

[0074] Select the automatic weather station model DZZ2, the wind direction sensor module of the sensor system, clarify the evaluation idea of the long-term unchanged wind direction, exclude the situation that the wind direction sensor is frozen due to too low temperature and the long-term lack of all elements, when the wind speed is greater than 0m / s, the wind direction is at a fixed value or the change angle is small, and exclude the situation that the wind direction is fixed at zero for a long time due to reasons such as cable short circuit or lack of measurement of the wind direction sensor.

[0075] Select evaluation sample one. For the situation of non-freezing and non-missing measurement, and the problem that the wind direction is in a fixed value or the change angle is small for a long time, select the data with a ten-minute wind speed greater than 0m / s within 24 hours (one day) before the current moment, sample at the whole hour, covering the time period from 00:00 to 23:00.

[0076] Build an algorithm group for the situation of non-freezing and non-missing measurement, and the wind direction is in a fixed value or the change angle is small for a long time. The algorithm rule: |instantaneous wind direction - ten-minute wind direction average of the sample set| < ±5°, and the lowest temperature > 0°C, and the whole missing measurement rate < 20%.

[0077] The evaluation probability is set to be greater than 99%, indicating that low temperature and missing measurement conditions are excluded. When there is wind within 24 hours, the difference between the instantaneous wind direction value and the average ten-minute wind direction in the sample set is less than 5°, and the data volume reaches more than 99%.

[0078] The first algorithm group is built through the above steps. Then, the second algorithm group is added, and it has an AND logical relationship with the first algorithm group.

[0079] Select the second evaluation sample, exclude the problem of the wind direction being fixed at zero for a long time, select the data within the previous 24 hours (one day) before the current moment, sample at the whole hour, covering the time period from 00:00 to 23:59.

[0080] Build an algorithm group to exclude the wind direction being fixed at zero for a long time. The algorithm rule is: instantaneous wind direction!= 0°.

[0081] The evaluation probability is set to be greater than 1%, indicating that the data volume of the instantaneous wind direction not being zero within 24 hours reaches more than 1% (that is, the instantaneous wind direction is not zero for more than 14 minutes within one day).

[0082] No more algorithm groups are added.

[0083] Output the evaluation result. Exclude low temperature and missing measurement conditions. When there is wind within 24 hours, the difference between the instantaneous wind direction value and the average ten-minute wind direction in the sample set is small, and the data volume reaches more than 99%; and the data volume of the instantaneous wind direction not being zero within 24 hours reaches more than 1%. If the above conditions are met, the evaluation status is set to faulty, and the problem content is given: the wind direction is stuck, there is no change in the wind direction for a long time or the change angle is too small. The solution is given: replace the wind direction sensor.

[0084] Example 3: For the phenomenon of data reporting delay in automatic weather station observations, Example 3 provides a building block type evaluation method for data reporting delay of DSD14 type automatic weather stations, including the following steps:

[0085] Select the automatic weather station model DSD14 and the communication module of the communication system, clarify the evaluation idea of data reporting delay, and the time interval between the observation time and the data storage time is long.

[0086] Select the evaluation sample. For the problem of data reporting delay, select the data within the previous 24 hours (one day) before the current moment, sample at the whole hour, covering the time period from 00:00 to 23:00.

[0087] Build an algorithm group for data reporting delay. The algorithm rule is: storage time - observation time > 120 seconds.

[0088] The evaluation probability is set to be greater than 80%, indicating that the data with the storage time being delayed by more than 120 seconds after the observation time within 24 hours reaches more than 80%.

[0089] No more algorithm groups are added.

[0090] Output the evaluation results. For the data with the storage time within 24 hours delayed by more than two minutes after the observation time, more than 80% of them meet the requirements. Set the evaluation status to sub-healthy, give the problem content: continuous communication transmission delay, and give the solutions: reset the clock; replace the lithium battery of the clock; replace the communication module; tighten the antenna; erase the metal oxide layer of the SIM card.

[0091] The present disclosure provides a modular ground meteorological equipment health assessment method, which can freely combine and build the evaluation algorithms of each module or system, and can modify and expand the algorithms according to the actual situation. This method can not only improve the accuracy and timeliness of evaluation, reduce the development cost, but also be widely applicable to different types of ground meteorological equipment and observation tasks, solving the problems of the traditional ground meteorological equipment health assessment architecture program being "written to death", with low flexibility, difficult adjustment and limited application scenarios. The modular ground meteorological equipment health assessment method has the characteristics of flexibility, accuracy and low cost, providing strong support for meteorological equipment guarantee.

[0092] It should be noted that, for the foregoing method embodiments, for the sake of simple description, they are all expressed as a series of action combinations. However, those skilled in the art should know that the present disclosure is not limited by the described action sequence, because according to the present disclosure, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily essential to the present disclosure.

[0093] The above is the introduction of the method embodiments. The following further illustrates the solution of the present disclosure through device embodiments.

[0094] Figure 2 The block diagram of a modular ground meteorological equipment health assessment device 200 according to an embodiment of the present disclosure is shown. As Figure 2 shown, the device 200 includes:

[0095] A target determination module 201, configured to determine an evaluation target for a module based on the type of the automatic station to be evaluated and the evaluation algorithm;

[0096] A sample selection module 202, configured to select an evaluation sample based on the evaluation target;

[0097] An algorithm construction module 203, configured to select a corresponding evaluation basic set based on the evaluation target to construct a modular evaluation algorithm;

[0098] A probability setting module 204, configured to determine the evaluation probability of the modular evaluation algorithm;

[0099] The result output module 205 is configured to determine whether the evaluation result obtained by the building block type evaluation algorithm meets the evaluation probability and output the corresponding health status.

[0100] Those skilled in the art can clearly understand that for the convenience and conciseness of description, the specific working processes of the described modules can refer to the corresponding processes in the foregoing method embodiments and will not be elaborated herein.

[0101] In the technical solution of the present disclosure, the acquisition, storage, and application of the user's personal information involved all comply with the provisions of relevant laws and regulations and do not violate public order and good customs.

[0102] According to an embodiment of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium, and a computer program product.

[0103] Figure 3 FIG. shows a schematic block diagram of an electronic device 300 that can be used to implement the embodiments of the present disclosure. The electronic device is intended to represent various forms of digital computers, such as, a laptop computer, a desktop computer, a workbench, a personal digital assistant, a server, a blade server, a mainframe computer, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as, a personal digital processor, a cellular phone, a smart phone, a wearable device, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0104] The electronic device 300 includes a computing unit 301, which can execute various appropriate actions and processes according to the computer program stored in the ROM 302 or the computer program loaded from the storage unit 308 into the RAM 303. In the RAM 303, various programs and data required for the operation of the electronic device 300 can also be stored. The computing unit 301, the ROM 302, and the RAM 303 are connected to each other through a bus 304. The I / O interface 305 is also connected to the bus 304.

[0105] A plurality of components in the electronic device 300 are connected to the I / O interface 305, including: an input unit 306, such as a keyboard, a mouse, etc.; an output unit 307, such as various types of displays, speakers, etc.; a storage unit 308, such as a magnetic disk, an optical disk, etc.; and a communication unit 309, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 309 allows the electronic device 300 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0106] The computing unit 301 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 301 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 301 executes the various methods and processes described above, such as method 100. For example, in some embodiments, method 100 may be implemented as a computer software program tangibly embodied in a machine-readable medium, such as the storage unit 308. In some embodiments, part or all of the computer program may be loaded and / or installed onto the electronic device 300 via the ROM 302 and / or the communication unit 309. When the computer program is loaded into the RAM 603 and executed by the computing unit 301, one or more steps of method 100 described above can be executed. Alternatively, in other embodiments, the computing unit 301 may be configured to execute method 100 in any other suitable manner (e.g., by means of firmware).

[0107] Various embodiments of the systems and techniques described above in this document can be implemented in digital electronic circuitry, integrated circuit systems, field-programmable gate arrays (FPGA), application-specific integrated circuits (ASIC), application-specific standard products (ASSP), system-on-a-chip (SOC), complex programmable logic devices (CPLD), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a dedicated or general-purpose programmable processor that receives data and instructions from a storage system, at least one input device, and at least one output device, and transmits the data and instructions to the storage system, the at least one input device, and the at least one output device.

[0108] The program code for implementing the methods of the present disclosure can be written in any combination of one or more programming languages. These program codes can be provided to the processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when the program codes are executed by the processor or controller, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The program code can be executed entirely on the machine, partially on the machine, as an independent software package partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0109] In the context of this disclosure, a machine-readable medium can be a tangible medium that can contain or store a program for use by or in connection with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0110] To provide for interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the computer. Other kinds of devices can also be used to provide for interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic, speech, or tactile input).

[0111] The systems and techniques described herein can be implemented in a computing system including a back-end component (e.g., as a data server), or a computing system including a middleware component (e.g., an application server), or a computing system including a front-end component (e.g., a user computer having a graphical user interface or a web browser through which the user can interact with an implementation of the systems and techniques described herein), or a computing system including any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), and the Internet.

[0112] A computer system can include a client and a server. The client and the server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, or a server of a distributed system, or a server incorporating a blockchain.

[0113] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution of this disclosure can be achieved, and no limitations are imposed herein.

[0114] The above specific embodiments do not constitute a limitation on the protection scope of this disclosure. Those skilled in the art should understand that various modifications, combinations, sub - combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure shall be included within the protection scope of this disclosure.

Claims

1. A method for health assessment of modular ground meteorological equipment, comprising: Determining an assessment objective for a module based on the ground meteorological equipment to be assessed and an assessment algorithm; Selecting assessment samples based on the selected objective; Selecting a corresponding assessment basis set based on the assessment objective to construct a modular assessment algorithm; Determining the assessment probability of the modular assessment algorithm; Judging whether the assessment result obtained by the modular assessment algorithm meets the assessment probability and outputting the corresponding health status, where the health status includes healthy, sub - healthy, and faulty.

2. The method according to claim 1, wherein The assessment algorithm for the module includes an acquisition system, a power supply system, a communication system, and a sensor system.

3. The method according to claim 1, wherein The selected objective includes an assessment duration, assessment sample conditions, and a data reading time period; the assessment basis set includes: assessment elements, logical operations, mathematical operations, relational comparison operations, mean calculation, and extreme value assessment.

4. The method according to claim 1, wherein The assessment probability is the proportion of data with a health status meeting the preset conditions screened out by the modular assessment algorithm in the selected assessment samples.

5. The method according to claim 1, wherein The step of judging whether the assessment result obtained by the modular assessment algorithm meets the assessment probability and outputting the corresponding health status includes: If the assessment result obtained by the modular assessment algorithm meets the assessment probability, directly output the corresponding health status, and give the problem location and corresponding solution for the sub - healthy or faulty status.

6. The method according to claim 1, characterized in that, There are multiple groups of the modular assessment algorithms, and each group of assessment algorithms corresponds to different assessment samples and assessment probabilities; according to the assessment results of each group of assessment algorithms and the logical relationship between each group of assessment algorithms, output the corresponding health status.

7. A device for health assessment of modular ground meteorological equipment, comprising: An objective determination module for determining an assessment objective for a module based on the ground meteorological equipment to be assessed and an assessment algorithm; A sample selection module for selecting assessment samples based on the selected objective; An algorithm construction module for selecting a corresponding assessment basis set based on the assessment objective to construct a modular assessment algorithm; A probability setting module for determining the assessment probability of the modular assessment algorithm; A result output module for judging whether the assessment result obtained by the modular assessment algorithm meets the assessment probability and outputting the corresponding health status, where the health status includes healthy, sub - healthy, and faulty.

8. An electronic device, comprising: At least one processor; And A memory communicatively connected to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, and when the instructions are executed by the at least one processor, the at least one processor is enabled to execute the method according to any one of claims 1 - 6.

9. A non-transitory computer-readable storage medium storing computer instructions, wherein, The computer instructions are used to cause the computer to execute the method according to any one of claims 1 - 6.

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