An intermittent pollution source odor gas collection and monitoring control system

Abstract

The present invention discloses an intermittent pollution source odor gas collection and monitoring control system, which relates to the field of gas collection and monitoring. It is used to solve the problem that the constant air extraction mode cannot track gas changes in real time, resulting in unequal gas concentration and collection efficiency. The gas emission concentration, gas emission flow rate, adsorbent consumption efficiency, and absorbent operation duration are collected and input into the data analysis model to obtain the absorption evaluation coefficient, which is compared and analyzed with the preset absorption threshold to obtain the comparison result. According to the comparison result, it is determined that the absorbent dosage is insufficient, and then the adjustment value of the absorption intensity is determined. By calculation, the volume difference of odor emissions from the intermittent pollution source and the difference value of gas collection to saturation are obtained. Through the time series model, gas emission volume prediction analysis is carried out to generate an absorption rate plan, balance the gas concentration and collection efficiency, and improve the collection efficiency and save energy.

Description

Technical Field

[0001] The present invention relates to the field of gas collection and monitoring. More specifically, the present invention relates to a control system for collecting and monitoring the odor gas of intermittent pollution sources. Background Art

[0002] For the collection and monitoring of the odor gas of intermittent pollution sources, a constant-flow air extraction method is usually adopted to directly extract the odor gas around the pollution source into a filtering device or an exhaust port. Specifically, during the high-emission period of the intermittent pollution source, the air extraction pump operates at a constant flow rate in order to bring more pollutants into the treatment device and analyze the emission law of the intermittent pollution source, so as to increase the air extraction frequency or the frequency of replacing the filtering material during the high-emission period. The prior art has the following deficiencies:

[0003] At present, the concentration, composition, and emission amount of the intermittently emitted odor gas change with time and the technological process. The constant air extraction mode cannot track the gas change in real time, resulting in the inequality between the gas concentration and the collection efficiency, consuming energy while possibly causing insufficient gas collection and reducing the reliability of gas collection. Therefore, a control system for collecting and monitoring the odor gas of intermittent pollution sources is proposed.

[0004] The above information disclosed in the background art section is only used to enhance the understanding of the background of the present disclosure. Therefore, it may include information that does not constitute the prior art known to those of ordinary skill in the art. Summary of the Invention

[0005] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a control system for collecting and monitoring the odor gas of intermittent pollution sources, and solves the problems raised in the above background art by determining the adjustment value of the absorption intensity and the absorption rate.

[0006] To achieve the above object, the present invention provides the following technical solution. A control system for collecting and monitoring the odor gas of intermittent pollution sources includes a data acquisition module, a data processing module, a gas analysis module, an emission prediction module, and a visualization port; the modules are signal-connected to each other;

[0007] The data acquisition module is used to collect gas emission characteristic information and absorption device characteristic information. Through data processing, including data type conversion, missing value processing, data standardization, and feature extraction, the gas emission concentration, gas emission flow rate, adsorbent consumption efficiency, and absorbent operation duration are obtained and sent to the data processing module;

[0008] The data processing module is used to obtain the gas emission concentration, gas emission flow rate, adsorbent consumption efficiency, and absorbent operation duration, establish a data analysis model, obtain an absorption evaluation coefficient, and send it to the gas analysis module;

[0009] The gas analysis module is used to obtain the absorption evaluation coefficient, compare and analyze it with a preset absorption threshold to obtain a comparison result. According to the comparison result, it determines that the absorption dose is insufficient and sends it to the visualization port, then determines the adjustment value of the absorption intensity and sends it to the emission prediction module;

[0010] The emission prediction module is used to obtain the adjustment value of the absorption intensity, calculate the volume difference of the odor emissions from intermittent pollution sources and the difference value of gas collection to saturation according to the adjustment value, conduct gas emission prediction analysis through a time series model, generate an absorption rate plan, and send it to the visualization port;

[0011] The visualization port is used to receive the information corresponding to insufficient absorption dose and the absorption rate plan.

[0012] In a preferred embodiment, the gas emission characteristic information includes gas emission concentration and gas emission flow rate; the absorption device characteristic information includes adsorbent consumption efficiency and adsorbent operation duration;

[0013] By calculating the ratio of the target gas volume to the total gas volume, and then substituting it into the multivariable linear regression correction to obtain the influence of temperature and humidity on the gas concentration measurement, the obtained original gas concentrations are added up to calculate the gas emission concentration ; where i is the i-th unit time;

[0014] Based on the differential pressure method calculation, and substituting the current temperature and humidity into the multivariable linear regression correction to calculate the gas emission flow rate ;

[0015] The original adsorbent consumption efficiency is obtained by calculating the ratio of the actual consumption of the adsorbent in the current unit time to the mass of the removed pollutants, and the environmental correction coefficient is introduced and substituted into the original adsorbent consumption efficiency to obtain the adsorbent consumption efficiency ;

[0016] The adsorbent operation duration is obtained by counting the effective adsorption duration of the adsorbent within the unit time .

[0017] In a preferred embodiment, the gas emission concentration , the gas emission flow rate , the adsorbent consumption efficiency and the adsorbent operation duration are obtained to generate an absorption evaluation coefficient , and the formula is:

[0018] ;

[0019] In the formula, is the absorption evaluation coefficient, , , and are respectively the preset proportionality coefficients of gas emission concentration, gas emission flow rate, adsorbent consumption efficiency, and absorbent operation duration, and , , and are all greater than 0.

[0020] In a preferred embodiment, after obtaining the absorption evaluation coefficient, the absorption evaluation coefficient is compared and analyzed with the continuously iterated absorption threshold;

[0021] If the absorption evaluation coefficient is greater than or equal to the absorption threshold, the absorption intensity corresponding to the current unit time is marked as the decreasing intensity, and a decreasing signal is generated;

[0022] If the absorption evaluation coefficient is less than the absorption threshold, the absorption intensity corresponding to the current unit time is marked as the increasing intensity, and an increasing signal is generated.

[0023] In a preferred embodiment, the numerical cumulative value of the absorption evaluation coefficients greater than or equal to the absorption threshold is respectively counted and weighted and subtracted from the numerical cumulative value of the absorption evaluation coefficients less than the absorption threshold to obtain the adjustment possibility of the absorption intensity. The specific formula is as follows:

[0024] ;

[0025] In the formula, Q is the adjustment possibility of the absorption intensity, is the numerical cumulative value of the absorption evaluation coefficients greater than or equal to the absorption threshold, is the numerical cumulative value of the absorption evaluation coefficients less than the absorption threshold; and are respectively the weight coefficients of the numerical cumulative value of the absorption evaluation coefficients greater than or equal to the absorption threshold and the numerical cumulative value of the absorption evaluation coefficients less than the absorption threshold;

[0026] The sign of the Q value is preferentially evaluated and compared with the preset decreasing threshold and increasing threshold. Specifically, if Q is greater than 0, it is compared with the decreasing threshold. If Q is less than 0, it is compared with the increasing threshold. If Q is equal to 0, the absorption intensity is not adjusted. Specifically:

[0027] Compare Q with the decreasing threshold. If Q is greater than or equal to the decreasing threshold, adjust the absorption intensity to the first decreasing intensity. If Q is less than the decreasing threshold, adjust the absorption intensity to the second decreasing intensity;

[0028] Compare Q with the increasing threshold. If Q is greater than or equal to the increasing threshold, generate an alarm signal and the words "absorbent dose insufficient" and send them to the visualization port. If Q is less than the increasing threshold, adjust the absorption intensity to the first increasing intensity.

[0029] In a preferred embodiment, each obtained adjustment value of the absorption intensity represents a difference in the odor emission volume of the current intermittent pollution source;

[0030] The odor emission volume difference of the intermittent pollution source is obtained by subtracting the odor emission volumes of the intermittent pollution source in adjacent unit times;

[0031] By setting the saturation threshold of the absorption device, subtracting the current gas collection amount from the saturation threshold to obtain the gas collection to saturation difference value.

[0032] In a preferred embodiment, the time series model used is the ARIMAX model. The specific steps for predicting the gas emission volume through the time series model are as follows:

[0033] Step A1, obtain the data for prediction;

[0034] Step A2, establish the ARIMAX model;

[0035] Step A3, use the maximum likelihood estimation (MLE) method to estimate the parameters of the ARIMAX model;

[0036] Step A4, verify the effect of the fitting model, and check the goodness of fit of the model through the residual analysis method;

[0037] Step A5, use the fitted model to predict the future absorption rate scheme, and take the maximum value of the prediction result as the highest point of the absorption rate in the future unit time.

[0038] In a preferred embodiment, the exogenous variables in the ARIMAX model include gas emission concentration, gas emission flow rate, adsorbent consumption efficiency, absorbent operation duration, odor emission volume difference of the intermittent pollution source, and gas collection to saturation difference value. The ARIMAX model formula is:

[0039]

[0040] In the formula, is the absorption rate of the current unit time, is the absorption rate of the unit time, is the constant term, is the autoregressive parameter of the i-th order, is the order of the autoregressive term, is the moving average parameter of the j-th order, is the current unit time, is the order of the moving average term, is the white noise term, representing random error, is the The white noise term of the time interval is the coefficient of the exogenous variable of, is the lag order of the exogenous variable, is the exogenous variable lagged by k periods.

[0041] In a preferred embodiment, in step A3, , , , , are calculated and obtained by the maximum likelihood estimation method.

[0042] Technical effects and advantages of the present invention:

[0043] 1. The present invention collects the gas emission concentration, gas emission flow rate, adsorbent consumption efficiency, and absorbent operation duration and inputs them into the data analysis model to obtain the absorption evaluation coefficient, and compares and analyzes it with the preset absorption threshold to obtain the comparison result. According to the comparison result, it is determined that the absorbent dosage is insufficient, and then the adjustment value of the absorption intensity is determined, realizing the dynamic tracking of the emission concentration, flow rate, and adsorbent performance, balancing the gas concentration and collection efficiency, and improving the collection efficiency and saving energy.

[0044] 2. The present invention calculates the intermittent pollution source odor emission volume difference and the gas collection to saturation difference value through the adjustment value of the absorption intensity, and conducts gas emission volume prediction analysis through the time series model to generate the absorption rate plan, avoiding gas reflux when the collection device is about to be saturated, reducing the risk of odor diffusion, improving the correctness of monitoring and taking corresponding measures, and reducing unnecessary adsorbent replacement to save resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 is a schematic module diagram of an intermittent pollution source odor gas collection and monitoring control system of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0046] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0047] The present disclosure mainly solves the problems of insufficient gas collection during high-concentration emission periods and excessive energy consumption during low-concentration emission periods. Among them, the odor of the pollution source has the characteristics of polluting the environment and being pungent, so the odor concentration of the gas is not considered, and it should be ensured that all the odor of the pollution source is collected to ensure the practicability of the system;

[0048] Specifically, by collecting real-time gas emission characteristic information and absorber characteristic information, analyzing the changing trends of gas concentration and gas volume, and using a time series model to predict and analyze future gas emissions, an absorber rate adjustment plan is determined.

[0049] Embodiment 1

[0050] The present invention discloses an intermittent pollution source odor gas collection and monitoring control system, as Figure 1 shown, which includes a data collection module, a data processing module, a gas analysis module, an emission prediction module, and a visualization port; the modules are signal-connected to each other;

[0051] The data collection module is used to collect gas emission characteristic information and absorber characteristic information. Through digital processing, including data type conversion, missing value processing, data standardization, and feature extraction, gas emission concentration, gas emission flow rate, adsorbent consumption efficiency, and absorber operation duration are obtained and sent to the data processing module;

[0052] Among them, data type conversion refers to converting the original data collected by the sensor into a standardized data type. For example, converting the voltage signal of the sensor into a concentration value and a flow unit, etc.;

[0053] Missing value processing refers to filling in the missing data that may occur during the sensor collection process through interpolation and mean filling to ensure the continuity and integrity of the data and avoid errors in subsequent processing;

[0054] Data standardization standardizes each item of collected data according to a unified scale, and normalizes parameters such as concentration value, temperature, and humidity;

[0055] Specifically, the above data operation methods are all prior arts and will not be elaborated here;

[0056] Among them, the gas emission characteristic information includes gas emission concentration and gas emission flow rate; the absorber characteristic information includes adsorbent consumption efficiency and absorber operation duration;

[0057] Specifically, the gas emission concentration, gas emission flow rate, adsorbent consumption efficiency, and absorber operation duration are all obtained in the current unit time. Further, the gas emission concentration and gas emission flow rate both consider the influence brought by environmental factors and will not be elaborated here;

[0058] The acquisition logic of the gas emission concentration is to measure the original gas concentration through gas, temperature, and humidity sensors, and record the environmental temperature and humidity parameters. Among them, it is calculated by the ratio of the target gas volume to the total gas volume, and then the influence of temperature and humidity on the gas concentration measurement is obtained through multivariate linear regression correction. The obtained original gas concentrations are added to calculate the gas emission concentration. where i is the i-th unit time;

[0059] Specifically, the original concentration data is adjusted through multivariate linear regression to eliminate the deviation caused by environmental factors. The formula is expressed as:

[0060]

[0061] In the formula, is the gas emission concentration, is the original concentration value, and the current temperature and humidity, and are the temperature and humidity under standard environmental conditions respectively, and are the correction coefficients;

[0062] It should be noted that the temperature and humidity under standard environmental conditions mean that under the current corresponding temperature and humidity conditions, the measured gas value concentration is the gas emission concentration. Specifically, the standard environment is obtained by the experimenters based on the gas test results and the corresponding relationship between the gas concentration and environmental factors, which is not limited here;

[0063] Specifically, the setting of the unit time is obtained by the experimenters based on the intermittent characteristics of the specific gas flow rate and the non-emission time length, which will not be elaborated here;

[0064] The acquisition logic of the gas emission flow rate is calculated based on the differential pressure method and is brought into the multivariate linear regression correction calculation with the current temperature and humidity to obtain the gas emission flow rate ;

[0065] Specifically, the differential pressure method is based on Bernoulli's equation and uses the differential pressure generated by the fluid at different positions in the pipeline to calculate the flow rate. The specific formula is expressed as follows:

[0066]

[0067] In the formula, is the original gas flow rate, is the differential pressure between the measurement positions, is the density of the gas;

[0068] Among them, the gas density is obtained through the ideal gas law It is obtained that considering the influence of temperature T and air pressure P, where R is the gas constant;

[0069] The specific multi-variable linear regression correction calculation formula is as follows:

[0070]

[0071] where is the gas emission flow rate, and are the measured current temperature and the standard temperature respectively, and are the density of dry air and the density of wet air respectively;

[0072] Among them, the correction formula for the influence of humidity on gas density is:

[0073]

[0074] where is the partial pressure of water vapor, and P is the total air pressure; specifically, the partial pressure of water vapor is related to the relative humidity and temperature;

[0075] It should be noted that the changes in temperature and humidity will change the density and viscosity of the gas, thereby indirectly affecting the accuracy of the calculated value of the gas flow rate. The specific values of the gas characteristics obtained by the experimenters by bringing in environmental factors improve the calculation accuracy of the gas emission concentration and the gas emission flow rate;

[0076] The acquisition logic of the adsorbent consumption efficiency is to calculate the original adsorbent consumption efficiency by taking the ratio of the actual consumption of the adsorbent per unit time to the mass of the removed pollutant;

[0077] Specifically, the mass of the removed pollutant is determined by the change in gas concentration, that is, by comparing the difference in pollutant concentration before and after adsorption. The specific formula is expressed as:

[0078]

[0079] where is the mass of the removed pollutant, is the gas flow rate, is the difference in pollutant concentration before and after adsorption;

[0080] Introduce the environmental correction coefficient into the original adsorbent consumption efficiency to obtain the adsorbent consumption efficiency ; the specific formula is as follows:

[0081]

[0082] where is the adsorbent consumption efficiency, is the consumption efficiency of the original adsorbent, which is a correction function of temperature T and humidity H;

[0083] It should be noted that the environmental correction coefficient includes the correction functions of temperature and humidity. The expressions and calculations of the specific correction functions have been described above (for example, multivariate linear regression correction is an expression of a correction function), and will not be elaborated here;

[0084] The acquisition logic of the absorbent operation duration is to obtain the absorbent operation duration by counting the effective adsorption duration of the absorbent per unit time ;

[0085] Specifically, the method of counting the duration is defined as when the removal efficiency of the absorbent meets the set conditions, it is regarded as the effective adsorption time, and the length of this time period is included in the cumulative operation duration;

[0086] It should be noted that the specific setting of the set conditions is set by the experimenter according to the absorbent dosage and absorbent characteristics. For example, when the removal efficiency is greater than or equal to 90%, it is set as the effective adsorption waiting, and there is no limitation here;

[0087] The data processing module is used to obtain the gas emission concentration, gas emission flow rate, adsorbent consumption efficiency, and absorbent operation duration, establish a data analysis model, obtain the absorption evaluation coefficient, and send it to the gas analysis module;

[0088] Among them, the data analysis model refers to a weighted analysis model, and the absorption evaluation coefficient is generated through weighted calculation;

[0089] Obtain the gas emission concentration 、the gas emission flow rate 、the adsorbent consumption efficiency and the absorbent operation duration , generate the absorption evaluation coefficient , and the formula based on which is:

[0090]

[0091] In the formula, is the absorption evaluation coefficient, 、 、 and are the preset proportionality coefficients of the gas emission concentration, gas emission flow rate, adsorbent consumption efficiency, and absorbent operation duration respectively, and 、 、 and are all greater than 0;

[0092] Among them, the gas emission concentration, gas emission flow rate, adsorbent consumption efficiency and absorbent operation time are all digital manifestations of the adjustment value of the absorption intensity of the current absorption device directly expressed;

[0093] It can be seen from the above formula that when the adsorbent consumption efficiency and the absorbent operation time are greater, it means that the performance of the absorbent is better and it can effectively remove more gas components, indicating that the higher the absorption efficiency, the stronger the gas removal capacity, the lower the absorption intensity of the absorption device can be, and the greater the absorption evaluation coefficient. Conversely, the greater the gas emission concentration and gas emission flow rate, the smaller the deviation evaluation coefficient.

[0094] The gas analysis module is used to obtain the absorption evaluation coefficient and compare it with the preset absorption threshold to obtain the comparison result. According to the comparison result, it is determined that the absorption dose is insufficient and sent to the visualization port, and then the adjustment value of the absorption intensity is determined and sent to the emission prediction module;

[0095] The logic of obtaining the absorption threshold is to collect a set of historical absorption intensity adjustment values, including manual adjustments by users and adjustments set in advance by users, and then divide the data set into a training set and a test set, set the evaluation index and clustering algorithm, and in each round of cross-validation, train the model on the training set and evaluate the model performance on the test set, and then adjust the absorption threshold according to the performance of the validation set. Therefore, the absorption threshold is constantly updated;

[0096] In the present invention, clustering algorithm is a type of unsupervised learning algorithm, which is used to divide the data points in the data set into groups or clusters with similarities; a common one is K-means clustering, which divides the data points in the data set into K clusters, so that the distance between the data point of each curve and the center point (centroid) of the cluster to which it belongs is minimized, and finally the effect of the adjusted absorption threshold is measured by the Euclidean distance, so as to set the absorption threshold;

[0097] After obtaining the absorption evaluation coefficient, the absorption evaluation coefficient is compared and analyzed with the continuously iterated absorption threshold;

[0098] If the absorption evaluation coefficient is greater than or equal to the absorption threshold, the absorption intensity corresponding to the current unit time is marked as a reduced intensity, and a reduction signal is generated;

[0099] If the absorption evaluation coefficient is less than the absorption threshold, the absorption intensity corresponding to the current unit time is marked as an increased intensity, and an increase signal is generated;

[0100] The numerical accumulation values of the absorption evaluation coefficients greater than or equal to the absorption threshold are counted respectively and weighted subtraction is performed with the numerical accumulation values of the absorption evaluation coefficients less than the absorption threshold to obtain the adjustment possibility of the absorption intensity. The specific formula is as follows:

[0101]

[0102] In the formula, Q is the adjustment possibility of the absorption intensity, is the numerical cumulative value of the absorption evaluation coefficient greater than or equal to the absorption threshold, is the numerical cumulative value of the absorption evaluation coefficient less than the absorption threshold; and are the weight coefficients of the numerical cumulative value of the absorption evaluation coefficient greater than or equal to the absorption threshold and the numerical cumulative value of the absorption evaluation coefficient less than the absorption threshold respectively;

[0103] First, evaluate the positive and negative of the Q value, and compare it with the preset reduction threshold and increase threshold. Specifically, if Q is greater than 0, then compare it with the reduction threshold. If Q is less than 0, then compare it with the increase threshold. If Q is equal to 0, then the absorption intensity is not adjusted. Specifically:

[0104] Compare Q with the reduction threshold. If Q is greater than or equal to the reduction threshold, then adjust the absorption intensity to the first reduction intensity. If Q is less than the reduction threshold, then adjust the absorption intensity to the second reduction intensity;

[0105] Compare Q with the increase threshold. If Q is greater than or equal to the increase threshold, then generate an alarm signal and the words "insufficient absorption dose" and send them to the visualization port. If Q is less than the increase threshold, then adjust the absorption intensity to the first increase intensity;

[0106] It should be noted that the first reduction intensity, the second reduction intensity, and the first increase intensity are all adjustment values of the absorption intensity. Those skilled in the art can understand that, for example, the first reduction intensity is set to a 25% reduction, the second reduction intensity is set to a 10% reduction, the first increase intensity is set to a 20% increase, etc., which are not limited here;

[0107] Specifically, for generating an alarm signal, those skilled in the art can understand that although increasing the absorption intensity can meet the collection of intermittent pollution source odors, it consumes too much energy, which may indicate insufficient current absorption dose or low absorption efficiency. It is necessary to replace or substitute the absorbent to avoid excessive energy consumption. Further, the expression of the generated words is not limited, but is defined by the experimenter when designing the system, which will not be elaborated here;

[0108] The present invention collects the gas emission concentration, gas emission flow rate, adsorbent consumption efficiency, and absorbent operation duration and substitutes them into the data analysis model to obtain the absorption evaluation coefficient, and compares and analyzes it with the preset absorption threshold to obtain the comparison result. According to the comparison result, it determines that the absorption dose is insufficient, and then determines the adjustment value of the absorption intensity, realizing the dynamic tracking of the emission concentration, flow rate, and adsorbent performance, balancing the gas concentration and collection efficiency, and improving the collection efficiency and saving energy.

[0109] Example 2

[0110] In Example 1 of the present invention, emphasis was placed on exemplifying the collection of gas emission concentration, gas emission flow rate, adsorbent consumption efficiency, and absorbent operation duration and bringing them into the data analysis model to obtain the absorption evaluation coefficient, and comparing and analyzing it with the preset absorption threshold to obtain the comparison result. According to the comparison result, it was determined that the absorbent dosage was insufficient and sent to the visualization port, and then the adjustment value of the absorption intensity was determined; however, in Example 1, only the adjustment of the absorption intensity was used to dynamically track the gas collection. Obviously, when the collection device was about to be saturated, intermittent dynamic collection would instead cause the collection device to be saturated and lead to gas reflux, affecting the collection efficiency and the risk of odor diffusion; for the above problems, Example 2 of the present invention is further refined;

[0111] Specifically, the saturated state and the about-to-be-saturated state of the collection device are set by the experimenter according to the specific device capacity and volume, which will not be elaborated here;

[0112] It can be understood that the experimenter can set a threshold according to the about-to-be-saturated state, and generate a warning signal and other specific operations when the threshold is reached, which will not be limited here;

[0113] The emission prediction module is used to obtain the adjustment value of the absorption intensity, calculate the odor emission volume difference of the intermittent pollution source and the gas collection-to-saturation difference value according to the adjustment value, perform gas emission prediction analysis through the time series model, generate the absorption rate plan, and send it to the visualization port;

[0114] Among them, each time the adjustment value of the absorption intensity is obtained, it represents that there is a difference in the odor emission volume of the current intermittent pollution source;

[0115] The acquisition logic of the odor emission volume difference of the intermittent pollution source is to record the gas emission volume within each unit time at each unit time. Specifically, the odor emission volume difference of the intermittent pollution source is calculated by subtracting the emission volumes of adjacent unit times; the specific formula is as follows:

[0116]

[0117] In the formula, is the odor emission volume difference of the intermittent pollution source, is the gas emission volume of the current unit time, is the gas emission volume of the previous unit time, where i is the i-th unit time;

[0118] The acquisition logic of the gas collection-to-saturation difference value is to calculate the difference between the current gas collection volume and the saturation threshold by setting the saturation threshold of the absorption device to obtain the gas collection-to-saturation difference value;

[0119] It should be noted that the saturation threshold is set by the experimenters according to the state of being about to be saturated, which will not be elaborated here;

[0120] It should be noted that the time series model in this embodiment adopts the ARIMAX model. Generating the absorption rate scheme means that under the condition of determining the adjustment value of the absorption intensity, through further analysis and adjustment, the absorption rate scheme is made more scientific and reasonable, so as to achieve the overall control of the absorption of odor and avoid the saturation of the collection device;

[0121] Furthermore, the specific steps of predicting the gas emission amount through the time series model are as follows:

[0122] Step A1, obtain the data for prediction;

[0123] Step A2, establish an ARIMAX model;

[0124] Step A3, use the maximum likelihood estimation (MLE) method to estimate the parameters of the ARIMAX model;

[0125] Step A4, verify the effect of the fitted model, and check the goodness of fit of the model through the residual analysis method;

[0126] Step A5, use the fitted model to predict the future absorption rate scheme, and take the maximum value of the prediction result as the highest point of the absorption rate per unit time in the future.

[0127] Specifically, the data for prediction includes the gas emission concentration, gas emission flow rate, adsorbent consumption efficiency, absorbent operation duration, and absorption rate data corresponding to each unit time; among them, the gas emission concentration, gas emission flow rate, adsorbent consumption efficiency, and absorbent operation duration corresponding to each unit time have been exemplified in Embodiment 1 and will not be elaborated here;

[0128] The absorption rate data refers to the historical absorption rate data, and this data is used as the main variable of the time series;

[0129] Furthermore, the basic form of the ARIMAX model is:

[0130]

[0131] In the formula, is the absorption rate of the current unit time, is the absorption rate of the unit time, is the constant term, is the autoregressive parameter of the i-th order, is the order of the autoregressive term, is the moving average parameter of the j-th order, is the current unit time, is the order of the moving average term, is the white noise term, representing random error, is the white noise term at the time interval, is the coefficient of the exogenous variable is the lag order of the exogenous variable, is the exogenous variable lagged by k periods;

[0132] It should be noted that the exogenous variable part can incorporate the influence of other relevant variables (such as gas emission concentration, gas emission flow rate, adsorbent consumption efficiency, absorbent operation duration, intermittent pollution source odor emission volume difference, and gas collection to saturation difference value) on the absorption rate;

[0133] It should be noted that in step A3, , , , , are calculated and obtained through the maximum likelihood estimation (MLE) method. The specific steps are as follows:

[0134] The error term obeys a normal distribution , then the likelihood function is:

[0135]

[0136] Take the logarithm of the likelihood function to obtain the log-likelihood function:

[0137]

[0138] By maximizing the log-likelihood function, the parameter estimates , , , , ;

[0139] Dynamically adjust the absorption rate strategy based on the maximum, minimum, and average values of the prediction results, and send it to the visualization port;

[0140] The following is an example of this embodiment:

[0141] The maximum value of the prediction result represents the highest point of the absorption rate in the future unit time. Formulate the absorption strategy during the peak period. At the predicted peak period of the absorption rate (i.e., the time point close to or equal to ), increase the output power of the device by 20% to ensure the stable collection of gas, avoid gas leakage, and at the same time generate an alarm message to remind the monitoring personnel to handle the gas in the collection device in a timely manner;

[0142] According to the lowest value of the prediction result or the low valley interval, formulate an absorption strategy during the low valley period. During the low absorption rate period (i.e., the time point close to or lower than ), reduce the output power of 15% of the device to extend the collection duration of the collection device;

[0143] According to the average value of the prediction result , formulate a balanced period absorption strategy. During the time period when the absorption rate is close to the average value, maintain the normal output of the device to ensure the continuous and stable operation of gas collection;

[0144] Among them, the settings for the peak period, balanced period, and low valley period are specifically implemented and divided by the experimenters, and the boundaries of this division are not limited;

[0145] The visualization port is used to receive information corresponding to insufficient absorption dose and the absorption rate scheme;

[0146] The present invention calculates the volume difference of odor emissions from intermittent pollution sources and the difference value of gas collection to saturation through the adjustment value of absorption intensity, conducts gas emission prediction analysis through a time series model, generates an absorption rate scheme, avoids gas reflux when the collection device is about to be saturated, reduces the risk of odor diffusion, improves the correctness of monitoring and corresponding measures, and reduces unnecessary adsorbent replacement to save resources.

[0147] The above formulas are all dimensionless and take their numerical calculations. The formula is obtained by collecting a large amount of data and performing software simulation to obtain a formula closest to the actual situation. The preset parameters in the formula are set by those skilled in the art according to the actual situation.

[0148] The above embodiments can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the processes or functions described in the embodiments of the present application are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center by wired or wireless (such as infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that can be accessed by a computer, or a data storage device such as a server or data center that contains one or more collections of available media. The available medium can be a magnetic medium (such as a floppy disk, hard disk, or magnetic tape), an optical medium (such as a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state drive.

[0149] It should be understood that in various embodiments of the present application, the magnitudes of the serial numbers of the above processes do not imply the order of execution, and the order of execution of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.

[0150] Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present application.

[0151] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the systems, devices, and units described above can refer to the corresponding processes in the foregoing method embodiments, and will not be elaborated herein.

[0152] In several embodiments provided in the present application, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces. The indirect couplings or communication connections of the devices or units can be in electrical, mechanical, or other forms.

[0153] The units described as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they can be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0154] In addition, in each embodiment of the present application, the functional units can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit.

[0155] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in each embodiment of the present application. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical discs that can store program codes.

[0156] The above is only the specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed in the present application, and all should be covered by the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. An intermittent pollution source odor gas collection and monitoring control system, characterized in that: It includes a data acquisition module, a data processing module, a gas analysis module, an emission prediction module, and a visualization port; the modules are signal-connected to each other; The data acquisition module is used to collect gas emission characteristic information and absorber characteristic information. Through digital processing, including data type conversion, missing value processing, data standardization, and feature extraction, it obtains gas emission concentration, gas emission flow rate, adsorbent consumption efficiency, and absorber operation duration, and sends them to the data processing module; The data processing module is used to obtain the gas emission concentration, gas emission flow rate, adsorbent consumption efficiency, and absorber operation duration, establish a data analysis model, obtain an absorption evaluation coefficient, and send it to the gas analysis module; The gas analysis module is used to obtain the absorption evaluation coefficient, compare and analyze it with a preset absorption threshold to obtain a comparison result. According to the comparison result, it determines that the absorbent dosage is insufficient and sends it to the visualization port, and then determines the adjustment value of the absorption intensity and sends it to the emission prediction module; The emission prediction module is used to obtain the adjustment value of the absorption intensity, calculate the difference in the odor emission volume of the intermittent pollution source and the difference in gas collection to saturation according to the adjustment value, conduct gas emission prediction analysis through a time series model, generate an absorption rate plan, and send it to the visualization port; The visualization port is used to receive the information corresponding to the insufficient absorbent dosage and the absorption rate plan; The gas emission characteristic information includes gas emission concentration and gas emission flow rate; the absorber characteristic information includes adsorbent consumption efficiency and absorber operation duration; Calculated by the ratio of the target gas volume to the total gas volume, and then the influence of temperature and humidity on gas concentration measurement is obtained through multivariate linear regression correction. The obtained original gas concentrations are added together to obtain the gas emission concentration ; where i is the i-th unit time; Calculated based on the differential pressure method, and the current temperature and humidity are brought into a multi-variable linear regression correction calculation to obtain the gas emission flow rate ; The original adsorbent consumption efficiency is calculated by taking the ratio of the actual consumption of the adsorbent in the current unit time to the mass of the removed pollutant. The environmental correction factor is introduced and substituted into the original adsorbent consumption efficiency to obtain the adsorbent consumption efficiency ; The operating duration of the absorbent is obtained by counting the effective adsorption duration of the absorbent per unit time ; Obtain the gas emission concentration , the gas emission flow rate , the adsorbent consumption efficiency and the absorbent operation duration , generate an absorption evaluation coefficient , and the formula is as follows: ； Wherein, is the absorption evaluation coefficient, , , and are respectively the preset proportionality coefficients of the gas emission concentration, the gas emission flow rate, the adsorbent consumption efficiency, and the absorbent operation duration, and , , and are all greater than 0; Respectively count the numerical cumulative value of the absorption evaluation coefficient greater than or equal to the absorption threshold and perform weighted subtraction calculation with the numerical cumulative value of the absorption evaluation coefficient less than the absorption threshold to obtain the adjustment possibility of the absorption intensity. The specific formula is as follows: ； Wherein, Q is the adjustability of the absorption intensity, is the numerical cumulative value of the absorption evaluation coefficient greater than or equal to the absorption threshold, is the numerical cumulative value of the absorption evaluation coefficient less than the absorption threshold; and are the weight coefficients of the numerical cumulative value of the absorption evaluation coefficient greater than or equal to the absorption threshold and the numerical cumulative value of the absorption evaluation coefficient less than the absorption threshold, respectively.

2. The intermittent pollution source odor gas collection and monitoring control system according to claim 1, wherein: After obtaining the absorption evaluation coefficient, compare and analyze the absorption evaluation coefficient with the continuously iterated absorption threshold; If the absorption evaluation coefficient is greater than or equal to the absorption threshold, mark the absorption intensity corresponding to the current unit time as the decreasing intensity and generate a decreasing signal; If the absorption evaluation coefficient is less than the absorption threshold, mark the absorption intensity corresponding to the current unit time as the increasing intensity and generate an increasing signal.

3. The intermittent pollution source odor gas collection and monitoring control system according to claim 2, characterized in that: Give priority to evaluating the positive and negative of the Q value and compare it with the preset decreasing threshold and increasing threshold. Specifically, if Q is greater than 0, bring it into the decreasing threshold for comparison. If Q is less than 0, bring it into the increasing threshold for comparison. If Q is equal to 0, do not adjust the absorption intensity. Specifically: Compare Q with the decreasing threshold. If Q is greater than or equal to the decreasing threshold, adjust the absorption intensity to the first decreasing intensity. If Q is less than the decreasing threshold, adjust the absorption intensity to the second decreasing intensity; Compare Q with the increasing threshold. If Q is greater than or equal to the increasing threshold, generate an alarm signal and send the words of insufficient absorbent dosage to the visualization port; if Q is less than the increasing threshold, adjust the absorption intensity to the first increasing intensity.

4. An intermittent pollution source odor gas collection and monitoring control system according to claim 3, characterized in that: Each time the adjustment value of the absorption intensity is obtained, it represents that there is a difference in the odor emission volume of the current intermittent pollution source; The odor emission volume difference of the intermittent pollution source is calculated by subtracting the odor emission volumes of adjacent unit time intervals of the intermittent pollution source. By setting the saturation threshold of the absorption device, the difference value of gas collection to saturation is calculated by subtracting the current gas collection volume from the saturation threshold.

5. The intermittent pollution source odor gas collection and monitoring control system according to claim 4, characterized in that: The time series model used is the ARIMAX model. The specific steps for predicting the gas emission volume through the time series model are as follows: Step A1, obtain the data for prediction. Step A2, establish the ARIMAX model. Step A3, use the maximum likelihood estimation (MLE) method to estimate the parameters of the ARIMAX model. Step A4, verify the effect of the fitted model and check the goodness of fit of the model through the residual analysis method. Step A5, use the fitted model to predict the future absorption rate plan, and take the maximum value of the prediction result as the highest point of the absorption rate per unit time in the future.

6. The intermittent pollution source odor gas collection and monitoring control system according to claim 5, characterized in that: The exogenous variables in the ARIMAX model include gas emission concentration, gas emission flow rate, adsorbent consumption efficiency, absorbent operation duration, the odor emission volume difference of the intermittent pollution source, and the difference value of gas collection to saturation. The ARIMAX model formula is: ； In the formula, is the absorption rate at the current unit time, is the absorption rate at the unit time, is a constant term, is the autoregressive parameter of the i-th order, is the order of the autoregressive term, is the moving average parameter of the j-th order, is the current unit time, is the order of the moving average term, is a white noise term, representing random error, is the white noise term at the time interval, is an exogenous variable coefficient, is the lag order of the exogenous variable, is the exogenous variable lagged by k periods.

7. An intermittent pollution source odor gas collection and monitoring control system according to claim 6, characterized in that: In step A3, , , , , are obtained by calculation using the maximum likelihood estimation method.

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