A gas sensor calibration device

Abstract

The present invention relates to the technical field of sensor detection equipment, and in particular provides a calibration device for a gas sensor; the device comprises a gas input component, a signal processing component, and a calibration adjustment component; the gas input component is used to obtain the type and value of a target gas required for the calibration of the gas sensor, and to keep the target gas pressure constant; the signal processing component is used to collect an analog signal of a fixedly installed gas sensor, and convert the analog signal into a voltage digital signal, and compare it with a set standard value to determine whether it is qualified. When it is unqualified, the calibration adjustment component performs zero point calibration and span calibration for further determination; the accuracy and stability of the target gas during the calibration process are ensured, the reliability of the calibration result is improved, whether the performance of the gas sensor is qualified is accurately and quickly determined, the calibration efficiency is improved, the intelligent calibration of the gas sensor is realized, the measurement accuracy and reliability of the gas sensor are improved, and a strong guarantee is provided for practical application.

Description

Technical Field

[0001] The present invention relates to the technical field of sensor detection equipment, and in particular to a calibration device for a gas sensor. Background Art

[0002] The determination of the working characteristics and technical indicators of the sensor reflects the quality of use and is reflected through the corresponding inspection data; the purpose of the inspection is to reveal the various inherent characteristics of the sensor itself and its adaptability to practical applications. Sensor calibration is a way to determine the input-output working characteristics of the sensor, the input-output characteristics of the various technical indicators of the sensor, and the process of determining its errors; the standard measurement equipment gives the standard value as the input of the sensor, and detects the output signal of the sensor at the same time, and obtains the various working characteristics of the sensor or determines the size of its error through data processing. However, the existing standard measurement equipment has a low degree of intelligence, and there are fewer gas-specific equipment, which affects the accuracy of the test results to a certain extent.

[0003] Prior art 1, Chinese patent, application number: 202310390832.8 discloses a gas sensor calibration device, method, equipment and medium, the device includes: a host computer module, used to send a calibration instruction to the main control module; a main control module, used to receive the calibration instruction and control the gas distribution task according to the calibration instruction; a gas distribution module, used to provide the standard gas required by the calibration module according to the gas distribution task; a calibration module, used to calibrate one or more gas sensors according to the standard gas and output the sensor calibration signal. Although different standard gas concentrations can be used to repeatedly calibrate multiple different types of gas sensors, and at the same time, the calibration accuracy of the gas sensor can be improved by controlling the concentration of the standard gas in real time, the whole process of gas sensor calibration can be automated and a large number of different types of gas sensors can be simultaneously calibrated, and the calibration signals of multiple different types of gas sensors can be processed simultaneously. However, the calibration method of the gas sensor is relatively single, and there is a lack of calibration adjustment of the gas sensor, which increases the production cost.

[0004] Prior art 2, Chinese patent, application number 202310003244.4 discloses an intelligent calibration device, which relates to the field of mining gas sensor testing technology, wherein the device includes: a cabinet; multiple gas sensors located in the cabinet and a transmission structure that drives all gas sensors to move synchronously along a preset trajectory; any gas sensor is located in an open cavity; the gas sensor and the cavity are used in pairs; and an inflatable calibration test assembly; when any gas sensor moves to a specific position with the transmission mechanism, the inflatable calibration test assembly located in the cabinet automatically extends and docks with the gas sensor in the cavity to fill the test gas, completing the automatic calibration test of the test gas. Although the real and sustainable intelligent improvement of the sensor testing level has been achieved, it is easy to be damaged in high humidity, high corrosion or extreme temperatures, and requires regular maintenance and calibration, with high maintenance requirements and maintenance costs.

[0005] Prior art three, Chinese patent, application number 202110962756.4 discloses a gas sensor calibration device and a gas sensor calibration system, the gas sensor calibration device includes: a bottom plate, a transmission device is provided on the bottom plate; a back plate, mounted on the bottom plate, the back plate is provided with a gas hood mounting surface; a gas hood, the number of gas hoods is at least one, the gas hood has a gas cavity, the gas hood is provided with an air inlet, an air outlet and a sensor docking interface that communicate with the gas cavity, and the gas hood is installed on the gas hood mounting surface; an installation base plate, an installation station for installing a gas sensor is provided on the installation base plate, the installation base plate is connected to the transmission device, and can drive the installation base plate to approach or move away from the gas hood mounting surface, so that the detection connector of the gas sensor installed at the installation station is docked with the sensor docking interface; a power on / off mechanism, which can connect the power to the gas sensor when the gas sensor is docked with the sensor docking interface. Although the calibration of the gas sensor can be achieved, the calibration process of the gas sensor is relatively complicated, which increases the difficulty and cost of operation.

[0006] At present, the prior art 1, prior art 2 and prior art 3 have the problems of lack of calibration method for gas sensors, relatively simple, high maintenance requirements and maintenance costs, and relatively complicated processes. Therefore, the present invention provides a calibration device for gas sensors to solve the above problems. Summary of the invention

[0007] In order to achieve the above object, the present invention adopts the following technical scheme:

[0008] One aspect of the present invention provides a gas sensor testing device, comprising:

[0009] The gas input component is used to obtain the type and value of the target gas required for the calibration of the gas sensor, activate the pressure reduction device module, input the target gas into the corresponding gas sensor, and keep the target gas pressure constant when the input target gas pressure reaches the set standard;

[0010] The signal processing component is used to collect the analog signal of the gas sensor, which includes the gas characteristics and concentration of the target gas detected by the gas sensor; convert the analog signal into a voltage digital signal, pre-process the voltage digital signal, and compare it with the set standard value. If it is within the set standard value range, it is qualified; if it is outside the set standard value range, it is unqualified;

[0011] The calibration adjustment component is used to trigger the calibration adjustment procedure according to the unqualified content outside the set standard value range received; use pure air for zero point calibration, and then use the target gas of known concentration for span calibration, record the response value of the gas sensor at each gear, and compare the response value with the response standard value. If it does not meet the response standard value, the current gas sensor is judged to be unqualified.

[0012] In an optional embodiment, the gas input component comprises:

[0013] The parameter acquisition module is responsible for confirming the gas sensor model, application field, and gas characteristics and standards to be tested before starting to acquire the target gas; the application fields include environmental monitoring, industrial safety, and food quality, and the standards include gas concentration range and response speed;

[0014] The concentration acquisition module is responsible for selecting one or more reference concentration values ​​as the target concentration and using a high gas concentration detection instrument to monitor and verify the actual concentration of the mixed gas in real time;

[0015] The pressure detection module is responsible for connecting the pressure reducing device to the gas input component, setting the initial pressure value of the pressure reducing device, turning on the pressure reducing device, and monitoring the pressure changes of the target gas. The pressure of the target gas is monitored in real time using a pressure sensor. If the gas pressure does not reach the set standard, it is adjusted by adjusting the valve of the pressure reducing device.

[0016] In an optional implementation, the pressure detection module includes:

[0017] The network connection submodule is responsible for the layout of pressure sensors and monitoring the pressure changes in gas flow; using communication protocols, the sensor network is connected to form a decentralized real-time data transmission network;

[0018] The strategy formation submodule is responsible for setting the sampling rate of each pressure sensor, detecting pressure fluctuations, and saving the detected anomalies in the database; identifying the relationship between gas pressure and environmental variables such as temperature, humidity, and flow rate, building a multivariate pressure prediction model, predicting future pressure changes based on historical data, and forming a dynamic adjustment strategy;

[0019] The parameter adjustment submodule is responsible for automatically updating the working parameters of the regulating valve after calculating the required pressure value; if the pressure exceeds the set range, the valve will be automatically adjusted to close or open, adjust the gas inflow, and keep the pressure within a safe range.

[0020] In an optional embodiment, the multivariate pressure prediction model of the strategy formation submodule includes:

[0021] Data preprocessing layer, multi-dimensional time series data collected from sensor networks, including pressure, temperature, humidity and flow rate; data standardization, missing value processing and time series reconstruction;

[0022] Feature extraction layer: The processed two-dimensional data is passed through multiple convolutional layers to extract local spatial features, combined with the maximum pooling layer to reduce the data dimension and extract higher-level feature patterns; the extracted spatial feature vectors are used for time series analysis;

[0023] The time series analysis layer captures the long-term dependencies in the time series data from the feature vector sequence output from the feature extraction layer, identifies the historical trends and patterns of pressure, and outputs the hidden state of each time step as the basis for predicting future pressure changes;

[0024] The joint prediction layer inputs the hidden state and the extracted spatial features; combines the spatial features with the temporal features, further processes them through the fully connected layer, and uses the fused features to perform multivariate pressure prediction; outputs the future pressure value prediction, confidence interval, and fault indicator;

[0025] The decision-making and feedback layer inputs the predicted pressure value and actual monitoring data; monitors the difference between the predicted and actual values ​​in real time, calculates the error, and loops the feedback information back to the model to optimize parameters and strategies; provides adjustment feedback to maintain the pressure within a safe range, and continuously adjusts the model prediction performance by combining historical data and real-time data;

[0026] In an optional implementation manner, the strategy formation submodule includes:

[0027] The data analysis unit is responsible for integrating the historical pressure data, temperature, humidity and flow rate multi-dimensional data from various sensors into a time series data stream, and regularly extracting time segments for analysis through the window sliding method; for each time segment of the input data, the change amplitude of the data within the time segment is calculated, and the learning rate and feature weight of the multivariate pressure prediction model are dynamically adjusted using the statistical characteristics of the change amplitude;

[0028] The error processing unit is responsible for real-time monitoring of the actual pressure value after the prediction of the multivariable pressure prediction model is generated, calculating the prediction error, and sending the error back to the multivariable pressure prediction model to guide the parameter adjustment of the multivariable pressure prediction model;

[0029] The feature extraction unit is responsible for the feedback results of parameter adjustment. It extracts features from historical multidimensional data and combines the feedback information to self-optimize the parameters of the multivariable pressure prediction model to obtain parameter combinations.

[0030] In an optional implementation manner, the signal processing component includes:

[0031] The signal acquisition module is responsible for connecting with the gas sensor through an interface and receiving the low-amplitude voltage analog signal output in real time, including the concentration, temperature and humidity characteristics of the gas; using the analog-to-digital converter to resolve the continuous analog signal into a discrete voltage digital signal according to the sampling frequency;

[0032] The analog-to-digital conversion module is responsible for enhancing and purifying the voltage digital signal after the voltage analog signal has been converted to digital, increasing the signal amplitude, and removing high-frequency noise and interference signals; applying a smoothing algorithm to reduce short-term fluctuations;

[0033] The signal comparison module is responsible for comparing the processed voltage digital signal with the set standard value in real time, and using the absolute error to determine whether it is within the specified range; when the voltage digital signal is within the tolerance range of the set standard value, the signal processing component outputs a high-level signal; if the voltage digital signal exceeds the set range of the standard value, the component outputs a low-level signal.

[0034] In an optional implementation, the signal comparison module includes:

[0035] The first comparison submodule is responsible for calculating the mean and standard deviation of the voltage digital signal using historical data and setting the threshold; determining the upper and lower limits of the voltage digital signal based on the set constants to form a tolerance range; after receiving each new voltage digital signal, comparing it with the set upper and lower limits; if the voltage digital signal exceeds the upper limit or is lower than the lower limit, marking it as abnormal; if the signal is within the range, continuing normal monitoring;

[0036] The second comparison submodule is responsible for marking the voltage digital signal as abnormal in the preliminary judgment layer, entering the discrimination enhancement layer, extracting multiple key features from the abnormal voltage digital signal, including the maximum value, minimum value, mean value, standard deviation and rate of change of the voltage digital signal, analyzing and classifying the voltage digital signal features, distinguishing between normal voltage digital signals and abnormal voltage digital signals, and generating a judgment result indicating whether the voltage digital signal is abnormal;

[0037] The third comparison submodule is responsible for determining whether to adjust the sampling frequency of the voltage digital signal according to the current state of the voltage digital signal for the voltage digital signal that is still marked as abnormal in the judgment enhancement layer.

[0038] In an optional implementation, the calibration adjustment component comprises:

[0039] The first program trigger module is responsible for receiving the report from the signal processing component in real time; when the voltage digital signal detected by the analog signal of the gas sensor does not match the set standard value, that is, is outside the set standard value range, the calibration adjustment program of the calibration adjustment component is triggered;

[0040] The second program trigger module is responsible for triggering the zero point calibration subroutine in the calibration adjustment program. It first introduces pure air and outputs a voltage signal close to zero in the absence of target gas, and compares the currently read voltage signal with the ideal zero point value.

[0041] The third program trigger module is responsible for triggering the span calibration subroutine after the zero calibration subroutine is completed, introducing a target gas of known concentration for span calibration; under the input of target gas of different concentrations, a series of output response values ​​are generated, and the response values ​​are compared with the response standard values ​​under the corresponding concentrations to determine whether the output of the sensor is within an acceptable range;

[0042] If the output signal at a known concentration meets the set response standard value, it is judged to be qualified; if it is unqualified, continue to make adjustments or make maintenance suggestions.

[0043] In an optional implementation manner, the second program triggering module includes:

[0044] The gas input submodule is responsible for introducing pure air for 1-2 minutes. When the display value of the reference standard gas sensor reaches 0, a trigger signal will be sent to the zero calibration module.

[0045] The zero calibration submodule is responsible for entering the zero calibration mode after receiving the trigger signal sent by the reference standard gas sensor. The measured gas sensor automatically calibrates the current gas concentration as the zero point, and the displayed value should be 0;

[0046] The device connection submodule, the gas input submodule and the zero point calibration submodule are connected by using an interface converter, and the trigger signal is transmitted to the zero point calibration submodule.

[0047] In an optional implementation manner, the third program triggering module includes:

[0048] The calibration gas input submodule is responsible for connecting the gas of known concentration, ensuring that the calibration gas concentration is within the measurement range of the sensor, and passing the calibration gas;

[0049] The calibration control submodule is responsible for recording the concentration of the calibration gas according to the concentration of the known gas and the value displayed by the reference standard gas sensor, and transmitting the concentration value to the span calibration module;

[0050] The span calibration submodule is responsible for receiving the values ​​from the calibration control module and adjusting the reading of the gas sensor under test to match the input calibration gas concentration. During the span calibration process, the reading should be 10% higher than the full scale value. After the calibration is completed, the response value of the gas sensor in each gear is recorded and compared with the response standard value. If it does not meet the response standard value, the current gas sensor is judged to be unqualified.

[0051] The gas input component of the present invention determines the type and value of the required target gas according to the verification requirements, and then activates the pressure reducing device module to input the target gas into the corresponding gas sensor in a controllable manner. During the input process, the gas input component continuously monitors the pressure of the target gas to ensure that it remains constant after reaching the set standard pressure; the signal processing component first collects the analog signal of the fixedly installed gas sensor, and then converts the analog signal into a voltage digital signal, performs preprocessing operations such as amplification and filtering on the converted voltage digital signal, and then compares the preprocessed voltage digital signal with the set standard value. If it is within the set standard value range, the gas sensor is judged to be qualified, if it exceeds the range, it is judged to be unqualified, and the calibration adjustment component is triggered; when the calibration adjustment component is triggered, the gas sensor is firstly zero-calibrated using pure air, and then the gas sensor is span-calibrated using a target gas of known concentration, and the response value of the gas sensor is recorded at multiple different concentration gears, and compared with the corresponding response standard value. If the response value of the gas sensor meets the response standard value at all test gears, it is judged to be qualified, otherwise it is unqualified, and corresponding feedback or processing suggestions are given. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0053] Figure 1 This is a schematic diagram of the functional modules of the gas sensor calibration device provided in Example 1 of the present invention;

[0054] Figure 2 This is a block diagram of a gas input component provided in Example 2 of the present invention;

[0055] Figure 3 This is a block diagram of a pressure detection module provided in Example 3 of the present invention;

[0056] Figure 4 A block diagram of a strategy forming submodule provided in Embodiment 4 of the present invention;

[0057] Figure 5 This is a block diagram of a signal processing component provided in Embodiment 5 of the present invention;

[0058] Figure 6 This is a block diagram of a signal comparison module provided in Embodiment 6 of the present invention;

[0059] Figure 7 This is a block diagram of a calibration adjustment component provided in Embodiment 7 of the present invention;

[0060] Figure 8 This is a block diagram of a second program triggering module provided in Embodiment 8 of the present invention;

[0061] Fig. 9 This is a block diagram of a third program triggering module provided in Embodiment 9 of the present invention;

[0062] Fig.10 A block diagram of an electronic device provided by an embodiment of the present invention;

[0063] Fig.11 A block diagram of a computer-readable storage medium provided for an embodiment of the present invention. DETAILED DESCRIPTION

[0064] The technical solutions in the embodiments of the present invention will be described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0065] In the following, the terms "first", "second", etc. are used only for convenience of description and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first", "second", etc. may explicitly or implicitly include one or more of the features. In the description of the present invention, unless otherwise specified, "plurality" means two or more.

[0066] In the present invention, unless otherwise clearly specified and limited, the term "connection" should be understood in a broad sense, for example, "connection" can be a fixed mechanical connection, or a detachable mechanical connection, or integrated; or, "connection" can be a direct connection, or an indirect connection through an intermediate medium. In addition, unless otherwise clearly specified and limited, the term "coupling" should be understood in a broad sense, for example, "coupling" can be a direct electrical connection, such as physical contact and electrical conduction between two components, and can also be understood as electrical connection between different components in a circuit structure through physical lines such as copper foil or wires on a printed circuit board (PCB) that can transmit electrical signals to transmit electrical signals; or, "coupling" can be an indirect electrical connection between two components through an intermediate medium; or, "coupling" can be an electrical connection between two components in an air-spaced / non-contact manner, for example, two components are electrically connected by capacitive coupling to transmit electrical signals.

[0067] In the embodiments of the present invention, directional terms such as "up", "down", "left" and "right" may be defined including but not limited to the orientation relative to the schematic placement of the components in the drawings. It should be understood that these directional terms may be relative concepts, which are used for relative description and clarification, and may change accordingly according to the change of the orientation of the components in the drawings.

[0068] The embodiments of the present invention can be used for the calibration of gas sensors to ensure that the gas sensors can accurately detect the concentration of the target gas and provide reliable data output; by comparing the sensor with a gas of known concentration, its accuracy can be confirmed and necessary corrections can be made. Improve the performance stability of the sensor. Through regular verification and calibration, performance degradation caused by factors such as time changes, changes in environmental conditions or sensor aging can be avoided, thereby ensuring the stability and consistency of the sensor in long-term use. To ensure safety and compliance, accurate gas detection is essential in certain application scenarios (such as industry, environmental monitoring, etc.). Ensuring the qualification of the sensor through an effective verification procedure can prevent potential safety hazards and avoid safety accidents caused by erroneous data. Data reliability verification, through the introduction of signal processing components, can ensure that the data collected by the sensor is properly processed and analyzed, enhance the credibility of the data, and provide a reliable basis for subsequent decision-making, monitoring or control.

[0069] Example 1: Figure 1 As shown, an embodiment of the present invention provides a gas sensor calibration device, comprising: a gas input component 1, a signal processing component 2, and a calibration adjustment component 3;

[0070] The gas input component 1 is used to obtain the type and value of the target gas required for the calibration of the gas sensor, activate the pressure reduction device module, input the target gas into the corresponding gas sensor, and keep the target gas pressure constant when the input target gas pressure reaches the set standard;

[0071] The signal processing component 2 is used to collect the analog signal of the gas sensor, which includes the gas characteristics and concentration of the target gas detected by the gas sensor; convert the analog signal into a voltage digital signal, pre-process the voltage digital signal, and compare it with the set standard value. If it is within the set standard value range, it is qualified; if it is outside the set standard value range, it is unqualified;

[0072] The calibration adjustment component 3 is used to trigger the calibration adjustment program according to the unqualified content outside the set standard value range received; use pure air to perform zero point calibration, and then use the target gas of known concentration to perform span calibration, record the response value of the gas sensor at each gear, and compare the response value with the response standard value. If it does not meet the response standard value, the current gas sensor is judged to be unqualified.

[0073] The gas input component 1 in the above embodiment determines the type and value of the required target gas according to the verification requirements, and then activates the pressure reducing device module to input the target gas into the corresponding gas sensor in a controllable manner. During the input process, the gas input component will continuously monitor the pressure of the target gas to ensure that it remains constant after reaching the set standard pressure; the signal processing component 2 first collects the analog signal of the fixedly installed gas sensor, and then converts the analog signal into a voltage digital signal, performs preprocessing operations such as amplification and filtering on the converted voltage digital signal, and then compares the preprocessed voltage digital signal with the set standard value. If it is within the set standard value range, the gas sensor is judged to be qualified, if it exceeds the range, it is judged to be unqualified, and the calibration adjustment component 3 is triggered; when the calibration adjustment component is triggered, the gas sensor is firstly zero-calibrated with pure air, and then the gas sensor is span-calibrated with a target gas of known concentration. At multiple different concentration levels, the response value of the gas sensor is recorded and compared with the corresponding response standard value. If the response value of the gas sensor meets the response standard value at all test levels, it is judged to be qualified, otherwise it is unqualified, and corresponding feedback or processing suggestions are given.

[0074] In summary, this embodiment accurately determines the type and value of the required target gas according to the verification requirements to ensure the pertinence and accuracy of the verification, enables the pressure reducing equipment module, and inputs the target gas into the corresponding gas sensor in a controllable and stable manner, thereby avoiding measurement errors caused by unstable gas flow or pressure. The pressure of the target gas is continuously monitored during the input process to ensure that it remains constant after reaching the set standard pressure, thereby providing a reliable guarantee for subsequent precise measurements, ensuring the accuracy and stability of the target gas during the verification process, improving the reliability of the verification results, and providing a stable and reliable gas input environment for subsequent signal processing and calibration adjustments; efficiently collects the analog signal of the gas sensor and converts it into a voltage digital signal for easy subsequent processing and analysis, performs preprocessing operations such as amplification and filtering on the voltage digital signal, thereby improving the signal-to-noise ratio and accuracy of the signal, and reducing the influence of noise and interference on the measurement results; compares and analyzes the preprocessed voltage digital signal with the set standard value to accurately and quickly judge the gas sensor Whether the performance of the sensor is qualified, it realizes the accurate processing and rapid analysis of the gas sensor output signal, and improves the verification efficiency; through comparative analysis, it can timely discover and determine whether the performance of the gas sensor is qualified, providing a scientific basis for subsequent calibration and adjustment; after receiving the unqualified trigger signal of the signal processing component, it automatically starts the calibration adjustment program, realizes the intelligent calibration of the gas sensor, and uses pure air and target gas of known concentration to perform zero point calibration and span calibration on the gas sensor in turn, ensuring that the response characteristics of the sensor at different concentrations meet the requirements; records the response value of the gas sensor at multiple different concentration levels, and compares and analyzes it with the corresponding response standard value, comprehensively evaluates the performance of the sensor, and ensures the accuracy and stability of the gas sensor under different conditions of use through automatic calibration and precise adjustment, improves the measurement accuracy and reliability of the gas sensor, and provides a strong guarantee for practical applications. Through comprehensive evaluation and feedback, it provides a reference basis for further optimization and improvement of the gas sensor.

[0075] Example 2: Figure 2 As shown, based on Example 1, the gas input component 1 provided in this embodiment of the present invention comprises:

[0076] The parameter acquisition module is responsible for confirming the gas sensor model, application field, and gas characteristics and standards to be tested before starting to acquire the target gas; the application fields include environmental monitoring, industrial safety, and food quality, and the standards include gas concentration range and response speed, etc.;

[0077] The concentration acquisition module is responsible for selecting one or more reference concentration values ​​as the target concentration and using a high gas concentration detection instrument to monitor and verify the actual concentration of the mixed gas in real time;

[0078] The pressure detection module is responsible for connecting the pressure reducing device to the gas input component, setting the initial pressure value of the pressure reducing device, turning on the pressure reducing device, and monitoring the pressure changes of the target gas. The pressure of the target gas is monitored in real time using a pressure sensor. If the gas pressure does not reach the set standard, it is adjusted by adjusting the valve of the pressure reducing device.

[0079] The parameter acquisition module in the above embodiment can automatically identify the model of the gas sensor to be calibrated, and understand its applicable scope and technical parameters; it can classify and identify the application fields of gas sensors (such as environmental monitoring, industrial safety and food quality, etc.), and extract the corresponding technical requirements; clarify the standards that gas calibration needs to meet, including gas concentration range and response speed. Significance achieved: By understanding the characteristics and application scenarios of gas sensors, it can provide the necessary basis for calibration and verification, ensuring that the inspection process is highly targeted and the results are effective; automated parameter acquisition reduces manual intervention, improves the efficiency and accuracy of calibration, and lays the foundation for each step in the calibration process. The concentration acquisition module selects one or more reference concentration values ​​as the target concentration according to known standards or actual needs; uses a high-precision gas concentration detection instrument to monitor and verify the actual concentration of the mixed gas in real time to ensure that the generated gas concentration meets the design requirements. Significance achieved: Real-time verification of the concentration of the mixed gas ensures that the input gas remains within the specific range that the sensor needs to detect, which is crucial to the accuracy of the calibration; by continuously detecting and confirming the concentration, the credibility of the output data is ensured, providing a reliable basis for the performance evaluation of the sensor and subsequent decision-making. The pressure detection module connects the pressure reducing device to the gas input component, sets the initial pressure value, and monitors the pressure changes of the gas in real time; the pressure of the target gas is continuously monitored through the pressure sensor, providing a feedback mechanism to ensure the constant gas pressure; if the pressure does not reach the set standard, it can be adjusted. The significance achieved: Ensure that the gas sensor can receive a pressure state that meets the standard requirements when being tested, which improves the consistency and repeatability of the test results; since the pressure changes in gas detection may cause measurement errors, real-time monitoring and adjustment can reduce the possibility of failures and errors, thereby ensuring the reliability of the entire verification process.

[0080] In summary, this embodiment can realize the system control and standardized operation of the gas sensor calibration process through the cooperation of various modules in the gas input component 1, ensuring the effective monitoring of various parameters during the calibration process. It improves the accuracy, efficiency and data reliability of the calibration, and provides a guarantee for the stability and safety of the entire gas detection system.

[0081] Example 3: Figure 3 As shown, based on Example 2, the pressure detection module provided by the embodiment of the present invention includes:

[0082] The network connection submodule is responsible for the layout of pressure sensors and monitoring the pressure changes in gas flow. It uses communication protocols to connect the sensor network to form a decentralized real-time data transmission network, allowing each sensor to work independently and share data.

[0083] The strategy formation submodule is responsible for setting the sampling rate of each pressure sensor, detecting pressure fluctuations, and saving the detected anomalies in the database; identifying the relationship between gas pressure and environmental variables such as temperature, humidity, and flow rate, building a multivariate pressure prediction model, predicting future pressure changes based on historical data, and forming a dynamic adjustment strategy;

[0084] Among them, the multivariate pressure prediction model includes:

[0085] Data preprocessing layer, which collects multi-dimensional time series data from sensor networks, including pressure, temperature, humidity, flow rate, etc.; data standardization, missing value processing, and time series reconstruction;

[0086] Feature extraction layer, processed two-dimensional data (for example, sensor data is reshaped into a two-dimensional matrix, one dimension of which is the time series and the other dimension is the environmental variable); extract local spatial features through multiple convolutional layers, combined with the maximum pooling layer to reduce the data dimension and extract higher-level feature patterns; the extracted spatial feature vectors are used for time series analysis;

[0087] The time series analysis layer captures the long-term dependencies in the time series data from the feature vector sequence output from the feature extraction layer, identifies the historical trends and patterns of pressure, and outputs the hidden state of each time step as the basis for predicting future pressure changes;

[0088] The joint prediction layer inputs the hidden state and the extracted spatial features; combines the spatial features with the temporal features, further processes them through the fully connected layer, and uses the fused features to perform multivariate pressure prediction; outputs the future pressure value prediction, confidence interval, and fault indicator;

[0089] The decision-making and feedback layer inputs the predicted pressure value and actual monitoring data; monitors the difference between the predicted and actual values ​​in real time, calculates the error, and loops the feedback information back to the model to optimize parameters and strategies; provides adjustment feedback to maintain the pressure within a safe range, and continuously adjusts the model prediction performance by combining historical data and real-time data;

[0090] The parameter adjustment submodule is responsible for automatically updating the working parameters of the regulating valve after calculating the required pressure value; if the pressure exceeds the set range, the valve will be automatically adjusted to close or open, adjust the gas inflow, and keep the pressure within a safe range.

[0091] In the above embodiment, the network connection submodule reasonably arranges sensors according to the gas flow path and the required monitoring accuracy to ensure that all key positions have pressure monitoring to form a complete coverage network; the data of each sensor is transmitted to the central control unit in real time instead of relying on a single central node, which improves the robustness and flexibility of the system. The significance achieved: ensure that the pressure changes in the gas flow can be detected and fed back in real time, reduce delays, and improve the response speed of the overall system; the decentralized architecture avoids the risk of single point failure. If a sensor has a problem, other sensors can continue to work, ensuring the stability and reliability of the entire system. The strategy formation submodule reasonably sets the sampling rate of each pressure sensor according to the fluid dynamic characteristics and application requirements to capture the rapidly changing pressure situation, and uses the algorithm to detect that when the pressure fluctuation exceeds the set range, it is marked as abnormal and saved in the database; the historical data is mined and modeled to identify the relationship between gas pressure and environmental variables (such as temperature, humidity, flow rate), so as to establish a pressure prediction model affected by multiple factors. Significance achieved: Provide scientific decision-making support based on data for gas pressure management, improve the calibration accuracy and performance of gas sensors by having real-time data and dynamic adjustment strategies; through the prediction model, it can predict pressure changes in advance and generate adjustment strategies in time to avoid overreaction caused by pressure changes, thereby improving the intelligence level and operation efficiency of the system. After calculating the required pressure, the parameter adjustment submodule automatically sends instructions to the intelligent control valve to adjust the valve opening and gas inflow; if the detected pressure exceeds the set range, it will automatically adjust to keep the gas pressure within a safe and acceptable range by controlling the opening or closing of the control valve. Significance achieved: The automatic adjustment function can effectively prevent safety hazards such as explosions or equipment damage caused by abnormal pressure, and ensure the stable operation of the system; through the automated adjustment process, it reduces dependence on manual operations, avoids delays or errors caused by human factors, and improves the overall efficiency of the system.

[0092] In summary, the three submodules of this embodiment constitute the overall architecture of the pressure detection module, and perform intelligent optimization for data acquisition, strategy formation, and parameter adjustment. The system's real-time monitoring, prediction, and response capabilities are enhanced, thereby achieving safe, efficient, and automated gas pressure management. This not only improves the calibration accuracy and stability of gas sensors, but also provides important support and guarantees for related industries (such as chemical industry, metallurgy, electronics, etc.).

[0093] Example 4: Figure 4 As shown, based on Example 3, the strategy formation submodule provided in this embodiment of the present invention includes:

[0094] The data analysis unit is responsible for integrating the historical pressure data, temperature, humidity, flow rate and other multi-dimensional data from various sensors into a time series data stream, and regularly extracting time segments for analysis through the window sliding method; for each time segment of the input data, the change amplitude of the data within the time segment is calculated, and the learning rate and feature weight of the multivariate pressure prediction model are dynamically adjusted using the statistical characteristics of the change amplitude;

[0095] The error processing unit is responsible for monitoring the actual pressure value in real time after the prediction of the multivariable pressure prediction model is generated, calculating the prediction error, and sending the error back to the multivariable pressure prediction model to guide the parameter adjustment of the multivariable pressure prediction model;

[0096] The feature extraction unit is responsible for the feedback results of parameter adjustment. It extracts features from historical multidimensional data and combines the feedback information to self-optimize the parameters of the multivariable pressure prediction model to obtain parameter combinations.

[0097] The data analysis unit in the above embodiment integrates multidimensional data such as historical pressure, temperature, humidity and flow rate into an orderly time series data stream to enhance the analyzability of the data; regularly extracts data segments through the sliding window method to ensure effective and continuous monitoring and analysis of real-time and historical data; dynamically evaluates the change amplitude of data within the time segment, and dynamically adjusts the learning rate and feature weight of the model according to the statistical characteristics of the change. Significance: It can quickly identify trends and anomalies, and provide a real-time and accurate data basis for subsequent prediction models; by dynamically adjusting the learning rate and feature weight of the model, the model can automatically optimize according to environmental changes, enhancing the accuracy and stability of the prediction. After the prediction is generated, the error processing unit continuously monitors the actual pressure value and calculates the error with the prediction result; the prediction error is fed back to the multivariate pressure prediction model to prompt the model to adjust its internal parameters. Significance: By real-time monitoring of the actual results, the sensitivity of the model to environmental changes is ensured, making the prediction more accurate; effectively using feedback information to achieve closed-loop control, improve the model's ability to respond to future data changes, and improve the overall learning efficiency and reliability of the model. The feature extraction unit extracts important features from historical multidimensional data based on the feedback results of parameter adjustment, and conducts in-depth analysis in combination with real-time feedback information; the extracted features and feedback information are used to continuously optimize the parameter combination of the multivariate pressure prediction model. Significance: Through the extraction and integration of features, the model can accurately capture the various variables that affect pressure changes and enhance the model's adaptability to complex environments; it promotes the self-optimization of the model so that it can automatically adjust its strategy and maintain excellent prediction performance when facing different external conditions.

[0098] In summary, the three units of this embodiment jointly construct a fully automatic and adaptive pressure prediction system; through automatic data analysis, real-time error monitoring and feature self-extraction, the intelligence of the system is improved and human intervention is reduced; through dynamic adjustment and self-optimization mechanisms, it is ensured that the model can always reflect the latest environmental status, improve the accuracy of the prediction and the reliability of the system; provide high-quality predictions and real-time feedback, so that decision makers can formulate response strategies more effectively and optimize gas flow management and safety measures.

[0099] Example 5: Figure 5 As shown, based on Example 1, the signal processing component 2 provided in this embodiment of the present invention includes:

[0100] The signal acquisition module is responsible for connecting with the gas sensor through an interface and receiving the low-amplitude voltage analog signal output in real time, including gas concentration, temperature, humidity and other characteristics; using the analog-to-digital converter to resolve the continuous analog signal into a discrete voltage digital signal according to the sampling frequency;

[0101] The analog-to-digital conversion module is responsible for enhancing and purifying the voltage digital signal after the voltage analog signal has been converted to digital, increasing the signal amplitude, and removing high-frequency noise and interference signals; applying a smoothing algorithm to reduce short-term fluctuations;

[0102] Among them, the expression of the analog-to-digital converter is:

[0103] ;

[0104] In the formula, represents the analog-to-digital conversion efficiency, Indicates the resolution of the analog-to-digital converter (number of bits), Indicates the frequency bandwidth (bandwidth) of the voltage analog signal, It represents the instantaneous voltage value of the input voltage analog signal at time t, T represents the total sampling time, Represents the filter function, which is a Gaussian filter or other complex filter function, used to simulate the characteristics of the actual voltage analog signal. Represents a multidimensional function, representing multiple influencing factors. represents the mean value of the input signal, Represents the variance of the input voltage analog signal, characterizing the change in the strength of the voltage analog signal. Represents additional adjustment parameters used to dynamically adjust noise suppression or gain control during analog-to-digital conversion. It represents the time constant representing the fluctuation of voltage analog signal, and is used to describe the time characteristics and filtering delay of voltage analog signal;

[0105] The expression of the smoothing algorithm is:

[0106] ;

[0107] Among them, the weight It is calculated by the following formula:

[0108] ;

[0109] In the formula, Indicates at a point in time The voltage analog signal output value after smoothing is Represents the original voltage analog signal at the time point The value of represents the window size or number of samples, represents the weight of each sample point, represents the attenuation factor (0 < < 1), controlling the decay of weights over time, represents the adjustment parameter, controlling the mean calculation, represents the shape parameter, which affects the characteristics of the weight distribution, represents the gamma function, which is used to expand the complexity of weight calculation;

[0110] The signal comparison module is responsible for comparing the processed voltage digital signal with the set standard value in real time, and using the absolute error to determine whether it is within the specified range; when the voltage digital signal is within the tolerance range of the set standard value, the signal processing component outputs a high-level signal; if the voltage digital signal exceeds the set range of the standard value, the component outputs a low-level signal.

[0111] The signal acquisition module in the above embodiment is connected to the gas sensor through an interface, and can receive the low-amplitude voltage analog signal output by the sensor in real time to ensure the timeliness of the information; the acquisition signal contains multiple characteristics such as gas concentration, temperature, humidity, etc., providing comprehensive gas detection parameters. The significance achieved: Real-time acquisition of multiple gas characteristics ensures that the monitoring system can obtain comprehensive environmental information and promote the comprehensiveness of subsequent analysis; it can capture the changes in gas properties in a timely manner and provide a basis for system decision-making, which is conducive to the realization of rapid response and control. The analog-to-digital conversion module converts the continuous analog signal into a discrete voltage digital signal, making it more suitable for digital processing; through a built-in enhancement circuit, the amplitude of the voltage digital signal is increased to make it more recognizable; digital filtering and noise suppression algorithms are used to remove high-frequency noise and interference in the signal and improve the purity of the signal; by applying smoothing algorithms (such as moving average), short-term fluctuations are reduced and long-term trends are extracted. The significance achieved: The voltage digital signal obtained after enhancement and purification provides a higher quality data basis for subsequent analysis, improves the signal-to-noise ratio and data reliability; smoothing reduces the uncertainty of measurement, making subsequent standard comparisons more accurate, thereby improving the credibility of the detection results. The signal comparison module can compare the processed voltage digital signal with the set standard value in real time, and judge whether it is within the specified range through absolute error; according to the comparison result, the output signal is high or low, representing qualified or unqualified respectively. Significance achieved: Real-time comparison and indication enable the system to respond to the status of the gas sensor immediately, quickly adjust the system operation or start the calibration procedure to ensure the normal operation of the sensor; by setting the standard value for qualification judgment, the reliability and accuracy of the gas sensor during use can be ensured, so that the performance of the entire detection system is improved.

[0112] In summary, the various modules of this embodiment work together to form a complete signal processing chain. This structure not only improves the quality and reliability of the signal, but also enhances the real-time response capability of the system, so that the performance of the gas sensor can be accurately evaluated. The design and function of each module are aimed at achieving a more efficient and stable gas detection system, providing strong technical support for industrial applications, environmental monitoring and other fields.

[0113] Example 6: Figure 6 As shown, based on Example 5, the signal comparison module provided in this embodiment of the present invention includes:

[0114] The first comparison submodule is responsible for calculating the mean and standard deviation of the voltage digital signal using historical data and setting the threshold; determining the upper and lower limits of the voltage digital signal based on the set constants to form a tolerance range; after receiving each new voltage digital signal, comparing it with the set upper and lower limits; if the voltage digital signal exceeds the upper limit or is lower than the lower limit, marking it as abnormal; if the signal is within the range, continuing normal monitoring;

[0115] The second comparison submodule is responsible for marking the voltage digital signal as abnormal in the preliminary judgment layer, entering the discrimination enhancement layer, extracting multiple key features from the abnormal voltage digital signal, including the maximum value, minimum value, mean value, standard deviation and rate of change of the voltage digital signal, analyzing and classifying the voltage digital signal features, distinguishing between normal voltage digital signals and abnormal voltage digital signals, and generating a judgment result indicating whether the voltage digital signal is abnormal;

[0116] The third comparison submodule is responsible for determining whether to adjust the sampling frequency of the voltage digital signal according to the current state of the voltage digital signal for the voltage digital signal that is still marked as abnormal in the judgment enhancement layer.

[0117] The first comparison submodule in the above embodiment uses historical data to calculate the mean and standard deviation of the voltage digital signal, sets a threshold, determines the tolerance range according to the set constant, compares the new signal with the threshold after receiving it, and marks it as abnormal or normal; through the calculation of the mean and standard deviation, a basic statistical description of the signal is provided, which enables the system to adaptively reflect the normal fluctuation range of the signal; accurate upper and lower limit settings can quickly identify potential anomalies, so as to take appropriate measures in the shortest time. Achievement significance: realize preliminary monitoring of signals, provide real-time feedback, and improve the system's response ability to abnormal signals; reduce interference caused by system false alarms, enhance system reliability, and ensure that the normal operating environment can be maintained continuously. The second comparison submodule conducts in-depth analysis of the voltage digital signal marked as abnormal; extracts multiple key features, such as maximum value, minimum value, mean value, standard deviation and rate of change, and classifies these features to generate judgment results; through feature extraction, a detailed description of the signal is provided, which enhances the understanding of signal behavior; complex classification methods (such as decision trees, support vector machines, etc.) can effectively distinguish normal and abnormal signals, reduce the misjudgment rate, and improve the accuracy of judgment. Significance achieved: Provides a deeper analysis basis for anomaly detection, ensuring that the system does not rely solely on surface information, but makes more reasonable judgments based on the characteristics of the signal, which helps identify the root causes of potential system problems, optimizes monitoring strategies, and provides data support for subsequent improvements. The third comparison submodule decides whether to adjust the sampling frequency based on the current signal state for the voltage digital signal that is still marked as abnormal in the discrimination enhancement layer; dynamically adjusting the sampling frequency can improve the ability to capture asynchronous signals, ensuring that the system can still obtain accurate data when the signal changes rapidly, thereby more effectively monitoring the signal. Significance achieved: Realizes real-time adaptation to signal processing, improves system flexibility, and ensures that the monitoring system can maintain efficient operation even in complex signal environments; adaptability can not only improve data accuracy, but also reduce the burden on back-end data analysis, optimize resource utilization, and improve overall system performance.

[0118] In summary, the signal comparison module of this embodiment constructs an efficient and accurate signal monitoring and analysis mechanism through the synergy of three submodules. The design of each submodule is aimed at improving the overall monitoring capability and providing support for real-time processing, in-depth analysis and dynamic response of signals. It strengthens the reliability and stability of the system and helps to detect and handle abnormal situations in a timely manner.

[0119] Embodiment 7: Based on Embodiment 1, the calibration adjustment component provided in the embodiment of the present invention comprises:

[0120] The first program trigger module is responsible for receiving the report from the signal processing component in real time; when the voltage digital signal detected by the analog signal of the gas sensor does not match the set standard value, that is, is outside the set standard value range, the calibration adjustment program of the calibration adjustment component is triggered;

[0121] The second program trigger module is responsible for triggering the zero point calibration subroutine in the calibration adjustment program. It first introduces pure air and outputs a voltage signal close to zero in the absence of target gas, and compares the currently read voltage signal with the ideal zero point value.

[0122] The third program trigger module is responsible for triggering the span calibration subroutine after the zero calibration subroutine is completed, introducing a target gas of known concentration for span calibration; under the input of target gas of different concentrations, a series of output response values ​​are generated, and the response values ​​are compared with the response standard values ​​under the corresponding concentrations to determine whether the output of the sensor is within an acceptable range;

[0123] If the output signal at a known concentration meets the set response standard value, it is judged to be qualified; if it is unqualified, continue to make adjustments or make maintenance suggestions.

[0124] The first program trigger module in the above embodiment receives the report from the signal processing component in real time; monitors the analog signal of the gas sensor and confirms whether its voltage digital signal is within the set standard value range; provides an efficient real-time monitoring mechanism to ensure that the system can quickly respond to the working status of the sensor; when an unqualified signal is detected, it can immediately trigger the subsequent calibration adjustment program to avoid potential measurement errors. Achievement significance: Improve the system's timely response capability and ensure that it can quickly switch to the calibration mode when a problem is found, which provides the necessary timeliness for subsequent calibration work; ensure that the system can actively maintain monitoring reliability and effectively prevent safety hazards caused by sensor errors. The second program trigger module introduces pure air and ensures that the sensor outputs a voltage signal close to zero in the absence of target gas; compares the read voltage signal with the ideal zero point value to determine the accuracy of the zero point calibration; ensures the accuracy of the sensor reference point. By calibrating in a zero gas environment, the influence of environmental factors on the sensor output can be eliminated; and a stable foundation is provided for subsequent concentration measurement and span calibration. Significance achieved: Through effective zero-point calibration, the system deviation of the sensor can be minimized, which is crucial to ensure the reliability of subsequent measurement results; it directly affects the performance of the sensor under various working conditions, and setting an accurate benchmark is crucial for the steady-state performance of the overall gas monitoring system. After the zero-point calibration, the third program trigger module triggers the span calibration subroutine to introduce a target gas of known concentration; records the sensor output response value at different concentrations, and compares it with the response standard value of the corresponding concentration to determine whether the sensor measurement is within an acceptable range; through span calibration, the accuracy of the sensor's response to gases of different concentrations in actual applications can be guaranteed, covering the full range of actual measurements; a systematic method is provided to facilitate verification through known standards, thereby improving the reliability of measurement results. Significance achieved: Ensure that the sensor maintains efficient and accurate response performance under a variety of gas concentrations, and improve the adaptability of the entire gas detection system to environmental changes; accurate calibration greatly improves the credibility of the sensor in actual use, and ensures safety and data accuracy in a wider range of application scenarios.

[0125] In summary, through the coordinated operation of these three program-triggered modules, the calibration and adjustment component of this embodiment not only improves the performance and accuracy of the gas sensor, but also enhances the overall reliability and flexibility of the gas detection system. The functions of each module are interconnected to ensure comprehensive coverage from signal reception, zero point calibration to span calibration, forming a complete set of effective gas sensor calibration mechanisms, which provides a strong guarantee for long-term monitoring applications. Overall, the structured design scheme can ensure the stability and accuracy of the system under various conditions, thereby maintaining the safety of gas monitoring.

[0126] Example 8: Figure 8 As shown, based on Example 7, the second program triggering module provided in this embodiment of the present invention includes:

[0127] The gas input submodule is responsible for introducing pure air for 1-2 minutes. When the display value of the reference standard gas sensor reaches 0, a trigger signal will be sent to the zero calibration module.

[0128] The zero calibration submodule is responsible for entering the zero calibration mode after receiving the trigger signal sent by the reference standard gas sensor. The measured gas sensor automatically calibrates the current gas concentration as the zero point, and the displayed value should be 0;

[0129] The device connection submodule, the gas input submodule and the zero point calibration submodule are connected by using an interface converter, and the trigger signal is transmitted to the zero point calibration submodule.

[0130] The gas input submodule in the above embodiment passes pure air into the gas sensor and continues ventilation for 1-2 minutes; monitors the display value of the reference standard gas sensor to determine whether it is 0, ensures that the sensor operates without the target gas, and provides a stable environment to ensure the true zero-point output; through continuous ventilation, removes any gas that may remain in the sensor, reduces environmental interference, and improves the accuracy of subsequent calibration. Achievement significance: Ensure that the gas sensor can accurately establish a reference environment when performing zero-point calibration, and provide necessary conditions for subsequent calibration work; avoid measurement errors caused by gas residues or environmental gas, and enhance the reliability of the system. After receiving the trigger signal sent by the gas input submodule, the zero-point calibration submodule enters the zero-point calibration mode; calibrates the current gas concentration of the gas sensor being tested to zero value, and the displayed output should be 0; confirms that the output channel of the sensor should output a voltage signal close to zero in the absence of any target gas; performs precise zero-point calibration to ensure that the sensor can provide accurate concentration measurement from zero point. Significance achieved: The accuracy of zero-point calibration is crucial to the overall performance of the gas sensor and is the basis for subsequent concentration measurements. Through a systematic calibration procedure, the accuracy and reliability of the gas sensor in actual use are ensured, reducing monitoring errors caused by improper calibration. The device connection submodule connects the gas input submodule and the zero-point calibration submodule, and transmits the trigger signal through the interface converter. It provides a stable communication bridge to ensure that the data and signals between the two submodules can interact efficiently and accurately, and ensure that the trigger signal can be transmitted to the zero-point calibration submodule in a timely and effective manner. Significance achieved: By ensuring that each module can be effectively connected, the stability and execution efficiency of the entire system are improved; technical support is provided for the smooth progress of the subsequent zero-point calibration process, ensuring the coordination of the system in operation, and avoiding calibration failures or errors due to signal transmission problems.

[0131] In summary, the second program trigger module of this embodiment forms an effective zero-point calibration process through the collaborative work of the gas input submodule, the zero-point calibration submodule and the device connection submodule. Each submodule not only assumes a specific function, but is also interrelated to jointly support the accurate implementation of zero-point calibration. The design of this module realizes the smooth conversion of the gas sensor from real environmental conditions to standard reference conditions, ensuring that the monitoring system can continue to produce reliable results. Through precise zero-point calibration, the overall measurement accuracy and data credibility of the system have been significantly improved, which helps to improve the effectiveness and safety of gas monitoring.

[0132] Example 9: Fig. 9 As shown, based on Example 7, the third program triggering module provided in this embodiment of the present invention includes:

[0133] The calibration gas input submodule is responsible for connecting the gas of known concentration, ensuring that the calibration gas concentration is within the measurement range of the sensor, and passing the calibration gas;

[0134] The calibration control submodule is responsible for recording the concentration of the calibration gas according to the concentration of the known gas and the value displayed by the reference standard gas sensor, and transmitting the concentration value to the span calibration module;

[0135] The span calibration submodule is responsible for receiving the values ​​from the calibration control module and adjusting the reading of the gas sensor under test to match the input calibration gas concentration. During the span calibration process, the reading should be 10% higher than the full scale value. After the calibration is completed, the response value of the gas sensor in each gear is recorded and compared with the response standard value. If it does not meet the response standard value, the current gas sensor is judged to be unqualified.

[0136] In the above embodiment, the calibration gas input module connects a gas of known concentration and adjusts its flow rate to ensure that the calibration gas concentration is within the effective measurement range of the sensor, thereby avoiding inaccurate calibration caused by too low or too high concentration, controlling the gas flow rate to avoid excessive pressure on the sensor, extending the service life of the sensor, and preventing damage caused by improper calibration process. It provides a stable and reliable calibration environment for subsequent calibration processes, is the basis for ensuring the accuracy of the calibration results, protects expensive sensor equipment, and reduces maintenance costs; the calibration control module accurately records the concentration of the calibration gas flow based on the known gas concentration and the displayed value of the reference standard gas sensor, and transmits the recorded calibration gas concentration value to the span calibration module, realizing data seamlessness. Seamless docking and automated processing improve the automation level of the calibration process, reduce errors caused by human intervention, provide precise data support for calibration adjustments, and ensure the accuracy and traceability of calibration; the span calibration module receives the values ​​from the calibration control module, and adjusts the readings of the measured gas sensor to match the input calibration gas concentration through algorithms or manual adjustments to achieve precise calibration of the span. After the calibration is completed, the response values ​​of the gas sensors in each gear are compared with the response standard values ​​to determine whether the sensor is qualified, ensuring the measurement standardization of the gas sensor at different concentrations, improving the overall performance of the sensor, and quickly determining whether the sensor is qualified, thereby improving the calibration efficiency and reducing the risk of unqualified sensors entering the production or use links.

[0137] Fig.10 A block diagram of an exemplary electronic device suitable for implementing embodiments of the present invention is shown.

[0138] The electronic device may include a central processing unit / microprocessor / main control chip, etc. 4; a storage medium 5, coupled to the central processing unit / microprocessor / main control chip, etc. 4, and storing computer executable instructions therein, for performing the steps of each method of an embodiment of the present invention when executed by the processor.

[0139] The central processing unit / microprocessor / main control chip 4 may include but is not limited to, for example, one or more processors or microprocessors.

[0140] The storage medium 5 may include, but is not limited to, for example, random access memory (RAM), read-only memory (ROM), flash memory, EPROM memory, EEPROM memory, registers, computer storage media (such as hard disk, floppy disk, solid state drive, removable disk, CD-ROM, DVD-ROM, Blu-ray disc, etc.).

[0141] In addition, the electronic device may also include (but not limited to) a data bus 6, an input / output bus / external bus / device bus 7, a display 8, and input / output devices 9 (eg, keyboard, mouse, speaker, etc.).

[0142] The central processing unit / microprocessor / main control chip etc. 4 can communicate with external devices (8, 9, etc.) through an I / O bus (H4) via a wired or wireless network (not shown).

[0143] The storage medium 5 may also store at least one computer executable instruction for executing the various functions and / or method steps in the embodiments described in the present technology when executed by the central processing unit / microprocessor / main control chip 4.

[0144] In one embodiment, the at least one computer executable instruction may also be compiled into or constitute a software product, wherein one or more computer executable instructions are executed by a processor to perform the various functions and / or method steps in the embodiments described in the present technology.

[0145] Fig.11 A schematic diagram of a computer-readable storage medium according to an embodiment of the present invention is shown.

[0146] like Fig.11 As shown, instructions are stored on a non-transitory computer-readable storage medium 11, and the instructions are, for example, computer-readable instructions 10. When the computer-readable instructions 10 are executed by the processor, the various methods described above can be executed. Non-transitory computer-readable storage media include, but are not limited to, for example, volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and / or cache memory (cache), etc. Non-transitory non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc. For example, the non-transitory computer-readable storage medium 11 can be connected to a computing device such as a computer, and then, when the computing device runs the computer-readable instructions 10 stored on the computer-readable storage medium 11, the various methods described above can be performed.

[0147] In the several embodiments provided by the present invention, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0148] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0149] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0150] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for executing all or part of the steps of the various embodiments of the present invention through a computer device (which can be a personal computer, server, or network device, etc.). The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (full name in English: Read-Only Memory, English abbreviation: ROM), random access memory (full name in English: Random Access Memory, English abbreviation: RAM), disk or optical disk, etc. Various media that can store program codes.

[0151] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A gas sensor testing device, characterized in that: Include: The gas input component is used to obtain the type and value of the target gas required for the calibration of the gas sensor, activate the pressure reduction device module, input the target gas into the corresponding gas sensor, and keep the target gas pressure constant when the input target gas pressure reaches the set standard; The signal processing component is used to collect the analog signal of the gas sensor, which includes the gas characteristics and concentration of the target gas detected by the gas sensor; convert the analog signal into a voltage digital signal, pre-process the voltage digital signal, and compare it with the set standard value. If it is within the set standard value range, it is qualified; if it is outside the set standard value range, it is unqualified; The calibration adjustment component is used to trigger the calibration adjustment procedure according to the unqualified content outside the set standard value range received; use pure air for zero point calibration, and then use the target gas of known concentration for span calibration, record the response value of the gas sensor at each gear, and compare the response value with the response standard value. If it does not meet the response standard value, the current gas sensor is judged to be unqualified; Signal processing components, including: The signal acquisition module is responsible for connecting with the gas sensor through an interface and receiving the low-amplitude voltage analog signal output in real time, including the concentration, temperature and humidity characteristics of the gas; using the analog-to-digital converter to resolve the continuous analog signal into a discrete voltage digital signal according to the sampling frequency; The analog-to-digital conversion module is responsible for enhancing and purifying the voltage digital signal after the voltage analog signal has been converted to digital, increasing the signal amplitude, and removing high-frequency noise and interference signals; applying a smoothing algorithm to reduce short-term fluctuations; The signal comparison module is responsible for comparing the processed voltage digital signal with the set standard value in real time, and using the absolute error to determine whether it is within the specified range; when the voltage digital signal is within the tolerance range of the set standard value, the signal processing component outputs a high-level signal; if the voltage digital signal exceeds the set range of the standard value, the component outputs a low-level signal; Signal comparison module, including: The first comparison submodule is responsible for calculating the mean and standard deviation of the voltage digital signal using historical data and setting the threshold; determining the upper and lower limits of the voltage digital signal based on the set constants to form a tolerance range; after receiving each new voltage digital signal, comparing it with the set upper and lower limits; if the voltage digital signal exceeds the upper limit or is lower than the lower limit, marking it as abnormal; If the signal is within range, continue monitoring normally; The second comparison submodule is responsible for marking the voltage digital signal as abnormal in the preliminary judgment layer, entering the discrimination enhancement layer, extracting multiple key features from the abnormal voltage digital signal, including the maximum value, minimum value, mean value, standard deviation and rate of change of the voltage digital signal, analyzing and classifying the voltage digital signal features, distinguishing between normal voltage digital signals and abnormal voltage digital signals, and generating a judgment result indicating whether the voltage digital signal is abnormal; The third comparison submodule is responsible for determining whether to adjust the sampling frequency of the voltage digital signal according to the current state of the voltage digital signal for the voltage digital signal that is still marked as abnormal in the judgment enhancement layer.

2. The gas sensor testing device according to claim 1, wherein: Gas input assembly, comprising: The parameter acquisition module is responsible for confirming the gas sensor model, application field, and gas characteristics and standards to be tested before starting to acquire the target gas; the application fields include environmental monitoring, industrial safety, and food quality, and the standards include gas concentration range and response speed; The concentration acquisition module is responsible for selecting one or more reference concentration values ​​as the target concentration and using a high gas concentration detection instrument to monitor and verify the actual concentration of the mixed gas in real time; The pressure detection module is responsible for connecting the pressure reducing device to the gas input component, setting the initial pressure value of the pressure reducing device, turning on the pressure reducing device, and monitoring the pressure changes of the target gas. The pressure of the target gas is monitored in real time using a pressure sensor. If the gas pressure does not reach the set standard, it is adjusted by adjusting the valve of the pressure reducing device.

3. The gas sensor testing device according to claim 2, wherein: Pressure detection module, including: The network connection submodule is responsible for the layout of pressure sensors and monitoring the pressure changes in gas flow; using communication protocols, the sensor network is connected to form a decentralized real-time data transmission network; The strategy formation submodule is responsible for setting the sampling rate of each pressure sensor, detecting pressure fluctuations, and saving the detected anomalies in the database; identifying the relationship between gas pressure and environmental variables such as temperature, humidity, and flow rate, building a multivariate pressure prediction model, predicting future pressure changes based on historical data, and forming a dynamic adjustment strategy; The parameter adjustment submodule is responsible for automatically updating the working parameters of the regulating valve after calculating the required pressure value; if the pressure exceeds the set range, the valve will be automatically adjusted to close or open, adjust the gas inflow, and keep the pressure within a safe range.

4. The gas sensor testing device according to claim 3, wherein: The multivariate stress prediction model of the strategy formation submodule includes: Data preprocessing layer, multi-dimensional time series data collected from sensor networks, including pressure, temperature, humidity and flow rate; data standardization, missing value processing and time series reconstruction; Feature extraction layer: The processed two-dimensional data is passed through multiple convolutional layers to extract local spatial features, combined with the maximum pooling layer to reduce the data dimension and extract higher-level feature patterns; the extracted spatial feature vectors are used for time series analysis; The time series analysis layer captures the long-term dependencies in the time series data from the feature vector sequence output by the feature extraction layer, identifies the historical trends and patterns of pressure, and outputs the hidden state of each time step as the basis for predicting future pressure changes; The joint prediction layer inputs the hidden state and the extracted spatial features; combines the spatial features with the temporal features, further processes them through the fully connected layer, and uses the fused features to perform multivariate pressure prediction; outputs the future pressure value prediction, confidence interval, and fault indicator; The decision-making and feedback layer inputs the predicted pressure value and actual monitoring data; monitors the difference between the predicted and actual values ​​in real time, calculates the error, and loops the feedback information back to the model to optimize parameters and strategies; provides regulatory feedback to maintain the pressure within a safe range, and continuously adjusts the model prediction performance based on historical data and real-time data.

5. The gas sensor testing device according to claim 3, wherein: Strategy formation submodule, including: The data analysis unit is responsible for integrating the historical pressure data, temperature, humidity and flow rate multi-dimensional data from various sensors into a time series data stream, and regularly extracting time segments for analysis through the window sliding method; for each time segment of the input data, the change amplitude of the data within the time segment is calculated, and the learning rate and feature weight of the multivariate pressure prediction model are dynamically adjusted using the statistical characteristics of the change amplitude; The error processing unit is responsible for monitoring the actual pressure value in real time after the prediction of the multivariable pressure prediction model is generated, calculating the prediction error, and sending the error back to the multivariable pressure prediction model to guide the parameter adjustment of the multivariable pressure prediction model; The feature extraction unit is responsible for the feedback results of parameter adjustment. It extracts features from historical multidimensional data and combines the feedback information to self-optimize the parameters of the multivariable pressure prediction model to obtain parameter combinations.

6. The gas sensor testing device according to claim 1, wherein: Calibration adjustment kit, including: The first program trigger module is responsible for receiving the report from the signal processing component in real time; when the voltage digital signal detected by the analog signal of the gas sensor does not match the set standard value, that is, is outside the set standard value range, the calibration adjustment program of the calibration adjustment component is triggered; The second program trigger module is responsible for triggering the zero point calibration subroutine in the calibration adjustment program. It first introduces pure air and outputs a voltage signal close to zero in the absence of target gas, and compares the currently read voltage signal with the ideal zero point value. The third program trigger module is responsible for triggering the span calibration subroutine after the zero calibration subroutine is completed, introducing a target gas of known concentration for span calibration; under the input of target gas of different concentrations, a series of output response values ​​are generated, and the response values ​​are compared with the response standard values ​​under the corresponding concentrations to determine whether the output of the sensor is within an acceptable range; If the output signal at a known concentration meets the set response standard value, it is judged to be qualified; if it is unqualified, continue to make adjustments or make maintenance suggestions.

7. The gas sensor testing device according to claim 6, wherein: The second program trigger module includes: The gas input submodule is responsible for introducing pure air for 1-2 minutes. When the display value of the reference standard gas sensor reaches 0, a trigger signal will be sent to the zero calibration module. The zero calibration submodule is responsible for entering the zero calibration mode after receiving the trigger signal sent by the reference standard gas sensor. The measured gas sensor automatically calibrates the current gas concentration as the zero point, and the displayed value should be 0; The device connection submodule, the gas input submodule and the zero point calibration submodule are connected by using an interface converter, and the trigger signal is transmitted to the zero point calibration submodule.

8. The gas sensor testing device according to claim 6, wherein: The third program trigger module includes: The calibration gas input submodule is responsible for connecting the gas of known concentration, ensuring that the calibration gas concentration is within the measurement range of the sensor, and passing the calibration gas; The calibration control submodule is responsible for recording the concentration of the calibration gas according to the concentration of the known gas and the value displayed by the reference standard gas sensor, and transmitting the concentration value to the span calibration module; The span calibration submodule is responsible for receiving the values ​​from the calibration control module and adjusting the reading of the gas sensor under test to match the input calibration gas concentration. During the span calibration process, the reading should be 10% higher than the full scale value. After the calibration is completed, the response value of the gas sensor in each gear is recorded and compared with the response standard value. If it does not meet the response standard value, the current gas sensor is judged to be unqualified.

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