CN111521647B - Gas concentration detection method, system, computer equipment and storage medium - Google Patents

Abstract

The application discloses a gas concentration detection method, system, computer equipment and storage medium, and relates to the field of gas sensor technology. The gas concentration detection method is applied to a gas sensor, and the gas sensor includes a heating electrode and a gas sensor. material, the heating electrode is used to heat the gas-sensing material, including: using a pulse voltage to drive the heating electrode to heat the gas-sensing material, and obtaining the gas sensor in the pulse width of the pulse voltage output voltage data to obtain a voltage array; input the voltage array into the target gas-sensing data analysis model to obtain the impedance of the gas sensor output by the target gas-sensing data analysis model; Impedance determines the concentration of the gas to be detected. The application can reduce the power consumption in the gas concentration detection process, and can respond quickly and shorten the detection time.

Description

Gas concentration detection method, system, computer equipment and storage medium

technical field

The present application relates to the technical field of gas sensing, in particular to a gas concentration detection method, system, computer equipment and storage medium.

Background technique

Gas sensors can be used to detect the concentration of one or more gases in the air, so that people can judge the air quality in the environment according to the concentration of one or more gases in the environment.

In the prior art, the method for detecting the gas concentration is as follows: the gas sensor is powered on and heated, and when the temperature reaches the optimum working temperature of the gas sensor material coated on the gas sensor, the voltage data output by the gas sensor is collected, Determine the concentration of the measured gas according to the voltage data output by the gas sensor.

However, in the above detection method, the process of heating the temperature of the gas sensor from normal temperature to the optimum working temperature of the gas sensor material takes a long time and consumes a lot of power.

Contents of the invention

Based on this, it is necessary to provide a gas concentration detection method, system, computer equipment and storage medium for the problems of long time consumption and high power consumption in existing detection methods.

A gas concentration detection method applied to a gas sensor, the gas sensor includes a heating electrode and a gas sensitive material, the heating electrode is used to heat the gas sensitive material, the method includes:

Use the pulse voltage to drive the heating electrode to heat the gas-sensitive material, obtain the voltage data output by the gas sensor in the pulse width of the pulse voltage, and obtain a voltage array;

Input the voltage array into the target gas-sensing data analysis model to obtain the impedance of the gas-sensing sensor output by the target gas-sensing data analysis model;

Determine the concentration of the gas to be detected according to the impedance of the gas sensor.

In one embodiment of the present application, before inputting the voltage array into the target gas sensing data analysis model, the method further includes:

Obtain a training sample set, the training sample set includes several groups of samples composed of different voltage arrays and the impedance of the gas sensor corresponding to the voltage array;

According to the training sample set, the initial neural network model is trained to obtain the target gas-sensing data analysis model.

In one embodiment of the present application, before inputting the voltage array into the target gas sensing data analysis model, it includes:

Obtain the specifications of the gas sensor;

A target gas-sensing data analysis model is determined from the target gas-sensing data analysis model group according to the specifications of the gas-sensing sensor, and the gas-sensing analysis model group includes multiple gas-sensing data analysis models.

In one embodiment of the present application, before inputting the voltage array into the target gas sensing data analysis model, the method further includes:

Perform normalization preprocessing on the voltage array.

In one embodiment of the present application, the gas sensor further includes a test electrode, the test electrode is connected to the heating electrode, and the gas-sensing material is coated on the surface of the test electrode, and the gas-sensing material is a metal oxide.

In one embodiment of the present application, the heating electrode is a micro-heating electrode prepared by a micro-nano fabrication process.

In an embodiment of the present application, the pulse width of the pulse voltage is greater than 0.1s and less than or equal to 20s.

A gas concentration detection system, applied to a gas sensor, the gas sensor includes a heating electrode and a gas sensitive material, the heating electrode is used to heat the gas sensitive material, the system includes:

The obtaining module is used to use the pulse voltage to drive the heating electrode to heat the gas sensitive material, obtain the voltage data output by the gas sensor in the pulse width of the pulse voltage, and obtain a voltage array;

The analysis module is used to input the voltage array into the target gas-sensing data analysis model to obtain the impedance of the gas-sensing sensor output by the target gas-sensing data analysis model;

The detection module is used to determine the concentration of the gas to be detected according to the impedance of the gas sensor.

A computer device, including a memory and a processor, the memory stores a computer program, and the computer program is executed by the processor to achieve the following steps:

Use the pulse voltage to drive the heating electrode to heat the gas-sensitive material, obtain the voltage data output by the gas sensor in the pulse width of the pulse voltage, and obtain a voltage array;

Input the voltage array into the target gas-sensing data analysis model to obtain the impedance of the gas-sensing sensor output by the target gas-sensing data analysis model;

Determine the concentration of the gas to be detected according to the impedance of the gas sensor.

A computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the following steps are implemented:

Use the pulse voltage to drive the heating electrode to heat the gas-sensitive material, obtain the voltage data output by the gas sensor in the pulse width of the pulse voltage, and obtain a voltage array;

Input the voltage array into the target gas-sensing data analysis model to obtain the impedance of the gas-sensing sensor output by the target gas-sensing data analysis model;

Determine the concentration of the gas to be detected according to the impedance of the gas sensor.

The beneficial effects brought by the technical solutions provided by the embodiments of the present application at least include:

The above gas concentration detection method, system, computer equipment and storage medium can improve speed and reduce power consumption. The gas concentration detection method is applied to a gas sensor. The gas sensor includes a heating electrode and a gas-sensing material, and the heating electrode is used to heat the gas-sensing material. Specifically, the pulse voltage is used to drive the heating electrode to heat the gas-sensing material, and the voltage data output by the gas-sensing sensor within the pulse width of the pulse voltage is collected to obtain a voltage array. The voltage array is input into the target gas-sensing data analysis model to obtain the impedance of the gas-sensing sensor output by the target gas-sensing data analysis model. Determine the concentration of the gas to be detected according to the impedance of the gas sensor. In this embodiment, by collecting the voltage data output by the gas sensor within the pulse duration of the pulse voltage, and then processing the voltage data through the target gas sensor data analysis model, the impedance of the gas sensor is obtained, and then the gas to be detected is determined. concentration. Among them, when the pulse voltage is applied, data can be collected. There is no need to wait until the thermally sensitive material has reached its optimum operating temperature before collecting data. Therefore, compared with the gas sensor of the traditional DC voltage heating method, it shortens the time it takes for the gas sensor material to rise from normal temperature to the optimal working temperature, and has low power consumption and fast response speed. And in this embodiment, the deep learning of the collected voltage data through the target gas sensor data analysis model improves the detection accuracy of the gas concentration, which is higher than the general pulse voltage heating gas sensor accuracy.

Description of drawings

Fig. 1 is a schematic diagram of the implementation environment of the gas concentration detection method provided by the embodiment of the present application;

FIG. 2 is a flow chart of a gas concentration detection method provided in an embodiment of the present application;

Fig. 3 is the schematic diagram of the pulse voltage provided by the embodiment of the present application;

4 is a schematic diagram of the voltage signal output by the gas sensor provided in the embodiment of the present application;

FIG. 5 is a schematic diagram of a sampled voltage array provided in an embodiment of the present application;

Fig. 6 is the frame diagram of the initial neural network model provided by the embodiment of the present application;

Fig. 7 is a comparative schematic diagram during the training process provided by the embodiment of the present application;

Fig. 8 is a schematic diagram of the verification process of the gas-sensing data analysis model provided by the embodiment of the present application;

FIG. 9 is a flow chart of another gas concentration detection method provided in the embodiment of the present application;

FIG. 10 is a block diagram of a gas concentration detection system provided in an embodiment of the present application;

FIG. 11 is a block diagram of a computer device provided by an embodiment of the present application.

Detailed ways

In order to make the purpose, technical solution and advantages of the present application clearer, the implementation manners of the present application will be further described in detail below in conjunction with the accompanying drawings.

Gas sensing technology can be used to detect the concentration of one or more specific gases in the air, so that people can judge the air quality in the environment according to the concentration of one or more gases in the environment. Therefore, gas sensing technology plays an important role in the application fields of people's daily life, industrial production and scientific research activities. For example, it can detect formaldehyde, benzene series and other volatile organic compounds that threaten people's life and health. In the fields of industrial production and scientific research activities, it can be used to detect the concentration of toxic gases in the environment, so as to predict whether there is a leakage of toxic gases.

In the prior art, the method of detecting the concentration of the gas to be measured by using the gas sensing technology is: power on the gas sensor and heat it, and when the temperature reaches the optimum working temperature of the gas sensitive material coated on the gas sensor, collect The voltage data output by the gas sensor is used to determine the concentration of the gas to be measured according to the voltage data output by the gas sensor.

Although the heating electrode can improve the working performance of the gas-sensing material, it takes a long time to heat the gas-sensing material from normal temperature to the optimal working temperature, and the power consumption in the heating process is relatively large. Moreover, when the temperature of the gas-sensing material reaches the optimum working temperature, it is still necessary to keep the gas-sensing material at the optimum working temperature so that accurate data can be collected, that is to say, during the entire data collection process, the heating electrode It also needs to be kept in a constant heating state, so it consumes more power.

At present, some research institutions propose to use machine learning to analyze gas sensing signals, such as "Using Feedforward Neural Networks for Gas Qualitative Analysis" (Journal of Instrumentation, 2000, 467:471-473) to use the results of signal processing for Qualitatively identify whether there is a specific gas in the atmosphere, but this work is only an early qualitative analysis of gas-sensing detection, and cannot quantitatively analyze the concentration of the detected gas; from "Improving gas identification accuracy of temperature-modulated gas sensor using an ensemble of classifiers (Chinese translation: Improving gas identification accuracy of temperature-modulated gas sensors using integrated classifiers)” (Sensors and Actuators B: Chemical,2013,187:241-246.) (Chinese translation: Sensors and Actuators B: Chemistry, 2013 ,187:241-246) The work in this literature mainly adjusts the substrate temperature of the gas sensor by adjusting the heating pulse amplitude, heats the substrate temperature of the gas sensor to the optimum working temperature, and keeps the gas sensor at the optimum working temperature The output voltage data below is input into the support vector machine (SVM) algorithm for gas sensing analysis. Although the scheme uses pulse voltage for heating, the process is to use pulse voltage to heat the gas sensor from normal temperature to the optimal working temperature. Then, the voltage data output by the gas sensor is processed to qualitatively analyze the type of gas to be measured. On the one hand, the heating process in this method still takes a long time. On the other hand, this method cannot realize the quantitative measurement of the concentration of the gas to be measured.

The present application proposes a gas concentration detection method, which can improve speed and reduce power consumption. In this method, the voltage data output by the gas sensor during the pulse duration of the pulse voltage is collected, and then the voltage data is processed through the target gas sensor data analysis model to obtain the impedance of the gas sensor, and then determine the concentration of the gas to be detected . It can be seen that, in this embodiment, the voltage data output by the gas sensor is collected within one pulse duration of the pulse voltage, and there is no need to wait for the heat-sensitive material to reach the optimum working temperature before collecting data. Therefore, the time it takes for the gas-sensitive material to rise from normal temperature to the optimum working temperature is shortened. Correspondingly, the power consumption in the process of heating the gas-sensitive material is also reduced.

Below, the implementation environment involved in the gas concentration detection method provided in the embodiment of the present application will be briefly described.

Please refer to Fig. 1, this implementation environment can include gas sensor and computer equipment (not shown in the figure), gas sensor includes test electrode 102 and heating electrode 101, under working condition, there is pulse voltage at both ends of heating electrode 101 , the heating electrode 101 is driven by a pulse voltage, so that the heating electrode 101 is heated. The test electrode 102 is an electrode for carrying gas-sensitive materials.

Optionally, the test electrode 102 is in the shape of a finger, and the test electrode 102 is in an open circuit state in a non-working state. After the gas-sensing material is coated on the testing electrode 102 and the gas-sensing material is at normal temperature, the impedance of the testing electrode 102 is very high. When the temperature of the gas-sensing material rises and the gas-sensing material senses the gas to be detected, the impedance at both ends of the test electrode 102 will decrease rapidly.

In this embodiment, the gas sensor further includes a load resistor (not shown in the figure), which is connected to a DC power supply after being connected in series with the test electrode 102 . In the non-working state, the test electrode 102 is in an open circuit state, and the series circuit is disconnected. In the working state, the test electrode 102 is turned on, the series circuit is turned on, and the voltage data obtained by the load resistance in the series circuit can be measured, and the voltage data obtained by the load resistance is the voltage data to be collected.

The gas sensor also includes signal acquisition equipment. The signal acquisition equipment is used to collect the voltage signal acquisition equipment of the load resistance and is connected to the computer equipment to receive the acquisition instructions sent by the computer equipment. After the signal acquisition equipment receives the acquisition instructions, it The output voltage signal is used for data acquisition. Specifically, as the temperature of the gas-sensitive material increases, the impedance of the test electrode decreases rapidly, and the total resistance in the series circuit changes, so the voltage data obtained by the load resistance is also in a state of continuous change. In this embodiment, the signal acquisition device can perform data acquisition on the voltage data in a continuously changing state to obtain a voltage array composed of multiple discrete voltage data.

The target gas-sensing data analysis model is pre-stored in the computer equipment, and the computer equipment can obtain the voltage array collected by the signal acquisition device, and input the voltage data in the voltage array to the target gas-sensing data analysis model in sequence, and the target gas-sensing data The analysis model can output the impedance of the gas sensor corresponding to the input voltage array, and determine the concentration of the gas to be detected according to the impedance of the gas sensor.

Please refer to FIG. 2, which shows a flow chart of a gas concentration detection method provided by an embodiment of the present application. The gas concentration detection method can be applied to the gas sensor in the implementation environment shown in FIG. 1. The gas sensor Including a heating electrode and a gas-sensing material, the heating electrode is used to heat the gas-sensing material, as shown in Figure 2, the gas concentration detection method may include the following steps:

Step 201 , the computer device uses the pulse voltage to drive the heating electrode to heat the gas-sensing material, acquires the voltage data output by the gas-sensing sensor within the pulse width of the pulse voltage, and obtains a voltage array.

When detecting the concentration of the gas to be measured, the computer equipment can send a heating instruction to the gas sensor, and after the heating electrode receives the heating instruction, a pulse voltage is applied to the heating electrode through the pulse circuit to heat the gas sensor. In this embodiment, as shown in FIG. 3 , the pulse voltage generally includes a rising edge, a falling edge, and a pulse width in a high level state between the rising edge and the falling edge. Wherein, the rising edge represents the start time point of the pulse voltage, the falling edge represents the end time point of the pulse voltage, and the pulse width represents the duration of the pulse. The rising curve in the pulse width in FIG. 3 is the voltage signal output by the gas sensor. In this embodiment, the pulse duration is equal to the sampling time for collecting the voltage data output by the gas sensor.

In this embodiment, the voltage signal output by the gas sensor is a continuous analog signal, as shown in Figure 4, which shows a schematic diagram of the voltage signal output by the gas sensor during the pulse heating process, the horizontal axis represents time, and each The unit time is 0.01s. The vertical axis represents voltage. The computer equipment can also send acquisition instructions to the signal acquisition equipment. After the signal acquisition equipment receives the acquisition instructions, it can perform the voltage signal output by the gas sensor within the pulse duration shown in Figure 3 according to the preset sampling frequency. Sampling to obtain the voltage data output by the gas sensor. Optionally, after discretely sampling the voltage signal, a voltage array can be obtained, and the voltage array includes multiple discrete voltage data, as shown in Figure 5, the time series that can be sampled and the coordinate system to which the sampled voltage data series are mapped , in this coordinate system, the X-axis divides the sampling time of 1s into 100 parts, and each part represents a duration of 0.01s. The Y-axis divides the voltage signal into 100 divisions after normalization, and the voltage data obtained by sampling You can find the corresponding value on the Y axis.

In this embodiment, after the voltage signal within the pulse duration corresponding to the pulse width of a pulse voltage is sampled according to a preset sampling frequency, a plurality of discrete voltage data obtained form a voltage array.

In this embodiment, the signal collection device can automatically upload the collected voltage array to the computer device, so that the computer device can obtain the voltage array.

Step 202, inputting the voltage array into the target gas-sensing data analysis model to obtain the impedance of the gas-sensing sensor output by the target gas-sensing data analysis model.

Optionally, the voltage data in the voltage array has a time sequence. When the voltage array is input into the target gas sensing data analysis model, it is input according to the time sequence of the voltage data in the voltage array.

Optionally, the target gas-sensing data analysis model may be a neural network model, a support vector machine model, an extreme learning model, and the like.

In this embodiment, since the voltage array is the voltage data collected during the pulse duration of the pulse voltage, and during the pulse duration, on the one hand, the heating time of the heating electrode is relatively short, so the gas-sensitive material may not be optimal. Operating temperature. And when the gas-sensing material does not reach the optimum working temperature, it means that the voltage data output by the gas-sensing sensor is still in a state of change. In this embodiment, only the voltage signal within the duration of the pulse is sampled, indicating that the sampled object is incomplete. Therefore, if the solution in the prior art is used to obtain the impedance of the gas sensor directly according to the voltage data, the obtained gas Sensitive sensor impedance is not accurate. Based on this, this embodiment proposes to use a software algorithm to map the voltage data in the collected voltage array to the impedance of the gas sensor, and compensate for the lack of accuracy of the collected voltage array in the process, so as to ensure The gas concentration detected by the technical scheme is accurate.

Optionally, before inputting the voltage array into the target gas-sensing data analysis model, this embodiment may also include the step of obtaining the target gas-sensing data analysis model:

An optional implementation is to train the target gas-sensing data analysis model, including the following steps:

Step A1, obtain a training sample set.

Wherein, the training sample set includes several groups of samples composed of different voltage arrays and the impedance of the gas sensor corresponding to the voltage arrays.

In this embodiment, the process of obtaining the training sample set may be:

Two gas sensors, such as gas sensor A and gas sensor B, are placed in the gas detection device with stable gas concentration, wherein gas sensor A is the gas sensor proposed in this embodiment using pulse voltage heating. Gas sensor B is a standard gas sensor, and the impedance of the gas sensor measured by gas sensor B is used as the impedance of the standard gas sensor, so as to facilitate training and correction of the impedance corresponding to the voltage array detected by gas sensor A .

The computer equipment sends heating commands to the gas sensor A and the gas sensor B respectively, and in the gas sensor A, the voltage data is collected during the pulse duration of the pulse voltage. Wherein, multiple pulse voltages can be applied to the gas sensor A, and a voltage array within the pulse duration of each pulse voltage can be obtained. It should be noted that there is an interval between two adjacent pulse voltages, and the length of the interval may not be fixed, but each time the pulse voltage is applied, the gas sensitive material of the gas sensor A needs to be in a normal temperature state.

Optionally, under the condition that the gas concentration is constant, a voltage array can be obtained each time the pulse voltage is applied.

Furthermore, the gas concentration can be slowly reduced through control devices such as valves, and after the gas concentration is reduced to a preset concentration, the pulse voltage is applied multiple times at the preset concentration to obtain multiple voltage arrays. By analogy, the gas concentration is slowly reduced, and multiple voltage arrays are obtained.

On the other hand, the gas sensor B is heated by a DC heating resistor. When the gas sensitive material of the gas sensor B reaches the optimum working temperature, the voltage data output by the gas sensor B is collected, and the gas sensor is calculated based on the voltage data. Impedance of sensor B.

When the gas concentration is slowly reduced, the impedance of the gas sensor B is obtained at each preset concentration.

At each preset concentration, the impedance of the gas sensor B is used as the impedance of the accurate gas sensor corresponding to the voltage array detected by the gas sensor A at the preset concentration.

In this embodiment, several groups of samples are composed of different voltage arrays and the impedance of the gas sensor corresponding to each voltage array.

Step A2, according to the training sample set, train the initial neural network model to obtain the target gas-sensing data analysis model.

As shown in Figure 6, it shows the frame diagram of the initial neural network model. In this embodiment, the initial neural network model is a standard full-link layer network structure, the first layer and the last layer are respectively the training data input layer or the training result output layer, and the number of hidden layers in the middle is 3-5 layers , each layer has 100-1000 neurons.

Further, in this embodiment, after enough data is collected, some data combinations are randomly selected to obtain a test sample set. The test sample set includes a number of different voltage arrays and the impedance of the gas sensor corresponding to the voltage array. group samples. The samples in the test sample set do not participate in the training process. After the model is trained with the training sample set, the trained model is predicted with the test sample set. In order to judge the gap between the predicted data and the actual data.

Among them, Figure 7 shows that the loss function of the training sample set and the test sample set is gradually decreasing during the training process, where 1 represents the loss curve corresponding to the training sample set, and 2 represents the loss curve corresponding to the test sample set, which means The training model gradually approaches the correct model during the training process, and finally stabilizes within the range of the correct model. Figure 8 shows the gap between the predicted data and the actual data, wherein, 3 represents the curve corresponding to the actual data, the accurate gas concentration detected by the actual data, 4 represents the curve corresponding to the predicted data, and the predicted data is a gas data analysis model Output gas concentration. Among them, the abscissa represents the number of predicted data, that is, the number of data to be predicted; the ordinate represents the gas concentration. When the gap between the predicted data and the actual data is smaller than the gap threshold, it is considered that the model has been trained, that is, the target gas-sensing data analysis model is obtained.

It should be noted that in this embodiment, the production specification of the gas sensor used when obtaining the training sample set determines the application object of the gas sensor data analysis model. That is, the gas sensor with the same production specifications as the gas sensor used when obtaining the training sample set can use the target gas sensor data analysis model to predict the voltage array.

In another optional implementation, different gas sensor data analysis models can be trained for gas sensors of different specifications by using the content disclosed in the above step A1 and step A2.

The multiple different gas-sensing data analysis models are stored in the computer device in the form of a gas-sensing data analysis model group. The specifications of the gas sensor corresponding to each gas-sensing data analysis model are also stored in the gas-sensing data analysis model group.

Specifications of gas sensors that are detecting gas concentrations can be acquired.

Then search the gas-sensing data analysis model corresponding to the specification of the gas-sensing sensor in the gas-sensing data analysis model group, and determine the gas-sensing data analysis model corresponding to the specification of the gas-sensing sensor as the target gas-sensing data analysis model.

Step 203, determine the concentration of the gas to be detected according to the impedance of the gas sensor.

The impedance of the gas sensor is the impedance of the detection motor in the gas sensor.

By obtaining the voltage data at both ends of the load resistance, the current of the load resistance is calculated, thereby calculating the impedance of the detection electrode connected in series with the load resistance. The impedance of the detection electrode is proportional to the concentration of the gas to be detected.

Therefore, the concentration of the gas to be detected can be calculated from the proportional relationship between the impedance of the gas sensor and the impedance of the detection electrode and the concentration of the gas to be detected.

In the gas concentration detection method in this embodiment, by collecting the voltage data output by the gas sensor within the pulse duration of the pulse voltage, and then processing the voltage data through the target gas sensor data analysis model, the impedance of the gas sensor is obtained, and then Determine the concentration of the gas to be detected. It can be seen that, in this embodiment, the voltage data output by the gas sensor is collected within one pulse duration of the pulse voltage, and there is no need to wait for the heat-sensitive material to reach the optimum working temperature before collecting data. Therefore, the time it takes for the gas-sensitive material to rise from normal temperature to the optimum working temperature is shortened. Correspondingly, the power consumption in the process of heating the gas-sensitive material is also reduced.

In an optional implementation, as shown in Figure 9, it shows a gas concentration detection method, the method includes the following steps:

Step 901 , use the pulse voltage to drive the heating electrode to heat the gas-sensing material, acquire the voltage data output by the gas-sensing sensor within the pulse width of the pulse voltage, and obtain a voltage array.

In this embodiment, reference may be made to the content disclosed in step 201, and details are not repeated here.

Step 902, perform normalization preprocessing on the voltage array.

The process of normalizing and preprocessing the voltage data arranged in time series in the voltage array may include the following:

Fit a voltage curve based on the voltage data in the voltage array.

Establish a two-dimensional coordinate system based on the voltage array, the X axis is time, and the Y axis is voltage data. Fit a voltage curve in this coordinate system.

Calculate the vertical distance from each voltage data in the voltage array to the voltage curve.

In the two-dimensional coordinate system, for each point corresponding to the voltage data, a tangent point is found on the voltage curve, the distance between the voltage data and the corresponding tangent point is the shortest distance, and the corresponding tangent point of the voltage data is calculated. shortest distance.

For the shortest distance corresponding to each voltage data, it is judged whether the shortest distance is smaller than the distance threshold, and if the shortest distance is smaller than the distance threshold, the voltage data is kept. When the shortest distance is greater than or equal to the distance threshold, the voltage data is discarded.

In this way, it can be ensured that all the voltage data are within a certain range around the voltage curve, thereby ensuring the linearity of the voltage data in the voltage array.

Step 903: Input the voltage array into the target gas-sensing data analysis model to obtain the impedance of the gas-sensing sensor output by the target gas-sensing data analysis model.

Reference may be made to the content disclosed in step 202, and details are not repeated here.

Step 904, determine the concentration of the gas to be detected according to the impedance of the gas sensor.

Reference may be made to the content disclosed in step 203, and details are not repeated here.

In this embodiment, by normalizing the voltage data in the voltage array, the characteristics of the voltage data in the voltage array are clearer, which facilitates data analysis and mapping in the target gas-sensing data analysis model, thereby improving The accuracy of the detected gas concentration.

In one embodiment of the present application, the gas sensor further includes a test electrode, the test electrode is connected to the heating electrode, and the gas-sensing material is coated on the surface of the test electrode, and the gas-sensing material is a metal oxide.

Gas sensors using metal oxides as gas-sensing materials have the advantages of low cost, simple fabrication, high sensitivity, long life and low sensitivity to humidity.

Optionally, in this embodiment, the heating electrode is a micro-heating electrode prepared by a micro-nano fabrication process.

The micro-heating electrode prepared by micro-nano processing technology has the characteristics of fast heating speed and high efficiency. And the temperature of the gas-sensing material can be rapidly increased by controlling the amplitude of the micro-heating electrode.

In this embodiment, the pulse width of the pulse voltage of the heating electrode can be controlled to be less than 20 s based on the micro heating electrode prepared by the micro-nano processing technology. Further, the minimum pulse width of the pulse voltage can reach 0.1s. That is to say, in this embodiment, when the pulse voltage is within the range of [0.1s, 20s], the impedance of the test electrode coated with the gas-sensitive material can be greatly changed, so that the pulse voltage can be collected voltage data. At present, according to the published existing literature or patents, the response time of the gas sensor heated by DC heating resistance is relatively long, and there is no technology with a response time in the range of [0.1s, 20s].

In this embodiment, only a pulse duration of 0.1s is required to complete data collection and analysis at the fastest, and the power consumption generated is only within the pulse duration of 0.1s. Compared with the direct current heating gas sensor in the prior art, the power consumption is reduced by at least 30-50 times. Therefore, the gas concentration detection method has the characteristics of ultra-low power consumption and fast response.

Please refer to FIG. 10 , which shows a block diagram of a gas concentration detection system provided by an embodiment of the present application. The gas concentration detection system may be configured in a computer device in an implementation environment. The gas concentration detection system is applied to a gas sensor. The gas sensor includes a heating electrode and a gas-sensitive material. The heating electrode is used to heat the gas-sensitive material. As shown in FIG. 10 , the gas concentration detection system may include an acquisition module 1001, An analysis module 1002 and a detection module 1003 .

The acquisition module 1001 is used to use the pulse voltage to drive the heating electrode to heat the gas-sensitive material, acquire the voltage data output by the gas sensor in the pulse width of the pulse voltage, and obtain a voltage array;

The analysis module 1002 is used to input the voltage array into the target gas-sensing data analysis model to obtain the impedance of the gas-sensing sensor output by the target gas-sensing data analysis model;

The detection module 1003 is used to determine the concentration of the gas to be detected according to the impedance of the gas sensor.

In one embodiment of the present application, the analysis module 1002 is also used to obtain a training sample set, which includes several groups of samples composed of different voltage arrays and the impedance of the gas sensor corresponding to the voltage array; according to the training sample set , train the initial neural network model, and obtain the target gas-sensing data analysis model.

In one embodiment of the present application, the analysis module 1002 is also used to obtain the specifications of the gas sensor; determine the target gas-sensing data analysis model from the gas-sensing data analysis model group according to the specifications of the gas-sensing sensor, and the gas-sensing analysis model group Including a variety of gas-sensing data analysis models.

In an embodiment of the present application, the analysis module 1002 is also used to perform normalization preprocessing on the voltage array.

In one embodiment of the present application, the gas sensor further includes a test electrode, the test electrode is connected to the heating electrode, and the gas-sensing material is coated on the surface of the test electrode, and the gas-sensing material is a metal oxide.

In one embodiment of the present application, the heating electrode is a micro-heating electrode prepared by a micro-nano fabrication process.

In an embodiment of the present application, the pulse width of the pulse voltage is greater than 0.1s and less than or equal to 20s.

For specific limitations on the gas concentration detection system, refer to the above-mentioned limitations on the gas concentration detection method, which will not be repeated here. Each module in the above-mentioned gas concentration detection system can be fully or partially realized by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, and can also be stored in the memory of the computer device in the form of software, so that the processor can invoke and execute the corresponding operations of the above-mentioned modules.

In one embodiment of the present application, a computer device is provided. The computer device may be a server, and its internal structure may be as shown in FIG. 11 . The computer device includes a processor, memory, network interface and database connected by a system bus. Wherein, the processor of the computer device is used to provide calculation and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs and databases. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The database can be used to store target gas-sensing data analysis models, and the network interface of the computer equipment is used to communicate with external terminals through a network connection. When the computer program is executed by the processor, a gas concentration detection method is realized.

Those skilled in the art can understand that the structure shown in Figure 11 is only a block diagram of a part of the structure related to the solution of this application, and does not constitute a limitation on the computer equipment on which the solution of this application is applied. The specific computer equipment can be More or fewer components than shown in the figures may be included, or some components may be combined, or have a different arrangement of components.

In one embodiment of the present application, a computer device is provided, including a memory and a processor, the memory stores a computer program, and the processor implements the following steps when executing the computer program:

Use the pulse voltage to drive the heating electrode to heat the gas-sensing material, obtain the voltage data output by the gas sensor in the pulse width of the pulse voltage, and obtain the voltage array; input the voltage array into the target gas-sensing data analysis model to obtain the target gas-sensing data Analyze the impedance of the gas sensor output by the model; determine the concentration of the gas to be detected according to the impedance of the gas sensor.

In one embodiment of the present application, when the processor executes the computer program, the following steps are also implemented: obtaining a training sample set, the training sample set includes several groups of samples composed of different voltage arrays and the impedance of the gas sensor corresponding to the voltage array ; According to the training sample set, train the initial neural network model to obtain the target gas-sensing data analysis model.

In one embodiment of the present application, when the processor executes the computer program, the following steps are also implemented: acquiring the specifications of the gas sensor; determining the target gas sensor data analysis model from the gas sensor data analysis model group according to the gas sensor specifications, The sensitivity analysis model group includes a variety of gas-sensing data analysis models.

In an embodiment of the present application, when the processor executes the computer program, the following steps are further implemented: performing normalization preprocessing on the voltage array.

The implementation principles and technical effects of the computer equipment provided by the embodiments of the present application are similar to those of the above-mentioned method embodiments, and will not be repeated here.

In one embodiment of the present application, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

Use the pulse voltage to drive the heating electrode to heat the gas-sensing material, obtain the voltage data output by the gas sensor in the pulse width of the pulse voltage, and obtain the voltage array; input the voltage array into the target gas-sensing data analysis model to obtain the target gas-sensing data Analyze the impedance of the gas sensor output by the model; determine the concentration of the gas to be detected according to the impedance of the gas sensor.

In one embodiment of the present application, when the computer program is executed by the processor, the following steps can also be implemented: obtaining a training sample set, the training sample set includes a number of different voltage arrays and the impedance of the gas sensor corresponding to the voltage array. Group samples; according to the training sample set, train the initial neural network model to obtain the target gas-sensing data analysis model.

In one embodiment of the present application, when the computer program is executed by the processor, the following steps can also be implemented: obtaining the specification of the gas sensor; determining the target gas sensor data analysis model from the gas sensor data analysis model group according to the specification of the gas sensor , the gas-sensing analysis model group includes a variety of gas-sensing data analysis models.

In an embodiment of the present application, when the computer program is executed by the processor, the following steps may also be implemented: performing normalization preprocessing on the voltage array.

The implementation principles and technical effects of the computer-readable storage medium provided by the embodiments of the present application are similar to those of the above-mentioned method embodiments, and details are not repeated here.

Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be implemented through computer programs to instruct related hardware, and the computer programs can be stored in a non-volatile computer-readable memory In the medium, when the computer program is executed, it may include the processes of the embodiments of the above-mentioned methods. Wherein, any references to memory, storage, database or other media used in the various embodiments provided in the present application may include non-volatile and/or volatile memory. Nonvolatile memory can include read only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Chain Synchlink DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

The technical features of the above-mentioned embodiments can be combined arbitrarily. To make the description concise, all possible combinations of the technical features in the above-mentioned embodiments are not described. However, as long as there is no contradiction in the combination of these technical features, should be considered as within the scope of this specification.

The above-mentioned embodiments only express several implementation modes of the present application, and the description thereof is relatively specific and detailed, but should not be construed as limiting the scope of the patent application. It should be noted that those skilled in the art can make several modifications and improvements without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the scope of protection of the patent application should be based on the appended claims.

Claims (10)

1. A gas concentration detection method, characterized in that it is applied in a gas sensor, and the gas sensor includes a test electrode, a heating electrode, a gas sensitive material and a load resistance, and the test electrode is connected to the heating electrode, The gas-sensitive material is coated on the surface of the test electrode, the load resistor is connected in series with the test electrode and connected to a DC power supply, the heating electrode is used to heat the gas-sensitive material, and the method includes : Using the pulse voltage to drive the heating electrode to heat the gas-sensitive material, obtain the voltage data output by the gas sensor within the pulse width of the pulse voltage, and obtain a voltage array, wherein the duration of the pulse is related to the voltage collected The sampling time of the data is equal; Input the voltage array into the target gas-sensing data analysis model to obtain the impedance of the gas-sensing sensor output by the target gas-sensing data analysis model, and the target gas-sensing data analysis model is a neural network model; determining the concentration of the gas to be detected according to the impedance of the gas sensor; Wherein, the gas sensor further includes a signal acquisition device, and the signal acquisition device performs data acquisition on the voltage data in which the load resistance is in a state of continuous change, and obtains the voltage array composed of a plurality of discrete voltage data. 2. The method according to claim 1, wherein before the input of the voltage array into the target gas sensing data analysis model, the method further comprises: Obtain a training sample set, the training sample set includes several groups of samples composed of different voltage arrays and the impedance of the gas sensor corresponding to the voltage array; According to the training sample set, an initial neural network model is trained to obtain the target gas-sensing data analysis model. 3. The method according to claim 1 or 2, wherein, before inputting the voltage array into the target gas sensing data analysis model, it includes: Obtain the specifications of the gas sensor; The target gas-sensing data analysis model is determined from a gas-sensing data analysis model group according to the specifications of the gas-sensing sensor, and the gas-sensing analysis model group includes multiple gas-sensing data analysis models. 4. The method according to claim 1 or 2, wherein, before inputting the voltage array into the target gas sensing data analysis model, the method further comprises: Perform normalization preprocessing on the voltage array. 5. The method according to claim 1 or 2, wherein the gas-sensitive material is a metal oxide. 6. The method according to claim 1 or 2, wherein the heating electrode is a micro-heating electrode prepared by a micro-nano fabrication process. 7. The method according to claim 1 or 2, characterized in that the pulse width of the pulse voltage is greater than 0.1s and less than or equal to 20s. 8. A gas concentration detection system, characterized in that it is applied in a gas sensor, the gas sensor includes a test electrode, a heating electrode, a gas sensitive material and a load resistor, the test electrode is connected to the heating electrode, The gas-sensitive material is coated on the surface of the test electrode, the load resistor is connected in series with the test electrode to a DC power supply, the heating electrode is used to heat the gas-sensitive material, and the system includes : An acquisition module, configured to use a pulse voltage to drive the heating electrode to heat the gas-sensitive material, acquire voltage data output by the gas sensor within the pulse width of the pulse voltage, and obtain a voltage array, wherein the pulse duration is It is equal to the sampling duration for collecting the voltage data; An analysis module, configured to input the voltage array into the target gas-sensing data analysis model to obtain the impedance of the gas-sensing sensor output by the target gas-sensing data analysis model, and the target gas-sensing data analysis model is a neural network Model; a detection module, configured to determine the concentration of the gas to be detected according to the impedance of the gas sensor; Wherein, the gas sensor further includes a signal acquisition device, and the signal acquisition device performs data acquisition on the voltage data in which the load resistance is in a state of continuous change, and obtains the voltage array composed of a plurality of discrete voltage data. 9. A computer device, comprising a memory and a processor, the memory stores a computer program, wherein the processor implements the method according to any one of claims 1 to 7 when executing the computer program step. 10. A computer-readable storage medium, on which a computer program is stored, characterized in that, when the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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