Four-in-one diffusion type gas detection method and detection terminal

Abstract

This invention relates to the field of detection technology, specifically to a four-in-one diffusion-type gas detection method and detection terminal, comprising the following steps: providing a detection terminal; calibrating the detection signal of the detection terminal; acquiring the ambient gas concentration based on the calibrated detection terminal; amplifying and filtering the analog-to-digital conversion sequences of each gas in the ambient gas and constructing a decoupling matrix; performing decoupling calculation on the mixed gas concentration based on the decoupling matrix; comparing the original concentration value with a preset threshold in a register to generate an alarm trigger signal; performing mode determination processing on the alarm trigger signal according to a preset mode in the register; and controlling the detection terminal to output an alarm command. This application, through a gas sensor combining electrochemical and catalytic combustion principles, achieves continuous monitoring of the concentrations of four gases: combustible gas, hydrogen sulfide, oxygen, and carbon monoxide, improving the accuracy of multi-gas detection in complex mixed gas environments.

Description

Technical Field

[0001] This invention relates to the field of detection technology, and more specifically, to a four-in-one diffusion gas detection method and detection terminal. Background Technology

[0002] Gas detection technology has wide applications in various fields such as production, environmental monitoring, and public safety. In industries such as chemical engineering, metallurgy, and mining, gas leaks and pollutant emissions pose significant threats to production safety and environmental protection. Therefore, the accuracy and real-time performance of gas detection technology are particularly important. Most existing gas detection methods rely on a single gas sensor to detect and trigger alarms based on gas concentration. However, current technologies cannot simultaneously detect multiple gases, and their detection accuracy and response speed often suffer from problems in complex environments with mixed gases.

[0003] Most existing gas detection technologies suffer from a significant technical deficiency: the difficulty in efficiently and accurately decoupling and analyzing the concentration signals of multiple gases. In practical applications, ambient gases often contain multiple components, such as carbon monoxide, methane, hydrogen sulfide, and oxygen. Sensor signals from these gases are prone to cross-interference, leading to decreased accuracy and reliability of detection results. Existing methods, through simple signal processing, cannot effectively distinguish the concentration values ​​of each gas component. This problem is particularly pronounced in high-concentration or complex gas environments, potentially causing false alarms or missed alarms, thus affecting the reliability of safety monitoring. For example, in industrial settings, false alarms can trigger unnecessary shutdowns, while missed alarms can lead to serious safety accidents.

[0004] Therefore, there is an urgent need for a new detection method and device that can effectively decouple complex signal data in multi-gas environments, thereby accurately calculating the concentration of each gas. Summary of the Invention

[0005] The main objective of this invention is to provide a four-in-one diffusion gas detection method and detection terminal, which aims to overcome the technical problem that existing technologies cannot decouple and analyze the concentration signals of multiple gases.

[0006] To address the aforementioned problems, this invention proposes a four-in-one diffusion-type gas detection method, the method comprising:

[0007] A detection terminal is provided, and the detection signal of the detection terminal is calibrated. The ambient gas concentration is obtained based on the calibrated detection terminal.

[0008] Based on the diffusion time constant, the cutoff acquisition frequency is set, and the analog-to-digital conversion sequences of each gas in the ambient gas are amplified and filtered to obtain a standard signal.

[0009] A decoupling matrix is ​​constructed based on the standard signal, and the concentration of the mixed gas is decoupled and calculated based on the decoupling matrix to obtain the original concentration values ​​of each gas.

[0010] The original concentration value is compared with a preset threshold in the register to generate a status identifier containing an exceedance flag. Multiple status identifiers are integrated to obtain an alarm trigger signal.

[0011] The alarm trigger signal is processed according to the preset mode in the register, and the detection terminal is controlled to output an alarm command.

[0012] Further, the step of calibrating the detection signal of the detection terminal includes:

[0013] The target gas is initially acquired and processed based on the sensor array on the detection terminal to obtain the original signal dataset, wherein the target gas includes combustible gas, oxygen, carbon monoxide and hydrogen sulfide.

[0014] Environmental parameters are acquired based on the environmental sensors on the detection terminal, and the voltage and resistance values ​​in the original signal dataset are adjusted according to the environmental parameters to generate a correction signal set;

[0015] Extract the voltage or resistance values ​​of each gas at different standard concentrations from the calibration signal set, construct the mapping relationship between signal values ​​and gas concentrations, and generate sensor linear parameters;

[0016] The voltage or resistance values ​​in the sensor array are corrected point by point based on the slope and intercept in the linear parameters of the sensor to obtain the calibrated detection signal.

[0017] Furthermore, the step of obtaining the ambient gas concentration based on the calibrated detection terminal includes:

[0018] The target gas in the environment is sampled synchronously through multiple channels using the multi-channel detection array of the calibrated detection terminal to obtain the original sampling signal.

[0019] The electrical signals of each channel in the detection array are processed by analog-to-digital conversion to obtain a digital concentration sequence reflecting the changes in the concentration of each gas.

[0020] Further, the step of amplifying and filtering the analog-to-digital conversion sequences of the gases in the ambient gas to obtain a standard signal includes:

[0021] The amplitude differences of each channel signal in the digital concentration sequence are obtained, and the digital concentration sequence is amplified according to the amplitude differences to obtain an amplitude equalization sequence.

[0022] Based on the diffusion time constant of each gas molecule, the cutoff frequency parameter corresponding to the gas diffusion rate is calculated. The amplitude equalization sequence is then processed in the frequency domain using a filter to obtain a low-noise sequence. The cutoff frequency of the filter is set according to the cutoff frequency parameter.

[0023] A sliding window with a preset number of bits is constructed, and an offset subtraction operation is performed on each data point in the low-noise sequence according to the sliding window to obtain a standard signal.

[0024] Further, the step of constructing the decoupling matrix based on the standard signal includes:

[0025] Extract the temperature and humidity characteristic parameters corresponding to the gas concentration changes in the standard signal to generate a temperature and humidity measurement vector;

[0026] The nonlinear interference components of the oxygen integral in the combustible gas channel are identified based on the humidity measurement vector. The amplitude and phase of the standard signal are adjusted based on the nonlinear interference components to generate a corrected gas signal.

[0027] The cross-response characteristics between carbon monoxide and hydrogen sulfide electrochemical sensors in the corrected gas signal are obtained. The corrected gas signal is then processed by signal separation based on the cross-response characteristics, and a decoupling matrix is ​​constructed based on the separated gas signal.

[0028] Further, the step of decoupling the concentration of the mixed gas based on the decoupling matrix to obtain the original concentration values ​​of each gas includes:

[0029] Calculate the principal eigenvalues ​​and corresponding eigenvectors of the decoupling matrix to generate a set of eigenvectors containing the independent features of each gas signal.

[0030] The corrected gas signal is subjected to projection transformation based on the feature vector set to obtain a projection signal set.

[0031] The projected signal set is subjected to signal component separation processing to obtain a single gas signal set, wherein the single gas signal set corresponds to the actual concentration of each target gas in the environment;

[0032] Based on the amplitude characteristics of the single gas signal set, the signal amplitude is inversely normalized to obtain the original concentration values ​​of each gas.

[0033] Further, the step of comparing the original concentration value with a preset threshold in the register to generate a status identifier containing an exceedance flag, and integrating multiple status identifiers to obtain an alarm trigger signal, includes:

[0034] Based on the original concentration value, the corresponding unit conversion factor is extracted from the register. Then, the original concentration value is standardized using the unit conversion factor to obtain a standardized concentration dataset.

[0035] Obtain the dimensional characteristics of the standardized concentration dataset, and generate comparator configuration parameters based on the dimensional characteristics and the preset threshold in the register;

[0036] The comparator configuration parameters are used to compare the concentration values ​​of each gas in the standardized concentration dataset to generate a single-channel comparison result set for each gas.

[0037] The exceeding status is flagged based on the single-channel comparison result set, and the processing results are logically integrated to obtain the alarm trigger signal.

[0038] Further, the step of performing mode determination processing on the alarm trigger signal according to the preset mode in the register includes:

[0039] The alarm trigger signal is classified according to the preset alarm rule base in the register to obtain a state classification dataset.

[0040] Based on the alarm priority labels in the state classification dataset, the alarm trigger signals are sorted by priority to obtain a priority sequence.

[0041] The alarm trigger signal is allocated to different time segments according to the priority sequence, and the over-limit flag of the alarm trigger signal in different time segments is matched with the preset signal modulation template to generate a modulation signal set including modulation signals corresponding to different alarm states.

[0042] The modulated signal set is encoded to obtain an encoded alarm instruction set, which is applied to the detection terminal.

[0043] Furthermore, after the step of controlling the detection terminal to output an alarm command, the method further includes:

[0044] Obtain the gas concentration data and alarm status data from the register, and calculate the trend of gas concentration data based on the gas concentration data and alarm status data;

[0045] Based on the changing trend, obtain the predicted time value required for the gas concentration to recover to the safe threshold, and compare the predicted time value with the preset time threshold.

[0046] If the predicted time value is greater than a preset time threshold, the alarm mode of the detection terminal is adjusted to a continuous alarm mode; if the predicted time value is less than or equal to the preset time threshold, the current alarm mode of the detection terminal is maintained.

[0047] This application also discloses a four-in-one diffusion gas detection terminal, applied to any of the four-in-one diffusion gas detection methods described above, comprising:

[0048] A sensor array for acquiring raw signals of the target gas;

[0049] Environmental sensor, used to acquire environmental parameters;

[0050] An analog-to-digital converter, wherein the analog-to-digital converter is used to convert the original signal into a digital signal;

[0051] The processor is connected to the sensor array, the environmental sensor, and the analog-to-digital converter. The processor is used to receive the digital signal and calculate the concentration value of each gas based on the digital signal and the environmental parameters.

[0052] An alarm module is connected to the processor and is used to output an alarm command based on the concentration value.

[0053] Beneficial effects:

[0054] This application utilizes a gas sensor combining electrochemical and catalytic combustion principles to achieve continuous online monitoring of the concentrations of four gases: combustible gas, hydrogen sulfide, oxygen, and carbon monoxide. It significantly improves the accuracy, real-time performance, and reliability of multi-gas detection in complex mixed gas environments. The method effectively acquires standard signals of ambient gases and reduces noise interference by calibrating the detection terminal signal and setting the cutoff acquisition frequency based on the diffusion time constant. By constructing a decoupling matrix to decouple the mixed gas concentration calculation, the original concentration values ​​of each gas component can be accurately separated, overcoming the insufficient detection accuracy problem caused by cross-interference of sensor signals in existing technologies. Furthermore, by comparing with preset thresholds to generate status indicators and integrating them into alarm trigger signals, combined with preset modes for mode determination processing, it quickly outputs audible and visual alarm commands, effectively avoiding false alarms or missed alarms and ensuring the reliability of safety monitoring.

[0055] Compared with existing technologies, this application can achieve multi-gas detection through optimized signal processing and decoupling algorithms, while supporting real-time concentration display, which can effectively ensure production safety and environmental protection requirements. Attached Figure Description

[0056] Figure 1 This is a schematic diagram of the steps of a four-in-one diffusion gas detection method in one embodiment of the present invention;

[0057] Figure 2 This is a schematic diagram of the structure of a four-in-one diffusion gas detection terminal according to an embodiment of the present invention;

[0058] Figure 3 This is a schematic diagram of the overall structure of a four-in-one diffusion gas detection terminal according to an embodiment of the present invention;

[0059] Explanation of reference numerals in the attached figures:

[0060] 10. Detection terminal; 100. Sensor array; 200. Environmental sensor; 300. Analog-to-digital converter; 400. Processor; 500. Alarm module.

[0061] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0062] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0063] Those skilled in the art will understand that, unless specifically stated otherwise, the singular forms “a,” “an,” “the,” and “the” used herein may also include the plural forms. It should be further understood that the term “comprising” as used in this specification means the presence of features, integers, steps, operations, elements, modules, and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, modules, components, and / or groups thereof. It should be understood that when an element is referred to as “connected” or “coupled” to another element, it may be directly connected or coupled to the other element, or there may be intermediate elements. Furthermore, “connected” or “coupled” as used herein may include wireless connection or wireless coupling. The term “and / or” as used herein includes all or any modules and all combinations of one or more associated listed items.

[0064] It will be understood by those skilled in the art that, unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. It should also be understood that terms such as those defined in general dictionaries should be understood to have the same meaning as in the context of the prior art, and should not be interpreted in an idealized or overly formal sense unless specifically defined as herein.

[0065] Reference Figure 1 This invention provides a four-in-one diffusion gas detection method, comprising the following steps:

[0066] S1: Provide a detection terminal, calibrate the detection signal of the detection terminal, and obtain the ambient gas concentration based on the calibrated detection terminal;

[0067] In step S1, a detection terminal is provided, integrating sensor modules based on electrochemical and catalytic combustion principles. The electrochemical sensor generates an electrical signal through a redox reaction between a specific electrode material and a target gas (such as carbon monoxide, hydrogen sulfide, or oxygen). Specifically, the electrode material interacts with gas molecules in an electrolyte environment, producing a current signal proportional to the gas concentration. For example, when detecting carbon monoxide, the working electrode surface in the electrochemical sensor undergoes an oxidation reaction with carbon monoxide molecules, generating an electron flow and thus forming a measurable current signal. The current intensity directly reflects the carbon monoxide concentration. The catalytic combustion sensor is used for detecting combustible gases (such as methane). Its working principle involves promoting a low-temperature combustion reaction between the combustible gas and oxygen through the surface of a catalyst. This reaction causes a change in the resistance of the sensor element (such as a platinum wire), and the amount of resistance change is positively correlated with the combustible gas concentration. For example, in a standard gas environment, the detection terminal can test the catalytic combustion sensor with a standard methane gas of known concentration, record its resistance change, and thus establish a resistance-concentration relationship curve. During the calibration phase, the detection terminal generates calibration baseline data by reading the voltage output and resistance change values ​​of the sensors in a standard gas environment. The calibration process involves placing the sensors in a standard gas environment of known concentration (such as 100 ppm carbon monoxide or 20% oxygen by volume), recording the current output of the electrochemical sensor or the resistance change value of the catalytic combustion sensor, and correlating these values ​​with the standard concentration values ​​to form a calibration curve. A full-range temperature and humidity compensation algorithm can be used to correct the signal. By acquiring ambient temperature and humidity data in real time, the detection terminal uses lookup tables and polynomial fitting techniques to adjust the zero-point and span parameters of the sensors, correcting signal drift caused by environmental factors. For example, when the temperature rises from 20℃ to 40℃, the lookup table method can adjust the output signal according to a preset temperature-signal drift relationship table, while polynomial fitting further refines the calibration curve through a mathematical model to ensure the stability of the signal output. After calibration, the detection terminal samples the ambient gas in real time using the electrochemical and catalytic combustion sensors, converting the gas concentration into an electrical signal. Electrochemical sensors generate current signals through electrochemical reactions initiated by target gases on the electrode surface. For example, hydrogen sulfide undergoes an oxidation reaction on the electrode to generate a current of a specific intensity. Catalytic combustion sensors detect changes in resistance caused by the combustion reaction of combustible gases on the catalyst surface. For example, the combustion of methane leads to an increase in the resistance of a platinum wire.

[0068] It is worth noting that the detection terminal can be in various portable or fixed device forms to meet the gas detection needs in different scenarios.

[0069] S2: Based on the diffusion time constant, the cutoff acquisition frequency is set, and the analog-to-digital conversion sequences of each gas in the ambient gas are amplified and filtered to obtain a standard signal;

[0070] In step S2, the analog-to-digital conversion sequence acquired by the environmental gas detection terminal is processed, converting analog signals (such as voltage or current signals corresponding to gas concentrations) into digital signals to form sequence data. This data typically comes from different types of sensor channels, such as combustible gas channels and electrochemical channels for oxygen, carbon monoxide, and hydrogen sulfide. The analog-to-digital conversion sequence is amplified to enhance the weak signals output by the sensors, bringing them to a resolvable amplitude range. For example, a combustible gas sensor may output a voltage signal at the microvolt level, while an electrochemical sensor (such as an oxygen or carbon monoxide sensor) typically outputs a current signal at the microampere level. These signals are amplified by a preamplifier circuit (such as an operational amplifier). The diffusion time constant is a parameter related to the diffusion rate of gas molecules within the sensor cavity of the detection terminal, and it is related to the physical structure of the sensor and the molecular characteristics of the gas. Different gases (such as oxygen, carbon monoxide, and hydrogen sulfide) have different diffusion rates. The cutoff acquisition frequency is adaptively adjusted according to the diffusion time constant, ensuring that signal acquisition can capture dynamic changes in gas concentration while avoiding interference from high-frequency noise. For example, hydrogen sulfide has a small diffusion time constant and a fast response speed, requiring a high cutoff frequency (such as 10 Hz).

[0071] In another embodiment, this can be achieved using a combination of first-order low-pass and notch filters. The first-order low-pass filter effectively attenuates signals above the cutoff frequency and weakens high-frequency vibration noise (such as interference caused by mechanical vibration), while the notch filter suppresses power frequency noise (such as 50Hz or 60Hz). After filtering, the analog-to-digital conversion sequence undergoes baseline preprocessing to eliminate zero-point offset. Zero-point offset refers to the phenomenon where the sensor output signal deviates from the ideal zero point in the absence of target gas or at low concentrations. The zero-point value calibrated at the factory can be used as a reference, and the current zero-point offset can be dynamically calculated using a steady-state background window (e.g., the average signal value over the last 5 seconds). For example, assuming the factory zero-point value of the carbon monoxide sensor is 0mV, but in the actual environment, due to increased temperature, the sensor output is 0.5mV in the absence of carbon monoxide, the 0.5mV offset is calculated using the steady-state background window and subtracted from the analog-to-digital conversion sequence to correct the signal. The generated preprocessed signal includes the purification signals of each channel, the zero-point offset timestamp, and the temperature and humidity measurement vectors. These signals are then integrated into a standard signal.

[0072] S3: Construct a decoupling matrix based on the standard signal, and perform decoupling calculation on the concentration of the mixed gas based on the decoupling matrix to obtain the original concentration value of each gas;

[0073] In step S3, a decoupling matrix is ​​constructed by analyzing the response characteristics of each sensor channel and the cross-interference relationships between gases. Specifically, for the phenomenon of the combustible gas channel being affected by fluctuations in oxygen volume fraction and the electrochemical cross-response between carbon monoxide and hydrogen sulfide, a small-scale decoupling matrix is ​​constructed using temperature and humidity measurement vectors. These vectors can be obtained through additional temperature and humidity sensors, and this data serves as auxiliary input to help correct the response bias of the gas sensors. For example, suppose the four sensor channels of the detection terminal correspond to the detection of CH4 (methane), CO (carbon monoxide), H2S (hydrogen sulfide), and O2 (oxygen), respectively. However, the output signal of the CH4 channel fluctuates due to changes in O2 concentration, and there is cross-response between the electrochemical sensors for CO and H2S. In this case, the standard signal can be represented as a vector S = [S1, S2, S3, S4], where S1 to S4 correspond to the signal values ​​of the four channels, respectively. The actual gas concentration vector C = [C CH4 C CO C H2S C O2 The relationship between the signal vector S and the response vector S can be represented by a matrix M, i.e., S = M × C, where M is a 4 × 4 response matrix, and its element Mij represents the response coefficient of the j-th gas to the i-th channel. For example, M 12 This represents the response coefficient of O2 to the CH4 channel. Due to crosstalk, M is usually not a diagonal matrix. The decoupling matrix is ​​the inverse of M. (-1) By calculating C=M (-1) The concentration C of each gas can be calculated from the standard signal S by multiplying by S. When constructing the decoupling matrix M, the value of each element Mij can be determined through experimental calibration. For example, the concentration of a single gas can be controlled in the laboratory, and the response signal of each channel can be measured to obtain each column of M, thus yielding the actual concentration value of each gas.

[0074] S4: Compare the original concentration value with a preset threshold in the register to generate a status identifier containing an exceedance flag, and integrate multiple status identifiers to obtain an alarm trigger signal;

[0075] In step S4, the register serves as a storage unit, pre-storing threshold data for each target gas. For example, each gas corresponds to a low alarm threshold (e.g., 50 ppm for carbon monoxide) and a high alarm threshold (e.g., 200 ppm). These thresholds can be pre-configured by the user according to industry standards or actual application scenarios and stored in the system's non-volatile memory. The comparator logic is invoked to determine the relationship between each gas concentration value and the preset threshold. For example, combustible gas CH4 has a default low alarm threshold of 10% LEL and a high alarm threshold of 50% LEL, while oxygen (O2) has a default low alarm threshold of 19.5% Vol. A multi-channel parallel comparison algorithm is used, allowing the concentration values ​​of multiple gases to be compared with their respective thresholds simultaneously without delay due to processing order or resource contention. This can be implemented using a multi-core processor or a dedicated digital signal processor (DSP), significantly improving system real-time performance. When the concentration value of a gas exceeds the preset threshold range, a status flag containing an exceedance indicator is generated. This flag is a binary or multi-bit digital signal used to represent the concentration status of the gas. The status indicators of multiple gases are integrated to generate a unified alarm trigger signal. This involves performing logical operations on the status indicators of all gases to determine the alarm status of the entire detection terminal. For example, a logical OR operation can be used, meaning that as long as any gas status indicator shows an out-of-range condition (i.e., non-zero), the alarm trigger signal will be set to the triggered state, generating a signal indicating that the alarm has been triggered.

[0076] S5: Perform mode determination processing on the alarm trigger signal according to the preset mode in the register, and control the detection terminal to output an alarm command;

[0077] In step S5, the alarm trigger signal generated in step S4 undergoes mode determination processing. Preset alarm mode rules are read from the register, including alarm logic for different gas concentration states, such as oxygen concentration being too low or too high, carbon monoxide concentration exceeding the standard, hydrogen sulfide concentration exceeding the standard, and combustible gas concentration exceeding the standard. In the mode determination processing, the detection terminal classifies the alarm trigger signal generated in step S4 using a logical judgment algorithm. Based on a state machine algorithm, it determines the current gas concentration state according to the input trigger signal and the unit and decimal place data in the register. After generating an alarm command, the detection terminal uses the Modbus protocol to read the alarm command data from the register, updates the alarm status in real time, and controls the operation of the tri-color indicator and buzzer. The tri-color indicator is typically categorized as green (normal), red (abnormal concentration), and yellow (sensor malfunction), with red further divided into solid (high concentration alarm) and flashing (oxygen abnormality alarm). For example, when the oxygen concentration is 18%, the combustible gas concentration is 50% LEL, or the carbon monoxide concentration is 160 ppm, the alarm light will remain constantly red, and an audible alarm will sound. When the oxygen concentration is 23% Vol, the combustible gas concentration is 10% LEL, or the carbon monoxide concentration is 24 ppm, the alarm light will flash red, and an audible alarm will sound. Within the normal operating range, the alarm light will be green. To optimize the output intensity of the audible signal, the detection terminal can use pulse width modulation (PWM) technology to control the loudness of the buzzer by adjusting the duty cycle, ensuring clear transmission of the audible signal in different environments. A sensor fault alarm will trigger a constantly lit yellow light, and the buzzer will emit a specific frequency fault tone, such as an intermittent 200Hz tone, to distinguish it from an abnormal concentration alarm.

[0078] In one specific embodiment, the preset rules included in the registers are shown in Table 1 below. After the detection terminal is powered on, it automatically loads Modbus protocol parameters, including address 0x01, baud rate 9600, data bits 8, no parity bit, and stop bit 1. It obtains the initial gas concentration value by reading registers 0-3, performs automatic zero-point tracking correction using the zero-point parameters of registers 15, 25, 35, and 45, performs multi-level calibration by combining the range parameters of registers 9, 19, 29, and 39 and the zero-point correction values ​​of registers 17, 27, 37, and 47, and simultaneously reads unit parameters through registers 12, 22, 32, and 42, performs full-range compensation by combining ambient temperature and humidity data, and generates the calibrated gas concentration reference value and calibration parameters. Based on the calibration parameters, the concentrations of combustible gas, oxygen, carbon monoxide, and hydrogen sulfide are collected and processed in real time to generate a real-time concentration value list. Using electrochemical and catalytic combustion sensors, raw AD signals are acquired through registers 4-7. These signals are then converted using the span parameters in registers 16, 26, 36, and 46 to generate concentration data for combustible gas (0-100% LEL), oxygen (0-30% Vol), carbon monoxide (0-2000 ppm), and hydrogen sulfide (0-100 ppm). The acquisition frequency is once per second, meeting the minimum polling cycle of the Modbus protocol. Concentration data from registers 0-3 are read using function code 0x03, and the decimal parameters in registers 11, 21, 31, and 41 are utilized. To ensure data resolution, the low and high alarm thresholds for each gas channel are obtained by reading registers 13, 14, 23, 24, 33, 34, 43, and 44. These thresholds include: 10% LEL for combustible gas and 50% LEL for high alarm; 19.5% Vol for oxygen and 23% Vol for high alarm; 24 ppm for carbon monoxide and 160 ppm for high alarm; and 20 ppm for hydrogen sulfide and 50 ppm for high alarm. The kernel algorithm is then used to compare the real-time concentration with the thresholds one by one to determine whether a low or high alarm condition has been triggered, generating an alarm status table that includes the exceedance conditions for each gas.

[0079]

[0080] Table 1

[0081] In one embodiment, the step of calibrating the detection signal of the detection terminal includes:

[0082] The target gas is initially acquired and processed based on the sensor array on the detection terminal to obtain the original signal dataset, wherein the target gas includes combustible gas, oxygen, carbon monoxide and hydrogen sulfide.

[0083] Environmental parameters are acquired based on the environmental sensors on the detection terminal, and the voltage and resistance values ​​in the original signal dataset are adjusted according to the environmental parameters to generate a correction signal set;

[0084] Extract the voltage or resistance values ​​of each gas at different standard concentrations from the calibration signal set, construct the mapping relationship between signal values ​​and gas concentrations, and generate sensor linear parameters;

[0085] The voltage or resistance values ​​in the sensor array are corrected point by point based on the slope and intercept in the linear parameters of the sensor to obtain the calibrated detection signal.

[0086] In the above embodiments, the detection terminal is equipped with a sensor array based on electrochemical and catalytic combustion principles to detect combustible gases, oxygen, carbon monoxide, and hydrogen sulfide. In a standard gas environment, the electrochemical sensor reacts with the target gas via a redox reaction using specific electrode materials, generating a current signal proportional to the gas concentration, which is then converted into a voltage output. The catalytic combustion sensor utilizes the catalyst surface to promote a low-temperature combustion reaction between combustible gas and oxygen, causing a change in the resistance of the sensor element; this resistance change is directly related to the combustible gas concentration. By collecting the voltage output or resistance change values ​​of each sensor at different standard concentrations, a raw signal dataset containing the initial responses of all sensors is generated. Through real-time monitoring by environmental sensors, a preset environmental compensation algorithm is used to correct the raw signal dataset, adjusting the voltage or resistance value of each sensor to generate a corrected signal set that eliminates interference from factors such as temperature, humidity, and air pressure. The voltage or resistance values ​​corresponding to each gas at different standard concentrations are extracted from the corrected signal set, and the slope and intercept of each sensor are calculated to generate linear parameters describing the sensor output characteristic curves. The slope reflects the sensor's response sensitivity, i.e., the rate of change of the signal value with gas concentration; the intercept represents the sensor's zero-point offset, i.e., the signal output at zero concentration. Using the slope and intercept from the linear parameters, combined with the known value of the standard gas concentration, calibration coefficients are calculated to eliminate response deviations caused by sensor aging or manufacturing differences. The linear parameters are then substituted into the expected output model at the standard gas concentration, and the difference between the actual and theoretical signal values ​​is compared to determine the adjustment factors. These adjustment factors are stored as a calibration coefficient set and applied to the voltage or resistance value of each sensor in the calibration signal set for point-by-point correction. By reconstructing the signal data, a calibration signal set highly consistent with the standard gas concentration is generated, eliminating the effects of individual sensor differences and long-term drift, and generating calibration reference data.

[0087] In one embodiment, the step of obtaining the ambient gas concentration based on the calibrated detection terminal includes:

[0088] The target gas in the environment is sampled synchronously through multiple channels using the multi-channel detection array of the calibrated detection terminal to obtain the original sampling signal.

[0089] The electrical signals of each channel in the detection array are processed by analog-to-digital conversion to obtain a digital concentration sequence reflecting the changes in the concentration of each gas.

[0090] In the above embodiments, the calibrated detection terminal utilizes a multi-channel detection array composed of electrochemical sensors and catalytic combustion sensors to simultaneously sample combustible gases, oxygen, carbon monoxide, and hydrogen sulfide in the environment, generating raw sampling signals containing the initial electrical signals of each gas. Specifically, the detection terminal simultaneously collects environmental gas samples through multiple parallel sensor channels. The electrochemical sensors generate weak current signals through the oxidation or reduction reactions of the target gas on the electrode surface, while the catalytic combustion sensors generate voltage signals through the resistance changes caused by the combustion reaction of combustible gases on the catalyst surface. These signals are initially amplified by a preamplifier circuit to generate raw sampling signals reflecting the concentration characteristics of each gas. Based on the raw sampling signals, an analog-to-digital converter (ADC) is used to perform analog-to-digital conversion on the electrical signals of each channel, obtaining a digital concentration sequence reflecting the concentration changes of each gas. The raw sampling signals are sampled at high frequency using a successive approximation ADC, with each channel signal converted to a digital value at a fixed sampling rate. A time synchronization mechanism is used during the sampling process to ensure the time consistency of each gas signal. The converted digital values ​​are then filtered to remove high-frequency noise interference, forming a digital concentration sequence containing the concentration characteristics of each gas.

[0091] In one embodiment, the step of amplifying and filtering the analog-to-digital conversion sequences of the gases in the ambient gas to obtain a standard signal includes:

[0092] The amplitude differences of each channel signal in the digital concentration sequence are obtained, and the digital concentration sequence is amplified according to the amplitude differences to obtain an amplitude equalization sequence.

[0093] Based on the diffusion time constant of each gas molecule, the cutoff frequency parameter corresponding to the gas diffusion rate is calculated. The amplitude equalization sequence is then processed in the frequency domain using a filter to obtain a low-noise sequence. The cutoff frequency of the filter is set according to the cutoff frequency parameter.

[0094] A sliding window with a preset number of bits is constructed, and an offset subtraction operation is performed on each data point in the low-noise sequence according to the sliding window to obtain a standard signal.

[0095] In the above embodiments, the amplitude differences of the signals in each channel of the digital concentration sequence are obtained. For example, the output signal amplitude of the combustible gas sensor is greater than that of the electrochemical oxygen sensor. A programmable gain amplifier is used to independently adjust the gain of the digital signal sequence of each channel. Specifically, a digital signal processor (DSP) analyzes the amplitude range of each channel signal in the initial sampling sequence, calculates the amplitude difference of each channel signal, and achieves this by statistically analyzing the peak value, mean, or standard deviation of each channel signal. Based on the sensitivity characteristics of each sensor type, a set of gain coefficients is preset. For example, a lower gain coefficient is set for the combustible gas channel, and a higher gain coefficient is set for the hydrogen sulfide channel to amplify its weaker signal. The DSP performs gain calculation on the digital signal sequence of each channel according to these coefficients, normalizing the signal amplitude to a uniform range, such as a normalized range of 0 to 1, thereby generating an amplitude-equalized sequence. The diffusion time constant is determined based on the physical properties of the gas molecules. Based on the diffusion time constant, the cutoff frequency parameter corresponding to the gas diffusion rate can be calculated using a formula, such as fc=1 / (2πτ), where τ is the diffusion time constant and fc is the cutoff frequency. For each channel's gas type, the DSP dynamically calculates the corresponding cutoff frequency parameters and configures the filter parameters accordingly. The filtering process is achieved by performing frequency domain processing on the amplitude equalization sequence. For example, a Fast Fourier Transform (FFT) is used to convert the signal to the frequency domain, the frequency response function of the filter is applied, and then an Inverse Fourier Transform (IFFT) is used to convert it back to the time domain, generating a low-noise sequence. A sliding window with a preset number of bits is constructed, such as a window containing N data points (N can be set according to the sampling frequency and application requirements, such as 10 or 50 data points), to analyze the local trends in the low-noise sequence. The sliding window slides across the sequence with a fixed step size (usually 1 data point). For each window position, the DSP calculates the average or median of the data within the window as the instantaneous zero-point offset value at that position. This offset value reflects the baseline drift caused by sensor aging, temperature drift, or other environmental factors. The DSP performs an offset subtraction operation on each data point in the low-noise sequence, subtracting the corresponding zero-point offset value from the original data point value, thereby generating a baseline-stabilized sequence. In another embodiment, the DSP reassembles the signal data from each channel according to a predefined unified data structure, such as a data packet format containing timestamps, channel identifiers, and concentration value vectors, performs data compression (such as removing redundant data), adds verification information, and generates a standard signal.

[0096] In one embodiment, the step of constructing the decoupling matrix based on the standard signal includes:

[0097] Extract the temperature and humidity characteristic parameters corresponding to the gas concentration changes in the standard signal to generate a temperature and humidity measurement vector;

[0098] The nonlinear interference components of the oxygen integral in the combustible gas channel are identified based on the humidity measurement vector. The amplitude and phase of the standard signal are adjusted based on the nonlinear interference components to generate a corrected gas signal.

[0099] The cross-response characteristics between carbon monoxide and hydrogen sulfide electrochemical sensors in the corrected gas signal are obtained. The corrected gas signal is then processed by signal separation based on the cross-response characteristics, and a decoupling matrix is ​​constructed based on the separated gas signal.

[0100] In the above embodiments, temperature and humidity characteristic parameters related to gas concentration changes are extracted from the standard signal to generate a temperature and humidity measurement vector. By analyzing the amplitude changes of the standard signal within different time windows and combining it with real-time environmental data collected by the temperature and humidity sensor built into the detection terminal, dynamic features related to temperature, humidity, and gas diffusion rate are extracted to form a multi-dimensional vector. The temperature and humidity measurement vector is used to identify the nonlinear interference components of the oxygen integral number in the combustible gas channel, and a corrected gas signal is generated by adjusting the amplitude and phase of the standard signal. By analyzing the dynamic features in the temperature and humidity measurement vector, the nonlinear interference pattern is identified, and the amplitude and phase of the signal are adjusted accordingly to generate a corrected signal that more closely approximates the actual gas concentration distribution. To address the cross-response characteristics between carbon monoxide and hydrogen sulfide electrochemical sensors in the calibrated gas signals, a combined time-domain and frequency-domain analysis method was employed for signal separation. By analyzing the response characteristics of the signals within a specific frequency range and considering the different reaction time constants of carbon monoxide and hydrogen sulfide in the electrochemical sensors, the mixed signal was decomposed into independent signal components, forming a signal set containing the independent characteristics of each gas. Based on this, a decoupling matrix was constructed. The construction of the decoupling matrix, through the separated gas signals, can effectively characterize the independent response characteristics of each gas in the detection system.

[0101] In one embodiment, the step of decoupling the concentration of the mixed gas based on the decoupling matrix to obtain the original concentration values ​​of each gas includes:

[0102] Calculate the principal eigenvalues ​​and corresponding eigenvectors of the decoupling matrix to generate a set of eigenvectors containing the independent features of each gas signal.

[0103] The corrected gas signal is subjected to projection transformation based on the feature vector set to obtain a projection signal set.

[0104] The projected signal set is subjected to signal component separation processing to obtain a single gas signal set, wherein the single gas signal set corresponds to the actual concentration of each target gas in the environment;

[0105] Based on the amplitude characteristics of the single gas signal set, the signal amplitude is inversely normalized to obtain the original concentration values ​​of each gas.

[0106] In the above embodiments, by performing eigenvalue decomposition on the decoupling matrix, the principal eigenvalues ​​of the matrix and their corresponding eigenvectors are calculated, generating a set of eigenvectors containing the independent features of each gas signal. This process treats the decoupling matrix as a linear transformation system, utilizing the eigenvalue decomposition method in linear algebra to ensure that the decomposition results reflect the independent distribution characteristics of each gas signal in multidimensional space. Based on the eigenvector set, the corrected gas signals are subjected to projection transformation processing. By projecting the signals onto a coordinate system composed of eigenvectors, a projected signal set is generated. The projection transformation maps the corrected gas signals to a new feature space through inner product operations, highlighting the independence of each gas signal and ensuring the consistency of signal data scale. The projected signal set is then subjected to signal component separation processing. Utilizing the orthogonality of each gas signal in the feature space, signal components related to combustible gas, oxygen, carbon monoxide, and hydrogen sulfide are extracted one by one to form a single gas signal set. The single gas signal set can directly correspond to the actual concentration of each target gas in the environment. By inversely normalizing the amplitude characteristics of a single gas signal set and combining the sensor linear parameters (such as slope and intercept) established during calibration, the original dimensions of the signal are recovered, and the original concentration values ​​of each gas are obtained. This process further refines the concentration data through linear interpolation, estimates the concentration values ​​at continuous time points, thereby improving the resolution and continuity of the concentration data and generating original concentration values ​​that reflect the true concentration of each gas.

[0107] It is worth noting that constructing the decoupling matrix involves extracting temperature and humidity features from the standard signal, correcting for oxygen interference, and separating the cross-response signals of carbon monoxide and hydrogen sulfide. The goal of this embodiment is to directly obtain the original concentration values ​​of each gas and convert the corrected mixed signal into specific concentration values.

[0108] In one embodiment, the step of comparing the original concentration value with a preset threshold in the register to generate a status identifier containing an exceedance flag, and integrating multiple status identifiers to obtain an alarm trigger signal, includes:

[0109] Based on the original concentration value, the corresponding unit conversion factor is extracted from the register. Then, the original concentration value is standardized using the unit conversion factor to obtain a standardized concentration dataset.

[0110] Obtain the dimensional characteristics of the standardized concentration dataset, and generate comparator configuration parameters based on the dimensional characteristics and the preset threshold in the register;

[0111] The comparator configuration parameters are used to compare the concentration values ​​of each gas in the standardized concentration dataset to generate a single-channel comparison result set for each gas.

[0112] The exceeding status is flagged based on the single-channel comparison result set, and the processing results are logically integrated to obtain the alarm trigger signal.

[0113] In the above embodiments, the unit conversion factor and accuracy requirements corresponding to each target gas are extracted from the register. For example, the original concentration values ​​of combustible gases are converted from percentages to a unified ppm unit. Unit conversion factors are applied to the original concentration values ​​for unit standardization, and accuracy adjustments are made based on decimal normalization requirements, converting all gas concentration values ​​into a standardized concentration dataset with unified dimensions and accuracy. The register stores preset low and high alarm thresholds for each target gas. For example, the low alarm threshold for oxygen might be 19.5% (volume fraction), and the high alarm threshold might be 23.5%, while the high alarm threshold for carbon monoxide might be 50 ppm. Based on the dimensional characteristics of the standardized concentration dataset, such as the unified ppm or percentage units, comparator configuration parameters are generated using these preset thresholds. These parameters include the upper and lower limits of the threshold range for each gas. After the comparator configuration is completed, a multi-channel parallel comparison algorithm is used to compare the threshold values ​​of each gas in the standardized concentration dataset. This process is achieved by checking each gas concentration value one by one to see if it falls within its corresponding low and high alarm threshold ranges. A single-channel comparison result set is generated for each gas, recording the relationship between each gas concentration value and the threshold. A status coding logic is used to assign a flag to each gas: when the concentration value exceeds the preset threshold range, a status identifier containing an "exceeding" flag is generated (e.g., 1 indicates exceeding the limit); when the concentration value is within the normal range, a status identifier containing a "normal" flag is generated (e.g., 0 indicates normal), forming a status identifier set containing the states of all target gases. The status identifier set is converted into an alarm trigger signal. When the vector contains any "exceeding" flag, an active alarm trigger signal (e.g., logic 1) is generated to trigger the alarm output of the detection terminal, such as an audible or visual alarm; when all states are normal, an inactive alarm trigger signal (e.g., logic 0) is generated, indicating that no alarm is needed.

[0114] In one embodiment, the step of performing mode determination processing on the alarm trigger signal according to a preset mode in the register includes:

[0115] The alarm trigger signal is classified according to the preset alarm rule base in the register to obtain a state classification dataset.

[0116] Based on the alarm priority labels in the state classification dataset, the alarm trigger signals are sorted by priority to obtain a priority sequence.

[0117] The alarm trigger signal is allocated to different time segments according to the priority sequence, and the over-limit flag of the alarm trigger signal in different time segments is matched with the preset signal modulation template to generate a modulation signal set including modulation signals corresponding to different alarm states.

[0118] The modulated signal set is encoded to obtain an encoded alarm instruction set, which is applied to the detection terminal.

[0119] In the above embodiments, a predefined rule base is used to analyze and classify alarm trigger signals. The rule base includes various preset conditions, such as the hazard levels of different gas concentrations, the influence of environmental parameters, and specific alarm trigger scenarios. By classifying the alarm trigger signals into states, complex signal data is decomposed into different state categories, such as normal, slightly exceeding limits, and severely exceeding limits. State classification is implemented through logical rules stored in registers. These rules exist in the form of conditional statements or decision trees, and are comprehensively judged in combination with gas type, concentration value, and other environmental parameters (such as temperature and humidity). Based on the alarm priority labels in the state classification dataset, alarm signals for different gases or states are sorted according to preset priority labels. Priority labels are stored in registers and represented in numerical form (e.g., 1 for highest priority, 5 for lowest priority), and are dynamically adjusted in combination with gas type, concentration exceeding degree, and potential hazard level. After the priority sequence is generated, the alarm trigger signals are presented in a specific way at different time segments, for example, by using different frequencies, pulse widths, or amplitudes to represent different alarm states. The allocation of time segments, or time multiplexing mechanism, is similar to Time Division Multiple Access (TDMA) in communication systems. Preset signal modulation templates include a series of standardized signal patterns; for example, high-frequency pulses represent severe alarms, low-frequency pulses represent minor alarms, or specific waveforms represent the exceeding status of specific gases. By matching the exceeding indicators with these templates, a series of modulated signals can be generated, reflecting the alarm status and enhancing signal distinguishability and anti-interference capabilities. The modulated signal set is further encoded to generate an encoded alarm instruction set, which is directly applied to the detection terminal to drive it to output specific alarm commands. The encoding process converts the modulated signals into digital or analog commands that the detection terminal hardware can recognize, for example, transmitting the signals to the alarm module via a specific protocol (such as I2C or SPI). The encoded instruction set may include the frequency and intensity of audible alarms, the color and flashing pattern of visual alarms, or other forms of output signals (such as vibration or remote notification).

[0120] In one embodiment, after the step of controlling the detection terminal to output an alarm command, the method further includes:

[0121] Obtain the gas concentration data and alarm status data from the register, and calculate the trend of gas concentration data based on the gas concentration data and alarm status data;

[0122] Based on the changing trend, obtain the predicted time value required for the gas concentration to recover to the safe threshold, and compare the predicted time value with the preset time threshold.

[0123] If the predicted time value is greater than a preset time threshold, the alarm mode of the detection terminal is adjusted to a continuous alarm mode; if the predicted time value is less than or equal to the preset time threshold, the current alarm mode of the detection terminal is maintained.

[0124] In the above embodiments, the gas concentration data refers to the original concentration values ​​of each gas obtained through calibration, sampling, amplification, filtering, and decoupling calculations. Alarm status data includes exceedance flags and related status indicators. The trend of gas concentration change can be calculated using time series analysis techniques, such as calculating the rate of change of concentration values ​​using a sliding window method, or using a regression model to predict the trend of concentration change over time. For example, analyzing the carbon monoxide concentration change curve over the past few minutes can determine whether it is continuously rising, falling, or stabilizing. After obtaining the trend, the predicted time required for the gas concentration to recover to a safe threshold is calculated based on this trend. This prediction process can be based on mathematical models, such as exponential decay models or linear regression models, combined with the gas diffusion time constant and environmental conditions to estimate the time required for the concentration to decrease to a safe level. For example, if hydrogen sulfide concentration exceeds the standard, but its trend shows that the concentration is rapidly decreasing, the model calculates that under the current ventilation conditions, the concentration will recover to the safe threshold within 10 minutes. The calculation of the predicted value comprehensively considers multiple factors, including the chemical properties of the gas, the airflow conditions in the environment, and the sensitivity of the detection terminal. Safety thresholds are stored in registers and can be set based on industry standards (such as OSHA or NIOSH exposure limits) or user-defined thresholds. The predicted time value is compared to the preset time threshold to determine how the detection terminal's alarm mode should be adjusted. The preset time threshold may be set according to the specific application scenario; for example, a shorter time (e.g., 5 minutes) may be set in high-risk environments, while a longer recovery time (e.g., 30 minutes) may be allowed in low-risk environments. If the predicted time value is greater than the preset time threshold, it indicates that the gas concentration is unlikely to recover to a safe level in a short time, and the detection terminal's alarm mode will be adjusted to a continuous alarm mode. This mode may manifest as a continuous beeping sound, a high-frequency flashing light, or other conspicuous alarm signals to alert the user to take emergency measures, such as evacuation or increased ventilation. Conversely, if the predicted time value is less than or equal to the preset time threshold, it indicates that the gas concentration is expected to recover within a reasonable time, and the current alarm mode will be maintained, such as intermittent or low-intensity alarms, to avoid unnecessary interference.

[0125] Reference Figure 2 and Figure 3 This application also discloses a four-in-one diffusion gas detection terminal 10, applied to any of the four-in-one diffusion gas detection methods described above, comprising: a sensor array 100 for acquiring raw signals of target gases; an environmental sensor 200 for acquiring environmental parameters; an analog-to-digital converter 300 for converting the raw signals into digital signals; a processor 400 connected to the sensor array, the environmental sensor, and the analog-to-digital converter, the processor receiving the digital signals and calculating the concentration values ​​of each gas based on the digital signals and the environmental parameters; and an alarm module 500 connected to the processor, the alarm module outputting an alarm command based on the concentration values.

[0126] In this embodiment, each sensor in the sensor array selectively responds to a specific gas. Through diffusion, target gas molecules come into contact with the sensor surface, generating an electrical signal as the raw signal. Environmental sensors monitor factors such as temperature and humidity that may affect the accuracy of gas detection. An analog-to-digital converter converts these analog raw signals into digital signals for processing by the processor. After receiving the digital signals, the processor uses pre-stored algorithms and calibration data, combined with environmental parameters, to perform compensation and correction, thereby accurately calculating the concentration value of each gas. When the processor detects that the gas concentration exceeds a preset safety threshold, it triggers an alarm module. The alarm module, according to the processor's instructions, outputs an alarm signal through sound, light, or other means to promptly remind the operator to take appropriate measures.

[0127] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. Any references to memory, storage, databases, or other media provided in this application and used in the embodiments can include non-volatile and / or volatile memory. Non-volatile 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 various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual-speed SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0128] The above description is merely a preferred embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structural or procedural transformations made based on the content of the present invention's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A four-in-one diffusion-type gas detection method, characterized in that, include: A detection terminal is provided, and the detection signal of the detection terminal is calibrated. The ambient gas concentration is obtained based on the calibrated detection terminal. Based on the diffusion time constant, the cutoff acquisition frequency is set, and the analog-to-digital conversion sequences of each gas in the ambient gas are amplified and filtered to obtain a standard signal. A decoupling matrix is ​​constructed based on the standard signal, and the concentration of the mixed gas is decoupled and calculated based on the decoupling matrix to obtain the original concentration values ​​of each gas. The original concentration value is compared with a preset threshold in the register to generate a status identifier containing an exceedance flag. Multiple status identifiers are integrated to obtain an alarm trigger signal. The alarm trigger signal is processed according to the preset mode in the register, and the detection terminal is controlled to output an alarm command. The step of constructing the decoupling matrix based on the standard signal includes: Extract the temperature and humidity characteristic parameters corresponding to the gas concentration changes in the standard signal to generate a temperature and humidity measurement vector; The nonlinear interference component of the oxygen integral in the combustible gas channel is identified based on the humidity measurement vector, and the amplitude and phase of the standard signal are adjusted based on the nonlinear interference component to generate a corrected gas signal. The cross-response characteristics between the carbon monoxide and hydrogen sulfide electrochemical sensors in the corrected gas signal are obtained. The corrected gas signal is then processed by signal separation based on the cross-response characteristics. A decoupling matrix is ​​then constructed based on the separated gas signal. The step of decoupling the concentration of the mixed gas based on the decoupling matrix to obtain the original concentration values ​​of each gas includes: Calculate the principal eigenvalues ​​and corresponding eigenvectors of the decoupling matrix to generate a set of eigenvectors containing the independent features of each gas signal. The corrected gas signal is subjected to projection transformation based on the feature vector set to obtain a projection signal set. The projected signal set is subjected to signal component separation processing to obtain a single gas signal set, wherein the single gas signal set corresponds to the actual concentration of each target gas in the environment; Based on the amplitude characteristics of the single gas signal set, the signal amplitude is inversely normalized to obtain the original concentration values ​​of each gas.

2. The four-in-one diffusion gas detection method according to claim 1, characterized in that, The step of calibrating the detection signal of the detection terminal includes: The target gas is initially collected and processed based on the sensor array on the detection terminal to obtain the original signal dataset, wherein the target gas includes combustible gas, oxygen, carbon monoxide and hydrogen sulfide. Environmental parameters are acquired based on the environmental sensors on the detection terminal, and the voltage and resistance values ​​in the original signal dataset are adjusted according to the environmental parameters to generate a correction signal set; Extract the voltage or resistance values ​​of each gas at different standard concentrations from the calibration signal set, construct the mapping relationship between signal values ​​and gas concentrations, and generate sensor linear parameters; The voltage or resistance values ​​in the sensor array are corrected point by point based on the slope and intercept in the linear parameters of the sensor to obtain the calibrated detection signal.

3. The four-in-one diffusion gas detection method according to claim 1, characterized in that, The step of obtaining the ambient gas concentration based on the calibrated detection terminal includes: The target gas in the environment is sampled synchronously through multiple channels using the multi-channel detection array of the calibrated detection terminal to obtain the original sampling signal. The electrical signals of each channel in the detection array are processed by analog-to-digital conversion to obtain a digital concentration sequence reflecting the changes in the concentration of each gas.

4. The four-in-one diffusion gas detection method according to claim 1, characterized in that, The step of amplifying and filtering the analog-to-digital conversion sequences of the gases in the ambient gas to obtain a standard signal includes: The amplitude differences of each channel signal in the digital concentration sequence are obtained, and the digital concentration sequence is amplified according to the amplitude differences to obtain an amplitude equalization sequence. Based on the diffusion time constant of each gas molecule, the cutoff frequency parameter corresponding to the gas diffusion rate is calculated. The amplitude equalization sequence is then processed in the frequency domain using a filter to obtain a low-noise sequence. The cutoff frequency of the filter is set according to the cutoff frequency parameter. A sliding window with a preset number of bits is constructed, and an offset subtraction operation is performed on each data point in the low-noise sequence according to the sliding window to obtain a standard signal.

5. The four-in-one diffusion gas detection method according to claim 1, characterized in that, The step of comparing the original concentration value with a preset threshold in the register to generate a status identifier containing an exceedance flag, and integrating multiple status identifiers to obtain an alarm trigger signal, includes: Based on the original concentration value, the corresponding unit conversion factor is extracted from the register. Then, the original concentration value is standardized using the unit conversion factor to obtain a standardized concentration dataset. Obtain the dimensional characteristics of the standardized concentration dataset, and generate comparator configuration parameters based on the dimensional characteristics and the preset threshold in the register; The comparator configuration parameters are used to compare the concentration values ​​of each gas in the standardized concentration dataset to generate a single-channel comparison result set for each gas. The exceeding status is flagged based on the single-channel comparison result set, and the processing results are logically integrated to obtain the alarm trigger signal.

6. The four-in-one diffusion gas detection method according to claim 1, characterized in that, The step of performing mode determination processing on the alarm trigger signal according to the preset mode in the register includes: The alarm trigger signal is classified according to the preset alarm rule base in the register to obtain a state classification dataset. Based on the alarm priority labels in the state classification dataset, the alarm trigger signals are sorted by priority to obtain a priority sequence. The alarm trigger signal is allocated to different time segments according to the priority sequence, and the over-limit flag of the alarm trigger signal in different time segments is matched with the preset signal modulation template to generate a modulation signal set including modulation signals corresponding to different alarm states. The modulated signal set is encoded to obtain an encoded alarm instruction set, which is applied to the detection terminal.

7. The four-in-one diffusion gas detection method according to claim 1, characterized in that, After the step of controlling the detection terminal to output an alarm command, the method further includes: Obtain the gas concentration data and alarm status data from the register, and calculate the trend of gas concentration data based on the gas concentration data and alarm status data; Based on the changing trend, obtain the predicted time value required for the gas concentration to recover to the safe threshold, and compare the predicted time value with the preset time threshold. If the predicted time value is greater than a preset time threshold, the alarm mode of the detection terminal is adjusted to a continuous alarm mode; if the predicted time value is less than or equal to the preset time threshold, the current alarm mode of the detection terminal is maintained.

8. A four-in-one diffusion-type gas detection terminal, characterized in that, The four-in-one diffusion gas detection method applied to any one of claims 1-7 includes: A sensor array for acquiring raw signals of the target gas; Environmental sensor, used to acquire environmental parameters; An analog-to-digital converter, wherein the analog-to-digital converter is used to convert the original signal into a digital signal; The processor is connected to the sensor array, the environmental sensor, and the analog-to-digital converter. The processor is used to receive the digital signal and calculate the concentration value of each gas based on the digital signal and the environmental parameters. An alarm module is connected to the processor and is used to output an alarm command based on the concentration value.

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