Data management method and device of gas flowmeter

Abstract

The invention discloses a data management method and device of a gas flowmeter, and relates to the technical field of data processing, and the method comprises the following steps: determining verification operation parameters in a control system by using voltage and signal types; controlling the bell jar gas flow standard device to perform verification operation on the gas flowmeter based on the verification operation parameters to obtain verification operation information, and transmitting the verification operation information to a control system based on channel evaluation; the control system analyzes parameters of the gas flowmeter based on the verification operation information to obtain target parameter information; and performing data classification processing on the target parameter information and the verification operation information based on the generative adversarial network to obtain a data classification result, generating target report information based on the data classification result, constructing a target index for the target report information, and storing the target report information and the target index. According to the invention, a more accurate and reliable verification operation report of the gas flowmeter can be formed.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a data management method and device for a gas flow meter. Background Art

[0002] In order to ensure the measurement accuracy of the gas flowmeter, it needs to be calibrated. At the same time, in order for relevant personnel to clearly and quickly understand the results of the calibration operation, the relevant data of the calibration operation needs to be analyzed and processed to form a report for relevant personnel to review. In order to ensure the timeliness of data analysis and processing, the calibration operation information needs to be transmitted to the control system in real time for analysis. Currently, most fixed channels are used for data transmission. However, this method often leads to low data transmission efficiency and increased bit error rate in more complex environments, making it difficult to meet the reliability and real-time requirements of data transmission. At the same time, before forming a report, the data needs to be classified. Currently, data classification usually relies on manual operation, but this method is too dependent on the professional quality of the relevant personnel, making it difficult to ensure the accuracy of data classification. In addition, this method consumes too much manpower and has low classification efficiency, resulting in the inability to form accurate and reliable gas flowmeter calibration operation reports. Summary of the Invention

[0003] The purpose of the present invention is to overcome the deficiencies of the prior art. The present invention provides a data management method and device for a gas flow meter to ensure the reliability and efficiency of data transmission and to form an accurate and reliable calibration operation report for the gas flow meter.

[0004] In order to solve the above technical problems, the present invention provides a data management method for a gas flow meter, the method comprising: Use voltage and signal type to determine verification operating parameters in the control system; Controlling the bell-shaped gas flow standard device to perform a calibration operation on the gas flow meter based on the calibration operation parameters, obtaining calibration operation information, and transmitting the calibration operation information to the control system based on channel evaluation; The control system performs parameter analysis of the gas flow meter based on the verification operation information to obtain target parameter information; performing data classification processing on the target parameter information and the verification operation information based on a generative adversarial network to obtain a data classification result; Target report information is generated based on the data classification result, a target index is constructed for the target report information, and the target report information and the target index are stored.

[0005] Optionally, determining the verification operation parameters using the voltage and signal type in the control system includes: Determining a safe operating voltage range of the gas flow meter, and determining power supply voltage information using a matching model based on the safe operating voltage range; Determining signal type information based on preset signal type selection rules; The verification operation parameters are generated based on the power supply voltage information and the signal type information in combination with the preset instrument parameters and the verification parameters.

[0006] Optionally, transmitting the verification operation information to the control system based on the channel assessment includes: Determine the interference source and signal-to-noise ratio during data transmission, and analyze channel signal strength changes based on the interference source and signal-to-noise ratio to obtain channel signal strength change data; Perform data transmission performance analysis on each channel based on channel signal data to obtain data transmission performance data; Screening candidate channels based on spectrum characteristics of the communication area to obtain several candidate channels, and determining a target channel from the candidate channels based on channel signal strength change data and data transmission performance data; A channel coding strategy and a signal modulation strategy are determined, and verification operation information is transmitted to the control system based on the target channel in combination with the channel coding strategy and the signal modulation strategy.

[0007] Optionally, performing data transmission performance analysis on each channel based on the channel signal data to obtain data transmission performance data includes: Perform bandwidth utilization prediction based on channel signal data to obtain bandwidth utilization prediction information; Determine the data transmission rate of each channel based on the bandwidth utilization prediction information combined with the adjustment factor; A stability analysis is performed on each channel to obtain stability data, and a data transmission performance analysis is performed on each channel based on the data transmission rate and the stability data to obtain data transmission performance data.

[0008] Optionally, performing parameter analysis of the gas flow meter based on the verification operation information to obtain target parameter information includes: Extract the bell jar intake volume, pulse equivalent and unit pulse time based on the verification operation information; The instantaneous flow rate is determined based on the bell jar intake volume, the average flow rate per unit pulse is determined based on the pulse equivalent and the unit pulse time, and the target parameter information is determined based on the instantaneous flow rate and the average flow rate per unit pulse.

[0009] Optionally, performing data classification processing on the target parameter information and the verification operation information based on the generative adversarial network to obtain a data classification result includes: Performing keyword extraction on the target parameter information and the verification operation information to obtain keyword information; Extracting feature point information of the target parameter information and the verification operation information, and analyzing the target distance between the feature point information and the classified feature point information; Based on the generative adversarial network, the target parameter information and the verification operation information are subjected to data classification processing using the keyword information and the target distance to obtain a data classification result.

[0010] Optionally, performing keyword extraction on the target parameter information and the verification operation information to obtain keyword information includes: Determine a first word string of target parameter information and verification operation information and a second word string of each keyword in the keyword library; Analyzing a joint probability distribution of the first word character string and the second word character string, and performing a distance calculation between the character strings based on the joint probability distribution to obtain target distance information; Similarity information between the first word character string and the second word character string is determined based on the target distance information, and keyword information of the target parameter information and the verification operation information is determined based on the similarity information.

[0011] Optionally, generating target report information based on the data classification result, constructing a target index for the target report information, and storing the target report information and the target index includes: Generate target report information using preset report templates based on data classification results; Setting a composite index field, and constructing a target index for the target report information based on the composite index field; A storage strategy is determined, and the target report information and target index are stored in a corresponding storage node based on the storage strategy.

[0012] Optionally, determining the storage strategy includes: Perform hot and cold zone analysis on each storage node in the storage space to obtain hot and cold zone analysis results; Performing node performance analysis on each storage node to obtain node performance data of each storage node, and determining an initial strategy based on the hot and cold area analysis results and the node performance data; The initial policy is tested to obtain test results, and the initial policy is adjusted based on the test results to obtain a storage policy.

[0013] In addition, the present invention also provides a data management device for a gas flow meter, the device comprising: Parameter determination module: used to determine the verification operation parameters using voltage and signal type in the control system; Data verification transmission module: used for controlling the bell-shaped gas flow standard device to perform a verification operation on the gas flow meter based on the verification operation parameters, obtaining verification operation information, and transmitting the verification operation information to the control system based on channel evaluation; Parameter analysis module: used for the control system to perform parameter analysis on the gas flow meter based on the verification operation information to obtain target parameter information; Data classification module: used to perform data classification processing on the target parameter information and verification operation information based on the generative adversarial network to obtain data classification results; Data storage module: used to generate target report information based on the data classification result, construct a target index for the target report information, and store the target report information and the target index.

[0014] In an embodiment of the present invention, the control system uses voltage and signal type to determine the calibration operation parameters, controls the bell-shaped gas flow standard device based on the calibration operation parameters to perform a calibration operation on the gas flow meter, obtains calibration operation information, and transmits the calibration operation information to the control system based on channel evaluation, which can ensure the reliability and efficiency of data transmission and avoid affecting the efficiency of data analysis. The control system performs parameter analysis of the gas flow meter based on the calibration operation information to obtain target parameter information, performs data classification processing on the target parameter information and the calibration operation information based on a generative adversarial network, and generates target report information based on the data classification results, which can effectively improve the accuracy and efficiency of data classification and make the generated target report more accurate. A target index is constructed for the target report information, and the target report information and the target index are stored so that the corresponding report information can be quickly searched and queried in the future. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0016] Figure 1 1 is a flow chart of a data management method for a gas flow meter according to an embodiment of the present invention; Figure 2 is a flow chart of a data management method for a gas flow meter in another embodiment of the present invention; Figure 3 1 is a schematic diagram of the structure of a data management device for a gas flow meter in an embodiment of the present invention; Figure 4 It is a schematic diagram of the structure of an electronic device in an embodiment of the present invention. DETAILED DESCRIPTION

[0017] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0018] Example 1 See also Figure 1 , Figure 1 : is a flow chart of a data management method for a gas flow meter in an embodiment of the present invention, the method comprising: S11: Determine verification operation parameters using voltage and signal type in the control system; In the specific implementation process of the present invention, the method of determining the calibration operation parameters using voltage and signal type in the control system includes: determining the working voltage safety range of the gas flow meter, and determining the power supply voltage information based on the working voltage safety range using a matching model; determining the signal type information based on a preset signal type selection rule; and generating the calibration operation parameters based on the power supply voltage information and signal type information in combination with preset instrument parameters and calibration parameters.

[0019] Specifically, the control system is equipped with a main calibration program and an auxiliary program, which operate together to perform data analysis and processing to determine the safe operating voltage range of the gas flowmeter. The safe operating voltage range can be found in the gas flowmeter's parameter table. Based on the safe operating voltage range, the supply voltage information is determined using a matching model. The matching model is a convergence model obtained by inputting a sample data set into a deep neural network for training. The safe operating voltage range is input into the matching model to obtain the required supply voltage information, such as DC voltage 24V and DC voltage 12V. The signal type information is determined based on preset signal type selection rules. The signal type information includes pulse, 4-20mA, and no signal. The preset signal type selection rules include requiring an accurate K value for the meter under test that uses pulse as the remote transmission signal. The K value is the number of pulses or frequency output generated when a unit volume of gas passes through the flowmeter. For the meter under test that uses 4-20mA current as the remote transmission signal, an accurate range is required. Based on the power supply voltage information and signal type information combined with the preset instrument parameters and calibration parameters, the calibration operation parameters are generated. The instrument parameters include the instrument name, model specifications, manufacturer, accuracy level, instrument type, etc. The calibration parameters include the calibration medium, ambient pressure, medium density, indoor temperature and humidity, time coefficient and bell jar equivalent, etc.

[0020] S12: controlling the bell-shaped gas flow standard device to perform a calibration operation on the gas flow meter based on the calibration operation parameters, obtaining calibration operation information, and transmitting the calibration operation information to the control system based on channel evaluation; In the specific implementation process of the present invention, the verification operation information is transmitted to the control system based on channel evaluation, including: determining the interference source and signal-to-noise ratio during the data transmission process, and performing channel signal strength change analysis based on the interference source and signal-to-noise ratio to obtain channel signal strength change data; performing data transmission performance analysis of each channel based on the channel signal data to obtain data transmission performance data; screening candidate channels based on the spectrum characteristics of the communication area to obtain several candidate channels, and determining the target channel among the several candidate channels based on the channel signal strength change data and the data transmission performance data; determining the channel coding strategy and the signal modulation strategy, and transmitting the verification operation information to the control system based on the target channel in combination with the channel coding strategy and the signal modulation strategy.

[0021] Furthermore, the data transmission performance analysis of each channel based on the channel signal data to obtain data transmission performance data includes: predicting bandwidth utilization based on the channel signal data to obtain bandwidth utilization prediction information; determining the data transmission rate of each channel based on the bandwidth utilization prediction information combined with an adjustment factor; performing stability analysis on each channel to obtain stability data, and performing data transmission performance analysis on each channel based on the data transmission rate and stability data to obtain data transmission performance data.

[0022] Specifically, after setting the calibration operation parameters, the control system controls the bell-shaped gas flow standard device to perform calibration operations on the gas flow meter based on the calibration operation parameters. There can be one or more gas flow meters. The calibration operation steps include: clicking the corresponding telescope on the main interface according to the caliber of the gas flow meter to be measured. Enter the corresponding parameters in the dialog box that pops up. For the flow meter with 4-20mA output, enter the upper and lower limits, and the lower limit is generally 0. Click OK after the input is completed; enter the calibration points and calibration times in the main interface (the default is the number of points required by the regulations); the calibration methods of this software are divided into fixed volume and non-fixed volume. Fixed volume generally uses a fixed volume (the volume between the two photoelectric samplers), while non-fixed volume is a continuous sampling volume. Users can switch through the checkbox as needed (select the fixed volume checkbox); when performing fixed volume verification, first select the fixed volume method, and then select the photoelectric sampler to be used for the start and end. Each time a change is made, the start must be selected first and then the end must be selected; for a pulse signal flow meter, if it is a low-frequency meter (100L / P), the low-frequency method must be used (select the low-frequency checkbox), and the number of pulses to be collected can be entered. However, a low-frequency meter cannot use the fixed volume method. The mode can only be continuous; after entering the replacement calibration point and times, the point is changed to become the current calibration point and times; open the bell jar outlet valve, the corresponding pipeline calibration valve, adjust the flow rate to make the flow rate reach the target flow rate, and observe whether the pressure and temperature are normal; lift the bell jar again, click "this time" or "next time", and the calibration will be carried out. The valve will automatically close after the calibration is completed; for gas meters, after the valve is automatically closed, wait for the gas meter pointer to stabilize before reading, and then click the stabilize button; after this calibration is completed, click record on the main interface to enter the data page to view the calibration results. After the calibration of this point is completed, adjust the flow rate and proceed to the next point calibration. When all flow points are calibrated and the calibration results are correct on the data page, enter the record number and save the information of this calibration operation, such as the set instrument parameters and calibration parameters, as well as the gas volume, time, pulse equivalent, pulse time and number of pulses entering the gas flowmeter to be tested from the bell jar, which is the calibration operation information.

[0023] Determine the interference sources and signal-to-noise ratio during data transmission. Interference sources include interference from other devices and internal interference within devices, such as wireless connection interference from Bluetooth devices. The signal-to-noise ratio refers to the ratio of the received useful signal to the noise. Channel signal strength change analysis is performed based on the interference sources and signal-to-noise ratio. The impact of each channel point is analyzed based on the interference sources and signal-to-noise ratio. The channel signal strength change value is determined based on the impact of each point, thus obtaining channel signal strength change data. Bandwidth utilization is predicted based on the channel signal data, which includes frequency characteristics and amplitude values ​​at different time points. This channel signal data is input into a neural network model to predict the channel bandwidth utilization over a period of time, thus obtaining bandwidth utilization prediction information. The data transmission rate for each channel is determined based on the bandwidth utilization prediction information combined with an adjustment factor. The adjustment factor is used to balance the impact of prediction uncertainties on the data transmission rate. The bandwidth utilization prediction information and the adjustment factor are input into the model to obtain the data transmission rate for each channel. A stability analysis is performed on each channel, and a stability coefficient for each channel is determined based on the bit error rate, packet loss rate, and delay of each channel, thereby obtaining stability data. A data transmission performance analysis is then performed on each channel based on the data transmission rate and stability data, and a data transmission performance coefficient is calculated based on the data transmission rate and stability data and their weighting factors, thereby obtaining data transmission performance data. Candidate channels are screened based on the spectrum characteristics of the communication area, which include the available frequency band, spectrum occupancy status, and signal interference strength of the current communication area. A determination is made as to whether the available frequency band of each channel meets preset requirements, which may include the frequency band range and technical specifications supported by the device. Several first channels whose available frequency bands meet the preset requirements are screened, and the spectrum occupancy status of each first channel is compared with a preset frequency domain occupancy threshold. The signal interference strength of each first channel is compared with a preset signal interference strength threshold. First channels whose spectrum occupancy status is less than the preset frequency domain occupancy threshold and whose signal interference strength is less than the preset signal interference strength threshold are screened as candidate channels, thereby obtaining several candidate channels. Candidate channels with sufficient resources for data transmission and that are not subject to excessive interference are screened first, thereby improving the efficiency of screening subsequent target channels. A target channel is determined from several candidate channels based on the channel signal strength change data and the data transmission performance data. A channel score is calculated for each candidate channel according to the channel signal strength change data and the data transmission performance data, and the candidate channel with the highest score is selected as the target channel.Determine the channel coding strategy and signal modulation strategy, select the corresponding coding rate and coding length from the channel coding table according to the channel efficiency, bit error rate and signal stability of the target channel, construct the channel coding strategy according to the corresponding coding rate and coding length, so that the obtained channel coding strategy can better cope with complex communication environments, input the channel efficiency, bit error rate and signal stability of the target channel into the support vector machine, analyze the corresponding signal modulation method, determine the signal modulation strategy according to the signal modulation method, and transmit the verification operation information to the control system based on the target channel in combination with the channel coding strategy and signal modulation strategy, encode the verification operation information through the channel coding strategy, convert the encoded verification operation information into a signal form on the target channel through the signal modulation strategy, and transmit the verification operation information to the control system in the target channel.

[0024] S13: The control system performs parameter analysis on the gas flow meter based on the verification operation information to obtain target parameter information; In the specific implementation process of the present invention, the parameter analysis of the gas flow meter is performed based on the calibration operation information to obtain the target parameter information, including: extracting the bell jar intake volume, pulse equivalent and unit pulse time based on the calibration operation information; determining the instantaneous flow rate based on the bell jar intake volume, determining the unit pulse average flow rate based on the pulse equivalent and unit pulse time, and determining the target parameter information based on the instantaneous flow rate and the unit pulse average flow rate.

[0025] Specifically, the control system receives the calibration operation information and extracts the bell jar intake volume, pulse equivalent, and unit pulse time based on the calibration operation information. The bell jar intake volume is the volume of gas entering the bell jar into the gas flowmeter to be tested, and the pulse equivalent is the volume or mass corresponding to each pulse signal. The instantaneous flow rate is determined based on the bell jar intake volume, the instantaneous flow rate is divided by the time, and the divided value is differentiated. The value obtained by the differentiation is the instantaneous flow rate. The average flow rate per unit pulse is determined based on the pulse equivalent and unit pulse time. The pulse equivalent is divided by the unit pulse time to obtain the average flow rate per unit pulse. The target parameter information is determined based on the instantaneous flow rate and the average flow rate per unit pulse.

[0026] S14: performing data classification processing on the target parameter information and the verification operation information based on a generative adversarial network to obtain a data classification result; In the specific implementation process of the present invention, the target parameter information and verification operation information are subjected to data classification processing based on the generative adversarial network to obtain data classification results, target report information is generated based on the data classification results, and a target index is constructed for the target report information, and the target report information and target index are stored, including: keyword extraction of the target parameter information and verification operation information to obtain keyword information; extracting feature point information of the target parameter information and verification operation information, and analyzing the target distance between the feature point information and the classified feature point information; and data classification processing of the target parameter information and verification operation information using the keyword information and target distance based on the generative adversarial network to obtain data classification results.

[0027] Furthermore, the keyword extraction of the target parameter information and the verification operation information to obtain the keyword information includes: determining a first word string of the target parameter information and the verification operation information and a second word string of each keyword in the keyword library; analyzing the joint probability distribution of the first word string and the second word string, and performing a string distance calculation based on the joint probability distribution to obtain target distance information; determining similarity information between the first word string and the second word string based on the target distance information, and determining the keyword information of the target parameter information and the verification operation information based on the similarity information.

[0028] Specifically, the first word string of the target parameter information and the verification operation information and the second word string of each keyword in the keyword library are determined, and the target parameter information and the verification operation information are subjected to word extraction. The corresponding first word string is obtained based on the extracted words, and each keyword in the keyword library has its own corresponding second word string. The joint probability distribution of the first word string and the second word string is analyzed, and the normal distribution and exponential distribution of the first word string and the second word string are calculated. The joint probability between the two is determined based on the normal distribution and the exponential distribution, which is the joint probability distribution. The distance between the strings is calculated based on the joint probability distribution. Data is sampled based on the joint probability distribution to obtain a third word string. The third word string contains information of the first word string and the second word string. A first distance matrix between the first word string and the third word string is calculated, and a second distance matrix between the second word string and the third word string is calculated. The distance matrix can be calculated using cosine similarity and string edit distance. The target distance information is obtained from the first distance matrix and the second distance matrix. Based on the target distance information, similarity information between the first word string and the second word string is determined. Similarity information between the first word string and the second word string is calculated based on the first eigenvector of the first distance matrix and the second eigenvector of the second distance matrix. The similarity information is the similarity information between the first word string and the second word string. Based on the similarity information, keyword information of the target parameter information and the verification operation information is determined, that is, the word corresponding to the first word string with the highest similarity is used as the keyword. Feature point information of the target parameter information and the verification operation information is extracted by a feature extraction network. The feature point information can be the coordinate points of the data features of the target parameter information and the verification operation information in the feature vector space. The data features can be corresponding text features such as model numbers and serial numbers. The target distance between the feature point information and the classified feature point information is analyzed. The classified feature points are the coordinate points of the classified target parameter information and the verification operation information in the vector space. The target distance is the distance between the coordinate points of the two. Based on the generative adversarial network, the target parameter information and verification operation information are subjected to data classification processing using the keyword information and target distance. The keyword information and target distance are input into the generative adversarial network to obtain the category to which each information in the target parameter information and verification operation information belongs in the report, and the information in the category is classified to obtain the data classification result.

[0029] S15: Generate target report information based on the data classification result, construct a target index for the target report information, and store the target report information and the target index.

[0030] In the specific implementation process of the present invention, the target report information is generated based on the data classification result, and a target index is constructed for the target report information, and the target report information and the target index are stored, including: generating the target report information based on the data classification result using a preset report template; setting a composite index field, and constructing a target index for the target report information based on the composite index field; determining a storage strategy, and storing the target report information and the target index in a corresponding storage node based on the storage strategy.

[0031] Furthermore, the determination of the storage strategy includes: performing a hot and cold area analysis on each storage node in the storage space to obtain the hot and cold area analysis results; performing a node performance analysis on each storage node to obtain the node performance data of each storage node, and determining the initial strategy based on the hot and cold area analysis results and the node performance data; testing the initial strategy to obtain the test results, and adjusting the initial strategy based on the test results to obtain the storage strategy.

[0032] Specifically, based on the data classification results, target report information is generated using a preset report template. The classified information is input into the preset report template to generate a target report. A composite index field is set, which may include a time field and a report number field, and a target index is constructed for the target report information based on the composite index field. The composite index fields are combined to form a target index corresponding to the target report information. A hot and cold zone analysis is performed on each storage node in the storage space. The load of each storage node within a preset period is analyzed using a long short-term memory network. Based on the predicted load information, a hot and cold zone analysis is performed on each storage node to obtain storage nodes corresponding to cold zones and storage nodes corresponding to hot zones, thereby obtaining hot and cold zone analysis results. A node performance analysis is performed on each storage node to obtain the storage space and spatial computing power of each storage node. Node performance analysis is performed based on the storage space and spatial computing power of each storage node to obtain node performance data for each storage node. An initial strategy is determined based on the hot and cold zone analysis results and the node performance data, thereby determining the corresponding storage node based on the hot and cold zone analysis results and the node performance data. Test the initial strategy, perform storage and query tests on the target report information and target index according to the initial strategy on the corresponding test platform, obtain test results, and adjust the initial strategy based on the test results. If the test results indicate insufficient capacity, increase the capacity of the corresponding node space to obtain a storage strategy, and store the target report information and target index in the corresponding storage node based on the storage strategy. Each report and index is uniquely corresponding, so that the required reports can be queried quickly and accurately in the future.

[0033] In an embodiment of the present invention, the control system uses voltage and signal type to determine the calibration operation parameters, controls the bell-shaped gas flow standard device based on the calibration operation parameters to perform a calibration operation on the gas flow meter, obtains calibration operation information, and transmits the calibration operation information to the control system based on channel evaluation, which can ensure the reliability and efficiency of data transmission and avoid affecting the efficiency of data analysis. The control system performs parameter analysis of the gas flow meter based on the calibration operation information to obtain target parameter information, performs data classification processing on the target parameter information and the calibration operation information based on a generative adversarial network, and generates target report information based on the data classification results, which can effectively improve the accuracy and efficiency of data classification and make the generated target report more accurate. A target index is constructed for the target report information, and the target report information and the target index are stored so that the corresponding report information can be quickly searched and queried in the future.

[0034] Example 2 See also Figure 2 , Figure 2 FIG. 1 is a flow chart of a method for managing data of a gas flow meter according to another embodiment of the present invention, the method comprising: S201: Determine verification operation parameters using voltage and signal type in the control system; S202: Controlling the bell-shaped gas flow standard device to perform a calibration operation on the gas flow meter based on the calibration operation parameters, obtaining calibration operation information, determining interference sources and a signal-to-noise ratio during data transmission, and performing a channel signal strength change analysis based on the interference sources and the signal-to-noise ratio to obtain channel signal strength change data; S203: Analyze the data transmission performance of each channel based on the channel signal data to obtain data transmission performance data; S204: Screening candidate channels based on the spectrum characteristics of the communication area to obtain several candidate channels, and determining a target channel from the candidate channels based on the channel signal strength change data and the data transmission performance data; S205: Determine a channel coding strategy and a signal modulation strategy, and transmit verification operation information to the control system based on the target channel in combination with the channel coding strategy and the signal modulation strategy; S206: The control system performs parameter analysis on the gas flow meter based on the verification operation information to obtain target parameter information; S207: Based on the generative adversarial network, data classification processing is performed on the target parameter information and the verification operation information to obtain a data classification result, target report information is generated based on the data classification result, and a target index is constructed for the target report information, and the target report information and the target index are stored.

[0035] In an embodiment of the present invention, the control system uses voltage and signal type to determine the calibration operation parameters, controls the bell-shaped gas flow standard device based on the calibration operation parameters to perform a calibration operation on the gas flow meter, obtains calibration operation information, and transmits the calibration operation information to the control system based on channel evaluation, which can ensure the reliability and efficiency of data transmission and avoid affecting the efficiency of data analysis. The control system performs parameter analysis of the gas flow meter based on the calibration operation information to obtain target parameter information, performs data classification processing on the target parameter information and the calibration operation information based on a generative adversarial network, and generates target report information based on the data classification results, which can effectively improve the accuracy and efficiency of data classification and make the generated target report more accurate. A target index is constructed for the target report information, and the target report information and the target index are stored so that the corresponding report information can be quickly searched and queried in the future.

[0036] Example 3 See also Figure 3 , Figure 3 : is a schematic diagram of the structure of a data management device for a gas flow meter in an embodiment of the present invention, the device comprising: Parameter determination module 31: used to determine the verification operation parameters using voltage and signal type in the control system; Data verification transmission module 32: used for controlling the bell-shaped gas flow standard device to perform a verification operation on the gas flow meter based on the verification operation parameters, obtaining verification operation information, and transmitting the verification operation information to the control system based on channel evaluation; Parameter analysis module 33: used for the control system to perform parameter analysis on the gas flow meter based on the verification operation information to obtain target parameter information; Data classification module 34: configured to perform data classification processing on the target parameter information and the verification operation information based on a generative adversarial network to obtain a data classification result; Data storage module: used to generate target report information based on the data classification result, construct a target index for the target report information, and store the target report information and the target index.

[0037] In the specific implementation process of the present invention, the specific implementation method of the device item can refer to the implementation method of the above-mentioned method item, which will not be repeated here.

[0038] In an embodiment of the present invention, the control system uses voltage and signal type to determine the calibration operation parameters, controls the bell-shaped gas flow standard device based on the calibration operation parameters to perform a calibration operation on the gas flow meter, obtains calibration operation information, and transmits the calibration operation information to the control system based on channel evaluation, which can ensure the reliability and efficiency of data transmission and avoid affecting the efficiency of data analysis. The control system performs parameter analysis of the gas flow meter based on the calibration operation information to obtain target parameter information, performs data classification processing on the target parameter information and the calibration operation information based on a generative adversarial network, and generates target report information based on the data classification results, which can effectively improve the accuracy and efficiency of data classification and make the generated target report more accurate. A target index is constructed for the target report information, and the target report information and the target index are stored so that the corresponding report information can be quickly searched and queried in the future.

[0039] Example 4 See also Figure 4 , Figure 4 It is a schematic diagram of the structure of an electronic device in an embodiment of the present invention.

[0040] The embodiment of the present invention further provides an electronic device, such as Figure 4 As shown, the electronic device includes a memory 41, a processor 43, and a computer program 42 stored in the memory 41 and executable on the processor 43. It will be understood by those skilled in the art that Figure 3The electronic devices shown do not constitute a limitation on all devices and may include more or fewer components than shown, or combinations of certain components. The memory 41 can be used to store the computer program 42 and various functional modules, and the processor 43 runs the computer program 42 stored in the memory 41, thereby executing various functional applications and data processing of the device. The memory can be internal memory or external memory, or include both internal memory and external memory. The internal memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), flash memory, or random access memory. The external memory can include a hard disk, floppy disk, ZIP disk, USB flash drive, magnetic tape, etc. The processor 43 can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor, a single-chip microcomputer, or processor 43, or any conventional processor. The processor and memory disclosed in the present invention include but are not limited to these types of processors and memories. The processor and memory disclosed in the present invention are only examples and not limitations.

[0041] As an embodiment, the electronic device includes: one or more processors 43, a memory 41, and one or more computer programs 42, wherein the one or more computer programs 42 are stored in the memory 41 and are configured to be executed by the one or more processors 43, and the one or more computer programs 42 are configured to execute the data management method of the gas flow meter in any of the above-mentioned embodiments. For the specific implementation process, please refer to the above-mentioned embodiments and will not be repeated here.

[0042] In an embodiment of the present invention, the control system uses voltage and signal type to determine the calibration operation parameters, controls the bell-shaped gas flow standard device based on the calibration operation parameters to perform a calibration operation on the gas flow meter, obtains calibration operation information, and transmits the calibration operation information to the control system based on channel evaluation, which can ensure the reliability and efficiency of data transmission and avoid affecting the efficiency of data analysis. The control system performs parameter analysis of the gas flow meter based on the calibration operation information to obtain target parameter information, performs data classification processing on the target parameter information and the calibration operation information based on a generative adversarial network, and generates target report information based on the data classification results, which can effectively improve the accuracy and efficiency of data classification and make the generated target report more accurate. A target index is constructed for the target report information, and the target report information and the target index are stored so that the corresponding report information can be quickly searched and queried in the future.

[0043] Those skilled in the art will appreciate that all or part of the steps in the various methods of the above embodiments can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable storage medium, which may include: a read-only memory (ROM), a random access memory (RAM), a disk or an optical disk, etc.

[0044] In addition, the above is a detailed introduction to the data management method and device for a gas flow meter provided in an embodiment of the present invention. Specific examples are used herein to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A data management method for a gas flow meter, characterized in that: The method comprises: Use voltage and signal type to determine verification operating parameters in the control system; Controlling the bell-shaped gas flow standard device to perform a calibration operation on the gas flow meter based on the calibration operation parameters, obtaining calibration operation information, and transmitting the calibration operation information to the control system based on channel evaluation; The control system performs parameter analysis of the gas flow meter based on the verification operation information to obtain target parameter information; performing data classification processing on the target parameter information and the verification operation information based on a generative adversarial network to obtain a data classification result; Target report information is generated based on the data classification result, a target index is constructed for the target report information, and the target report information and the target index are stored.

2. The data management method for a gas flow meter according to claim 1, characterized in that: Determining the verification operation parameters by using the voltage and signal type in the control system includes: Determining a safe operating voltage range of the gas flow meter, and determining power supply voltage information using a matching model based on the safe operating voltage range; Determining signal type information based on preset signal type selection rules; The verification operation parameters are generated based on the power supply voltage information and the signal type information in combination with the preset instrument parameters and the verification parameters.

3. The data management method of a gas flow meter according to claim 1, characterized in that: The transmitting the verification operation information to the control system based on the channel evaluation includes: Determine the interference source and signal-to-noise ratio during data transmission, and analyze channel signal strength changes based on the interference source and signal-to-noise ratio to obtain channel signal strength change data; Perform data transmission performance analysis on each channel based on channel signal data to obtain data transmission performance data; Screening candidate channels based on spectrum characteristics of the communication area to obtain several candidate channels, and determining a target channel from the candidate channels based on channel signal strength change data and data transmission performance data; A channel coding strategy and a signal modulation strategy are determined, and verification operation information is transmitted to the control system based on the target channel in combination with the channel coding strategy and the signal modulation strategy.

4. The data management method for a gas flow meter according to claim 3, characterized in that: The performing of data transmission performance analysis on each channel based on the channel signal data to obtain data transmission performance data includes: Perform bandwidth utilization prediction based on channel signal data to obtain bandwidth utilization prediction information; Determine the data transmission rate of each channel based on the bandwidth utilization prediction information combined with the adjustment factor; A stability analysis is performed on each channel to obtain stability data, and a data transmission performance analysis is performed on each channel based on the data transmission rate and the stability data to obtain data transmission performance data.

5. The data management method for a gas flow meter according to claim 1, characterized in that: The performing of parameter analysis of the gas flow meter based on the verification operation information to obtain target parameter information includes: Extract the bell jar intake volume, pulse equivalent and unit pulse time based on the verification operation information; The instantaneous flow rate is determined based on the bell jar intake volume, the average flow rate per unit pulse is determined based on the pulse equivalent and the unit pulse time, and the target parameter information is determined based on the instantaneous flow rate and the average flow rate per unit pulse.

6. The data management method for a gas flow meter according to claim 1, characterized in that: The performing data classification processing on the target parameter information and the verification operation information based on the generative adversarial network to obtain the data classification result includes: Performing keyword extraction on the target parameter information and the verification operation information to obtain keyword information; Extracting feature point information of the target parameter information and the verification operation information, and analyzing the target distance between the feature point information and the classified feature point information; Based on the generative adversarial network, the target parameter information and the verification operation information are subjected to data classification processing using the keyword information and the target distance to obtain a data classification result.

7. The data management method for a gas flow meter according to claim 6, characterized in that: The step of extracting keywords from the target parameter information and the verification operation information to obtain keyword information includes: Determine a first word string of target parameter information and verification operation information and a second word string of each keyword in the keyword library; Analyzing a joint probability distribution of the first word character string and the second word character string, and performing a distance calculation between the character strings based on the joint probability distribution to obtain target distance information; Similarity information between the first word character string and the second word character string is determined based on the target distance information, and keyword information of the target parameter information and the verification operation information is determined based on the similarity information.

8. The data management method for a gas flow meter according to claim 1, characterized in that: Generating target report information based on the data classification result, constructing a target index for the target report information, and storing the target report information and the target index include: Generate target report information using preset report templates based on data classification results; Setting a composite index field, and constructing a target index for the target report information based on the composite index field; A storage strategy is determined, and the target report information and target index are stored in a corresponding storage node based on the storage strategy.

9. The data management method for a gas flow meter according to claim 8, characterized in that: Determining the storage strategy includes: Perform hot and cold zone analysis on each storage node in the storage space to obtain hot and cold zone analysis results; Performing node performance analysis on each storage node to obtain node performance data of each storage node, and determining an initial strategy based on the hot and cold area analysis results and the node performance data; The initial policy is tested to obtain test results, and the initial policy is adjusted based on the test results to obtain a storage policy.

10. A data management device for a gas flow meter, characterized in that: The device comprises: Parameter determination module: used to determine the verification operation parameters using voltage and signal type in the control system; Data verification transmission module: used for controlling the bell-shaped gas flow standard device to perform a verification operation on the gas flow meter based on the verification operation parameters, obtaining verification operation information, and transmitting the verification operation information to the control system based on channel evaluation; Parameter analysis module: used for the control system to perform parameter analysis on the gas flow meter based on the verification operation information to obtain target parameter information; Data classification module: used to perform data classification processing on the target parameter information and verification operation information based on the generative adversarial network to obtain data classification results; Data storage module: used to generate target report information based on the data classification result, construct a target index for the target report information, and store the target report information and the target index.

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