Gas data integrated management system and method based on NDIR

Abstract

The invention discloses a gas data integrated management system and method based on NDIR, and relates to the technical field of gas sensors, in the aspect of data processing, by collecting temperature, humidity and pressure sensor data and combining historical data to determine a sampling interval, gas measurement data can be accurately calibrated, and interference of environmental factors on measurement precision is overcome; in the aspect of change analysis, first and second rate change intervals are obtained, the normal change range of environmental parameters can be clearly defined, and abnormal fluctuation can be conveniently perceived in time; in the aspect of an early warning mechanism, the change rate in the second sampling time is compared with two intervals, graded early warning is achieved, for example, primary early warning shows that large abnormity exists, secondary early warning shows that potential risks exist, early warning prompts are triggered when data of the two intervals are included at the same time, and environment abnormity of different degrees can be effectively dealt with; in addition, after an early warning prompt is triggered, a correlation coefficient is calculated and compared with a threshold value, and the credibility of measurement data can be evaluated.

Description

Technical Field

[0001] The present invention relates to the technical field of gas sensors, and in particular to a gas data integrated management system and method based on NDIR. Background Art

[0002] At present, NDIR gas sensors are widely used in many fields such as industrial production monitoring, environmental air quality testing, indoor air quality assessment, and biomedical analysis due to their unique advantages, and they undertake the important task of accurately detecting the concentrations of various gases.

[0003] However, in actual use, it is found that NDIR sensors do not always maintain stable and accurate detection performance when detecting gas concentration. They are easily affected by environmental factors such as temperature, humidity and pressure, resulting in inaccurate measured gas data.

[0004] Currently, a temperature sensor, humidity sensor and pressure sensor are usually added inside the NDIR gas sensor to implement temperature, humidity and pressure compensation to calibrate the gas measurement data. However, this method has extremely high requirements on the sensitivity of the sensor and cannot determine the credibility of the sensor measurement data. Summary of the invention

[0005] The object of the present invention is to provide a gas data integrated management system and method based on NDIR to solve the problems raised in the prior art.

[0006] To achieve the above object, the present invention provides the following technical solution: a gas data integrated management method based on NDIR, the method comprising:

[0007] Step S100: collecting and storing the temperature value, humidity value and pressure value measured by the temperature sensor, humidity sensor and pressure sensor inside the NDIR gas sensor according to the sampling interval;

[0008] Step S200: continuously collecting the temperature value, humidity value and pressure value measured by the temperature sensor, humidity sensor and pressure sensor within a first sampling time, and processing the collected data respectively to obtain a first rate change interval;

[0009] Step S300: Analyze the data collected in step S100 according to the first rate change interval to obtain a second rate change interval;

[0010] Step S400: continuously acquiring the temperature value, humidity value and pressure value of the environment in which the gas to be measured is located within the second sampling time, and analyzing the change rate of the temperature value, humidity value and pressure value;

[0011] Step S500: comparing the change rate with the first rate change interval and the second rate change interval, and determining a warning level according to the comparison result;

[0012] Step S600: Obtain the warning result. If the warning prompt is triggered, the correlation coefficient of the temperature, humidity and pressure of the gas to be tested is calculated, and the correlation coefficient is compared with the correlation coefficient threshold to determine whether to trigger the sound and light warning.

[0013] Furthermore, step S100 includes:

[0014] Step S101: collecting historical measurement values ​​of gas concentration measured by the NDIR gas sensor in historical data;

[0015] Step S102: sort the historical measurement values ​​in ascending order and divide them into data sets P i , where i=1, 2, 3 or 4, respectively calculate the median Q1 of the data set P1 and the median Q3 of the data set P3, the interval Δd between the historical measurement values ​​is Q3-Q1, and the historical measurement values ​​that are less than Q1-1.5*Δd or greater than Q3+1.5*Δd in the historical measurement values ​​are regarded as abnormal values;

[0016] Step S103: Count the abnormal values, arrange the measurement time of the abnormal values ​​in chronological order, and calculate the average time interval of the abnormal values. The calculation formula of the average time interval is:

[0017]

[0018] Among them, t i+1 ,t i Respectively represent the measurement time corresponding to the i+1th and ith outliers in the outlier sequence; ω i represents the weight corresponding to the measurement time interval between the ith outlier value and the i+1th measurement value; m represents the number of outliers; Δt represents the average time interval between outliers;

[0019] Step S104: Calculate the sampling interval for sampling the temperature sensor, humidity sensor and pressure sensor. The sampling interval calculation formula is as follows:

[0020]

[0021] Wherein, T represents the sampling interval for sampling the temperature value, humidity value and pressure value measured by the temperature sensor, humidity sensor and pressure sensor; N j represents the number of normal values ​​between the jth outlier and the j+1th outlier;

[0022] Step S105: collecting the temperature value, humidity value and pressure value monitored in real time by the temperature sensor, humidity sensor and pressure sensor inside the NDIR gas sensor according to the sampling interval;

[0023] Step S106: Create a data storage structure way i , where i=1, 2 or 3; the real-time collected temperature values, humidity values ​​and pressure values ​​are stored in the data storage structures way1, way2 and way3 respectively in chronological order;

[0024] The historical data collected in the above steps covers the measurement results of the sensor on the gas concentration at different times and environmental conditions in the past; in the above step S102, the value of i is 1, 2, 3 or 4, which uses the interquartile range method in the statistical method to identify outliers; in step S106, the data structure way is established i , the value of i is 1, 2 or 3, which is set according to the collected parameters. The parameters collected by the present invention mainly include temperature value, humidity value and pressure value.

[0025] Further, step S200 includes:

[0026] Step S201: Calculate the first sampling time T1=k1T according to the sampling interval; wherein k1 is a safety factor; T1 represents the first sampling time;

[0027] Step S202: continuously collecting the temperature value, humidity value and pressure value within a first sampling time;

[0028] Step S203: The collected temperature value, humidity value and pressure value are expressed as {(X, Y, Z), t} i The data are recorded in the form of, where X represents the collected temperature value; Y represents the collected humidity value; Z represents the collected pressure value; t is the timestamp; i represents the number of the collected data;

[0029] Step S204: sorting the collected data according to the time series, and calculating the temperature change rate, humidity change rate and pressure change rate respectively;

[0030] The temperature change rate The humidity change rate The pressure change rate

[0031] Among them, V X 、V Y 、V Z Respectively represent the temperature change rate, humidity change rate, and pressure change rate; X i+1 , X i Respectively represent the temperature values ​​contained in the i+1th group and the ith group of sampling data; Yi+1 , Y i Respectively represent the humidity values ​​contained in the i+1th group and the ith group of sampling data; Z i+1 , Z i Respectively represent the pressure values ​​contained in the i+1th group and the ith group of sampling data; t i+1 ,t i They represent the time corresponding to the data collection of the i+1th group and the ith group respectively;

[0032] Step S205: screening the calculated temperature change rate, humidity change rate and pressure change rate to obtain the maximum and minimum values ​​of the temperature change rate, the maximum and minimum values ​​of the humidity change rate and the maximum and minimum values ​​of the pressure change rate;

[0033] Step S206: constructing a first rate change interval through the maximum and minimum values ​​of the temperature change rate, the maximum and minimum values ​​of the humidity change rate, and the maximum and minimum values ​​of the pressure change rate; the first rate change interval includes a first temperature change rate interval, a first humidity change rate interval, and a first pressure change rate interval;

[0034] The above steps are for constructing a first rate change interval for subsequent determination of whether the environmental parameters are within a normal range; the first sampling time in the above steps is less than the average time interval for the occurrence of abnormal values, and the size of the first sampling time is adjusted by a safety factor to ensure that the collected data are all normal values.

[0035] Furthermore, step S300 includes:

[0036] Step S301: extracting temperature values, humidity values ​​and pressure values ​​from data storage structures way1, way2 and way3 respectively in chronological order;

[0037] Step S302: Calculate the temperature change rate, humidity change rate and pressure change rate according to the temperature value and the collection time corresponding to the temperature value, the humidity value and the collection time corresponding to the humidity value, and the pressure value and the collection time corresponding to the pressure value;

[0038] Step S303: Compare the temperature change rate, the humidity change rate, and the pressure change rate with the first rate change interval respectively, and obtain the temperature change rate, humidity change rate, and pressure change rate that are not in the first rate change interval;

[0039] Step S304: Filter out the maximum and minimum values ​​of the temperature change rate, the humidity change rate, and the pressure change rate;

[0040] Step S305: Obtaining a second rate change interval through the maximum and minimum values ​​of the temperature change rate, the humidity change rate, and the pressure change rate;

[0041] The above steps are to further obtain the second rate change interval on the basis of the first rate change interval, so as to more comprehensively evaluate the change of the environmental parameters.

[0042] Furthermore, step S400 includes:

[0043] Step S401: Calculate the second sampling time T2=k2T according to the sampling interval; wherein k2 is the sampling coefficient; T2 represents the second sampling time;

[0044] Step S402: Record the initial temperature value, humidity value, and pressure value of the gas to be tested within the second sampling time, and monitor the initial temperature value, humidity value, and pressure value in real time. When the initial temperature value, humidity value, and pressure value change, the current temperature value, humidity value, pressure value, and the corresponding sampling time are recorded in {(X, Y, Z), t} i The recording is performed in the form of: wherein X, Y, and Z represent the current temperature value, humidity value, and pressure value, respectively; t represents the current corresponding sampling time; i represents the number of the i-th group of sampling data;

[0045] Step S403: Calculate the temperature change rate, humidity change rate, and pressure change rate according to the recorded temperature value, humidity value, and pressure value and the corresponding sampling time, and convert the calculated temperature change rate, humidity change rate, and pressure change rate into {V X ,V Y ,V Z} j where j represents the number of the jth group of change rate data; V X 、V Y 、V Z Respectively represent the temperature change rate, humidity change rate, and pressure change rate calculated based on the j-th group and the j+1-th group of sampling data;

[0046] The above steps prepare for the subsequent analysis of changes in the environmental parameters of the gas to be measured, by calculating the second sampling time and calculating the temperature, humidity and pressure change rates of the gas to be measured within the second sampling time; the above second sampling time is also calculated based on the average time interval of the occurrence of abnormal values, and the size of the second sampling time is controlled by the sampling coefficient, so that the second sampling time is greater than the average time interval, ensuring that the collected data is more comprehensive.

[0047] Furthermore, step S500 includes:

[0048] Step S501: Compare the temperature change rate, humidity change rate, and pressure change rate recorded in the second sampling time with the first rate change interval respectively. If the temperature change rate, humidity change rate, and pressure change rate are all outside the first rate change interval, trigger a first-level sound and light warning;

[0049] Step S502: Compare the temperature change rate, humidity change rate, and pressure change rate recorded in the second sampling time with the second rate change interval respectively. If the temperature change rate, humidity change rate, and pressure change rate are all within the second rate change interval, trigger a secondary sound and light warning;

[0050] Step S503: If the temperature change rate, humidity change rate or pressure change rate recorded within the second sampling time includes both the temperature change rate, humidity change rate or pressure change rate in the first rate change interval and the temperature change rate, humidity change rate or pressure change rate in the second rate change interval, triggering an early warning prompt;

[0051] The above steps compare and analyze the temperature, humidity and pressure change rates recorded within the second sampling time based on the first rate change interval and the second rate change interval, thereby triggering warnings of different levels.

[0052] Furthermore, step S600 includes:

[0053] Step S601: Identify the warning result. If the warning prompt is triggered, calculate the correlation coefficient threshold according to the temperature value, humidity value and pressure value collected within the first sampling time. The correlation coefficient calculation formula is as follows:

[0054]

[0055] in, α represents the correlation coefficient threshold; γ XY is the correlation coefficient between temperature and humidity, γ XZ is the correlation coefficient between temperature and pressure, γ YZ is the correlation coefficient between humidity and pressure; X i represents the temperature value contained in the i-th group of collected data, is the mean value of all the collected temperature values; Y i Indicates the humidity value contained in the i-th group of collected data, is the mean value of all humidity values ​​collected; Z i represents the pressure value contained in the i-th group of collected data, is the mean value corresponding to all the collected pressure values; n represents the number of collected data sets;

[0056] Step S602: Calculate the correlation coefficient β among the temperature, humidity and pressure of the gas to be measured within the second sampling time by using the correlation coefficient calculation formula;

[0057] Step S603: comparing the correlation coefficient β of the temperature, humidity and pressure of the gas to be measured within the second sampling time with the correlation coefficient threshold α, and if β>α, triggering a third-level sound and light warning;

[0058] Based on triggering the early warning prompt, the above steps further determine whether it is necessary to trigger the third-level sound and light warning by calculating the correlation coefficient and the correlation coefficient threshold, so as to more accurately evaluate the abnormal degree of environmental parameter changes.

[0059] Furthermore, in order to better implement the above method, a gas data integrated management system based on NDIR is also provided, the system includes a data acquisition module, a data storage module, a data processing module, and an early warning judgment module;

[0060] The data acquisition module is responsible for collecting the temperature, humidity and pressure values ​​measured by the temperature sensor, humidity sensor and pressure sensor inside the NDIR gas sensor according to a specific sampling interval;

[0061] Data storage module, establish data storage structure way i ; Where i = 1, 2 or 3; the temperature value, humidity value and pressure value collected by the data acquisition module in real time are stored in the corresponding data storage structure way in chronological order i middle;

[0062] The data processing module determines the sampling interval by analyzing historical data; calculates and constructs the first and second rate change intervals; and calculates the correlation coefficient and the correlation coefficient threshold when the warning is triggered;

[0063] The early warning judgment module implements graded early warning according to the rate change range and correlation coefficient threshold obtained by the data processing module.

[0064] Further, the data processing module includes a sampling interval calculation unit, a rate change interval acquisition unit and a correlation coefficient calculation unit;

[0065] The sampling interval calculation unit collects historical measurement values ​​of gas concentration measured by the NDIR gas sensor, sorts the historical measurement values ​​and calculates the median by grouping, and then determines the abnormal value; calculates the average time interval of the abnormal value by counting the measurement time of the abnormal value, and calculates the sampling interval for sampling the temperature, humidity and pressure sensors in combination with the number of normal values ​​of the interval between the abnormal values;

[0066] The rate change interval acquisition unit continuously collects temperature, humidity, and pressure values ​​within a first sampling time, calculates the change rate of the temperature, humidity, and pressure values, and screens out the maximum and minimum values ​​to construct a first rate change interval; extracts data from a data storage structure and calculates the change rate, compares the change rate with the first rate change interval, obtains the change rate that is not within the first rate change interval, and then obtains a second rate change interval;

[0067] The correlation coefficient calculation unit calculates the correlation coefficient threshold value according to the temperature value, humidity value and pressure value collected within the first sampling time when the early warning prompt is triggered; at the same time, calculates the correlation coefficient of the temperature, humidity and pressure of the gas to be measured within the second sampling time.

[0068] Further, the early warning judgment module includes a first-level early warning judgment unit, a second-level early warning judgment unit, and a third-level early warning judgment unit;

[0069] The first-level warning judgment unit compares the temperature change rate, humidity change rate, and pressure change rate recorded in the second sampling time with the first rate change interval respectively. If the change rates are all outside the first rate change interval, a first-level sound and light warning is triggered;

[0070] The secondary warning judgment unit compares the temperature change rate, humidity change rate, and pressure change rate within the second sampling time with the second rate change interval, and triggers the secondary sound and light warning if they are all within the second rate change interval;

[0071] The third-level warning judgment unit triggers a warning prompt when the temperature change rate, humidity change rate or pressure change rate recorded within the second sampling time contains both data from the first rate change interval and data from the second rate change interval. The third-level sound and light warning is triggered by calculating the correlation coefficient of the gas to be tested and comparing it with the correlation coefficient threshold. If the correlation coefficient is greater than the correlation coefficient threshold, the third-level sound and light warning is triggered.

[0072] Compared with the prior art, the present invention has the following beneficial effects: in data processing, by collecting temperature, humidity and pressure sensor data and combining historical data to determine the sampling interval, the gas measurement data can be accurately calibrated to overcome the interference of environmental factors on the measurement accuracy; in change analysis, the first and second rate change intervals are obtained, the normal change range of environmental parameters can be clearly defined, and abnormal fluctuations can be detected in time; in the early warning mechanism, the rate of change within the second sampling time is compared with the two intervals to achieve graded early warning, such as the first-level early warning prompts a large abnormality, the second-level early warning indicates a potential risk, and the early warning prompt is triggered when the data of the two intervals are included at the same time, which can effectively deal with environmental anomalies of different degrees; in addition, after the early warning prompt is triggered, the correlation coefficient is calculated and compared with the threshold, so as to evaluate the credibility of the measurement data. BRIEF DESCRIPTION OF THE DRAWINGS

[0073] Figure 1 It is a method flow diagram of the NDIR-based gas data integrated management system and method of the present invention;

[0074] Figure 2 It is a schematic diagram of the system structure of the NDIR-based gas data integrated management system and method of the present invention. DETAILED DESCRIPTION

[0075] Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in the field without making any creative work shall fall within the scope of protection of the present invention.

[0076] Example: Figure 1-Figure 2 As shown, the present invention provides a technical solution, a gas data integration management method based on NDIR, the method comprising:

[0077] Step S100: collecting and storing the temperature value, humidity value and pressure value measured by the temperature sensor, humidity sensor and pressure sensor inside the NDIR gas sensor according to the sampling interval;

[0078] Wherein, step S100 includes:

[0079] Step S101: collecting historical measurement values ​​of gas concentration measured by the NDIR gas sensor in historical data;

[0080] Step S102: sort the historical measurement values ​​in ascending order and divide them into data sets P i , where i=1, 2, 3 or 4, respectively calculate the median Q1 of the data set P1 and the median Q3 of the data set P3, the interval Δd between the historical measurement values ​​is Q3-Q1, and the historical measurement values ​​that are less than Q1-1.5*Δd or greater than Q3+1.5*Δd in the historical measurement values ​​are regarded as abnormal values;

[0081] Step S103: Count the abnormal values, arrange the measurement time of the abnormal values ​​in chronological order, and calculate the average time interval of the abnormal values. The calculation formula of the average time interval is:

[0082]

[0083] Among them, t i+1 ,t i Respectively represent the measurement time corresponding to the i+1th and ith outliers in the outlier sequence; ω i represents the weight corresponding to the measurement time interval between the ith outlier value and the i+1th measurement value; m represents the number of outliers; Δt represents the average time interval between outliers;

[0084] Step S104: Calculate the sampling interval for sampling the temperature sensor, humidity sensor and pressure sensor. The sampling interval calculation formula is as follows:

[0085]

[0086] Wherein, T represents the sampling interval for sampling the temperature value, humidity value and pressure value measured by the temperature sensor, humidity sensor and pressure sensor; N j represents the number of normal values ​​between the jth outlier and the j+1th outlier;

[0087] Step S105: collecting the temperature value, humidity value and pressure value monitored in real time by the temperature sensor, humidity sensor and pressure sensor inside the NDIR gas sensor according to the sampling interval;

[0088] Step S106: Create a data storage structure way i , where i=1, 2 or 3; the real-time collected temperature values, humidity values ​​and pressure values ​​are stored in the data storage structures way1, way2 and way3 respectively in chronological order;

[0089] In the embodiment of the present invention, the number of outliers is 5; the measurement time corresponding to the outliers is 10s, 20s, 40s, 60s, and 90s; the weights corresponding to the measurement time intervals between outliers are 1, 1, 1, and 1, respectively; the number of normal values ​​between every two outliers is 5, 8, 6, and 7; then the average time interval Δt = [(20-10) + (40-20) + (60-40) + (90-60)] / (5-1) = 20s; the sampling interval T = [(5-1) × 20] / (5 + 8 + 6 + 7) = 3.08s;

[0090] Step S200: continuously collecting the temperature value, humidity value and pressure value measured by the temperature sensor, humidity sensor and pressure sensor within a first sampling time, and processing the collected data respectively to obtain a first rate change interval;

[0091] Wherein, step S200 includes:

[0092] Step S201: Calculate the first sampling time T1=k1T according to the sampling interval; wherein k1 is a safety factor; T1 represents the first sampling time;

[0093] Step S202: continuously collecting the temperature value, humidity value and pressure value within a first sampling time;

[0094] Step S203: The collected temperature value, humidity value and pressure value are expressed as {(X, Y, Z), t} i The data are recorded in the form of, where X represents the collected temperature value; Y represents the collected humidity value; Z represents the collected pressure value; t is the timestamp; i represents the number of the collected data;

[0095] Step S204: sorting the collected data according to the time series, and calculating the temperature change rate, humidity change rate and pressure change rate respectively;

[0096] The temperature change rate The humidity change rate The pressure change rate

[0097] Among them, V X 、V Y 、V Z Respectively represent the temperature change rate, humidity change rate, and pressure change rate within the first sampling time; X i+1 , X i Respectively represent the temperature values ​​contained in the i+1th group and the ith group of sampling data; Y i+1 , Y i Respectively represent the humidity values ​​contained in the i+1th group and the ith group of sampling data; Z i+1 , Z i Respectively represent the pressure values ​​contained in the i+1th group and the ith group of sampling data; t i+1 ,t i They represent the time corresponding to the data collection of the i+1th group and the ith group respectively;

[0098] Step S205: screening the calculated temperature change rate, humidity change rate and pressure change rate to obtain the maximum and minimum values ​​of the temperature change rate, the maximum and minimum values ​​of the humidity change rate and the maximum and minimum values ​​of the pressure change rate;

[0099] Step S206: constructing a first rate change interval through the maximum and minimum values ​​of the temperature change rate, the maximum and minimum values ​​of the humidity change rate, and the maximum and minimum values ​​of the pressure change rate; the first rate change interval includes a first temperature change rate interval, a first humidity change rate interval, and a first pressure change rate interval;

[0100] Step S300: Analyze the data collected in step S100 according to the first rate change interval to obtain a second rate change interval;

[0101] Wherein, step S300 includes:

[0102] Step S301: extracting temperature values, humidity values ​​and pressure values ​​from data storage structures way1, way2 and way3 respectively in chronological order;

[0103] Step S302: Calculate the temperature change rate, humidity change rate and pressure change rate according to the temperature value and the collection time corresponding to the temperature value, the humidity value and the collection time corresponding to the humidity value, and the pressure value and the collection time corresponding to the pressure value;

[0104] Step S303: Compare the temperature change rate, the humidity change rate, and the pressure change rate with the first rate change interval respectively, and obtain the temperature change rate, humidity change rate, and pressure change rate that are not in the first rate change interval;

[0105] Step S304: Filter out the maximum and minimum values ​​of the temperature change rate, the humidity change rate, and the pressure change rate;

[0106] Step S305: Obtaining a second rate change interval through the maximum and minimum values ​​of the temperature change rate, the humidity change rate, and the pressure change rate;

[0107] Step S400: continuously acquiring the temperature value, humidity value and pressure value of the environment in which the gas to be measured is located within the second sampling time, and analyzing the change rate of the temperature value, humidity value and pressure value;

[0108] Wherein, step S400 includes:

[0109] Step S401: Calculate the second sampling time T2=k2T according to the sampling interval; wherein k2 is the sampling coefficient; T2 represents the second sampling time;

[0110] Step S402: Record the initial temperature value, humidity value, and pressure value of the gas to be tested within the second sampling time, and monitor the initial temperature value, humidity value, and pressure value in real time. When the initial temperature value, humidity value, and pressure value change, the current temperature value, humidity value, pressure value, and the corresponding sampling time are recorded in {(X, Y, Z), t} i The recording is performed in the form of: wherein X, Y, and Z represent the current temperature value, humidity value, and pressure value, respectively; t represents the current corresponding sampling time; i represents the number of the i-th group of sampling data;

[0111] Step S403: Calculate the temperature change rate, humidity change rate, and pressure change rate according to the recorded temperature value, humidity value, and pressure value and the corresponding sampling time, and convert the calculated temperature change rate, humidity change rate, and pressure change rate into {V X ,V Y ,V Z} j where j represents the number of the jth group of change rate data; V X 、V Y 、V Z Respectively represent the temperature change rate, humidity change rate, and pressure change rate calculated based on the j-th group and the j+1-th group of sampling data;

[0112] Step S500: comparing the change rate with the first rate change interval and the second rate change interval, and determining a warning level according to the comparison result;

[0113] Wherein, step S500 includes:

[0114] Step S501: Compare the temperature change rate, humidity change rate, and pressure change rate recorded in the second sampling time with the first rate change interval respectively. If the temperature change rate, humidity change rate, and pressure change rate are all outside the first rate change interval, trigger a first-level sound and light warning;

[0115] Step S502: Compare the temperature change rate, humidity change rate, and pressure change rate recorded in the second sampling time with the second rate change interval respectively. If the temperature change rate, humidity change rate, and pressure change rate are all within the second rate change interval, trigger a secondary sound and light warning;

[0116] Step S503: If the temperature change rate, humidity change rate or pressure change rate recorded within the second sampling time includes both the temperature change rate, humidity change rate or pressure change rate in the first rate change interval and the temperature change rate, humidity change rate or pressure change rate in the second rate change interval, triggering an early warning prompt;

[0117] Step S600: Obtaining the warning result. If the warning prompt is triggered, the correlation coefficient of the temperature, humidity and pressure of the gas to be tested is calculated, and the correlation coefficient is compared with the correlation coefficient threshold to determine whether to trigger the sound and light warning;

[0118] Wherein, step S600 includes:

[0119] Step S601: Identify the warning result. If the warning prompt is triggered, calculate the correlation coefficient threshold according to the temperature value, humidity value and pressure value collected within the first sampling time. The correlation coefficient calculation formula is as follows:

[0120]

[0121] in, α represents the correlation coefficient threshold; γ XY is the correlation coefficient between temperature and humidity, γ XZ is the correlation coefficient between temperature and pressure, γ YZ is the correlation coefficient between humidity and pressure; X i represents the temperature value contained in the i-th group of collected data, is the mean value of all the collected temperature values; Y i Indicates the humidity value contained in the i-th group of collected data, is the mean value of all humidity values ​​collected; Z i represents the pressure value contained in the i-th group of collected data, is the mean value corresponding to all the collected pressure values; n represents the number of collected data sets;

[0122] In the embodiment of the present invention, 5 sets of data are collected: temperature value X = [20, 22, 23, 21, 24], humidity value Y = [40, 42, 43, 41, 44], pressure value Z = [100, 102, 103, 101, 104];

[0123] but

[0124]

[0125] Substituting the data into the formula, we can calculate γ XY =1;γ XZ =1;γ YZ =1; then the correlation coefficient threshold α=1;

[0126] Step S602: Calculate the correlation coefficient β among the temperature, humidity and pressure of the gas to be measured within the second sampling time by using the correlation coefficient calculation formula;

[0127] Step S603: comparing the correlation coefficient β of the temperature, humidity and pressure of the gas to be measured within the second sampling time with the correlation coefficient threshold α, and if β>α, triggering a third-level sound and light warning;

[0128] In order to better implement the above method, a gas data integrated management system based on NDIR is also provided, the system includes a data acquisition module, a data storage module, a data processing module, and an early warning judgment module;

[0129] The data acquisition module is responsible for collecting the temperature, humidity and pressure values ​​measured by the temperature sensor, humidity sensor and pressure sensor inside the NDIR gas sensor according to a specific sampling interval;

[0130] Data storage module, establish data storage structure way i ; Where i = 1, 2 or 3; the temperature value, humidity value and pressure value collected by the data acquisition module in real time are stored in the corresponding data storage structure way in chronological order i middle;

[0131] The data processing module determines the sampling interval by analyzing historical data; calculates and constructs the first and second rate change intervals; and calculates the correlation coefficient and the correlation coefficient threshold when the warning is triggered;

[0132] The early warning judgment module implements graded early warning according to the rate change interval and correlation coefficient threshold obtained by the data processing module;

[0133] Wherein, the data processing module includes a sampling interval calculation unit, a rate change interval acquisition unit and a correlation coefficient calculation unit;

[0134] The sampling interval calculation unit collects historical measurement values ​​of gas concentration measured by the NDIR gas sensor, sorts the historical measurement values ​​and calculates the median by grouping, and then determines the abnormal value; calculates the average time interval of the abnormal value by counting the measurement time of the abnormal value, and calculates the sampling interval for sampling the temperature, humidity and pressure sensors in combination with the number of normal values ​​of the interval between the abnormal values;

[0135] The rate change interval acquisition unit continuously collects temperature, humidity, and pressure values ​​within a first sampling time, calculates the change rate of the temperature, humidity, and pressure values, and screens out the maximum and minimum values ​​to construct a first rate change interval; extracts data from a data storage structure and calculates the change rate, compares the change rate with the first rate change interval, obtains the change rate that is not within the first rate change interval, and then obtains a second rate change interval;

[0136] The correlation coefficient calculation unit calculates the correlation coefficient threshold value according to the temperature value, humidity value and pressure value collected during the first sampling time when the early warning prompt is triggered; at the same time, calculates the correlation coefficient of the temperature, humidity and pressure of the gas to be measured during the second sampling time;

[0137] Among them, the early warning judgment module includes a first-level early warning judgment unit, a second-level early warning judgment unit and a third-level early warning judgment unit;

[0138] The first-level warning judgment unit compares the temperature change rate, humidity change rate, and pressure change rate recorded in the second sampling time with the first rate change interval respectively. If the change rates are all outside the first rate change interval, a first-level sound and light warning is triggered;

[0139] The secondary warning judgment unit compares the temperature change rate, humidity change rate, and pressure change rate within the second sampling time with the second rate change interval, and triggers the secondary sound and light warning if they are all within the second rate change interval;

[0140] The third-level warning judgment unit triggers a warning prompt when the temperature change rate, humidity change rate or pressure change rate recorded within the second sampling time contains both data from the first rate change interval and data from the second rate change interval. The third-level sound and light warning is triggered by calculating the correlation coefficient of the gas to be tested and comparing it with the correlation coefficient threshold. If the correlation coefficient is greater than the correlation coefficient threshold, the third-level sound and light warning is triggered.

[0141] Finally, it should be noted that the above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A gas data integration management method based on NDIR, characterized in that: The method comprises: Step S100: collecting and storing the temperature value, humidity value and pressure value measured by the temperature sensor, humidity sensor and pressure sensor inside the NDIR gas sensor according to the sampling interval; Step S200: continuously collecting the temperature value, humidity value and pressure value measured by the temperature sensor, humidity sensor and pressure sensor within a first sampling time, and processing the collected data respectively to obtain a first rate change interval; Step S300: Analyze the data collected in step S100 according to the first rate change interval to obtain a second rate change interval; Step S400: continuously acquiring the temperature value, humidity value and pressure value of the environment in which the gas to be measured is located within the second sampling time, and analyzing the change rate of the temperature value, humidity value and pressure value; Step S500: comparing the change rate with the first rate change interval and the second rate change interval, and determining a warning level according to the comparison result; Step S600: Obtain the warning result. If the warning prompt is triggered, the correlation coefficient of the temperature, humidity and pressure of the gas to be tested is calculated, and the correlation coefficient is compared with the correlation coefficient threshold to determine whether to trigger the sound and light warning.

2. The NDIR-based gas data integrated management method according to claim 1, characterized in that: The step S100 includes: Step S101: collecting historical measurement values ​​of gas concentration measured by the NDIR gas sensor in historical data; Step S102: sort the historical measurement values ​​in ascending order and divide them into data sets P i , where i=1, 2, 3 or 4, respectively calculate the median Q1 of the data set P1 and the median Q3 of the data set P3, the interval Δd between the historical measurement values ​​is Q3-Q1, and the historical measurement values ​​that are less than Q1-1.5*Δd or greater than Q3+1.5*Δd in the historical measurement values ​​are regarded as abnormal values; Step S103: Count the abnormal values, arrange the measurement time of the abnormal values ​​in chronological order, and calculate the average time interval of the abnormal values. The calculation formula of the average time interval is: Among them, t i+1 ,t i Respectively represent the measurement time corresponding to the i+1th and ith outliers in the outlier sequence; ω i represents the weight corresponding to the measurement time interval between the ith outlier value and the i+1th measurement value; m represents the number of outliers; Δt represents the average time interval between outliers; Step S104: Calculate the sampling interval for sampling the temperature sensor, humidity sensor and pressure sensor. The sampling interval calculation formula is as follows: Wherein, T represents the sampling interval for sampling the temperature value, humidity value and pressure value measured by the temperature sensor, humidity sensor and pressure sensor; N j represents the number of normal values ​​between the jth outlier and the j+1th outlier; Step S105: collecting the temperature value, humidity value and pressure value monitored in real time by the temperature sensor, humidity sensor and pressure sensor inside the NDIR gas sensor according to the sampling interval; Step S106: Create a data storage structure way i , where i=1, 2 or 3; the real-time collected temperature values, humidity values ​​and pressure values ​​are stored in the data storage structures way1, way2 and way3 respectively in chronological order.

3. The NDIR-based gas data integrated management method according to claim 1, characterized in that: The step S200 includes: Step S201: Calculate the first sampling time T1=k1T according to the sampling interval; wherein k1 is a safety factor; T1 represents the first sampling time; Step S202: continuously collecting the temperature value, humidity value and pressure value within a first sampling time; Step S203: The collected temperature value, humidity value and pressure value are expressed as {(X, Y, Z), t} i The data are recorded in the form of, where X represents the collected temperature value; Y represents the collected humidity value; Z represents the collected pressure value; t is the timestamp; i represents the number of the collected data; Step S204: sorting the collected data according to the time series, and calculating the temperature change rate, humidity change rate and pressure change rate respectively; The temperature change rate The humidity change rate The pressure change rate Among them, V X 、V Y 、V Z Respectively represent the temperature change rate, humidity change rate, and pressure change rate; X i+1 , X i Respectively represent the temperature values ​​recorded in the i+1th group and the ith group of sampling data; Y i+1 , Y i Respectively represent the humidity values ​​recorded in the i+1th group and the ith group of sampling data; Z i+1 , Z i Respectively represent the pressure values ​​recorded in the i+1th group and the ith group of sampling data; t i+1 ,t i They represent the time corresponding to the data collection of the i+1th group and the ith group respectively; Step S205: screening the calculated temperature change rate, humidity change rate and pressure change rate to obtain the maximum and minimum values ​​of the temperature change rate, the maximum and minimum values ​​of the humidity change rate and the maximum and minimum values ​​of the pressure change rate; Step S206: Construct a first rate change interval through the maximum and minimum values ​​of the temperature change rate, the maximum and minimum values ​​of the humidity change rate, and the maximum and minimum values ​​of the pressure change rate; the first rate change interval includes a first temperature change rate interval, a first humidity change rate interval, and a first pressure change rate interval.

4. The NDIR-based gas data integrated management method according to claim 1, characterized in that: The step S300 includes: Step S301: extracting temperature values, humidity values ​​and pressure values ​​from data storage structures way1, way2 and way3 respectively in chronological order; Step S302: Calculate the temperature change rate, humidity change rate and pressure change rate according to the temperature value and the collection time corresponding to the temperature value, the humidity value and the collection time corresponding to the humidity value, and the pressure value and the collection time corresponding to the pressure value; Step S303: Compare the temperature change rate, the humidity change rate, and the pressure change rate with the first rate change interval respectively, and obtain the temperature change rate, humidity change rate, and pressure change rate that are not in the first rate change interval; Step S304: Filter out the maximum and minimum values ​​of the temperature change rate, the humidity change rate, and the pressure change rate; Step S305: Obtain a second rate change interval through the maximum and minimum values ​​of the temperature change rate, the humidity change rate, and the pressure change rate.

5. The NDIR-based gas data integrated management method according to claim 1, characterized in that: The step S400 includes: Step S401: Calculate the second sampling time T2=k2T according to the sampling interval; wherein k2 is the sampling coefficient; T2 represents the second sampling time; Step S402: Record the initial temperature value, humidity value, and pressure value of the gas to be tested within the second sampling time, and monitor the initial temperature value, humidity value, and pressure value in real time. When the initial temperature value, humidity value, and pressure value change, the current temperature value, humidity value, pressure value, and the corresponding sampling time are recorded in {(X, Y, Z), t} i The recording is performed in the form of: wherein X, Y, and Z represent the current temperature value, humidity value, and pressure value, respectively; t represents the current corresponding sampling time; i represents the number of the i-th group of sampling data; Step S403: Calculate the temperature change rate, humidity change rate, and pressure change rate according to the recorded temperature value, humidity value, and pressure value and the corresponding sampling time, and convert the calculated temperature change rate, humidity change rate, and pressure change rate into {V X ,V Y ,V Z } j where j represents the number of the jth group of change rate data; V X 、V Y 、V Z They respectively represent the temperature change rate, humidity change rate, and pressure change rate calculated based on the j-th and j+1-th group of sampling data.

6. The NDIR-based gas data integrated management method according to claim 1, characterized in that: The step S500 includes: Step S501: Compare the temperature change rate, humidity change rate, and pressure change rate recorded in the second sampling time with the first rate change interval respectively. If the temperature change rate, humidity change rate, and pressure change rate are all outside the first rate change interval, trigger a first-level sound and light warning; Step S502: Compare the temperature change rate, humidity change rate, and pressure change rate recorded in the second sampling time with the second rate change interval respectively. If the temperature change rate, humidity change rate, and pressure change rate are all within the second rate change interval, trigger a secondary sound and light warning; Step S503: If the temperature change rate, humidity change rate or pressure change rate recorded within the second sampling time includes both the temperature change rate, humidity change rate or pressure change rate in the first rate change interval and the temperature change rate, humidity change rate or pressure change rate in the second rate change interval, an early warning prompt is triggered.

7. The NDIR-based gas data integrated management method according to claim 1, characterized in that: The step S600 includes: Step S601: Identify the warning result. If the warning prompt is triggered, calculate the correlation coefficient threshold according to the temperature value, humidity value and pressure value collected within the first sampling time. The correlation coefficient calculation formula is as follows: in, α represents the correlation coefficient threshold; γ XY is the correlation coefficient between temperature and humidity, γ XZ is the correlation coefficient between temperature and pressure, γ YZ is the correlation coefficient between humidity and pressure; X i represents the temperature value contained in the i-th group of collected data, is the mean value of all collected temperature values; Y i Indicates the humidity value contained in the i-th group of collected data, is the mean value of all humidity values ​​collected; Z i represents the pressure value contained in the i-th group of collected data, is the mean value corresponding to all the collected pressure values; n represents the number of collected data sets; Step S602: Calculate the correlation coefficient β among the temperature, humidity and pressure of the gas to be measured within the second sampling time by using the correlation coefficient calculation formula; Step S603: Compare the correlation coefficient β of the temperature, humidity and pressure of the gas to be measured within the second sampling time with the correlation coefficient threshold α. If β>α, trigger a third-level sound and light warning.

8. A gas data integrated management system based on NDIR, used to execute the gas data integrated management method based on NDIR according to any one of claims 1 to 7, characterized in that: The system includes a data acquisition module, a data storage module, a data processing module, and an early warning judgment module; The data acquisition module is responsible for collecting the temperature value, humidity value and pressure value measured by the temperature sensor, humidity sensor and pressure sensor inside the NDIR gas sensor according to a specific sampling interval; The data storage module establishes a data storage structure way i ; Where i = 1, 2 or 3; the temperature value, humidity value and pressure value collected by the data acquisition module in real time are stored in the corresponding data storage structure way in chronological order i middle; The data processing module determines the sampling interval by analyzing historical data; calculates and constructs the first and second rate change intervals; and calculates the correlation coefficient and the correlation coefficient threshold when the warning is triggered; The early warning judgment module implements graded early warning according to the rate change interval and correlation coefficient threshold value obtained by the data processing module.

9. The NDIR-based gas data integrated management system according to claim 8, characterized in that: The data processing module includes a sampling interval calculation unit, a rate change interval acquisition unit and a correlation coefficient calculation unit; The sampling interval calculation unit collects historical measurement values ​​of gas concentration measured by the NDIR gas sensor, sorts the historical measurement values ​​and calculates the median by grouping, and then determines the abnormal value; calculates the average time interval of the abnormal value by counting the measurement time of the abnormal value, and calculates the sampling interval for sampling the temperature, humidity, and pressure sensors in combination with the number of normal values ​​of the interval between the abnormal values; The rate change interval acquisition unit continuously collects temperature, humidity, and pressure values ​​within a first sampling time, calculates the change rates of the temperature, humidity, and pressure values, and selects the maximum and minimum values ​​to construct a first rate change interval; Extracting data from the data storage structure and calculating a change rate, comparing the change rate with a first rate change interval, obtaining a change rate that is not within the first rate change interval, and then obtaining a second rate change interval; The correlation coefficient calculation unit calculates the correlation coefficient threshold value according to the temperature value, humidity value and pressure value collected within the first sampling time when the early warning prompt is triggered; at the same time, calculates the correlation coefficient of the temperature, humidity and pressure of the gas to be measured within the second sampling time.

10. The NDIR-based gas data integrated management system according to claim 8, characterized in that: The warning judgment module includes a first-level warning judgment unit, a second-level warning judgment unit and a third-level warning judgment unit; The first-level warning judgment unit compares the temperature change rate, humidity change rate, and pressure change rate recorded in the second sampling time with the first rate change interval respectively, and if the change rates are all outside the first rate change interval, a first-level sound and light warning is triggered; The secondary warning judgment unit compares the temperature change rate, humidity change rate, and pressure change rate within the second sampling time with the second rate change interval, and triggers the secondary sound and light warning if they are all within the second rate change interval; The three-level warning judgment unit triggers a warning prompt when the temperature change rate, humidity change rate or pressure change rate recorded within the second sampling time contains both data from the first rate change interval and data from the second rate change interval. The three-level warning judgment unit calculates the correlation coefficient of the gas to be tested and compares it with the correlation coefficient threshold. If the correlation coefficient is greater than the correlation coefficient threshold, the three-level sound and light warning is triggered.

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