A method and system for generating industrial waste gas odor fingerprint

Abstract

The present invention is applicable to the technical field of odor fingerprint, and in particular, to a method and system for generating an odor fingerprint of industrial waste gas, the method comprising: obtaining real-time parameters of industrial equipment, configuring a fluctuation range, and defining a standard working condition, extracting the absorption characteristics of industrial waste gas from a pre-deployed online spectrometer, generating an absorption spectrum, and extracting a number of characteristic peaks, traversing the wavenumbers corresponding to the characteristic peaks; creating leaf nodes corresponding to the characteristic peaks one by one, writing the wavenumbers and characteristic peaks into the leaf nodes, creating a root node, and integrating all leaf nodes. The present invention can quickly identify abnormal components in industrial waste gas under fluctuating working conditions by determining the fluctuation fingerprint, thereby optimizing production process control and improving environmental protection efficiency. By determining the target fingerprint, the specific components in the sample can be accurately identified, data processing complexity can be reduced, and analysis efficiency can be improved, which greatly improves the management level of industrial waste gas.

Description

Technical Field

[0001] The present invention relates to the technical field of odor fingerprints, and in particular to a method and system for generating an industrial waste gas odor fingerprint. Background Art

[0002] In industrial production, odor fingerprint is a technology used to identify and analyze the odor characteristics in exhaust gas. It uses infrared spectrometers and mass spectrometers to analyze and detect the combination of odor molecules, generate unique signals, and perform data processing to detect whether there are toxic gases in industrial exhaust gas, thereby monitoring exhaust gas emissions, evaluating treatment effects, and optimizing industrial production processes.

[0003] In the prior art, the components of industrial waste gas are monitored by measuring the spectrum of unknown gas and matching it with known fingerprints in the odor gas fingerprint library. However, analyzing all gas components one by one will take up a lot of time and computing resources, especially in complex industrial waste gas. Therefore, "how to compare only the characteristic peaks in the standard spectrum and the test spectrum" is the technical problem that the present invention needs to solve. Summary of the invention

[0004] The purpose of the present invention is to provide a method and system for generating an industrial waste gas odor fingerprint to solve the problem of "how to compare only the characteristic peaks in the standard spectrum and the test spectrum" raised in the above background technology.

[0005] To achieve the above object, the present invention provides the following technical solutions: A method for generating an industrial waste gas odor fingerprint, the method comprising: Obtain the real-time parameters of industrial equipment, configure the fluctuation range, and define the standard working conditions. Extract the absorption characteristics of industrial waste gas from the pre-deployed online spectrometer, generate an absorption spectrum, extract several characteristic peaks, and traverse the wave numbers corresponding to the characteristic peaks; Create leaf nodes corresponding to the characteristic peaks one by one, write the wavenumbers and characteristic peaks into the leaf nodes, create a root node, integrate all leaf nodes, generate a standard fingerprint, and transfer the standard fingerprint into the root node; Based on the real-time parameters, a fluctuation condition is defined, and a distinguishing peak is extracted from the absorption spectrum corresponding to the fluctuation condition, the distinguishing peak and the standard fingerprint are integrated to obtain a fluctuation fingerprint, and a corresponding relationship between the fluctuation fingerprint and the fluctuation condition is configured; Obtain the absorption spectrum of the test sample to determine whether there is a distinguishing peak. If so, calculate the correlation coefficient between the test sample and the fluctuation fingerprint, and find the fluctuation fingerprint with the largest correlation coefficient, which is defined as the target fingerprint, to estimate the exhaust gas components in the test sample; If not, the exhaust composition of the test sample is estimated using the standard fingerprint.

[0006] Furthermore, the steps of obtaining real-time parameters of industrial equipment, configuring fluctuation ranges, and defining standard working conditions include: Configuring the influencing factors of the standard working condition and correcting the fluctuation range; It is determined whether the real-time parameter is within the fluctuation range. If so, a snapshot of the real-time parameter is captured and the snapshot is defined as a standard operating condition.

[0007] Furthermore, the steps of extracting the absorption characteristics of the industrial waste gas from the pre-deployed online spectrometer, generating an absorption spectrum, extracting a number of characteristic peaks, and traversing the wave numbers corresponding to the characteristic peaks include: Extracting the absorption peak from the absorption spectrum, performing preprocessing, correcting the spectral deviation in the absorption peak, and obtaining a characteristic peak; All characteristic peaks are integrated to construct a standard spectrum library, and the library is updated in real time using the real-time parameters.

[0008] Furthermore, the step of creating leaf nodes corresponding to the characteristic peaks one by one, writing the wavenumbers and characteristic peaks into the leaf nodes, and creating a root node includes: Defining monitoring nodes and calculating the intensity of the characteristic peaks; Construct an early warning strategy, and trigger the early warning strategy when the intensity is greater than a preset threshold.

[0009] Furthermore, the step of defining a fluctuating operating condition based on the real-time parameters and extracting a distinguishing peak from an absorption spectrum corresponding to the fluctuating operating condition comprises: Dividing the fluctuating operating conditions into several levels, wherein the levels include: low risk level, medium risk level and high risk level; A trigger mechanism based on the high risk level is constructed, the trigger mechanism is integrated into a root node, and adjustment permissions for industrial equipment are issued to the root node.

[0010] Furthermore, the step of integrating the distinguishing peak and the standard fingerprint to obtain the fluctuation fingerprint and configuring the corresponding relationship between the fluctuation fingerprint and the fluctuation working condition comprises: Based on the preset DCS central control system, the occurrence time of the fluctuating working condition is recorded and a time window is established; The parameter adjustment in the DCS central control system within the time window is read out and the parameter adjustment is stored.

[0011] Furthermore, the step of calculating the correlation coefficient between the test sample and the fluctuation fingerprint includes: Define the illumination intensity of the characteristic peaks in the standard spectrum and the test spectrum, and record them as and ; Calculate the average values ​​of all light intensities in the standard spectrum and the test spectrum, and record them as and ; Use the preset correlation coefficient formula to calculate the correlation coefficient and construct the evaluation rules; The correlation coefficient formula is: ; in ,、 , To test the deviation of the light intensity of each characteristic peak in the spectrum, is the deviation of the light intensity of each characteristic peak in the standard spectrum, and r is the correlation coefficient.

[0012] Furthermore, the system comprises: The traversal module is used to obtain the real-time parameters of industrial equipment, configure the fluctuation range, and define the standard working conditions. It extracts the absorption characteristics of industrial waste gas from the pre-deployed online spectrometer, generates an absorption spectrum, extracts several characteristic peaks, and traverses the wave numbers corresponding to the characteristic peaks; A transfer module is used to create leaf nodes corresponding to the characteristic peaks one by one, write the wave number and characteristic peak into the leaf nodes, create a root node, integrate all leaf nodes, generate a standard fingerprint, and transfer the standard fingerprint into the root node; A configuration module, for defining a fluctuation condition according to the real-time parameters, extracting a distinguishing peak from an absorption spectrum corresponding to the fluctuation condition, integrating the distinguishing peak and a standard fingerprint to obtain a fluctuation fingerprint, and configuring a corresponding relationship between the fluctuation fingerprint and the fluctuation condition; The estimation module is used to obtain the absorption spectrum of the test sample and determine whether there is a distinguishing peak. If so, calculate the correlation coefficient between the test sample and the fluctuation fingerprint, and find the fluctuation fingerprint with the largest correlation coefficient, which is defined as the target fingerprint, to estimate the exhaust gas components in the test sample. If not, use the standard fingerprint to estimate the exhaust gas components of the test sample.

[0013] Furthermore, the traversal module includes: A correction unit, used to configure the influencing factors of the standard working condition and correct the fluctuation range; a definition unit, configured to determine whether the real-time parameter is within a fluctuation range, and if so, to capture a snapshot of the real-time parameter and define the snapshot as a standard operating condition; A correction unit, used to extract an absorption peak from the absorption spectrum, perform preprocessing, correct the spectral deviation in the absorption peak, and obtain a characteristic peak; The updating unit is used to integrate all characteristic peaks, build a standard spectrum library, and perform real-time updating using the real-time parameters.

[0014] Furthermore, the transfer module includes: A calculation unit, used to define a monitoring node and calculate the intensity of the characteristic peak; The trigger unit is used to construct an early warning strategy, and when the intensity is greater than a preset threshold, the early warning strategy is triggered.

[0015] Compared with the prior art, the present invention has the following beneficial effects: By extracting characteristic peaks from the absorption spectrum under standard working conditions, the analysis efficiency can be greatly improved, the computational complexity can be reduced, and data comparison can be more convenient. By generating standard fingerprints, the efficiency of data recognition and matching can be improved, and the risk of misjudgment and missed judgment can be reduced. By determining the fluctuation fingerprint, the abnormal components of industrial waste gas under fluctuating conditions can be quickly identified, thereby optimizing production process control and improving environmental protection efficiency. By determining the target fingerprint, the specific components in the test sample can be accurately identified, reducing data processing complexity, improving analysis efficiency, and improving the management level of industrial waste gas. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 A flowchart of a method for generating an industrial waste gas odor fingerprint provided by an embodiment of the present invention; Figure 2 A first sub-flow diagram of the method for generating an industrial waste gas odor fingerprint provided by an embodiment of the present invention; Figure 3 A second sub-flow chart of the method for generating an industrial waste gas odor fingerprint provided by an embodiment of the present invention; Figure 4 A third sub-flow chart of the method for generating an industrial waste gas odor fingerprint provided by an embodiment of the present invention; Figure 5 A fourth sub-flow chart of the method for generating an industrial waste gas odor fingerprint provided by an embodiment of the present invention; Figure 6 A block diagram of the composition of a system for generating an industrial waste gas odor fingerprint provided by an embodiment of the present invention; Figure 7 A block diagram of the composition of the traversal module in the system for generating the industrial waste gas odor fingerprint provided by an embodiment of the present invention; Figure 8 A block diagram of the composition of the transfer module in the system for generating the industrial waste gas odor fingerprint provided by an embodiment of the present invention; Fig. 9 A block diagram of the configuration module in the system for generating the industrial waste gas odor fingerprint provided by an embodiment of the present invention; Fig.10A block diagram of the composition of the estimation module in the system for generating the industrial waste gas odor fingerprint provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0017] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0018] In Example 1, Figure 1 The implementation process of the method for generating the industrial waste gas odor fingerprint provided by the embodiment of the present invention is shown, and is described in detail below, as follows: S100: Obtain the real-time parameters of industrial equipment, configure the fluctuation range, and define the standard working conditions. Extract the absorption characteristics of industrial waste gas from the pre-deployed online spectrometer, generate an absorption spectrum, extract several characteristic peaks, and traverse the wave numbers corresponding to the characteristic peaks.

[0019] The real-time parameters of industrial equipment are collected by using the DCS central control system or on-site readings, and the corresponding fluctuation range is configured for each real-time parameter. If the real-time parameter is within the fluctuation range, the current operating condition is defined as the standard operating condition. The absorption characteristics of industrial waste gas are collected by using an online spectrometer pre-deployed at the exhaust port, and an absorption spectrum is generated. The absorption spectrum contains absorption peaks of different waste gases, and these peaks correspond to different wave numbers. The absorption peaks can identify the various components in the industrial waste gas, and the wave number can help with the qualitative and quantitative analysis of the industrial waste gas.

[0020] S200: creating leaf nodes corresponding to the characteristic peaks one by one, writing the wavenumbers and characteristic peaks into the leaf nodes, creating a root node, integrating all leaf nodes, generating a standard fingerprint, and transferring the standard fingerprint into the root node.

[0021] Create leaf nodes, which are the basic units of data storage and are attached to the root node; write the specific information of the characteristic peak (such as absorption intensity) and its corresponding wave number into the leaf node, and integrate all leaf nodes to generate a standard fingerprint; the standard fingerprint reflects the absorption characteristics and composition distribution of industrial waste gas under standard working conditions.

[0022] S300: Based on the real-time parameters, a fluctuation condition is defined, and a distinguishing peak is extracted from the absorption spectrum corresponding to the fluctuation condition, the distinguishing peak and the standard fingerprint are integrated to obtain a fluctuation fingerprint, and a corresponding relationship between the fluctuation fingerprint and the fluctuation condition is configured.

[0023] If the real-time parameters exceed the fluctuation range, the production parameters at the corresponding moment are defined as the fluctuation conditions. The absorption spectra corresponding to the leaf nodes and the fluctuation conditions are compared. The distinguishing peaks different from the leaf nodes are extracted from the absorption spectra of the fluctuation conditions. The distinguishing peaks are integrated with the standard fingerprint to obtain the fluctuation fingerprint. The corresponding relationship between the fluctuation fingerprint and the fluctuation condition is established, and the exhaust emission characteristics under each condition are mapped to the specific fluctuation fingerprint.

[0024] In this embodiment, each fluctuation fingerprint includes two parts, one is a distinguishing peak, and the other is a characteristic peak in the standard fingerprint.

[0025] S400: Obtain an absorption spectrum of the test sample to determine whether there is a distinguishing peak. If so, calculate the correlation coefficient between the test sample and the fluctuation fingerprint, and find the fluctuation fingerprint with the largest correlation coefficient, define it as the target fingerprint, and estimate the exhaust gas components in the test sample; If not, the exhaust composition of the test sample is estimated using the standard fingerprint.

[0026] When it is necessary to compare the odor fingerprint of industrial waste gas, the collected industrial waste gas is determined as the test sample, and the absorption spectra of the normal working conditions and the test sample are compared to determine whether there are distinguishing peaks in the absorption spectrum corresponding to the test sample. If so, the preset calculation formula is used to calculate the correlation coefficient between the test sample and the fluctuation fingerprint, and the fluctuation fingerprint with the largest correlation coefficient is found and defined as the target fingerprint; the waste gas components in the test sample are estimated based on the characteristic peaks in the target fingerprint; if there are no distinguishing peaks in the absorption spectrum of the test sample, the test sample is directly compared with the standard fingerprint, and the standard fingerprint is used to infer the waste gas components in the test sample.

[0027] In Example 2, Figure 2 The implementation process of the method for generating the industrial waste gas odor fingerprint provided by the embodiment of the present invention is shown. The steps of obtaining the real-time parameters of the industrial equipment, configuring the fluctuation range, and defining the standard working conditions are described in detail as follows: S101: configuring the influencing factors of the standard working condition and correcting the fluctuation range.

[0028] Determine the influencing factors of standard operating conditions, such as output, environment, etc., and adjust the fluctuation range according to different influencing factors.

[0029] S102: Determine whether the real-time parameter is within the fluctuation range. If yes, take a snapshot of the real-time parameter and define the snapshot as a standard operating condition.

[0030] If the real-time parameters are within the fluctuation range, it means that the operating status of the industrial equipment meets the requirements of the standard operating conditions. In this case, a snapshot of the real-time parameters is taken, the instantaneous values ​​of all relevant parameters are recorded, and the data in the snapshot is marked as the standard operating conditions.

[0031] In Example 3, Figure 2 The implementation process of the method for generating the industrial waste gas odor fingerprint provided by the embodiment of the present invention is shown. The following is a detailed description of the steps of extracting the absorption characteristics of the industrial waste gas from the pre-deployed online spectrometer, generating an absorption spectrum, extracting several characteristic peaks, and traversing the wave numbers corresponding to the characteristic peaks, as follows: S103: extracting absorption peaks from the absorption spectrum, performing preprocessing, correcting spectral deviations in the absorption peaks, and obtaining characteristic peaks.

[0032] All significant absorption peaks are extracted from the absorption spectrum of industrial waste gas. The absorption peaks represent the characteristic absorption information of different components in the waste gas. Due to differences in sampling equipment or sampling environment, there may be spectral deviations in the absorption peaks, such as peak position drift or intensity changes, so the extracted absorption peaks need to be preprocessed, including smoothing filtering to remove noise, baseline correction to eliminate background interference and normalization processing. By comparing and correcting the absorption peaks in the standard spectral library, the spectral deviation is adjusted so that the wavenumber position and intensity of the absorption peak are consistent with the standard value, and finally the characteristic peak is obtained.

[0033] S104: Integrate all characteristic peaks, construct a standard spectrum library, and update it in real time using the real-time parameters.

[0034] Integrate all characteristic peaks to build a standard spectral library, and use real-time parameters to update the standard spectral library in real time.

[0035] In Example 4, Figure 3 The implementation process of the method for generating the industrial waste gas odor fingerprint provided by the embodiment of the present invention is shown. The steps of creating a leaf node corresponding to the characteristic peak one by one, writing the wave number and the characteristic peak into the leaf node, and creating a root node are described in detail as follows: S201: Define monitoring nodes and calculate the intensity of the characteristic peaks.

[0036] Create several monitoring nodes, where the monitoring nodes are mainly used to calculate the intensity of characteristic peaks.

[0037] S202: constructing an early warning strategy, and triggering the early warning strategy when the intensity is greater than a preset threshold.

[0038] Create an early warning strategy. When the intensity is greater than the preset threshold, the early warning strategy is triggered. The early warning strategy can push alarm information to the DCS central control system.

[0039] In Example 5, Figure 4 The implementation process of the method for generating the industrial waste gas odor fingerprint provided by the embodiment of the present invention is shown. The following is a detailed description of the steps of defining the fluctuation condition based on the real-time parameters and extracting the distinguishing peaks from the absorption spectrum corresponding to the fluctuation condition, as follows: S301: Divide the fluctuating operating conditions into several levels, wherein the levels include: a low risk level, a medium risk level, and a high risk level.

[0040] The fluctuating operating conditions are divided into low risk level, medium risk level and high risk level.

[0041] S302: Construct a trigger mechanism based on the high risk level, integrate the trigger mechanism into a root node, and issue adjustment permissions for industrial equipment to the root node.

[0042] Construct a trigger mechanism, where the trigger mechanism is the interlock between equipment; for example, at a certain moment, if the fluctuating operating conditions are at a high risk level, the preset equipment interlock is activated, the vent valve is closed, and the industrial waste gas is discharged to the intermediate storage tank to prevent venting when the composition of the industrial waste gas is abnormal; when starting the interlock between equipment, it is necessary to obtain the adjustment authority of the corresponding industrial equipment in advance.

[0043] In Example 6, Figure 4 The implementation process of the method for generating the industrial waste gas odor fingerprint provided by the embodiment of the present invention is shown. The steps of integrating the distinguishing peak and the standard fingerprint to obtain the fluctuation fingerprint and configuring the corresponding relationship between the fluctuation fingerprint and the fluctuation working condition are described in detail as follows: S303: Based on the preset DCS central control system, the generation time of the fluctuating working condition is recorded and a time window is established.

[0044] Record the occurrence and end time of the fluctuating conditions and create a time window.

[0045] S304: Read out the parameter adjustment in the DCS central control system within the time window, and store the parameter adjustment.

[0046] Determine the parameter adjustment under the generation time and end time, wherein the parameter adjustment is the adjustment of the valve position, pump speed and flow rate in the DCS central control system, and the parameter adjustment is stored.

[0047] In Example 7, Figure 5 The implementation process of the method for generating the industrial waste gas odor fingerprint provided by the embodiment of the present invention is shown. The steps of calculating the correlation coefficient between the test sample and the fluctuation fingerprint are described in detail as follows: S401: Define the light intensity of the characteristic peaks in the standard spectrum and the test spectrum, and record them as and ; From the spectrum, read out the light intensity of each characteristic peak in the standard spectrum and the test spectrum, and record them as and ; S402: Calculate the average values ​​of all light intensities in the standard spectrum and the test spectrum, and record them as and ; Use the preset correlation coefficient formula to calculate the correlation coefficient and construct the evaluation rules; The correlation coefficient formula is: ; in ,、 , To test the deviation of the light intensity of each characteristic peak in the spectrum, is the deviation of the light intensity of each characteristic peak in the standard spectrum, and r is the correlation coefficient.

[0048] The average values ​​of the light intensity in the standard spectrum and the test spectrum are calculated by weighted averaging, and the correlation coefficient formula is used to calculate the correlation between the standard spectrum and the test spectrum. The correlation coefficient formula is the Pearson correlation coefficient, which is used to determine whether there is a correlation between two variables. The value range of r is In this embodiment, if r=1 is calculated, it means that there is a positive correlation between the illumination intensities of the standard spectrum and the test spectrum, that is, the two increase or decrease at the same time. Conversely, if r=-1, it means that there is a negative correlation between the illumination intensities of the standard spectrum and the test spectrum. If r=0, it means that there is no correlation between the illumination intensities of the standard spectrum and the test spectrum. The evaluation rule is that the larger the correlation coefficient, the closer the test sample is to the exhaust gas components under normal operating conditions.

[0049] Figure 6 The structure block diagram of the industrial waste gas odor fingerprint generation system provided by an embodiment of the present invention is shown. The industrial waste gas odor fingerprint generation system 1 includes: The traversal module 11 is used to obtain the real-time parameters of the industrial equipment, configure the fluctuation range, and define the standard working conditions, extract the absorption characteristics of the industrial waste gas from the pre-deployed online spectrometer, generate an absorption spectrum, and extract several characteristic peaks, and traverse the wave numbers corresponding to the characteristic peaks; A transfer module 12 is used to create leaf nodes corresponding to the characteristic peaks one by one, write the wave number and characteristic peak into the leaf nodes, create a root node, integrate all leaf nodes, generate a standard fingerprint, and transfer the standard fingerprint into the root node; A configuration module 13 is used to define a fluctuation condition according to the real-time parameters, extract a distinguishing peak from the absorption spectrum corresponding to the fluctuation condition, use the distinguishing peak to shift the standard fingerprint to obtain a fluctuation fingerprint, and configure a corresponding relationship between the fluctuation fingerprint and the fluctuation condition; The estimation module 14 is used to obtain the absorption spectrum of the test sample and determine whether there is a distinguishing peak. If yes, calculate the correlation coefficient between the test sample and the fluctuation fingerprint, and find the fluctuation fingerprint with the largest correlation coefficient, define it as the target fingerprint, and estimate the exhaust gas components in the test sample. If not, calculate the correlation coefficient between the test sample and the standard fingerprint.

[0050] Figure 7 The structural block diagram of the system for generating the industrial waste gas odor fingerprint provided by the embodiment of the present invention is shown, and the traversal module 11 includes: A correction unit 111, configured to configure the influencing factors of the standard working condition and correct the fluctuation range; A definition unit 112, configured to determine whether the real-time parameter is within a fluctuation range, and if so, to capture a snapshot of the real-time parameter and define the snapshot as a standard operating condition; The correction unit 113 is used to extract the absorption peak from the absorption spectrum, perform preprocessing, correct the spectrum deviation in the absorption peak, and obtain the characteristic peak; The updating unit 114 is used to integrate all characteristic peaks, establish a standard spectrum library, and perform real-time updating using the real-time parameters.

[0051] Figure 8 The structure diagram of the system for generating the industrial waste gas odor fingerprint provided by the embodiment of the present invention is shown, and the transfer module 12 includes: The monitoring unit 121 is used to define monitoring nodes and calculate the strength of the monitoring nodes; The trigger unit 122 is used to construct an early warning strategy, and when the intensity is greater than a preset threshold, the early warning strategy is triggered.

[0052] Fig. 9 The structure diagram of the system for generating the industrial waste gas odor fingerprint provided by the embodiment of the present invention is shown, and the configuration module 13 includes: A segmentation unit 131 is used to segment the fluctuating operating condition into a plurality of levels, wherein the levels include: a low risk level, a medium risk level, and a high risk level; The issuing unit 132 is used to construct a trigger mechanism based on the high risk level, integrate the trigger mechanism into the root node, and issue the adjustment authority of the industrial equipment to the root node; The building unit 133 is used to record the generation time of the fluctuation condition and build a time window according to the preset DCS central control system; The storage unit 134 is used to read out the parameter adjustment in the DCS central control system within the time window and store the parameter adjustment.

[0053] Fig.10 The structural block diagram of the system for generating the industrial waste gas odor fingerprint provided by the embodiment of the present invention is shown, and the estimation module 14 includes: The calculation unit 141 is used to define the standard spectrum and the test spectrum, which are respectively recorded as and , calculate the average values ​​of the standard spectrum and the test spectrum, and record them as and ; The evaluation unit 142 is used to calculate the correlation coefficient using a preset correlation coefficient formula and construct an evaluation rule. The correlation coefficient formula is: ,in , , r is the correlation coefficient.

[0054] The traversal module 11 is mainly used to complete step S100, the transfer module 12 is mainly used to complete step S200, the configuration module 13 is mainly used to complete step S300, and the estimation module 14 is mainly used to complete step S400; The correction unit 111 is mainly used to complete step S101, the definition unit 112 is mainly used to complete step S102, the calibration unit 113 is mainly used to complete step S103, and the updating unit 114 is mainly used to complete step S104; The monitoring unit 121 is mainly used to complete step S201, and the triggering unit 122 is mainly used to complete step S202; The segmentation unit 131 is mainly used to complete step S301, the issuing unit 132 is mainly used to complete step S302, the building unit 133 is mainly used to complete step S303, and the storage unit 134 is mainly used to complete step S304; The calculation unit 141 is mainly used to complete step S401, and the evaluation unit 142 is mainly used to complete step S402.

[0055] The technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0056] The above-mentioned embodiments only express several implementation methods of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the patent of the present invention. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

[0057] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for generating an industrial waste gas odor fingerprint, characterized in that: The method comprises: Obtain the real-time parameters of industrial equipment, configure the fluctuation range, and define the standard working conditions. Extract the absorption characteristics of industrial waste gas from the pre-deployed online spectrometer, generate an absorption spectrum, extract several characteristic peaks, and traverse the wave numbers corresponding to the characteristic peaks; Create leaf nodes corresponding to the characteristic peaks one by one, write the wavenumbers and characteristic peaks into the leaf nodes, create a root node, integrate all leaf nodes, generate a standard fingerprint, and transfer the standard fingerprint into the root node; Based on the real-time parameters, a fluctuation condition is defined, and a distinguishing peak is extracted from the absorption spectrum corresponding to the fluctuation condition, the distinguishing peak and the standard fingerprint are integrated to obtain a fluctuation fingerprint, and a corresponding relationship between the fluctuation fingerprint and the fluctuation condition is configured; Obtain the absorption spectrum of the test sample to determine whether there is a distinguishing peak. If so, calculate the correlation coefficient between the test sample and the fluctuation fingerprint, and find the fluctuation fingerprint with the largest correlation coefficient, which is defined as the target fingerprint, to estimate the exhaust gas components in the test sample; If not, the exhaust composition of the test sample is estimated using the standard fingerprint.

2. The method for generating an industrial waste gas odor fingerprint according to claim 1, characterized in that: The steps of obtaining real-time parameters of industrial equipment, configuring fluctuation ranges, and defining standard working conditions include: Configuring the influencing factors of the standard working condition and correcting the fluctuation range; It is determined whether the real-time parameter is within the fluctuation range. If so, a snapshot of the real-time parameter is captured and the snapshot is defined as a standard operating condition.

3. The method for generating an industrial waste gas odor fingerprint according to claim 1, characterized in that: The steps of extracting the absorption characteristics of industrial waste gas from the pre-deployed online spectrometer, generating an absorption spectrum, extracting several characteristic peaks, and traversing the wave numbers corresponding to the characteristic peaks include: Extracting the absorption peak from the absorption spectrum, performing preprocessing, correcting the spectral deviation in the absorption peak, and obtaining a characteristic peak; All characteristic peaks are integrated to construct a standard spectrum library, and the library is updated in real time using the real-time parameters.

4. The method for generating an industrial waste gas odor fingerprint according to claim 1, characterized in that: The steps of creating leaf nodes corresponding to the characteristic peaks one by one, writing the wavenumbers and characteristic peaks into the leaf nodes, and creating a root node include: Defining monitoring nodes and calculating the intensity of the characteristic peaks; Construct an early warning strategy, and trigger the early warning strategy when the intensity is greater than a preset threshold.

5. The method for generating an industrial waste gas odor fingerprint according to claim 1, characterized in that: The step of defining a fluctuating operating condition based on the real-time parameters and extracting a distinguishing peak from an absorption spectrum corresponding to the fluctuating operating condition comprises: Dividing the fluctuating operating conditions into several levels, wherein the levels include: low risk level, medium risk level and high risk level; A trigger mechanism based on the high risk level is constructed, the trigger mechanism is integrated into a root node, and adjustment permissions for industrial equipment are issued to the root node.

6. The method for generating an industrial waste gas odor fingerprint according to claim 1, characterized in that: The step of integrating the distinguishing peak and the standard fingerprint to obtain the fluctuation fingerprint and configuring the corresponding relationship between the fluctuation fingerprint and the fluctuation working condition comprises: Based on the preset DCS central control system, the occurrence time of the fluctuating working condition is recorded and a time window is established; The parameter adjustment in the DCS central control system within the time window is read out and the parameter adjustment is stored.

7. The method for generating an industrial waste gas odor fingerprint according to claim 1, characterized in that: The step of calculating the correlation coefficient between the test sample and the fluctuation fingerprint comprises: Define the illumination intensity of the characteristic peaks in the standard spectrum and the test spectrum, and record them as and ; Calculate the average values ​​of all light intensities in the standard spectrum and the test spectrum, and record them as and ; Use the preset correlation coefficient formula to calculate the correlation coefficient and construct the evaluation rules; The correlation coefficient formula is: ； in ,、 , To test the deviation of the light intensity of each characteristic peak in the spectrum, is the deviation of the light intensity of each characteristic peak in the standard spectrum, and r is the correlation coefficient.

8. A system for generating industrial waste gas odor fingerprints, characterized in that: The system comprises: The traversal module is used to obtain the real-time parameters of industrial equipment, configure the fluctuation range, and define the standard working conditions. It extracts the absorption characteristics of industrial waste gas from the pre-deployed online spectrometer, generates an absorption spectrum, extracts several characteristic peaks, and traverses the wave numbers corresponding to the characteristic peaks; A transfer module is used to create leaf nodes corresponding to the characteristic peaks one by one, write the wave number and characteristic peak into the leaf nodes, create a root node, integrate all leaf nodes, generate a standard fingerprint, and transfer the standard fingerprint into the root node; A configuration module, for defining a fluctuation condition according to the real-time parameters, extracting a distinguishing peak from an absorption spectrum corresponding to the fluctuation condition, integrating the distinguishing peak and a standard fingerprint to obtain a fluctuation fingerprint, and configuring a corresponding relationship between the fluctuation fingerprint and the fluctuation condition; The estimation module is used to obtain the absorption spectrum of the test sample and determine whether there is a distinguishing peak. If so, calculate the correlation coefficient between the test sample and the fluctuation fingerprint, and find the fluctuation fingerprint with the largest correlation coefficient, which is defined as the target fingerprint, to estimate the exhaust gas components in the test sample. If not, use the standard fingerprint to estimate the exhaust gas components of the test sample.

9. The system for generating industrial waste gas odor fingerprint according to claim 8, characterized in that: The traversal module includes: A correction unit, used to configure the influencing factors of the standard working condition and correct the fluctuation range; a definition unit, configured to determine whether the real-time parameter is within a fluctuation range, and if so, to capture a snapshot of the real-time parameter and define the snapshot as a standard operating condition; A correction unit, used to extract an absorption peak from the absorption spectrum, perform preprocessing, correct the spectral deviation in the absorption peak, and obtain a characteristic peak; The updating unit is used to integrate all characteristic peaks, build a standard spectrum library, and perform real-time updating using the real-time parameters.

10. The system for generating industrial waste gas odor fingerprint according to claim 8, characterized in that: The transfer module comprises: A calculation unit, used to define a monitoring node and calculate the intensity of the characteristic peak; The trigger unit is used to construct an early warning strategy, and when the intensity is greater than a preset threshold, the early warning strategy is triggered.

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