Temperature and humidity monitoring method and server for electromagnetic compatibility laboratory

Abstract

The invention relates to the technical field of data processing, in particular to a temperature and humidity monitoring method and server for an electromagnetic compatibility laboratory, and the method comprises the steps: receiving first temperature and humidity data sent by at least one temperature and humidity sensor which is in communication connection with the server, the temperature and humidity sensor is arranged in at least one electromagnetic compatibility laboratory; performing adaptive processing on the first temperature and humidity data to obtain second temperature and humidity data; abnormal analysis is carried out on the second temperature and humidity data, target temperature and humidity data are obtained, and the target temperature and humidity data comprise abnormal temperature and humidity data and normal temperature and humidity data; and transmitting the target temperature and humidity data to a display device in the humidity remote monitoring system, so that the display device displays the target temperature and humidity data in real time. According to the method, the accuracy and real-time performance of temperature and humidity monitoring are improved, the maintenance cost is reduced, and the anti-interference capability of the system is enhanced.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a temperature and humidity monitoring method and server for an electromagnetic compatibility laboratory. Background Art

[0002] Under the current technological background, environmental temperature and humidity monitoring plays a vital role in many key areas. Third-party testing and certification, medicine, biology, materials, agriculture, chemical research laboratories, industrial production and storage, especially the electromagnetic compatibility of electronic products, have extremely high requirements for the stability and accuracy of environmental temperature and humidity.

[0003] However, the existing temperature and humidity monitoring technology has many shortcomings: on the one hand, the traditional temperature and humidity monitoring system relies on battery power supply, which requires regular battery replacement, and lacks real-time monitoring and remote control functions, making it difficult to cope with real-time changes in environmental parameters. On the other hand, although the wireless monitoring system based on ZigBee technology is easy to install and has strong scalability, its transmission distance is limited and its power consumption is high, which limits its application in a wider area. At the same time, although the system based on the GSM module can send environmental parameters, it cannot achieve real-time monitoring and can only send text messages at fixed times and locations.

[0004] In addition, the monitoring system based on NB-IoT technology has advantages in low power consumption and long-distance transmission, but its application in special environments such as electromagnetic compatibility laboratories is not yet widespread, and anti-electromagnetic interference technology needs further research. Existing monitoring systems generally have the following problems: insufficient real-time monitoring capabilities, high maintenance costs, limited transmission distances, poor anti-interference capabilities, insufficient system scalability, and poor user experience. Summary of the invention

[0005] One purpose of an embodiment of the present invention is to provide a temperature and humidity monitoring method and server for an electromagnetic compatibility laboratory, which is used to solve the technical problems in the prior art of insufficient real-time monitoring capability, high maintenance cost, limited transmission distance, poor anti-interference ability, and insufficient system scalability.

[0006] In a first aspect, an embodiment of the present invention provides a temperature and humidity monitoring method for an electromagnetic compatibility laboratory, which is applied to a server in a temperature and humidity remote monitoring system, and the method includes:

[0007] Receiving first temperature and humidity data sent by at least one temperature and humidity sensor, wherein the temperature and humidity sensor is communicatively connected to the server and the temperature and humidity sensor is deployed in at least one electromagnetic compatibility laboratory;

[0008] Adaptively processing the first temperature and humidity data to obtain second temperature and humidity data;

[0009] Performing an abnormality analysis on the second temperature and humidity data to obtain target temperature and humidity data, wherein the target temperature and humidity data includes abnormal temperature and humidity data and normal temperature and humidity data;

[0010] The target temperature and humidity data are transmitted to a display device in the humidity remote monitoring system so that the display device displays the target temperature and humidity data in real time.

[0011] In a second aspect, an embodiment of the present invention provides a temperature and humidity monitoring device for an electromagnetic compatibility laboratory, which is applied to a server in a temperature and humidity remote monitoring system, and the device includes:

[0012] A receiving unit, configured to receive first temperature and humidity data sent by at least one temperature and humidity sensor, wherein the temperature and humidity sensor is communicatively connected to the server and is deployed in at least one electromagnetic compatibility laboratory;

[0013] a processing unit, configured to adaptively process the first temperature and humidity data to obtain second temperature and humidity data;

[0014] an analyzing unit, configured to perform an abnormality analysis on the second temperature and humidity data to obtain target temperature and humidity data, wherein the target temperature and humidity data includes abnormal temperature and humidity data and normal temperature and humidity data;

[0015] A transmitting unit is used to transmit the target temperature and humidity data to a display device in the humidity remote monitoring system, so that the display device displays the target temperature and humidity data in real time.

[0016] In a third aspect, an embodiment of the present invention provides a server, including:

[0017] at least one processor; and,

[0018] a memory communicatively connected to the at least one processor; wherein,

[0019] The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to the first aspect.

[0020] In a fourth aspect, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, wherein the computer program includes program instructions, and when the program instructions are executed by a processor, the processor executes the method as described in the first aspect.

[0021] In the scheme implemented by the above-mentioned temperature and humidity monitoring method, server, device and storage medium for electromagnetic compatibility laboratory, this method can realize real-time monitoring of the environmental conditions of the electromagnetic compatibility laboratory by receiving first temperature and humidity data sent by at least one temperature and humidity sensor and ensuring the communication connection between the sensor and the server, that is, the remote communication capability enables management personnel to obtain key environmental data without being present in person, thereby improving the convenience and efficiency of monitoring; adaptively processing the first temperature and humidity data to obtain more accurate and stable second temperature and humidity data helps to eliminate sensor noise and system errors and ensure the reliability of monitoring results, that is, it can adapt to environmental changes, improve data accuracy, and provide high-quality basic data for subsequent analysis; further processing the second temperature and humidity data Abnormal analysis of data can effectively distinguish between normal and abnormal temperature and humidity data, which helps to detect abnormal changes in environmental conditions in a timely manner; further abnormal analysis can be used to obtain target temperature and humidity data, including abnormal and normal data, to provide decision support for laboratory environmental management, so that managers can take corresponding measures for different environmental conditions, such as adjusting laboratory conditions or initiating emergency plans; the target temperature and humidity data are transmitted to the display device in real time to ensure the visualization and immediacy of environmental data. Real-time display helps to quickly identify environmental changes, allowing managers to respond quickly, thereby preventing potential risks and damages; it further improves the level of intelligence of electromagnetic compatibility laboratory environmental management, reduces the need for human intervention, and reduces management costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative labor.

[0023] Figure 1 It is a structural schematic diagram of a temperature and humidity remote monitoring system in one embodiment of the present invention;

[0024] Figure 2 It is a flow chart of a temperature and humidity monitoring method for an electromagnetic compatibility laboratory in one embodiment of the present invention;

[0025] Figure 3 It is a structural schematic diagram of a temperature and humidity monitoring device for an electromagnetic compatibility laboratory in one embodiment of the present invention;

[0026] Figure 4 It is a schematic diagram of the structure of a server in one embodiment of the present invention. DETAILED DESCRIPTION

[0027] In order to make the purpose, technical scheme and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0028] It should be noted that, if there is no conflict, the various features in the embodiments of the present invention can be combined with each other, all within the scope of protection of the present invention. In addition, although the functional modules are divided in the device schematic diagram and the logical order is shown in the flow chart, in some cases, the steps shown or described can be performed in a different order from the module division in the device or the flow chart. Furthermore, the words "first", "second", "third", etc. used in the present invention do not limit the data and execution order, but only distinguish the same items or similar items with basically the same functions and effects.

[0029] The technical solution of this application can be applied to various electromagnetic compatibility laboratory scenarios.

[0030] In the temperature and humidity monitoring method for an electromagnetic compatibility laboratory, a server in a temperature and humidity remote monitoring system is applied, wherein: Figure 1 This is a structural schematic diagram of a temperature and humidity remote monitoring system provided in an embodiment of the present application. The temperature and humidity remote monitoring system 10 includes a temperature and humidity sensor 20, a data transmission module 30, a server 40 and a display device 50.

[0031] Among them, the temperature and humidity remote monitoring system is a comprehensive system used to monitor and manage temperature and humidity data in the environment in real time.

[0032] The temperature and humidity sensor 20 is a high-precision sensor used to measure the temperature and humidity data in the electromagnetic compatibility laboratory in real time. The temperature and humidity sensor is deployed in at least one electromagnetic compatibility laboratory. The temperature and humidity sensor 20 is usually equipped with a wired (such as RS-485) or wireless (such as Wi-Fi, Bluetooth) communication interface for data transmission.

[0033] The data transmission module 30 is responsible for transmitting the temperature and humidity data collected by the sensor 20 to the server 40. The data transmission module 30 can be transmitted by wired transmission (such as Ethernet, serial communication) or wireless transmission (such as Wi-Fi, 4G / 5G network). In order to ensure data security, the transmission process may include encryption measures. The data transmission module 30 may include network management functions to ensure the stability and reliability of data transmission.

[0034] Among them, the server 40 is responsible for receiving, processing, storing and analyzing temperature and humidity data. The server 40 runs adaptive filtering algorithms and other data processing programs to optimize data quality. The server 40 has a large-capacity storage space for long-term storage of temperature and humidity data. The server 40 supports remote access, allowing users to monitor data via the Internet. The server 40 can be configured with an alarm system to automatically notify relevant personnel when environmental conditions exceed preset thresholds.

[0035] The display device 50 is used to display the processed temperature and humidity data in real time for user monitoring. The display type of the display device 50 can be a computer monitor, an LED display screen, or any other suitable display device. The display device 50 may have a touch screen or other interactive functions to enable users to operate and view data more conveniently. The display device 50 can display data from multiple sensors at the same time and provide data visualization tools such as charts and trend analysis.

[0036] Specifically, the temperature and humidity remote monitoring system can collect and process environmental data in real time and provide instant feedback; it supports the storage and analysis of historical data to help users identify trends and anomalies; when the temperature and humidity exceed the set range, the system can automatically issue an alarm notification to remind users to take measures; users can remotely access the system through the Internet to view data and manage equipment.

[0037] In summary, through the collaborative work of the above modules, the temperature and humidity remote monitoring system can effectively help users monitor and manage environmental conditions and improve work efficiency and safety.

[0038] In view of this, the present application proposes a temperature and humidity monitoring method for an electromagnetic compatibility laboratory to solve the above problems, which is described in detail below.

[0039] See also Figure 2 , Figure 2 A flow chart of a temperature and humidity monitoring method for an electromagnetic compatibility laboratory provided by an embodiment of the present invention, the method comprising the following steps:

[0040] S10. Receive first temperature and humidity data sent by at least one temperature and humidity sensor, where the temperature and humidity sensor is communicatively connected to the server and is deployed in at least one electromagnetic compatibility laboratory.

[0041] The first temperature and humidity data refers to the original environmental data directly obtained from the temperature and humidity sensor, including the values ​​of temperature and humidity. The first temperature and humidity data is the initial measurement result without any processing.

[0042] The communication connection refers to a data transmission path established between the sensor and the server. The communication connection can be wired (such as Ethernet, USB, etc.) or wireless (such as Wi-Fi, Bluetooth, ZigBee, etc.). S20. Adaptively process the first temperature and humidity data to obtain second temperature and humidity data.

[0043] Among them, the electromagnetic compatibility (EMC) laboratory is a facility used to test and verify the performance of electronic equipment and systems in an electromagnetic environment. Its purpose is to ensure that the equipment operates normally in an electromagnetic environment without interference and does not interfere with other equipment. Such laboratories are usually equipped with shielded rooms, anechoic chambers and various test equipment.

[0044] Specifically, the server obtains data from the temperature and humidity sensor through a preset communication protocol and interface.

[0045] Specifically, the temperature and humidity sensors are installed at appropriate locations in the electromagnetic compatibility laboratory so that they can accurately measure the environmental conditions in the laboratory.

[0046] It can be seen that in this embodiment, the environmental conditions of the electromagnetic compatibility laboratory can be effectively monitored through the temperature and humidity sensors in the electromagnetic compatibility laboratory, and the monitoring data can be timely and accurately transmitted to the server for processing and analysis.

[0047] S20. Adaptively process the first temperature and humidity data to obtain second temperature and humidity data.

[0048] Adaptive processing is the process of dynamically adjusting data processing algorithms to optimize results under different environmental conditions. Adaptive processing can automatically adjust its parameters or methods based on real-time changing input data or environmental conditions to improve data accuracy and reliability.

[0049] The second temperature and humidity data is data that has been processed by adaptive processing, and is usually more accurate and reliable. Through adaptive processing, noise, errors or inconsistencies in the original data are corrected or eliminated.

[0050] Optionally, before adaptively processing the first temperature and humidity data, the first temperature and humidity data may need to be preprocessed, such as removing obvious outliers, filling missing data, or standardizing the data format.

[0051] Among them, the specific implementation process of adaptively processing the first temperature and humidity data to obtain the second temperature and humidity data can be referred to S201-S202, and no repeated limitation is made here.

[0052] It can be seen that, in this embodiment, the quality of temperature and humidity data can be significantly improved through adaptive processing, that is, the accuracy and reliability of temperature and humidity data can be improved, providing a more reliable basis for subsequent monitoring and decision-making.

[0053] S201. In one embodiment, the adaptive processing of the first temperature and humidity data to obtain the second temperature and humidity data includes: performing feature analysis on the first temperature and humidity data to obtain first feature data corresponding to the first temperature and humidity data; determining an adaptive filtering algorithm corresponding to the first temperature and humidity data based on the first feature data corresponding to the first temperature and humidity data; determining filtering parameters of the filter in the server based on the adaptive filtering algorithm, the filtering parameters being used to process the first temperature and humidity data; and performing data processing on the first temperature and humidity data based on the filtering parameters to obtain second temperature and humidity data.

[0054] Feature analysis refers to extracting useful information or features from raw data in order to better understand the structure or behavior of the data. Feature analysis may involve signal processing techniques such as Fourier transform or wavelet transform to identify frequency characteristics or time-local features.

[0055] The first characteristic data is the result obtained by performing characteristic analysis on the first temperature and humidity data, and it usually includes statistical characteristics of the data (such as mean, variance, frequency component, etc.) or other information that helps to describe the data behavior.

[0056] Among them, the adaptive filtering algorithm is an algorithm that can automatically adjust its parameters according to the characteristics of the input data to optimize the filtering performance. The adaptive filtering algorithm includes but is not limited to the least mean square (LMS), recursive least square (RLS), etc.

[0057] Specifically, according to the first characteristic data, a suitable adaptive filtering algorithm is selected. The selection process takes into account the characteristics of the data, such as noise level, dynamic changes or nonlinear behavior. Different filtering algorithms are suitable for different data characteristics. For example, the Kalman filter is suitable for linear Gaussian systems, while the adaptive mean filter may be more suitable for nonlinear or non-Gaussian data.

[0058] Among them, the filter parameters are the parameters used to process data inside the filter, such as weight coefficient, step size, delay, etc. The setting of the filter parameters has a direct impact on the performance of the filter.

[0059] The first temperature and humidity data is filtered using the determined filtering parameters. The filtering process removes noise from the data, corrects errors, and smoothes the data curve. After filtering, the second temperature and humidity data is generated. The second temperature and humidity data more accurately reflects the real environmental conditions and is suitable for subsequent analysis and decision-making.

[0060] It can be seen that in this embodiment, the server can efficiently extract feature information from the original temperature and humidity data, select a suitable filtering algorithm and optimize filtering parameters, thereby improving the quality and reliability of the data.

[0061] S202. In one embodiment, the method of determining the adaptive filtering algorithm corresponding to the first temperature and humidity data based on the first characteristic data corresponding to the first temperature and humidity data includes: judging whether the first characteristic data corresponding to the first temperature and humidity data satisfies a preset smooth signal characteristic; if the preset smooth signal characteristic is satisfied, determining the first adaptive filtering algorithm as the adaptive filtering algorithm corresponding to the first temperature and humidity data; or, if the preset smooth signal characteristic is not satisfied, determining the second adaptive filtering algorithm as the adaptive filtering algorithm corresponding to the first temperature and humidity data.

[0062] Among them, a stationary signal is a signal whose statistical characteristics do not change over time. This means that the characteristics of a stationary signal, such as the mean, variance, autocorrelation and other statistics, remain constant over time. Stationary signals are usually easy to predict and process because their characteristics do not change over time.

[0063] Specifically, the statistical properties of a stationary signal (such as mean and variance) do not change over time and have obvious periodicity, such as periodic fluctuations caused by certain environmental factors.

[0064] Among them, usually, the mean and variance of a stationary signal are constant in time, and the autocorrelation function depends only on the time difference rather than the absolute time. The judgment process may involve statistical tests, such as unit root test, stationarity test, etc., to quantify the stationarity of the signal.

[0065] Among them, if the preset stable signal characteristics are met, the first adaptive filtering algorithm is determined to be the adaptive filtering algorithm corresponding to the first temperature and humidity data, and the first adaptive filtering algorithm can be a mean filter, a low-pass filter or an LMS (Least Mean Squares) algorithm, which is not limited here. For stable signals, the LMS algorithm can effectively track the changes in the signal and provide sufficient filtering performance.

[0066] Among them, if the preset stationary signal characteristics are not met, the current signal is non-stationary, so the second adaptive filtering algorithm can be a Kalman filter, an adaptive noise eliminator or an RLS (Recursive Least Squares) algorithm, which is not limited here. The RLS algorithm has a faster convergence speed and can quickly adapt to signal changes. The RLS algorithm can provide higher filtering accuracy when processing non-stationary signals. The RLS algorithm can better handle the time-varying and bursty nature of the signal because it takes into account all past data, rather than just the most recent few data points.

[0067] Therefore, stationarity → LMS algorithm: is suitable for situations where the statistical characteristics of the signal do not change over time.

[0068] Non-stationarity → RLS algorithm: Applicable to situations where the statistical characteristics of the signal change over time.

[0069] It can be seen that in this embodiment, a suitable adaptive filtering algorithm is selected according to the characteristics of the temperature and humidity data to ensure the accuracy and reliability of the monitoring process.

[0070] S30. Perform an abnormality analysis on the second temperature and humidity data to obtain target temperature and humidity data, where the target temperature and humidity data includes abnormal temperature and humidity data and normal temperature and humidity data.

[0071] Among them, anomaly analysis is used to identify abnormal patterns or values ​​in the data. In temperature and humidity monitoring, anomalies may refer to extreme temperature or humidity values, or sudden changes that do not conform to the laws of environmental changes.

[0072] Among them, the target temperature and humidity data is the result data obtained after abnormal analysis, which is divided into abnormal temperature and humidity data and normal temperature and humidity data. Abnormal data usually requires further attention or processing, while normal data is used for routine analysis and application.

[0073] Among them, abnormal temperature and humidity data refer to data points identified as abnormal in anomaly analysis, which may indicate that environmental conditions are beyond the normal range.

[0074] Among them, normal temperature and humidity data refer to data points identified as normal in anomaly analysis, which reflect the normal operating conditions of the laboratory environment.

[0075] Optionally, anomaly analysis may include but is not limited to statistical methods, machine learning methods, and time series analysis methods. Among them, the statistical method may be Z-score, box plot method, used to detect outliers; the machine learning method may be isolation forest, support vector machine, used to identify anomalies in complex patterns; the time series analysis method may be ARIMA model, used to detect abnormal fluctuations in time series.

[0076] Among them, the specific implementation process of performing abnormal analysis on the second temperature and humidity data to obtain the target temperature and humidity data can be referred to S301-S304, and no repeated limitation is made here.

[0077] It can be seen that through abnormal analysis in this embodiment, the temperature and humidity environment of the laboratory can be effectively monitored, and then the abnormal conditions in the temperature and humidity data can be effectively identified and processed, which helps to maintain the stability and safety of the laboratory environment and ensure the accuracy and reliability of the experimental data.

[0078] S301. In one embodiment, the abnormality analysis of the second temperature and humidity data to obtain target temperature and humidity data includes: performing data preprocessing on the second temperature and humidity data to obtain preprocessed third temperature and humidity data; performing feature extraction on the third temperature and humidity data to obtain second feature data corresponding to the third temperature and humidity data; performing feature data screening on the second feature data to obtain target feature data suitable for abnormality analysis; inputting the target feature data into a preset model for training to obtain an abnormality analysis value output by the preset model, wherein the preset model is a pre-trained model and includes historical temperature and humidity data in the pre-training; and obtaining the target temperature and humidity data according to the abnormality analysis value.

[0079] Data preprocessing refers to cleaning, converting and standardizing raw data before data analysis to improve data quality and analysis results. Preprocessing includes steps such as removing noise, filling missing values ​​and data normalization.

[0080] In a specific implementation, the data preprocessing process can be to clean the second temperature and humidity data to remove noise and outliers; further fill in missing values, possibly using interpolation or average value replacement; then, normalize or standardize the data to ensure the comparability of different data dimensions; finally, output the preprocessed third temperature and humidity data.

[0081] Among them, the third temperature and humidity data is preprocessed data with higher quality and consistency, suitable for in-depth analysis and feature extraction.

[0082] Among them, feature data screening is to select the most valuable features for analysis from the extracted feature set to reduce computational complexity and improve model accuracy.

[0083] Specifically, the feature data screening process can use correlation analysis, information gain, principal component analysis and other methods to select the most important features.

[0084] The second data feature may include mean value, standard deviation, kurtosis, skewness, frequency component, etc.

[0085] A pre-set model is a model that has been trained and is ready for prediction or classification to perform a specific task, such as anomaly analysis. The model uses historical data during training to learn the patterns and characteristics of the data.

[0086] Specifically, the preset model may be a supervised learning model, such as a random forest, a neural network, etc., which has been trained on historical temperature and humidity data.

[0087] The abnormal analysis value is the result output by the preset model after analyzing the input data, which is used to identify abnormalities in the data. The abnormal analysis value can be a numerical value or a score, which is used to indicate the degree to which the data point deviates from the normal state.

[0088] It can be seen that the server in this embodiment can effectively preprocess and analyze temperature and humidity data, extract key features and perform anomaly detection. The use of further preset models improves the accuracy and efficiency of anomaly analysis.

[0089] S302. In one embodiment, the target temperature and humidity data are obtained based on the abnormal analysis value, including: when the abnormal analysis value is within the preset temperature and humidity data range, determining that the second temperature and humidity data corresponding to the target characteristic data is the normal temperature and humidity data; or, when the abnormal analysis value is not within the preset temperature and humidity data range, determining that the second temperature and humidity data corresponding to the target characteristic data is the abnormal temperature and humidity data.

[0090] The preset temperature and humidity data range is a normal temperature and humidity value range set according to historical data, environmental standards or business requirements. The preset temperature and humidity data range is usually used to determine whether the current data conforms to the normal state.

[0091] Among them, normal temperature and humidity data refers to data within the preset temperature and humidity data range, indicating that the environmental conditions meet the expected normal operating conditions.

[0092] Among them, abnormal temperature and humidity data refers to data that exceeds the preset temperature and humidity data range, indicating that the environmental conditions may have an adverse effect on the experiment or equipment operation.

[0093] Specifically, based on the abnormal analysis value being within the preset range, the corresponding second temperature and humidity data is classified as normal; based on the abnormal analysis value being outside the preset range, the corresponding second temperature and humidity data is classified as abnormal.

[0094] Optionally, for normal temperature and humidity data, record and continue to monitor; for abnormal temperature and humidity data, trigger an alarm or take corrective measures such as equipment inspection, environmental adjustment or data correction; feed the analysis results back to the system to optimize the model and preset range, and improve the accuracy of subsequent analysis.

[0095] It can be seen that in this embodiment, the abnormal analysis value can effectively identify and classify normal and abnormal conditions in the temperature and humidity data, which further helps to quickly respond to environmental changes, prevent potential risks, and ensure the smooth progress of the experiment.

[0096] S303. In one embodiment, the abnormal analysis of the second temperature and humidity data to obtain the target temperature and humidity data includes: obtaining historical temperature and humidity data and the corresponding first electromagnetic compatibility laboratory serial number; obtaining the second electromagnetic compatibility laboratory serial number corresponding to the second temperature and humidity data; if the first electromagnetic compatibility laboratory serial number is the same as the second electromagnetic compatibility laboratory serial number, then comparing the historical temperature and humidity data with the second temperature and humidity data to obtain a first comparison value; when the first comparison value is within a first preset comparison threshold, determining that the second temperature and humidity data is the normal temperature and humidity data; or, when the first comparison value is not within the first preset comparison threshold, determining that the second temperature and humidity data is the abnormal temperature and humidity data.

[0097] Among them, historical temperature and humidity data refers to the temperature and humidity information recorded from the electromagnetic compatibility laboratory over the past period of time. Historical temperature and humidity data is used to analyze trends, set benchmarks, and conduct comparative analysis.

[0098] The first electromagnetic compatibility laboratory serial number refers to the unique identifier assigned to a specific electromagnetic compatibility laboratory, which is used to distinguish different laboratories. The serial number is associated with the historical temperature and humidity data to ensure the accuracy of the data source.

[0099] The second electromagnetic compatibility laboratory serial number refers to the unique identifier of the laboratory currently collecting the second temperature and humidity data.

[0100] Specifically, if the serial numbers are the same, it means that the current data and the historical data are from the same laboratory, and the data comparison can continue.

[0101] The first comparison value is a result obtained by comparing the historical temperature and humidity data with the second temperature and humidity data, and the first comparison value indicates the degree of difference between the two.

[0102] The first preset comparison threshold is used to determine whether the comparison value is within an acceptable range to determine whether the temperature and humidity data are normal. The first preset comparison threshold can be set manually or obtained by experiment, and is not limited here.

[0103] Specifically, the process of obtaining the serial number may be extracting it from a database or a data storage system.

[0104] It can be seen that in this embodiment, the serial number of the electromagnetic compatibility laboratory is used to determine whether they are from the same laboratory. If they are in the same laboratory, the normality of the current data is directly evaluated using historical data, thereby improving the accuracy and efficiency of electromagnetic compatibility laboratory environment monitoring.

[0105] S304. In one embodiment, after obtaining the second electromagnetic compatibility laboratory serial number corresponding to the second temperature and humidity data, the method also includes: if the first electromagnetic compatibility laboratory serial number and the second electromagnetic compatibility laboratory serial number are not the same, obtaining an error value, and the error value is obtained according to the first standard value corresponding to the first electromagnetic compatibility laboratory serial number and the second standard value corresponding to the second electromagnetic compatibility laboratory serial number; according to the error value, performing data processing on the second temperature and humidity data to obtain fourth temperature and humidity data; performing data comparison on the historical temperature and humidity data and the fourth temperature and humidity data to obtain a second comparison value; when the second comparison value is within the second preset comparison threshold, determining that the second temperature and humidity data is the normal temperature and humidity data; or, when the second comparison value is not within the second preset comparison threshold, determining that the second temperature and humidity data is the abnormal temperature and humidity data.

[0106] The error value is the difference between the standard values ​​of two different electromagnetic compatibility laboratories, which is used to correct or evaluate the consistency of data.

[0107] Among them, the standard value is the benchmark value set by each electromagnetic compatibility laboratory based on its equipment and environmental conditions to ensure the consistency and accuracy of the data.

[0108] Among them, the first standard value is the reference temperature and humidity standard value associated with the first electromagnetic compatibility laboratory serial number; the second standard value is the reference temperature and humidity standard value associated with the second electromagnetic compatibility laboratory serial number.

[0109] The fourth temperature and humidity data is obtained by performing error correction on the second temperature and humidity data, aiming to eliminate the influence of differences between laboratories.

[0110] The second comparison value is a value obtained by comparing and analyzing the historical temperature and humidity data with the corrected fourth temperature and humidity data, and is used to evaluate the degree of data deviation.

[0111] The second preset comparison threshold is used to determine the standard range of the second comparison result, and is used to distinguish between normal and abnormal states. The second preset comparison threshold can be set manually or obtained by experiment, and is not limited here.

[0112] Specifically, the process of calculating the error value can be direct difference, that is, simple numerical subtraction; or, proportional adjustment, if the standard value is in the form of a ratio or percentage, a proportional calculation is performed.

[0113] The data processing may be to correct the second temperature and humidity data using the calculated error value to generate the fourth temperature and humidity data. The correction process may include: adding and subtracting the error value, adjusting the data according to the error value; scaling, scaling the data according to the error value.

[0114] Specifically, if the comparison value is within the second preset comparison threshold range: the second temperature and humidity data is determined to be normal temperature and humidity data, and the data is considered to be in line with historical trends and expectations; if the comparison value is not within the threshold range, the second temperature and humidity data is determined to be abnormal temperature and humidity data, which may indicate a potential problem and requires further investigation.

[0115] It can be seen that the server in this embodiment can process temperature and humidity data from different electromagnetic compatibility laboratories, even if there are differences in the standard values ​​of these laboratories, further ensuring that the temperature and humidity data can be accurately evaluated and monitored even in different laboratory environments, thereby maintaining the accuracy and reliability of the experiment.

[0116] S40: Transmit the target temperature and humidity data to a display device in the humidity remote monitoring system, so that the display device displays the target temperature and humidity data in real time.

[0117] Among them, display devices refer to hardware devices used to display temperature and humidity data in real time, such as monitors, display screens, mobile devices, etc. They are windows for users to view and monitor environmental data.

[0118] In the transmission process, an appropriate communication protocol (such as TCP / IP, serial communication, etc.) is used to send the target temperature and humidity data from the server to the display device. The transmission process may include data packaging, encryption (if necessary) and sending.

[0119] Further, after receiving the data, the display device decodes it and displays it on the screen. The display can be a chart, a digital readout, or any other intuitive form so that the user can quickly understand the current environmental conditions.

[0120] Optionally, the server continuously collects new temperature and humidity data and updates the information on the display device periodically (e.g., every second or every minute). Real-time updates ensure that users always see the latest data, which is critical for monitoring and responding to environmental changes.

[0121] Optionally, allow the user to interact with the display device, such as adjusting display settings, viewing historical data, or receiving alert notifications.

[0122] It can be seen that the humidity remote monitoring system in this embodiment can provide an intuitive interface, allowing users to monitor and manage environmental humidity in real time.

[0123] The method can realize real-time monitoring of the environmental conditions of the electromagnetic compatibility laboratory by receiving first temperature and humidity data sent by at least one temperature and humidity sensor and ensuring the communication connection between the sensor and the server, that is, the remote communication capability enables the management personnel to obtain key environmental data without being present in person, thereby improving the convenience and efficiency of monitoring; adaptive processing is performed on the first temperature and humidity data to obtain more accurate and stable second temperature and humidity data, which helps to eliminate sensor noise and system errors and ensure the reliability of the monitoring results, that is, it can adapt to environmental changes, improve the accuracy of the data, and provide high-quality basic data for subsequent analysis; further abnormal analysis is performed on the second temperature and humidity data, which can effectively distinguish between normal and abnormal Normal temperature and humidity data helps to detect abnormal changes in environmental conditions in a timely manner; further abnormal analysis is used to obtain target temperature and humidity data, including abnormal and normal data, which provides decision support for laboratory environmental management, allowing managers to take corresponding measures for different environmental conditions, such as adjusting laboratory conditions or initiating emergency plans; the target temperature and humidity data is transmitted to the display device in real time to ensure the visualization and immediacy of environmental data. Real-time display helps to quickly identify environmental changes, allowing managers to respond quickly, thereby preventing potential risks and damages; the level of intelligence of electromagnetic compatibility laboratory environmental management is further improved, the need for human intervention is reduced, and management costs are reduced.

[0124] It should be noted that, in each of the above-mentioned embodiments, there is not necessarily a certain order between the above-mentioned steps. A person skilled in the art can understand, based on the description of the embodiments of the present application, that in different embodiments, the above-mentioned steps may have different execution orders, that is, they may be executed in parallel, may be executed interchangeably, and so on.

[0125] As another aspect of the embodiment of the present application, the embodiment of the present application provides a temperature and humidity monitoring device for an electromagnetic compatibility laboratory. The temperature and humidity monitoring device for an electromagnetic compatibility laboratory can be a software module, which includes a number of instructions stored in a memory, and the processor can access the memory and call the instructions for execution to complete the temperature and humidity monitoring method for an electromagnetic compatibility laboratory described in the above-mentioned various embodiments.

[0126] See also Figure 3 , Figure 3 Schematic diagram of a temperature and humidity monitoring device for an electromagnetic compatibility laboratory provided in an embodiment of the present application. Figure 3 As shown, the server used in the temperature and humidity remote monitoring system, the temperature and humidity monitoring device 300 for the electromagnetic compatibility laboratory includes:

[0127] A receiving unit 301 is used to receive first temperature and humidity data sent by at least one temperature and humidity sensor, wherein the temperature and humidity sensor is communicatively connected to the server and is deployed in at least one electromagnetic compatibility laboratory;

[0128] A processing unit 302 is used to adaptively process the first temperature and humidity data to obtain second temperature and humidity data;

[0129] An analysis unit 303 is used to perform an abnormality analysis on the second temperature and humidity data to obtain target temperature and humidity data, where the target temperature and humidity data includes abnormal temperature and humidity data and normal temperature and humidity data;

[0130] The transmitting unit 304 is used to transmit the target temperature and humidity data to the display device in the humidity remote monitoring system, so that the display device displays the target temperature and humidity data in real time.

[0131] The method can realize real-time monitoring of the environmental conditions of the electromagnetic compatibility laboratory by receiving first temperature and humidity data sent by at least one temperature and humidity sensor and ensuring the communication connection between the sensor and the server, that is, the remote communication capability enables the management personnel to obtain key environmental data without being present in person, thereby improving the convenience and efficiency of monitoring; adaptive processing is performed on the first temperature and humidity data to obtain more accurate and stable second temperature and humidity data, which helps to eliminate sensor noise and system errors and ensure the reliability of the monitoring results, that is, it can adapt to environmental changes, improve the accuracy of the data, and provide high-quality basic data for subsequent analysis; further abnormal analysis is performed on the second temperature and humidity data, which can effectively distinguish between normal and abnormal Normal temperature and humidity data helps to detect abnormal changes in environmental conditions in a timely manner; further abnormal analysis is used to obtain target temperature and humidity data, including abnormal and normal data, which provides decision support for laboratory environmental management, allowing managers to take corresponding measures for different environmental conditions, such as adjusting laboratory conditions or initiating emergency plans; the target temperature and humidity data is transmitted to the display device in real time to ensure the visualization and immediacy of environmental data. Real-time display helps to quickly identify environmental changes, allowing managers to respond quickly, thereby preventing potential risks and damages; the level of intelligence of electromagnetic compatibility laboratory environmental management is further improved, the need for human intervention is reduced, and management costs are reduced.

[0132] In one embodiment, in the adaptive processing of the first temperature and humidity data to obtain the second temperature and humidity data, the processing unit 302 is further used to: perform feature analysis on the first temperature and humidity data to obtain first feature data corresponding to the first temperature and humidity data; determine an adaptive filtering algorithm corresponding to the first temperature and humidity data based on the first feature data corresponding to the first temperature and humidity data; determine filtering parameters of the filter in the server based on the adaptive filtering algorithm, and the filtering parameters are used to process the first temperature and humidity data; and perform data processing on the first temperature and humidity data based on the filtering parameters to obtain second temperature and humidity data.

[0133] In one embodiment, in determining the adaptive filtering algorithm corresponding to the first temperature and humidity data based on the first characteristic data corresponding to the first temperature and humidity data, the processing unit 302 is further used to: determine whether the first characteristic data corresponding to the first temperature and humidity data satisfies a preset smooth signal characteristic; if the preset smooth signal characteristic is satisfied, determine that the first adaptive filtering algorithm is the adaptive filtering algorithm corresponding to the first temperature and humidity data; or, if the preset smooth signal characteristic is not satisfied, determine that the second adaptive filtering algorithm is the adaptive filtering algorithm corresponding to the first temperature and humidity data.

[0134] In one embodiment, in performing an abnormality analysis on the second temperature and humidity data to obtain target temperature and humidity data, the analysis unit 303 is further used to: perform data preprocessing on the second temperature and humidity data to obtain preprocessed third temperature and humidity data; perform feature extraction on the third temperature and humidity data to obtain second feature data corresponding to the third temperature and humidity data; perform feature data screening on the second feature data to obtain target feature data suitable for abnormality analysis; input the target feature data into a preset model for training to obtain an abnormality analysis value output by the preset model, wherein the preset model is a pre-trained model and includes historical temperature and humidity data in the pre-training; and obtain the target temperature and humidity data based on the abnormality analysis value.

[0135] In one embodiment, in obtaining the target temperature and humidity data according to the abnormal analysis value, the analysis unit 303 is further used to: when the abnormal analysis value is within the preset temperature and humidity data range, determine that the second temperature and humidity data corresponding to the target characteristic data is the normal temperature and humidity data; or, when the abnormal analysis value is not within the preset temperature and humidity data range, determine that the second temperature and humidity data corresponding to the target characteristic data is the abnormal temperature and humidity data.

[0136] In one embodiment, in the abnormal analysis of the second temperature and humidity data to obtain the target temperature and humidity data, the analysis unit 303 is also used to: obtain historical temperature and humidity data and the corresponding first electromagnetic compatibility laboratory serial number; obtain the second electromagnetic compatibility laboratory serial number corresponding to the second temperature and humidity data; if the first electromagnetic compatibility laboratory serial number and the second electromagnetic compatibility laboratory serial number are the same, compare the historical temperature and humidity data with the second temperature and humidity data to obtain a first comparison value; when the first comparison value is within the first preset comparison threshold, determine that the second temperature and humidity data is the normal temperature and humidity data; or, when the first comparison value is not within the first preset comparison threshold, determine that the second temperature and humidity data is the abnormal temperature and humidity data.

[0137] In one embodiment, after obtaining the second electromagnetic compatibility laboratory serial number corresponding to the second temperature and humidity data, the analysis unit 303 is further used to: if the first electromagnetic compatibility laboratory serial number and the second electromagnetic compatibility laboratory serial number are not the same, obtain an error value, and the error value is obtained according to the first standard value corresponding to the first electromagnetic compatibility laboratory serial number and the second standard value corresponding to the second electromagnetic compatibility laboratory serial number; according to the error value, perform data processing on the second temperature and humidity data to obtain fourth temperature and humidity data; perform data comparison on the historical temperature and humidity data and the fourth temperature and humidity data to obtain a second comparison value; when the second comparison value is within the second preset comparison threshold, determine that the second temperature and humidity data is the normal temperature and humidity data; or, when the second comparison value is not within the second preset comparison threshold, determine that the second temperature and humidity data is the abnormal temperature and humidity data.

[0138] It should be noted that the temperature and humidity monitoring device for an electromagnetic compatibility laboratory can execute the temperature and humidity monitoring method for an electromagnetic compatibility laboratory provided in the embodiment of the present application, and has the corresponding functional modules and beneficial effects of the execution method. For technical details not fully described in the embodiment of the temperature and humidity monitoring device for an electromagnetic compatibility laboratory, please refer to the temperature and humidity monitoring method for an electromagnetic compatibility laboratory provided in the embodiment of the present application.

[0139] See also Figure 4 , Figure 4 4 is a schematic diagram of a server structure provided in an embodiment of the present application. The server includes one or more processors 41 and a memory 42. The memory 42 is connected to the one or more processors 41, for example, connected to the processor 41 via a bus.

[0140] The processor 41 is configured to support the server to execute the corresponding functions in the method in the above method embodiment. The processor 41 can be a central processing unit (CPU), a network processor (NP), a hardware chip or any combination thereof. The above hardware chip can be an application specific integrated circuit (ASIC), a programmable logic device (PLD) or a combination thereof. The above PLD can be a complex programmable logic device (CPLD), a field-programmable gate array (FPGA), a generic array logic (GAL) or any combination thereof.

[0141] The memory 42 is used to store program codes, etc. The memory 42 may include a volatile memory (VM), such as a random access memory (RAM); the memory 42 may also include a non-volatile memory (NVM), such as a read-only memory (ROM), a flash memory, a hard disk drive (HDD) or a solid-state drive (SSD); the memory 42 may also include a combination of the above-mentioned types of memories.

[0142] The memory 42 can be used to store non-volatile software programs, non-volatile computer executable programs and modules, such as program instructions / modules corresponding to the temperature and humidity monitoring method for an electromagnetic compatibility laboratory in the embodiment of the present application. The processor 41 executes various functional applications and data processing of the temperature and humidity monitoring method for an electromagnetic compatibility laboratory and the temperature and humidity monitoring device for an electromagnetic compatibility laboratory by running the non-volatile software programs, instructions and modules stored in the memory 42, that is, to realize the functions of the various modules or units of the temperature and humidity monitoring method for an electromagnetic compatibility laboratory and the temperature and humidity monitoring device for an electromagnetic compatibility laboratory provided in the above method embodiment.

[0143] The memory 42 may include a program storage area and a data storage area, wherein the program storage area may store an operating system and an application required for at least one function. The data storage area may store data created according to the use of the temperature and humidity monitoring device for an electromagnetic compatibility laboratory, etc. In some embodiments, the memory 42 may optionally include a memory 42 remotely arranged relative to the processor 41, and these remote memories 42 may be connected to the temperature and humidity monitoring device for an electromagnetic compatibility laboratory via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0144] The one or more modules are stored in the memory 42. When executed by the one or more processors 41, the temperature and humidity monitoring method for the electromagnetic compatibility laboratory in any of the above-mentioned method embodiments is executed, for example, the method steps described in the above-mentioned method embodiments are executed to realize the functions of the modules described in the above-mentioned device embodiments.

[0145] An embodiment of the present application further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, wherein the computer program includes program instructions, and when the program instructions are executed by a computer, the computer executes the method described in the above embodiment.

[0146] A person skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium, and when the program is executed, it can include the processes of the embodiments of the above-mentioned methods. The storage medium can be a disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM), etc.

[0147] The above disclosure is only the preferred embodiment of the present application, which certainly cannot be used to limit the scope of rights of the present application. Therefore, equivalent changes made according to the claims of the present application are still within the scope covered by the present application.

Claims

1. A temperature and humidity monitoring method for an electromagnetic compatibility laboratory, characterized in that: Applied to a server in a temperature and humidity remote monitoring system, the method comprises: Receiving first temperature and humidity data sent by at least one temperature and humidity sensor, wherein the temperature and humidity sensor is communicatively connected to the server and the temperature and humidity sensor is deployed in at least one electromagnetic compatibility laboratory; Adaptively processing the first temperature and humidity data to obtain second temperature and humidity data; Performing an abnormality analysis on the second temperature and humidity data to obtain target temperature and humidity data, wherein the target temperature and humidity data includes abnormal temperature and humidity data and normal temperature and humidity data; The target temperature and humidity data are transmitted to a display device in the humidity remote monitoring system so that the display device displays the target temperature and humidity data in real time.

2. The method according to claim 1, characterized in that The step of adaptively processing the first temperature and humidity data to obtain second temperature and humidity data includes: Performing feature analysis on the first temperature and humidity data to obtain first feature data corresponding to the first temperature and humidity data; determining an adaptive filtering algorithm corresponding to the first temperature and humidity data according to first characteristic data corresponding to the first temperature and humidity data; Determine, according to the adaptive filtering algorithm, filtering parameters of the filter in the server, wherein the filtering parameters are used to process the first temperature and humidity data; The first temperature and humidity data are processed according to the filtering parameters to obtain second temperature and humidity data.

3. The method according to claim 2, characterized in that The step of determining an adaptive filtering algorithm corresponding to the first temperature and humidity data according to the first characteristic data corresponding to the first temperature and humidity data includes: Determining whether first characteristic data corresponding to the first temperature and humidity data meets a preset stable signal characteristic; If the preset stable signal characteristics are met, determining the first adaptive filtering algorithm as the adaptive filtering algorithm corresponding to the first temperature and humidity data; or, If the preset stable signal characteristics are not met, the second adaptive filtering algorithm is determined to be the adaptive filtering algorithm corresponding to the first temperature and humidity data.

4. The method according to claim 1, characterized in that The performing abnormal analysis on the second temperature and humidity data to obtain target temperature and humidity data includes: Performing data preprocessing on the second temperature and humidity data to obtain preprocessed third temperature and humidity data; Performing feature extraction on the third temperature and humidity data to obtain second feature data corresponding to the third temperature and humidity data; Performing feature data screening on the second feature data to obtain target feature data suitable for abnormality analysis; Inputting the target feature data into a preset model for training to obtain an abnormal analysis value output by the preset model, wherein the preset model is a pre-trained model and includes historical temperature and humidity data in the pre-training; According to the abnormal analysis value, the target temperature and humidity data are obtained.

5. The method according to claim 4, characterized in that The step of obtaining target temperature and humidity data according to the abnormal analysis value includes: When the abnormal analysis value is within the preset temperature and humidity data range, determining that the second temperature and humidity data corresponding to the target characteristic data is the normal temperature and humidity data; or, When the abnormal analysis value is not within the preset temperature and humidity data range, the second temperature and humidity data corresponding to the target characteristic data is determined to be the abnormal temperature and humidity data.

6. The method according to claim 1, characterized in that The performing abnormal analysis on the second temperature and humidity data to obtain target temperature and humidity data includes: Obtain historical temperature and humidity data and the corresponding first electromagnetic compatibility laboratory serial number; Obtaining the serial number of the second electromagnetic compatibility laboratory corresponding to the second temperature and humidity data; If the first electromagnetic compatibility laboratory serial number is the same as the second electromagnetic compatibility laboratory serial number, then comparing the historical temperature and humidity data with the second temperature and humidity data to obtain a first comparison value; When the first comparison value is within a first preset comparison threshold, it is determined that the second temperature and humidity data is the normal temperature and humidity data; or, When the first comparison value is not within the first preset comparison threshold, it is determined that the second temperature and humidity data is the abnormal temperature and humidity data.

7. The method according to claim 6, characterized in that After obtaining the second electromagnetic compatibility laboratory serial number corresponding to the second temperature and humidity data, the method further includes: If the first electromagnetic compatibility laboratory serial number and the second electromagnetic compatibility laboratory serial number are different, obtaining an error value, wherein the error value is obtained according to a first standard value corresponding to the first electromagnetic compatibility laboratory serial number and a second standard value corresponding to the second electromagnetic compatibility laboratory serial number; According to the error value, performing data processing on the second temperature and humidity data to obtain fourth temperature and humidity data; Compare the historical temperature and humidity data with the fourth temperature and humidity data to obtain a second comparison value; When the second comparison value is within the second preset comparison threshold, it is determined that the second temperature and humidity data is the normal temperature and humidity data; or, When the second comparison value is not within the second preset comparison threshold, it is determined that the second temperature and humidity data is the abnormal temperature and humidity data.

8. A temperature and humidity monitoring device for an electromagnetic compatibility laboratory, applied to a server in a temperature and humidity remote monitoring system, the device comprising: A receiving unit, configured to receive first temperature and humidity data sent by at least one temperature and humidity sensor, wherein the temperature and humidity sensor is communicatively connected to the server and is deployed in at least one electromagnetic compatibility laboratory; a processing unit, configured to adaptively process the first temperature and humidity data to obtain second temperature and humidity data; an analyzing unit, configured to perform an abnormality analysis on the second temperature and humidity data to obtain target temperature and humidity data, wherein the target temperature and humidity data includes abnormal temperature and humidity data and normal temperature and humidity data; A transmitting unit is used to transmit the target temperature and humidity data to a display device in the humidity remote monitoring system, so that the display device displays the target temperature and humidity data in real time.

9. A server, comprising a memory and a processor, wherein the memory is connected to the processor, and the processor is used to execute one or more computer programs stored in the memory, and when the processor executes the one or more computer programs, the server implements the method according to any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, wherein the computer program comprises program instructions, and when the program instructions are executed by a processor, the processor is caused to execute the method according to any one of claims 1 to 7.

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