Electronic nose system for multi-component gas detection and identification method thereof

Abstract

The invention discloses an electronic nose system for multi-component gas detection and an identification method thereof, and belongs to the technical field of gas sensing and mode identification. The system comprises a gas acquisition module, a multi-channel gas sensor array, a signal processing module, an operation core and a communication module, the gas collection module optimizes a gas flow path through a bionic nasal cavity structure design so as to improve the detection sensitivity; the multi-channel gas sensor array integrates a plurality of gas sensitive units and is used for synchronously detecting the concentrations of gases such as CO, VOCs, NO2 and H2S; the signal processing module is combined with an adaptive filtering algorithm and a wavelet denoising technology to eliminate cross interference; and the operation core performs dynamic classification on the multi-component gas characteristics through a neural network algorithm. According to the invention, the problems of cross sensitivity and low precision of a traditional electronic nose in multi-component detection are solved, and real-time monitoring and accurate identification of gas in a complex environment are realized.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent gas detection, and in particular to an electronic nose system for multi-component gas detection, which can realize rapid and accurate detection of multiple gases. Background Art

[0002] With the acceleration of industrialization and urbanization, gas pollution is becoming increasingly serious, posing a serious threat to the environment and human health. Traditional gas detection methods usually rely on a single sensor with a limited detection range and low accuracy, which makes it difficult to meet the needs of multi-component gas detection in complex environments. As an emerging gas detection technology, the electronic nose system can achieve rapid identification and quantitative analysis of multiple gases by simulating the biological olfactory system. However, the existing electronic nose system still has shortcomings in gas collection, signal processing and data transmission, and an efficient and reliable multi-component gas detection solution is urgently needed. Summary of the invention

[0003] The purpose of the present invention is to provide an electronic nose system for multi-component gas detection and an identification method thereof, which can realize high-precision detection and real-time monitoring of multiple gases by optimizing gas collection, signal processing and data transmission modules.

[0004] The present invention adopts the following technical solution:

[0005] The gas collection module (1) is used to collect the gas to be tested and evenly distribute it to the detection area of ​​the sensor array.

[0006] The multi-channel gas sensor array (2) is used to detect gas and output original electrical signals.

[0007] The signal processing module (3) is used to amplify, filter and perform analog-to-digital conversion on the signal output by the sensor.

[0008] The computing core (4) is used to run the gas identification algorithm and the concentration calculation algorithm, and store and analyze the detection results.

[0009] The communication module (5) is used to perform data interaction with a host computer or a cloud platform to achieve real-time data transmission and remote control.

[0010] The power management module (6) is used to provide power to the system and manage the charging and discharging process of the power supply.

[0011] The display module (7) is used to display the detection results and system status information in real time.

[0012] Furthermore, the gas collection module includes a gas sampling pump, a gas filtering unit and a gas distributor. The gas sampling pump is connected to the gas source to be tested through a conduit to actively inhale the gas to be tested; the gas filtering unit is used to remove particulate matter and interfering components in the gas; and the gas distributor evenly distributes the filtered gas to each detection channel of the multi-channel gas sensor array.

[0013] Furthermore, the multi-channel gas sensor array includes a plurality of gas sensor units, each of which includes at least one of a metal oxide semiconductor sensor, an electrochemical sensor, and an infrared spectrum sensor. The metal oxide semiconductor sensor is used to detect volatile organic compounds (VOCs), the electrochemical sensor is used to detect toxic gases and combustible gases, and the infrared spectrum sensor is used to detect gases such as carbon dioxide and methane.

[0014] Furthermore, the signal processing module includes a signal amplification unit, a filtering unit and an analog-to-digital conversion unit. The signal amplification unit is used to amplify the weak electrical signal output by the sensor; the filtering unit is used to remove high-frequency noise and low-frequency drift in the signal; and the analog-to-digital conversion unit is used to convert the analog signal into a digital signal and transmit it to the computing core.

[0015] Furthermore, the computing core includes a microprocessor and a storage unit. The microprocessor is used to run the gas identification algorithm and the concentration calculation algorithm, and analyze and process the input digital signal; the storage unit is used to store the gas characteristic database, the algorithm program and the detection results.

[0016] Furthermore, the communication module includes a wireless transmission unit and a protocol conversion unit. The wireless transmission unit exchanges data with a host computer or a cloud platform via Wi-Fi, LoRa or Bluetooth protocol; the protocol conversion unit is used to convert the data output by the computing core into a format that complies with the communication protocol.

[0017] Furthermore, the power management module includes a battery unit, a charging management unit and a voltage conversion unit. The battery unit is used to provide power to the system; the charging management unit is used to manage the charging and discharging process of the battery; and the voltage conversion unit is used to convert the battery voltage into the operating voltage required by each module of the system.

[0018] Furthermore, the display module includes a liquid crystal display screen and a status indicator light. The liquid crystal display screen is used to display the gas type, concentration and system status information in real time; the status indicator light is used to indicate the working status and alarm information of the system.

[0019] It can be seen from the above technical solutions that, compared with the prior art, the present invention has the following beneficial effects:

[0020] The present invention can achieve high-precision detection of multiple gases through the combination of a multi-channel gas sensor array and a signal processing module. The communication module supports multiple wireless communication protocols, can upload detection data in real time and receive control instructions. The computing core runs an advanced gas identification algorithm, can automatically identify gas types and calculate concentrations. The power management module optimizes power distribution and extends the system's battery life. The display module provides intuitive detection results and system status information for easy user operation and monitoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 The figure is a structural block diagram of the electronic nose system of the present invention.

[0022] Figure 2 Detailed schematic diagrams of each structure.

[0023] Figure 3 Schematic diagram of the gas classification algorithm process.

[0024] Figure 4 Schematic diagram of the method for displaying results.

[0025] Figure 5 This is the effect picture of uploading the recognition results to the cloud platform. DETAILED DESCRIPTION

[0026] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0027] like Figure 2 As shown, in the gas collection module (1), the gas sampling pump is connected to the gas source to be tested through the conduit port to actively inhale the gas to be tested. The gas filtration unit adopts a multi-layer filter structure, which can effectively remove particulate matter and interfering components in the gas. The gas distributor adopts a split flow design to ensure that the gas is evenly distributed to each detection channel of the sensor array.

[0028] In the multi-channel gas sensor array (2), each sensor unit in the sensor array selects a metal oxide semiconductor sensor, an electrochemical sensor or an infrared spectrum sensor according to detection requirements. The sensor array is connected to the signal processing module via an SPI bus and outputs a raw electrical signal.

[0029] In the signal processing module (3), the signal amplification unit adopts a low-noise amplifier, which can effectively amplify weak electrical signals. The filtering unit adopts a digital filter to remove high-frequency noise and low-frequency drift in the signal. The analog-to-digital conversion unit adopts a high-precision ADC chip to convert analog signals into digital signals.

[0030] In the computing core (4), the microprocessor uses a high-performance ARM chip to run the gas identification algorithm and the concentration calculation algorithm. The storage unit uses a Flash memory, such as Figure 3 As shown, a gas feature database and a neural network gas classification algorithm program are stored.

[0031] The gas identification algorithm is used to process and analyze the data output by the signal processing module (3) to achieve accurate identification of the gas type and concentration. The algorithm adopts the following technical solutions:

[0032] Feedforward Neural Network (FNN)

[0033] A feedforward neural network is a classic artificial neural network model, and its structure includes an input layer, a hidden layer and an output layer. In the present invention, the input layer receives a digital signal from a signal processing module (3), the hidden layer extracts features of the input data through a nonlinear activation function (such as ReLU or Sigmoid), and the output layer outputs the prediction results of gas types and concentrations. The training process of the feedforward neural network adopts a backpropagation algorithm to optimize network parameters by minimizing a loss function (such as mean square error).

[0034] Genetic Neural Network (GNN)

[0035] In order to further improve the accuracy and robustness of gas identification, the present invention combines the genetic algorithm (GA) to optimize the parameters of the feedforward neural network. The genetic neural network simulates the biological evolution process and uses operations such as selection, crossover and mutation to globally optimize the weights and biases of the neural network.

[0036] In the communication module (5), the wireless transmission unit supports Wi-Fi, LoRa and Bluetooth protocols and can exchange data with a host computer or a cloud platform. The protocol conversion unit uses a dedicated chip to convert data into a format that complies with the communication protocol.

[0037] In the power management module (6), the battery unit adopts a lithium-ion battery to provide stable power output. The charging management unit supports fast charging and overcharging protection functions. The voltage conversion unit adopts a DC-DC converter to convert the battery voltage into the operating voltage required by each module of the system.

[0038] In the display module (7), the liquid crystal display screen adopts a high-resolution touch screen to display the detection results and system status information in real time. The status indicator light adopts an LED light to indicate the working status and alarm information of the system.

[0039] The above embodiments of the present invention are for inspiration. Through the above description, technicians in this field can make various changes and modifications without departing from the scope of the invention. The technical scope of this invention is not limited to the content of the specification, and must be determined according to the scope of the claims.

Claims

1. An electronic nose system for multi-component gas detection and its identification method, characterized in that: include: Gas collection module (1), multi-channel gas sensor array (2), signal processing module (3), computing core (4), communication module (5), power management module (6), and display module (7). The outlet end of the gas collection module (1) is connected to the inlet end of the multi-channel gas sensor array (2) via a sealed conduit, and is used to evenly distribute the gas to be tested to the detection area of ​​the sensor array; The signal output end of the multi-channel gas sensor array (2) is connected to the input end of the signal processing module (3) via a serial bus, and is used to transmit the electrical signal detected by the multi-channel gas sensor array (2) to the signal processing module (3); The output end of the signal processing module (3) is connected to the ADC pin of the computing core (4) through a parallel data line, so as to input the digital signal after filtering out noise into the computing core; The serial communication interface of the computing core (4) is connected to the receiving end of the communication module (5) through a serial port protocol, provides a neural network algorithm for gas classification, and transmits the classified gas feature vector and concentration information to the communication module (5); The communication module (5) has a wireless transmission unit (such as Wi-Fi or LoRa) connected to a host computer for remote communication, and is used to upload data in real time and receive control instructions. The power management module (6) is used to provide power to the system and manage the charging and discharging process of the power supply. It includes a high-performance battery pack, a charging management circuit and a power distribution unit, and has low power consumption management and overcharge and overdischarge protection functions to ensure stable operation of the system and extend battery life. The display module (7) is used to display the detection results and system status information in real time. It uses a high-resolution display, supports backlight adjustment, and can be operated through a touch screen or physical buttons, making it convenient for users to view data and make system settings.

2. The electronic nose system for multi-component gas detection and the identification method thereof according to claim 1, characterized in that: The multi-channel gas sensor array (2) comprises a plurality of gas sensor units (21), each gas sensor unit (21) comprising: at least one of a metal oxide semiconductor sensor (211), an electrochemical sensor (212) and an infrared spectrum sensor (213); The metal oxide semiconductor sensor (211) is used to detect volatile organic compounds (VOCs); The electrochemical sensor (212) is used to detect toxic gases and combustible gases; The infrared spectrum sensor (213) is used to detect gases such as carbon dioxide and methane.

3. The electronic nose system for multi-component gas detection and the identification method thereof according to claims 1-2, characterized in that: The signal processing module (3) comprises: a signal amplification unit (31), a filtering unit (32) and an analog-to-digital conversion unit (33); The signal amplification unit (31) is used to amplify the weak electrical signal output by the multi-channel gas sensor array (2); The filtering unit (32) is used to remove noise interference in the signal; The analog-to-digital conversion unit (33) is used to convert an analog signal into a digital signal and transmit the digital signal to the computing core (4).

4. The electronic nose system for multi-component gas detection and the identification method thereof according to claims 1-3, characterized in that: The computing core (4) comprises: a microprocessor (41) and a storage unit (42); The microprocessor (41) is used to run a gas identification algorithm and a concentration calculation algorithm, and to analyze and process input digital signals; The gas identification algorithm: uses a feedforward neural network and a genetic neural network for identification, and can be subsequently trained on a cloud platform to update the neural network model parameters; The storage unit (42) is used to store a gas characteristic database, an algorithm program and detection results.

5. The electronic nose system for multi-component gas detection according to claims 1-4, characterized in that: The communication module (5) comprises: a wireless transmission unit (51) and a protocol conversion unit (52); The wireless transmission unit (51) is used to exchange data with a host computer or a cloud platform via Wi-Fi, LoRa or Bluetooth protocol; The protocol conversion unit (52) is used to convert the data output by the operation core (4) into a format that complies with the communication protocol.

6. The electronic nose system for multi-component gas detection according to claims 1-5, characterized in that: It also includes a power management module (6), wherein the power management module (6) includes: a battery unit (61), a charging management unit (62) and a voltage conversion unit (63); The battery unit (61) is used to provide electrical energy to the system; The charging management unit (62) is used to manage the charging and discharging process of the battery; The voltage conversion unit (63) is used to convert the battery voltage into the working voltage required by each module of the system.

7. The electronic nose system for multi-component gas detection according to claims 1-6, characterized in that: It also includes a display module (7), wherein the display module (7) includes: a liquid crystal display screen (71) and a status indicator light (72); The liquid crystal display screen (71) is used to display gas type, concentration and system status information in real time; The status indicator light (72) is used to indicate the working status and alarm information of the system.

8. An electronic nose system for multi-component gas detection and an identification method thereof, comprising the electronic nose system as claimed in any one of claims 1 to 7.

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