Self-adaptive environment compensation and fault prediction algorithm for gas detection instrument

Abstract

The invention discloses a self-adaptive environment compensation and fault prediction algorithm for a gas detection instrument, and relates to the technical field of gas detection compensation and fault prediction, and the algorithm comprises the following steps: constructing a detection test space, and recording a test result; analyzing the environmental influence duration of the gas detection instrument, and performing time sequence proofreading on a test result to obtain experimental data; performing self-adaptive environment compensation analysis on the gas detection instrument to form a self-adaptive environment compensation algorithm; setting a reaction cabin, and extracting response characteristics of the response curve; performing fault prediction on the gas detection instrument based on the time sequence change of the response characteristics; the method is used for solving the problems that according to an existing gas detection compensation and fault prediction technology, influence factors on detection precision are not comprehensively considered, a response curve is difficult to solve in daily use, and gas concentration compensation and instrument fault prediction are not accurate enough.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of gas detection compensation and fault prediction, in particular to an adaptive environmental compensation and fault prediction algorithm for a gas detection instrument. BACKGROUND

[0002] Gas detection compensation and fault prediction technology refers to an algorithm and data processing method that real-time corrects and compensates for measurement errors generated by gas sensors under various environmental conditions, analyzes sensor working state data, historical performance and operating characteristics, uses machine learning, artificial intelligence and data mining methods to predict possible sensor faults or performance degradation in advance, and realizes an integrated technical system of error correction and preventive maintenance.

[0003] The existing gas detection compensation and fault prediction technology usually uses a fixed compensation function to compensate for gas concentration without considering the influence of different environments on the accuracy of the gas detection instrument. Therefore, the compensation accuracy of the traditional fixed compensation is low. At the same time, the existing gas detection compensation and fault prediction technology is difficult to accurately predict the faults of the gas detection instrument because the fault judgment of the gas detection instrument depends on the response curve, which is difficult to evaluate in daily use. For example, in the patent application with the publication number CN114217021A, a gas detection concentration compensation method, detection method and detection device are disclosed. This scheme uses a fixed compensation function to compensate for gas concentration without considering the influence of different environments on the accuracy of the gas detection instrument. The existing gas detection compensation and fault prediction technology also has the problem that the factors affecting the detection accuracy are not considered comprehensively and it is difficult to solve the response curve in daily use, resulting in inaccurate gas concentration compensation and instrument fault prediction. SUMMARY

[0004] The present application aims to at least solve one of the technical problems in the prior art by constructing a detection test space, randomly changing the environmental parameters in the detection test space every first test duration, recording the test results, then analyzing the environmental influence duration of the gas detection instrument, time correcting the test results based on the environmental influence duration, obtaining experimental data, analyzing the influence relationship of temperature and humidity on detection accuracy based on the experimental data, obtaining the temperature precision influence relationship and the humidity precision influence relationship, then dividing the temperature precision influence relationship and the humidity precision influence relationship into reference relationship and calibration relationship, then performing adaptive environmental compensation analysis on the gas detection instrument based on the reference relationship and the calibration relationship, forming an adaptive environmental compensation algorithm, setting a reaction chamber, testing the response curve of the gas detection instrument through the reaction chamber, extracting the response characteristics of the response curve, and finally monitoring the health status of the gas detection instrument based on the response characteristics, and predicting the failure of the gas detection instrument based on the time sequence change of the response characteristics, to solve the problem that the existing gas detection compensation and failure prediction technology does not consider the influence factors of detection accuracy comprehensively and is difficult to solve the response curve in daily use, resulting in inaccurate concentration compensation of gas and instrument failure prediction.

[0005] To achieve the above-mentioned purpose, the present application provides an adaptive environmental compensation and failure prediction algorithm for a gas detection instrument, comprising the following steps: Construct a detection test space, randomly change the environmental parameters in the detection test space every first test duration, and record the test results; Analyze the environmental influence duration of the gas detection instrument, time correct the test results based on the environmental influence duration, and obtain experimental data; Based on the experimental data, analyze the influence relationship of temperature and humidity on detection accuracy, and perform adaptive environmental compensation analysis on the gas detection instrument to form an adaptive environmental compensation algorithm; Set a reaction chamber, test the response curve of the gas detection instrument through the reaction chamber, and extract the response characteristics of the response curve; Monitor the health status of the gas detection instrument based on the response characteristics, and predict the failure of the gas detection instrument based on the time sequence change of the response characteristics.

[0006] Further, constructing a detection test space, randomly changing the environmental parameters in the detection test space every first test duration, and recording the test results comprises the following sub-steps: Construct a detection test space, the detection test space is a closed space capable of changing environmental parameters, and there is an air inlet and an air outlet in it for maintaining the concentration of test gas stable; Put test gas of a first test concentration into the detection test space, and keep the test gas at the first test concentration at all times; randomly change the environmental parameters in the detection test space every first test duration, the environmental parameters including the environmental temperature and the environmental humidity; install a gas detection instrument in the detection test space, detect the concentration of the test gas in real time through the gas detection instrument, and name it as a detection concentration, and record a detection time, the detection time and the detection concentration being test results.

[0007] Further, when analyzing the environmental influence duration of the gas detection instrument, the test results are time-sequentially corrected based on the environmental influence duration to obtain experimental data including the following sub-steps: set the environmental parameters in the detection test space to a first test state, detect the gas concentration of the test gas after the first test duration, and name it as a correction auxiliary concentration, continuously record the first test duration, and statistically analyze the range of the correction auxiliary concentration in the first test duration, and name it as a correction concentration range; change the environmental parameters in the detection test space, record the correction auxiliary concentration in real time and time, and when the correction auxiliary concentration exceeds the correction concentration range, stop timing and obtain the duration of timing, and name it as an environmental influence duration; advance the detection time in the test results by the environmental influence duration to obtain a correction time, name the environmental temperature and the environmental humidity corresponding to the correction time as a correction temperature and a correction humidity, respectively, associate the correction temperature and the correction humidity with the detection concentration, and form experimental data, the experimental data including the detection concentration, the correction time, the correction temperature and the correction humidity.

[0008] Further, based on the experimental data, the influence relationship of temperature and humidity on detection accuracy is analyzed, and adaptive environmental compensation analysis is performed on the gas detection instrument to form an adaptive environmental compensation algorithm including the following sub-steps: Based on the experimental data, the influence relationship of temperature and humidity on detection accuracy is analyzed to obtain a temperature accuracy influence relationship and a humidity accuracy influence relationship; divide the temperature accuracy influence relationship and the humidity accuracy influence relationship into a reference relationship and a calibration relationship; based on the reference relationship and the calibration relationship, the gas detection instrument is subjected to adaptive environmental compensation analysis to form an adaptive environmental compensation algorithm.

[0009] Further, based on the experimental data, the influence relationship of temperature and humidity on detection accuracy is analyzed to obtain a temperature accuracy influence relationship and a humidity accuracy influence relationship including the following sub-steps: label the detection concentration as P1, label the first test concentration as P2, calculate (P1-P2) / P2, and obtain a detection deviation; respectively, and the detection deviation is respectively entered into the temperature precision influence analysis graph and the humidity precision influence analysis graph, and the coordinate points in the temperature precision influence analysis graph and the humidity precision influence analysis graph are respectively named as temperature precision influence analysis points and humidity precision influence analysis points; The temperature precision influence curve and the humidity precision influence curve are obtained by regression analysis on the temperature precision influence analysis graph and the humidity precision influence analysis graph. The temperature precision influence curve and the temperature precision influence analysis points thereof are the temperature precision influence relationship, and the humidity precision influence curve and the humidity precision influence analysis points thereof are the humidity precision influence relationship.

[0010] Further, the temperature precision influence relationship and the humidity precision influence relationship are divided into a reference relationship and a calibration relationship, including the following sub-steps: The standard deviations of the temperature precision influence curve and the humidity precision influence curve are obtained, and are respectively named as temperature standard deviation and humidity standard deviation. If the temperature standard deviation is less than or equal to the humidity standard deviation, the temperature precision influence analysis graph is named as a reference analysis graph, and the humidity precision influence analysis graph is named as a calibration analysis graph; if the temperature standard deviation is greater than the humidity standard deviation, the humidity precision influence analysis graph is named as a reference analysis graph, and the temperature precision influence analysis graph is named as a calibration analysis graph. The temperature precision influence analysis points or the humidity precision influence analysis points corresponding to the reference analysis graph are named as reference analysis points, the temperature precision influence analysis points or the humidity precision influence analysis points corresponding to the calibration analysis graph are named as calibration analysis points, the temperature precision influence curve or the humidity precision influence curve corresponding to the reference analysis graph is named as a reference influence curve, and the temperature precision influence curve or the humidity precision influence curve corresponding to the calibration analysis graph is named as a calibration influence curve. The reference analysis graph, the reference analysis points, and the reference influence curve are the reference relationship, and the calibration analysis graph, the calibration analysis points, and the calibration influence curve are the calibration relationship.

[0011] Further, based on the reference relationship and the calibration relationship, an adaptive environmental compensation analysis is performed on the gas detection instrument to form an adaptive environmental compensation algorithm, including the following sub-steps: The gas concentration detected by the gas detection instrument in real time is obtained and is named as real-time concentration, and the environmental temperature and the environmental humidity at the previous environmental influence time length of the current time are obtained and are respectively named as effective temperature and effective humidity. If the reference analysis graph is a temperature precision influence analysis graph, the effective temperature is named as the reference parameter, and the effective humidity is named as the calibration parameter; if the reference analysis graph is a humidity precision influence analysis graph, the effective humidity is named as the reference parameter, and the effective temperature is named as the calibration parameter; A reference analysis point in the reference analysis graph is obtained, where the X axis is equal to the reference parameter, and the reference analysis point is named as a reference reference point. A value of the reference reference point on the Y axis is named as a reference reference difference value. A corresponding calibration humidity or calibration temperature of the reference reference point is named as a calibration reference parameter; The calibration reference parameter is numbered, and is represented by a symbol CH i , where i is a non-zero natural number and i is a serial number of CH i . The CH i is substituted into the calibration analysis curve to obtain a value of the Y axis of a coordinate point on the calibration analysis curve, where the X axis is equal to CH i . The value is named as a calibration reference difference value, and is represented by a symbol CR i . A corresponding reference reference difference value of CH i is marked as CD ; A value of the Y axis of a coordinate point on the calibration analysis curve, where the X axis is equal to the calibration parameter, is named as a calibration anchor difference value, and is represented by a symbol CM. Suppose that a corresponding reference analysis point in the effective temperature and effective humidity environment is a first assumption point. A value of the Y axis of the first assumption point is marked as F, and there is a relationship . F is solved by a formula . The F is a prediction deviation. Increasing a proportion of the prediction deviation can complete adaptive environmental compensation of the real-time concentration. Finally, an actual concentration is obtained.

[0012] Further, a reaction cabin is set. A response curve of the gas detection instrument is tested by the reaction cabin. Response characteristics of the response curve are extracted, including the following sub-steps. The reaction cabin is installed in the gas detection instrument. The reaction cabin includes a reaction box and a liquid storage box. Baking soda powder is placed in the reaction box, and edible citric acid is injected into the liquid storage box. The reaction box and the liquid storage box are connected by a pipeline and an intelligent control valve. Every interval of a first period, the intelligent control valve is opened, and a test volume of edible citric acid is injected into the reaction box. At this time, the baking soda powder and the edible citric acid react chemically to produce carbon dioxide. The response curve of the gas detection instrument is tested based on the reaction cabin, and the response characteristics of the response curve are extracted.

[0013] Further, the response curve of the gas detection instrument is tested based on the reaction cabin, and the response characteristics of the response curve are extracted, including the following sub-steps. Before the reaction occurs, record the carbon dioxide concentration, named as normal concentration, after the reaction occurs, record the change of carbon dioxide concentration with time, stop recording when the carbon dioxide concentration returns to the normal concentration, obtain the response data, specifically a two-dimensional coordinate system with X axis as time and Y axis as carbon dioxide concentration, wherein the curve formed by the change of carbon dioxide concentration with time is recorded, that is, the response curve; Obtain the highest point of the response curve, named as response point, obtain the time length taken by the carbon dioxide concentration from the normal concentration to the response point, named as response time length; Obtain the time length taken by the carbon dioxide concentration from the response point to the normal concentration, named as recovery time length, the response time length and the recovery time length are the response characteristics.

[0014] Further, based on the response characteristics, the health state of the gas detection instrument is monitored, and based on the time sequence change of the response characteristics, the gas detection instrument is fault predicted, including the following sub-steps: Obtain the health standard of the response characteristics, the health standard includes the response standard and the recovery standard; Record the response characteristics obtained by each test, number the response characteristics according to the chronological order, represented by symbol H j , wherein j is a non-zero natural number and j is the serial number of H; Establish a two-dimensional coordinate system with j as the horizontal axis and H j as the vertical axis, named as fault prediction coordinate system, the fault prediction coordinate system includes response fault prediction coordinate system and recovery fault prediction coordinate system, record the response time length in H j into the response fault prediction coordinate system, record the recovery time length in H j into the recovery fault prediction coordinate system; Perform regression analysis on the response fault prediction coordinate system and the recovery fault prediction coordinate system to obtain the response fault prediction function and the recovery fault prediction function, obtain the expected prediction time, substitute the expected prediction time into the response fault prediction function and the recovery fault prediction function, and solve to obtain the response prediction time length and the recovery prediction time length; If the response prediction time length is greater than or equal to the response standard or the recovery prediction time length is greater than or equal to the recovery standard, output the instrument fault signal.

[0015] The present application has the following advantages: the present application constructs a detection test space, randomly changes the environmental parameters in the detection test space every first test duration, records the test results, then analyzes the environmental influence duration of the gas detection instrument, time-corrects the test results based on the environmental influence duration, obtains experimental data, analyzes the influence relationship of temperature and humidity on detection accuracy based on the experimental data, obtains the temperature precision influence relationship and the humidity precision influence relationship, then divides the temperature precision influence relationship and the humidity precision influence relationship into reference relationship and calibration relationship, and then performs adaptive environmental compensation analysis on the gas detection instrument based on the reference relationship and the calibration relationship, forms an adaptive environmental compensation algorithm, the advantages are that the environmental temperature and the environmental humidity have certain influence on the detection accuracy of the gas concentration, if only a fixed compensation function is used for unified compensation, the error of the compensated gas concentration is still large, and the temperature and humidity are included in the reference range, and the reference relationship and the calibration relationship are divided based on the influence degree of temperature and humidity on the detection accuracy, the reference relationship is taken as the standard, and then the calibration relationship is used to calibrate the reference relationship, so that the gas concentration under various temperature and humidity conditions can be more accurately compensated, and the accuracy and rationality of the gas concentration detection compensation are improved; The present application tests the response curve of the gas detection instrument through the reaction cabin, extracts the response characteristics of the response curve, finally monitors the health status of the gas detection instrument based on the response characteristics, and predicts the fault of the gas detection instrument based on the time sequence change of the response characteristics, and the advantages are that the reaction cabin solves the problem that it is difficult to collect the response curve in the daily use process, and improves the accuracy and effectiveness of the fault prediction of the gas detection instrument. BRIEF DESCRIPTION OF DRAWINGS

[0016] Figure 1 The step flow chart of the method of the present application is shown in the figure; Figure 2 The temperature precision influence analysis diagram of the present application is shown in the figure; Figure 3 The humidity precision influence analysis diagram of the present application is shown in the figure; Figure 4 The reference point of the present application is shown in the figure; Figure 5 The response data of the present application is shown in the figure; Figure 6 The response fault prediction coordinate system of the present application is shown in the figure. DETAILED DESCRIPTION

[0017] With reference to the accompanying drawings, the technical solutions in the embodiments of the present application will be described clearly and completely. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all the other embodiments obtained by those ordinarily skilled in the art without creative effort belong to the scope of the present application.

[0018] Embodiment 1, please refer to Figure 1 As shown in the figure, the present application provides an adaptive environmental compensation and fault prediction algorithm for a gas detection instrument, including the following steps: Step S1, a detection test space is constructed, the environmental parameters in the detection test space are randomly changed every first test duration, and the test results are recorded; step S1 includes the following sub-steps: Step S101, a detection test space is constructed, the detection test space is a closed space in which the environmental parameters can be changed, and an air inlet and an air outlet are present therein, for maintaining the concentration of the test gas stable; Step S102, a test gas of a first test concentration is put into the detection test space, and the test gas is kept at the first test concentration at all times; Step S103, the environmental parameters in the detection test space are randomly changed every first test duration, the environmental parameters including the environmental temperature and the environmental humidity; Step S104, a gas detection instrument is installed in the detection test space, the concentration of the test gas is detected in real time by the gas detection instrument, named as the detection concentration, and the detection time is recorded, the detection time and the detection concentration being the test results; In a specific implementation, the detection test space only needs to ensure that the concentration of the test gas and the temperature and humidity inside can be controlled, the test gas should be selected as a safe gas without toxicity and harm, and the test gas is selected as oxygen in the embodiment. The first test concentration is only for analyzing the deviation of the gas concentration, and any value can be selected, which can be set by the tester. In the embodiment, the first test concentration is 20.9%, which is because the oxygen content in the air is also close to 20.9%. If the detection test space exchanges with the outside air by mistake, it will not have a greater impact on the test result. The setting of the first test duration should be combined with the environmental impact duration in the subsequent analysis process. Usually, when analyzing the environmental impact duration, the first test duration is set to more than 2h to ensure that the gas detection instrument can be fully affected by the environmental parameters, and then the first test duration can be set according to the test obtained environmental impact duration. This is to save time in subsequent testing. Since the environmental impact duration has not been tested, it is not listed here. During the analysis process of the environmental impact duration, it will be described in detail. The environmental parameters in the detection test space are randomly changed every first test duration to simulate the detection results of the gas detection instrument on the test gas under different temperature and humidity conditions. For example, at 2025.5.26 18:33:46, the environmental temperature is 12℃, the environmental humidity is 25%, the concentration of oxygen in the detection test space is detected as 20.7%, that is, the detection concentration is 20.7%, the detection time is 2025.5.26 18:33:46, and the corresponding environmental temperature is 12℃ and the environmental humidity is 25%. It should be noted that the environmental temperature and the environmental humidity correspond to the detection time, not the detection concentration.

[0019] Step S2, analyze the environmental impact duration of the gas detection instrument, and perform time sequence correction on the test result based on the environmental impact duration to obtain experimental data; step S2 includes the following sub-steps: Step S201, set the environmental parameters in the detection test space to the first test state, detect the gas concentration of the test gas after the first test duration, and name it as the correction auxiliary concentration. The first test duration is continuously recorded, the range of the correction auxiliary concentration in the first test duration is counted, and the correction concentration range is named; Step S202, change the environmental parameters in the detection test space, record the correction auxiliary concentration in real time and count the time, and when the correction auxiliary concentration exceeds the correction concentration range, stop counting and obtain the time duration, which is named as the environmental impact duration; Step S203, the detection time in the test result is advanced by the environment influence time length to obtain a calibration time, the environment temperature corresponding to the calibration time is named as a calibration temperature, and the environment humidity corresponding to the calibration time is named as a calibration humidity, the calibration temperature and the calibration humidity are associated with the detection concentration to constitute experimental data, and the experimental data include the detection concentration, the calibration time, the calibration temperature, and the calibration humidity; In a specific implementation, the first test state can be randomly set, because at this time, the test is performed on the time length required for the environmental parameters to affect the reading of the gas detection instrument, and the specific value of the environmental parameters does not need to be considered. In this embodiment, the first test state is set to an environmental temperature of 18°C and an environmental humidity of 30%, the temperature in the detection test space is set to 18°C, and the humidity is set to 30%. At this time, the first test time is temporarily set to 2h, because the 2h time is relatively long, and the gas detection instrument will definitely be fully affected by the environmental parameters. After 2h, the oxygen concentration in the detection test space is detected again to obtain the calibration auxiliary concentration. At this time, the calibration auxiliary concentration has been fully affected by the environmental parameters, resulting in a deviation in the reading. However, since the environmental parameters are unchanged, the calibration auxiliary concentration will be in a stable range, that is, the calibration concentration range. For example, after 2h, it is detected that the oxygen concentration in the detection test space is always in the range of [20.78%, 20.91%] during the third hour and the fourth hour. At this time, the calibration concentration range is [20.78%, 20.91%]. Then, the environmental parameters are changed, and at this time, the environmental parameters are changed to an environmental temperature of 34°C and an environmental humidity of 40%. The calibration auxiliary concentration is still in the calibration concentration range for a short time, because at this time, the gas detection instrument has not been fully affected by the changed environmental parameters. However, at the 16th second after the environmental parameters are changed, it is found that the calibration auxiliary concentration is 20.95%, which is not in the calibration concentration range, indicating that the gas detection instrument has been affected by the changed environmental parameters. Therefore, the environmental influence time is 16s, indicating that the environmental parameters can affect the reading of the gas detection instrument after 16s. The detection time in the test result is advanced by the environmental influence time. For example, in step S1, the detection concentration is 20.7%, the detection time is 2025.5.26 18:33:46, the corresponding environmental temperature is 12°C, and the environmental humidity is 25%. The detection time is advanced by 16s to obtain the calibration time of 2025.5.26 18:33:30, indicating that the gas concentration detected at 2025.5.26 18:33:46 is actually affected by the environmental parameters at 2025.5.26 18:33:30, rather than the real-time environmental parameters. Therefore, the environmental temperature and the environmental humidity at 2025.5.26 18:33:30 are obtained as the calibration temperature and the calibration humidity, and finally the calibration time is 2025.5.26 18:33:30, the detection concentration is 20.7%, the calibration temperature is 15°C, and the calibration humidity is 30%. This is one piece of experimental data. The test results are calibrated to obtain different experimental data.

[0020] In step S3, the influence relationship of temperature and humidity on the detection accuracy is analyzed based on the experimental data, and the self-adaptive environmental compensation analysis of the gas detection instrument is performed to form a self-adaptive environmental compensation algorithm. Step S3 includes the following substeps: Step S301, based on the experimental data analysis temperature and humidity on the influence of detection accuracy, get temperature precision influence relationship and humidity precision influence relationship; Step S301 includes the following sub-steps: Step S3011, the detection concentration is marked as P1, the first test concentration is marked as P2, (P1-P2) / P2 is calculated, and the detection deviation is obtained; Please refer to Figures 2-3 As shown in step S3012, a two-dimensional coordinate system is established with the correction temperature and the correction humidity as the X axis and the detection deviation as the Y axis, respectively named as temperature precision influence analysis diagram and humidity precision influence analysis diagram, and the detection deviation is recorded in the temperature precision influence analysis diagram and the humidity precision influence analysis diagram according to the correction temperature and the correction humidity, respectively. The coordinate points in the temperature precision influence analysis diagram and the humidity precision influence analysis diagram are respectively named as temperature precision influence analysis points and humidity precision influence analysis points; Step S3013, regression analysis is performed on the temperature precision influence analysis diagram and the humidity precision influence analysis diagram, and the temperature precision influence curve and the humidity precision influence curve are obtained; Step S3014, the temperature precision influence curve and its temperature precision influence analysis points are the temperature precision influence relationship, and the humidity precision influence curve and its humidity precision influence analysis points are the humidity precision influence relationship; In the specific implementation, for example, in the experimental data listed in step S2, the detection concentration is 20.7%, and the first test concentration is 20.9%. The detection deviation is calculated to be-0.0096, and the calculation result is kept to four decimal places. The gas concentration detected by the gas detection instrument is lower than the actual concentration by-0.0096, that is, when the environmental temperature is 15°C and the environmental humidity is 30%, the gas concentration detected by the gas detection instrument is lower than the actual concentration by-0.0096. The temperature precision influence analysis diagram is constructed as shown in Figure 2 As shown in the humidity precision influence analysis diagram Figure 3 As shown in Figure 2 And Figure 3 The curves in the temperature precision influence curve and the humidity precision influence curve are obtained, and thus the temperature precision influence relationship and the humidity precision influence relationship are obtained.

[0021] Step S302, dividing the temperature precision influence relationship and the humidity precision influence relationship into reference relationship and calibration relationship; Step S302 includes the following sub-steps: Step S3021, obtaining the standard deviation of the temperature precision influence curve and the humidity precision influence curve, respectively named as temperature standard deviation and humidity standard deviation; Step S3022, if the temperature standard deviation is less than or equal to the humidity standard deviation, the temperature precision influence analysis graph is named as the reference analysis graph, and the humidity precision influence analysis graph is named as the calibration analysis graph; if the temperature standard deviation is greater than the humidity standard deviation, the humidity precision influence analysis graph is named as the reference analysis graph, and the temperature precision influence analysis graph is named as the calibration analysis graph. Step S3023, the temperature precision influence analysis point or the humidity precision influence analysis point corresponding to the reference analysis graph is named as the reference analysis point, the temperature precision influence analysis point or the humidity precision influence analysis point corresponding to the calibration analysis graph is named as the calibration analysis point, the temperature precision influence curve or the humidity precision influence curve corresponding to the reference analysis graph is named as the reference influence curve, and the temperature precision influence curve or the humidity precision influence curve corresponding to the calibration analysis graph is named as the calibration influence curve. Step S3024, the reference analysis graph, the reference analysis point and the reference influence curve are the reference relationship, and the calibration analysis graph, the calibration analysis point and the calibration influence curve are the calibration relationship. In a specific implementation, the reference relationship and the calibration relationship are obtained by the following steps. Figure 2 and Figure 3 It is known that the fitting effect of the humidity precision influence curve is much higher than that of the temperature precision influence curve, that is, the temperature standard deviation is less than the humidity standard deviation, which means that the environmental humidity has a greater impact on the reading of the gas detection instrument, and therefore the environmental humidity is used as the reference for analysis, and the environmental temperature is used as the auxiliary, so that the reference analysis graph is the humidity precision influence analysis graph, the calibration analysis graph is the temperature precision influence analysis graph, the reference analysis point is the humidity precision influence analysis point, the calibration analysis point is the temperature precision influence analysis point, the reference influence curve is the humidity precision influence curve, and the calibration influence curve is the temperature precision influence curve.

[0022] Step S303, adaptive environmental compensation analysis is performed on the gas detection instrument based on the reference relationship and the calibration relationship to form an adaptive environmental compensation algorithm. Step S303 includes the following sub-steps. Step S3031, the gas concentration detected by the gas detection instrument in real time is obtained and named as the real-time concentration, and the environmental temperature and the environmental humidity at the previous environmental influence time length of the current time are obtained and named as the effective temperature and the effective humidity respectively. Step S3032, if the reference analysis graph is the temperature precision influence analysis graph, the effective temperature is named as the reference parameter, and the effective humidity is named as the calibration parameter; if the reference analysis graph is the humidity precision influence analysis graph, the effective humidity is named as the reference parameter, and the effective temperature is named as the calibration parameter. Please refer to Figure 4As shown, in step S3033, a reference analysis point in the reference analysis graph where the X-axis is equal to the reference parameter is obtained, named as a reference reference point, a value of the reference reference point on the Y-axis is named as a reference reference difference value, and a corresponding correction humidity or correction temperature of the reference reference point is obtained, named as a correction reference parameter; In step S3034, the correction reference parameter is numbered, and is represented by a symbol CH i , where i is a non-zero natural number and i is a serial number of CH i , and CH i is substituted into the correction analysis curve to obtain a value of the Y-axis of a coordinate point on the correction analysis curve where the X-axis is equal to CH i , which is represented by a symbol CR i , and a corresponding reference reference difference value of CH i is marked as CD ; In step S3035, a value of the Y-axis of a coordinate point on the correction analysis curve where the X-axis is equal to the correction parameter is obtained, named as a correction anchor difference value, and is represented by a symbol CM. In a specific implementation, it is assumed that the gas detection instrument in this embodiment detects that the real-time concentration of oxygen in the room is 19.8% at 2025.7.18 12:26:44, the environmental temperature and the environmental humidity 16s before 2025.7.18 12:26:44 are obtained, that is, the environmental temperature and the environmental humidity at 2025.7.18 12:26:28 are obtained as the effective temperature and the effective humidity, the effective temperature is 10℃, the effective humidity is 50%, the reference parameter is 50% at this time, the correction parameter is 10℃, a reference analysis point in the reference analysis graph where the X-axis is equal to 50% is obtained as a reference reference point, and the reference reference point is as shown in Figure 4 , where the reference reference point includes (50, 0.02) and (50, 0.039), 0.02 and 0.039 are the reference reference difference values, and the reference reference point (50, 0.02) is taken as an example, the point is obtained by recording the experimental data that the detection concentration is 20.482%, the correction temperature is 35℃, and the correction humidity is 50%, and the detection deviation corresponding to the detection concentration 20.482% is 0.02, so the correction reference parameter of the reference reference point is 35℃, and the correction reference parameter of (50, 0.039) is 15℃ by analogy, CH1 and CH2 are obtained by numbering, that is, CH1 is 35℃, and CH2 is 15℃, the value of the Y-axis of a coordinate point in the correction analysis curve where the X-axis is equal to 35℃ is obtained, and CR1 is 0.048, the value of the Y-axis of a coordinate point in the correction analysis curve where the X-axis is equal to 15℃ is obtained, and CR2 is -0.019, CD1 of CH1 is 0.02, CD2 of CH2 is 0.039, the correction parameter is 10℃, and the coordinate point on the correction analysis curve where the X-axis is equal to 10℃ is obtained as (10, -0.045), that is, the correction anchor difference value CM is -0.045.

[0023] Step S3036, assuming that the corresponding reference analysis point in the effective temperature and effective humidity environment is the first assumption point, marking the value of the first assumption point on the Y axis as F, there is a relationship Solving F by the formula F is the prediction deviation, increasing the real-time concentration by the prediction deviation can complete the adaptive environmental compensation of the real-time concentration, and finally obtain the actual concentration; In a specific implementation, assuming that the detection deviation of the gas detection instrument is F under the condition that the environmental temperature is 10 DEG C and the environmental humidity is 50%, the first assumption point is obtained by substituting it into the reference analysis graph, at this time the X axis of the first assumption point is 50, but the Y axis F is unknown, at this time the detection deviation is mainly affected by the environmental humidity, but it is also weakly affected by the environmental temperature, so the actual detection deviation is distributed on both sides of the reference analysis curve, not in the reference analysis curve, and the general change trend of the detection deviation obtained from the calibration analysis graph changes with the environmental temperature, taking the reference point (50, 0.02) as an example, CR1 and CD1 are 0.048 and 0.02 respectively, and CM is-0.045, CR1 represents the general distribution of the detection deviation when the environmental temperature is 15 DEG C, and CM represents the general distribution of the detection deviation when the environmental temperature is 10 DEG C, since the deviation of each reference point from the reference influence curve is affected by the environmental temperature, the up and down position distribution of the first assumption point relative to each reference point in the reference analysis graph should be similar to the proportion of CM and CR i , that is, there is a relationship , and the conversion obtains Although the relationship is approximately equal to, but the position relationship between the first assumption point and multiple reference points can be used to obtain more accurate results, wherein CR1 is 0.048, CD1 is 0.02, CM is-0.045, CR2 is-0.019, CD2 is 0.039, max() is the maximum value operator, and finally F is solved to be 0.0054, and the real-time concentration is 19.8%, and increasing the proportion of 0.0054 is 19.8% x (1+0.0054)=19.90692%, and rounding the percentage to one decimal place is 19.9%.

[0024] Step S4, setting a reaction chamber, testing the response curve of the gas detection instrument through the reaction chamber, and extracting the response characteristics of the response curve; step S4 includes the following substeps: Step S401, installing a reaction chamber in the gas detection instrument, the reaction chamber including a reaction box and a liquid storage box, putting baking soda powder in the reaction box, and injecting edible citric acid in the liquid storage box, the reaction box and the liquid storage box being connected through a pipeline and an intelligent control valve; Step S402, every interval first period, open the intelligent control valve, inject the test volume of citric acid into the reaction box, at this time the baking soda powder and the citric acid have a chemical reaction to produce carbon dioxide; In specific implementation, the baking soda powder and the citric acid are both safe, and the small amount of carbon dioxide produced by the chemical reaction will not affect the environment or the human body, but can make the carbon dioxide concentration in a small range near the gas detection instrument quickly rise and then fall, so as to test the response curve of the gas detection instrument. At the same time, the baking soda powder and the citric acid can be replaced after being completely consumed. The first period is set by the test personnel. Since the change of the response curve of the gas detection instrument needs to be observed for a long time, the observation period is relatively long, so the first period can be lengthened, for example, once a day or once every two days. In this embodiment, no specific requirement is made. In this embodiment, the first period is taken as an example and is equal to one day.

[0025] Step S403, test the response curve of the gas detection instrument based on the reaction chamber and extract the response characteristics of the response curve; Step S403 includes the following sub-steps: Please refer to Figure 5 As shown in the figure, step S4031, before the reaction occurs, record the carbon dioxide concentration, named as normal concentration. After the reaction occurs, record the change of the carbon dioxide concentration with time in real time. When the carbon dioxide concentration returns to the normal concentration, stop recording to obtain the response data. The response data is a two-dimensional coordinate system with X axis as time and Y axis as carbon dioxide concentration. The curve formed by the change of the carbon dioxide concentration with time is recorded in the two-dimensional coordinate system, which is the response curve. Step S4032, obtain the highest point of the response curve, named as response point, and obtain the time length that the carbon dioxide concentration takes from the normal concentration to the response point, named as response time length; Step S4033, obtain the time length that the carbon dioxide concentration takes from the response point to the normal concentration, named as recovery time length. The response time length and the recovery time length are the response characteristics. In specific implementation, before the reaction occurs, the normal concentration of 0.04% is recorded, which represents that the carbon dioxide concentration in the air under normal conditions is usually 0.04%. After the reaction occurs, the change of the carbon dioxide concentration with time is recorded in real time. When the carbon dioxide concentration returns to the normal concentration, stop recording to obtain the response data as shown in the figure. Figure 5 The curve in the figure is the response curve. The highest point on the response curve is the response point. The response time length is 8s, and the recovery time length is 16s. The response time length represents the response speed of the gas detection instrument to the change of the gas concentration, and the recovery time length represents the response speed of the gas detection instrument to return to the normal level after the gas concentration recovers.

[0026] Step S5 involves monitoring the health status of the gas detector based on its response characteristics and predicting faults in the gas detector based on the temporal changes in these response characteristics. Step S5 includes the following sub-steps: Step S501: Obtain the health criteria for the response characteristics, including response criteria and recovery criteria; Step S502: Record the response features obtained from each test, number the response features in chronological order, and use the symbol H. j This indicates that j is a non-zero natural number and j is the index of H; Please see Figure 6 As shown, in step S503, with j as the horizontal axis, H j Establish a two-dimensional coordinate system for the vertical axis, named the fault prediction coordinate system. The fault prediction coordinate system includes the response fault prediction coordinate system and the recovery fault prediction coordinate system. H j The response time in the input is entered into the response fault prediction coordinate system according to j, and H is set to... j The recovery time is entered into the recovery fault prediction coordinate system according to j; Step S504: Perform regression analysis on the response fault prediction coordinate system and the recovery fault prediction coordinate system to obtain the response fault prediction function and the recovery fault prediction function, obtain the expected prediction time, substitute the expected prediction time into the response fault prediction function and the recovery fault prediction function, and solve to obtain the response prediction duration and the recovery prediction duration. Step S505: If the response prediction time is greater than or equal to the response standard or the recovery prediction time is greater than or equal to the recovery standard, then output an instrument fault signal. In practice, the response standard is within 15 seconds, and the recovery standard is within 20 seconds, i.e., [0, 15 seconds] and [0, 20 seconds]. By comparison, if the response time and recovery time are both within the response standard, it means that the gas detection instrument is currently functioning normally. The response characteristics are then numbered according to the chronological order, for example, if response characteristics for a total of 100 days are monitored, they are numbered from H1 to H2. 100 Construct a response fault prediction coordinate system and restore the fault prediction coordinate system and H j The response time is entered into the response fault prediction coordinate system according to j, and H is also entered into the system. j The recovery time is entered into the recovery fault prediction coordinate system according to j. Taking the response fault prediction coordinate system as an example, the response fault prediction coordinate system is constructed as follows: Figure 6 As shown, j is actually the number of days. Figure 6 The curve in the figure is the curve corresponding to the response fault prediction function. The curve shows that the response time exceeds 15 seconds on the 176th day, which means that the response time of the gas detection instrument will be unqualified on the 176th day and maintenance is required.

[0027] Embodiment 2, the application provides an electronic device, which can comprise a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory complete mutual communication through the communication bus. The memory stores computer readable instructions, and the processor can call the instructions in the memory, and when the computer readable instructions are executed by the processor, steps in an adaptive environment compensation and fault prediction algorithm for a gas detection instrument are run to realize the following functions: a detection test space is constructed, and test results are recorded; a duration of environmental influence of the gas detection instrument is analyzed, and the test results are time-sequenced corrected to obtain experimental data; adaptive environment compensation analysis is performed on the gas detection instrument to form an adaptive environment compensation algorithm; a reaction chamber is set, and response characteristics of a response curve are extracted; and the gas detection instrument is fault predicted based on time-sequential changes of the response characteristics.

[0028] In addition, the logical instructions in the memory described above can be implemented in the form of a software function unit and sold or used as an independent product, and can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the application essentially or the part that contributes to the prior art or part of the technical solutions can be embodied in the form of a software product, and the computer software product is stored in a storage medium, includes a plurality of instructions to make a computer device (which can be a personal computer, a server, or a network device, etc.) execute all or part of the steps of the method described in various embodiments of the application. The foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk or an optical disk, and various media that can store program codes.

[0029] Embodiment 3, the application further provides a computer program product, which comprises a computer program stored on a computer readable storage medium, and the computer program comprises program instructions, and when the program instructions are executed by a computer, the computer can execute an adaptive environment compensation and fault prediction algorithm for a gas detection instrument provided by the above-mentioned method, and the method comprises the following steps: constructing a detection test space, recording test results; analyzing a duration of environmental influence of the gas detection instrument and time-sequentially correcting the test results to obtain experimental data; performing adaptive environment compensation analysis on the gas detection instrument to form an adaptive environment compensation algorithm; setting a reaction chamber, and extracting response characteristics of a response curve; and fault predicting the gas detection instrument based on time-sequential changes of the response characteristics.

[0030] Embodiment 4, the application also provides a computer readable storage medium, and the application provides a storage medium, which stores a computer program, and the computer program is executed by a processor to run the steps in the adaptive environmental compensation and fault prediction algorithm for the gas detection instrument to achieve the following functions: constructing a detection test space, recording test results; analyzing the environmental influence duration of the gas detection instrument and time correcting the test results to obtain experimental data; performing adaptive environmental compensation analysis on the gas detection instrument to form an adaptive environmental compensation algorithm; setting a reaction chamber and extracting response characteristics of a response curve; and performing fault prediction on the gas detection instrument based on the time sequence changes of the response characteristics.

[0031] Through the above description of the embodiments, the embodiments of the application can be provided as a method, a system or a computer program product. Based on such understanding, the above technical solutions can be embodied in the form of a software product, which can be stored in a computer readable storage medium, such as a ROM / RAM, a magnetic disk, an optical disk, etc., and includes a plurality of instructions to make a computer device (which can be a personal computer, a server, or a network device, etc.) execute the methods described in various embodiments or some parts of the embodiments.

[0032] In the embodiments provided by the present application, it should be understood that the disclosed system or method can be implemented in other ways. The embodiments described above are only illustrative. For example, the division of the modules or units is only a logical function division, and there can be another division manner in actual implementation. For example, a plurality of modules or units can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the shown or discussed modules can be indirect coupling or communication connection through some communication interfaces. The coupling or communication connection can be electrical, mechanical or in other forms.

[0033] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, rather than limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: it can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement for some technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. An adaptive environmental compensation and failure prediction algorithm for a gas detection instrument, characterized in that, The method comprises the following steps: A detection test space is constructed, and the environmental parameters in the detection test space are randomly changed every first test duration, and the test results are recorded; The environmental influence duration of the gas detection instrument is analyzed, and the test results are time-sequenced corrected based on the environmental influence duration to obtain experimental data; The influence relationship of temperature and humidity on detection accuracy is analyzed based on the experimental data, and adaptive environmental compensation analysis is performed on the gas detection instrument to form an adaptive environmental compensation algorithm; A reaction chamber is set, the response curve of the gas detection instrument is tested through the reaction chamber, and the response characteristics of the response curve are extracted; The health status of the gas detection instrument is monitored based on the response characteristics, and the gas detection instrument is fault predicted based on the time sequence change of the response characteristics.

2. The adaptive environmental compensation and failure prediction algorithm for a gas detection instrument of claim 1, wherein, A detection test space is constructed, and the environmental parameters in the detection test space are randomly changed every first test duration, and the test results are recorded, including the following sub-steps: A detection test space is constructed, which is a closed space capable of changing environmental parameters, and an air inlet and an air outlet are provided in the detection test space for maintaining the concentration of the test gas stable; A test gas of a first test concentration is put into the detection test space, and the test gas is kept at the first test concentration at all times; The environmental parameters in the detection test space are randomly changed every first test duration, including the environmental temperature and the environmental humidity; A gas detection instrument is installed in the detection test space, the concentration of the test gas is detected in real time by the gas detection instrument, and the detected concentration is named as the detection concentration, and the detection time is recorded, which is the test result.

3. The adaptive environmental compensation and failure prediction algorithm for a gas detection instrument of claim 2, wherein, The environmental influence duration of the gas detection instrument is analyzed, and the test results are time-sequenced corrected based on the environmental influence duration to obtain experimental data, including the following sub-steps: The environmental parameters in the detection test space are set to a first test state, and the gas concentration of the test gas is detected after the first test duration, which is named as the correction auxiliary concentration, and the first test duration is continuously recorded, and the range of the correction auxiliary concentration in the first test duration is counted, which is named as the correction concentration range; The environmental parameters in the detection test space are changed, and the correction auxiliary concentration is recorded in real time and timed, and when the correction auxiliary concentration exceeds the correction concentration range, the timing is stopped and the duration obtained by timing is obtained, which is named as the environmental influence duration; The detection time in the test result is advanced by the environmental influence duration to obtain the correction time, and the environmental temperature and the environmental humidity corresponding to the correction time are named as the correction temperature and the correction humidity respectively, and the correction temperature and the correction humidity are associated with the detection concentration to form experimental data, which includes the detection concentration, the correction time, the correction temperature and the correction humidity.

4. The adaptive environmental compensation and failure prediction algorithm for a gas detection instrument of claim 3, wherein, The influence relationship of temperature and humidity on detection accuracy is analyzed based on the experimental data, and adaptive environmental compensation analysis is performed on the gas detection instrument to form an adaptive environmental compensation algorithm, including the following sub-steps: The influence relationship of temperature and humidity on detection accuracy is analyzed based on the experimental data, and the temperature precision influence relationship and the humidity precision influence relationship are obtained; The temperature precision influence relationship and the humidity precision influence relationship are divided into a reference relationship and a calibration relationship; The adaptive environmental compensation algorithm is formed by performing adaptive environmental compensation analysis on the gas detection instrument based on the benchmark relationship and the calibration relationship.

5. The adaptive environmental compensation and failure prediction algorithm for a gas detection instrument of claim 4, wherein, The temperature precision influence relationship and the humidity precision influence relationship are obtained by analyzing the influence of temperature and humidity on detection precision based on experimental data, including the following sub-steps: Mark the detection concentration as P1, mark the first test concentration as P2, calculate (P1-P2) / P2 to obtain the detection deviation; A two-dimensional coordinate system is established with the calibration temperature and the calibration humidity as the X-axis and the detection deviation as the Y-axis, respectively named as the temperature precision influence analysis graph and the humidity precision influence analysis graph, and the detection deviation is recorded in the temperature precision influence analysis graph and the humidity precision influence analysis graph according to the calibration temperature and the calibration humidity, respectively, and the coordinate points in the temperature precision influence analysis graph and the humidity precision influence analysis graph are named as the temperature precision influence analysis point and the humidity precision influence analysis point, respectively; Regression analysis is performed on the temperature precision influence analysis graph and the humidity precision influence analysis graph to obtain the temperature precision influence curve and the humidity precision influence curve; The temperature precision influence curve and the temperature precision influence analysis point thereof are the temperature precision influence relationship, and the humidity precision influence curve and the humidity precision influence analysis point thereof are the humidity precision influence relationship.

6. The adaptive environmental compensation and failure prediction algorithm for a gas detection instrument of claim 5, wherein, The temperature precision influence relationship and the humidity precision influence relationship are divided into benchmark relationship and calibration relationship, including the following sub-steps: The standard deviations of the temperature precision influence curve and the humidity precision influence curve are obtained and named as the temperature standard deviation and the humidity standard deviation, respectively; If the temperature standard deviation is less than or equal to the humidity standard deviation, the temperature precision influence analysis graph is named as the benchmark analysis graph, and the humidity precision influence analysis graph is named as the calibration analysis graph; if the temperature standard deviation is greater than the humidity standard deviation, the humidity precision influence analysis graph is named as the benchmark analysis graph, and the temperature precision influence analysis graph is named as the calibration analysis graph; The temperature precision influence analysis point or the humidity precision influence analysis point corresponding to the benchmark analysis graph is named as the benchmark analysis point, the temperature precision influence analysis point or the humidity precision influence analysis point corresponding to the calibration analysis graph is named as the calibration analysis point, the temperature precision influence curve or the humidity precision influence curve corresponding to the benchmark analysis graph is named as the benchmark influence curve, and the temperature precision influence curve or the humidity precision influence curve corresponding to the calibration analysis graph is named as the calibration influence curve; The benchmark analysis graph, the benchmark analysis point, and the benchmark influence curve are the benchmark relationship, and the calibration analysis graph, the calibration analysis point, and the calibration influence curve are the calibration relationship.

7. The adaptive environmental compensation and failure prediction algorithm for a gas detection instrument of claim 6, wherein, The adaptive environmental compensation algorithm is formed by performing adaptive environmental compensation analysis on the gas detection instrument based on the benchmark relationship and the calibration relationship, including the following sub-steps: The gas concentration detected by the gas detection instrument in real time is obtained and named as the real-time concentration, and the environmental temperature and the environmental humidity at the previous environmental influence time length of the current time are obtained and named as the effective temperature and the effective humidity, respectively; If the reference analysis graph is a temperature precision influence analysis graph, the effective temperature is named as the reference parameter, and the effective humidity is named as the calibration parameter; if the reference analysis graph is a humidity precision influence analysis graph, the effective humidity is named as the reference parameter, and the effective temperature is named as the calibration parameter; A reference analysis point in the reference analysis graph is obtained, wherein the X axis is equal to the reference parameter, and the reference analysis point is named as a reference reference point; a value of the reference reference point on the Y axis is named as a reference reference difference value; a corresponding calibration humidity or calibration temperature of the reference reference point is named as a calibration reference parameter; The calibration reference parameter is numbered by a symbol CH i , wherein i is a non-zero natural number and i is the serial number of CH i , CH i is substituted into the calibration analysis curve to obtain the value of the Y axis of the coordinate point on the calibration analysis curve whose X axis is equal to CH i , which is named as a calibration reference difference value and is represented by a symbol CR i , and the corresponding reference reference difference value is marked as CD i ; A value of a coordinate point on the Y axis of the calibration analysis curve is obtained, wherein the X axis is equal to the calibration parameter, and the value is named as a calibration anchor difference value, and the calibration anchor difference value is represented by a symbol CM; Assuming that the corresponding reference analysis point in the effective temperature and effective humidity environment is the first assumption point, the value of the first assumption point on the Y axis is marked as F, and there is a relationship Solve F by formula The F is the prediction deviation, and increasing the proportion of the prediction deviation can complete the adaptive environment compensation of the real-time concentration, and finally the actual concentration is obtained.

8. The adaptive environmental compensation and failure prediction algorithm for a gas detection instrument of claim 7, wherein, A reaction chamber is set, a response curve of the gas detection instrument is tested by the reaction chamber, and response characteristics of the response curve are extracted, including the following sub-steps: The reaction chamber is installed in the gas detection instrument, the reaction chamber includes a reaction box and a liquid storage box, baking soda powder is placed in the reaction box, and edible citric acid is injected into the liquid storage box, and the reaction box and the liquid storage box are connected by a pipeline and an intelligent control valve; Every first period, the intelligent control valve is opened, and a test volume of edible citric acid is injected into the reaction box, at which time the baking soda powder reacts with the edible citric acid to generate carbon dioxide; The response curve of the gas detection instrument is tested based on the reaction chamber, and the response characteristics of the response curve are extracted.

9. The adaptive environmental compensation and prognostics algorithm for a gas detection instrument of claim 8, wherein, The response curve of the gas detection instrument is tested based on the reaction chamber, and the response characteristics of the response curve are extracted, including the following sub-steps: Before the reaction occurs, the carbon dioxide concentration is recorded and named as a normal concentration, after the reaction occurs, the carbon dioxide concentration is recorded in real time over time, and when the carbon dioxide concentration returns to the normal concentration, the recording is stopped, to obtain response data, the response data is specifically a two-dimensional coordinate system with X axis as time and Y axis as carbon dioxide concentration, wherein a curve formed by the change of the carbon dioxide concentration over time is recorded, that is, the response curve; A highest point of the response curve is obtained and named as a response point, and a time length during which the carbon dioxide concentration changes from the normal concentration to the response point is obtained and named as a response time length; A time length during which the carbon dioxide concentration changes from the response point to the normal concentration is obtained and named as a recovery time length, and the response time length and the recovery time length are the response characteristics.

10. The adaptive environmental compensation and failure prediction algorithm for a gas detection instrument of claim 9, wherein, Based on the response characteristics, the health status of the gas detection instrument is monitored, and based on the time sequence change of the response characteristics, the gas detection instrument is predicted for failure, including the following sub-steps: A health standard of the response characteristics is obtained, and the health standard includes a response standard and a recovery standard; The response characteristics obtained in each test are recorded, the response characteristics are numbered in the order of time, and the response characteristics are represented by symbols H j , where j is a non-zero natural number and j is the serial number of H. A two-dimensional coordinate system is established with j as the horizontal axis and H j as the vertical axis, and is named as a failure prediction coordinate system, which includes a response failure prediction coordinate system and a recovery failure prediction coordinate system, and the response duration in H j is recorded in the response failure prediction coordinate system according to j, and the recovery duration in H j is recorded in the recovery failure prediction coordinate system according to j. Regression analysis is performed on a response fault prediction coordinate system and a recovery fault prediction coordinate system, to obtain a response fault prediction function and a recovery fault prediction function, an expected prediction time is obtained, the expected prediction time is substituted into the response fault prediction function and the recovery fault prediction function, and a response prediction time length and a recovery prediction time length are obtained by solving; If the response prediction time length is greater than or equal to the response standard or the recovery prediction time length is greater than or equal to the recovery standard, an instrument failure signal is output.

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