Automatic calibration device and method for continuously monitoring smoke concentration

Abstract

The invention relates to an automatic calibration device and method for continuously monitoring smoke dust concentration, and belongs to the technical field of environment monitoring. The device comprises a drying device, a dynamic heating system, a receiver and a radioactive source, a drying position, a sampling position and a detection position are sequentially arranged from left to right or from right to left; wherein the position where the drying device is located is a drying position, the lower portion of an exhaust pipe wrapped by the dynamic heating system is a sampling position, and the middle position where the receiver and the radioactive source are located is a beta-ray intensity detection position; and calculating the concentration of the smoke dust to be measured by adopting a smoke dust concentration automatic calibration algorithm according to the measured beta-ray intensity and sampling flow. According to the invention, long-time, high-precision, continuous and reliable operation of the light scattering smoke dust concentration continuous monitoring instrument can be ensured.

Description

Technical Field

[0001] The present invention belongs to the technical field of environmental monitoring, and relates to an automatic calibration device and method for continuous monitoring of soot concentration. Background Art

[0002] The main sources of pollution in the atmospheric environment come from the flue gas emissions of stationary pollution sources (such as coal-fired power plants, etc.). The soot particles therein are suspended in the air for a long time, which will not only reduce the amount of solar radiation, resulting in poor growth and development of plants, but also cause the "heat island effect" of the ground air. In addition, if humans inhale soot for a long time, it may cause various diseases. Therefore, HJ 76-2017 "Technical Requirements and Detection Methods for Continuous Emission Monitoring Systems of Stationary Pollution Sources" clearly requires that the soot concentration monitoring system should have a detection lower limit of ≤0.5 mg / m 3 and be equipped with a regular calibration function to ensure the validity of monitoring data.

[0003] In the field of continuous monitoring technology for soot concentration, domestic and foreign scholars have formed a variety of technical routes: In terms of optical measurement methods, the three-wavelength laser scattering method proposed by the Han Jinke team (Measurement Science and Technology, 2020) analyzes the incident light in three bands of 532 nm, 650 nm, and 980 nm. Theoretically, it can cover the particle size range of 0.1-10 μm. However, in the actual industrial environment, the dynamic change of the refractive index of particulate matter caused by the fluctuation of combustion conditions results in a deviation of ±15% in the calibration curve. Although the light scattering integration system developed by Zhang Chenyu et al. (Environmental Monitoring in China, 2021) uses Gaussian beam collimation technology to extend the measurement path to 2 meters, the uneven spatial distribution caused by flue gas turbulence still causes the problem of insufficient representativeness of local concentration.

[0004] In terms of improving detection accuracy, the direct-reading detector designed by the Zhao Te team (Chinese Journal of Environmental Engineering, 2022) based on the β-ray attenuation principle can eliminate more than 90% of the water mist interference through a 150°C constant temperature vaporization module. However, the C-14 radiation source it uses has a half-life decay (the signal intensity decreases by about 3.7% per year), and frequent source strength compensation calibration is required. Although the wind tunnel calibration device constructed by Zhao Li et al. (Chinese Journal of Scientific Instrument, 2019) can simulate a standard concentration field of 0-200 mg / m 3 , the temperature and humidity difference between the laboratory environment and the on-site working conditions results in a calibration transfer error of more than 8%.

[0005] In terms of the evolution of calibration technology, there are significant bottlenecks in the current mainstream solutions: The laboratory weighing method (GB / T 16157-1996) requires shutting down the machine for sampling for more than 48 hours, which cannot meet the real-time requirements of ultra-low emission monitoring; Although the dual-light path online calibration system developed by the Sun Jinghua team (Optics and Precision Engineering, 2021) shortens the calibration period to 4 hours, under the condition of high dust concentration (>50mg / m 3 ), the ash accumulation thickness on the reflecting mirror surface of the reference light path can reach 3-5μm per month, resulting in a baseline drift error of more than 20%. More critically, all existing calibration technologies rely on external references (such as β-ray detection values, standard dust samples). When the performance of the reference equipment deteriorates itself, the entire monitoring system will generate systematic errors.

[0006] Through in-depth analysis of technical defects, it can be seen that the existing continuous monitoring system for soot concentration faces three technical barriers: 1) The inherent contradiction between the time-varying optical parameters under complex working conditions and the static characteristics of the calibration model; 2) The distortion of the quantity traceability caused by environmental interference during the transfer of the calibration reference; 3) The continuous error accumulation caused by the insufficient anti-pollution ability of the online calibration device itself.

[0007] Therefore, there is an urgent need to study an automatic calibration technology for continuous monitoring of soot concentration that does not require manual operation, is not affected by pollution, and can be carried out in-situ on-site. Summary of the Invention

[0008] In view of this, the purpose of the present invention is to provide an automatic calibration device and method for continuous monitoring of soot concentration, realizing in-situ automatic calibration of soot concentration and ensuring the accuracy and reliability of long-term continuous monitoring of soot concentration.

[0009] To achieve the above purpose, the present invention provides the following technical solutions:

[0010] An automatic calibration device for continuous monitoring of soot concentration includes a drying device 11, a dynamic heating system 1, a receiver 2, a radiation source 3, a sliding table 9, and a sampling pump 8. The device is successively a drying position, a sampling position, and a detection position from left to right; among them, the position where the drying device 11 is located is the drying position, the lower part of the suction pipe wrapped by the dynamic heating system 1 is the sampling position, and the middle position where the receiver 2 and the radiation source 3 are located is the β-ray intensity detection position;

[0011] The process of measuring the soot concentration by the automatic calibration device is as follows: First, the filter paper 4 is accurately moved to the drying position by the sliding table 9 for drying the filter paper 4; subsequently, the filter paper 4 is moved to the detection position, and the β-ray intensity is measured through the clean filter paper; then, the filter paper is moved to the sampling position, and the sampling pump 8 is started to introduce flue gas; during this process, the dynamic heating system 1 heats the suction pipe to ensure that the soot particles can be effectively intercepted on the filter paper; after sampling, the sliding table 9 moves the dust-containing filter paper to the drying position and the detection position again for drying treatment and β-ray intensity measurement respectively; finally, the soot concentration to be measured is calculated through the measured data such as β-ray intensity and sampling flow rate.

[0012] Preferably, the device further includes a flow sensor 6 for collecting the gas flow rate.

[0013] Preferably, the device further includes an encoder 10 for recording the movement trajectory of the filter paper.

[0014] Preferably, the device further includes a paper roll system 5 for fixing and storing the filter paper.

[0015] Preferably, when calculating the soot concentration to be measured, an automatic calibration algorithm for soot concentration is used for calibration. Specifically, it is assumed that m continuous optical scattering monitoring data are obtained within a unit time T, and then the average value is denoted as G j , and after n unit times T, multiple data G 1 , G 2 , …, G n are obtained; at the same time, the β-ray intensity data β 1 , β 2 , …, β n of the automatic calibration device during this period are obtained;

[0016] Calculate the comparison coefficient D j , as shown in the following formula:

[0017]

[0018] where 1 ≤ j ≤ n;

[0019] Based on the least mean square algorithm, an automatic calibration algorithm for soot concentration is established, as shown in the following formula:

[0020]

[0021] where is the calibration coefficient, is the calibration offset value; G m is the calibrated continuous optical scattering monitoring concentration value; G' is the real-time soot concentration value of the continuous optical scattering monitoring; f j is the slope direction coefficient. If D j ≥ 0, then fj = 1, otherwise f j = -1; f d is the trend direction coefficient. If f d = 1, otherwise f d = -1; m j is the calibrated slope direction coefficient. If G j -G j-1 ≥β j then m j = 1, otherwise m j = -1; m k is the calibrated slope direction coefficient. If then m k = 1, otherwise m k = -1.

[0022] The beneficial effects of the present invention are as follows: The present invention designs a device capable of real-time automatic calibration of a light scattering continuous monitoring instrument and establishes a corresponding automatic calibration algorithm, thereby realizing in-situ automatic calibration of the soot concentration and ensuring the accuracy and reliability of long-term continuous monitoring of the soot concentration. The specific contributions are as follows:

[0023] (1) Based on the β-ray principle, experimental research on the influence of humidity on the measurement of soot concentration is carried out, and an efficient dehumidification mechanism is designed, thus completing the design of an automatic calibration device for monitoring the emission soot concentration.

[0024] (2) Analyze the measurement principles of light scattering continuous monitoring and β-ray automatic calibration, and based on the least mean square algorithm, propose an automatic calibration algorithm suitable for soot concentration monitoring.

[0025] (3) Experiments prove that the developed automatic calibration equipment for soot concentration has significant effects in dehumidification, with a measurement error of 9.23%; the established calibration algorithm can ensure the continuous and stable operation of the instrument, and the maximum monitoring error is 10.65%.

[0026] Other advantages, objectives and features of the present invention will be elaborated to some extent in the subsequent description, and to some extent, will be obvious to those skilled in the art based on the study of the following text, or can be taught from the practice of the present invention. The objectives and other advantages of the present invention can be realized and obtained through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be described in detail preferably with reference to the accompanying drawings, where:

[0028] Figure 1 is the basic idea of automatic calibration;

[0029] Figure 2 Schematic diagram of measuring soot concentration by β-ray

[0030] Figure 3 Schematic diagram of the dehumidification mechanism of the automatic calibration equipment

[0031] Figure 4 Schematic diagram of the structure of the β-ray automatic calibration equipment

[0032] Figure 5 Schematic diagram of the installation positions of the soot concentration monitoring instrument and the automatic calibration equipment

[0033] Figure 6 Measurement error diagram of the automatic calibration equipment after dehumidification

[0034] Figure 7 Measurement error diagram of the optical scattering continuous monitoring instrument with or without a calibration algorithm

[0035] Reference numerals: 1 - dynamic heating system, 2 - receiver, 3 - radiation source, 4 - filter paper, 5 - paper roll system, 6 - flow sensor, 7 - proportional valve, 8 - sampling pump, 9 - sliding table, 10 - encoder, 11 - drying device. Specific embodiments

[0036] The following specific examples illustrate the embodiments of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments. Various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the drawings provided in the following embodiments only illustrate the basic concept of the present invention in a schematic manner. Without conflict, the following embodiments and the features in the embodiments can be combined with each other.

[0037] Among them, the drawings are only for illustrative purposes, showing only schematic diagrams, not physical diagrams, and should not be construed as a limitation to the present invention; in order to better illustrate the embodiments of the present invention, some components in the drawings will be omitted, enlarged or reduced, which do not represent the dimensions of the actual products; for those skilled in the art, it is understandable that some well-known structures and their descriptions in the drawings may be omitted.

[0038] In the accompanying drawings of the embodiments of the present invention, the same or similar reference numerals correspond to the same or similar components; in the description of the present invention, it should be understood that if there are terms such as "upper", "lower", "left", "right", "front", "rear", etc. indicating the orientation or positional relationship, they are based on the orientation or positional relationship shown in the accompanying drawings. This is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation. Therefore, the terms describing the positional relationship in the accompanying drawings are only for illustrative purposes and cannot be construed as a limitation of the present invention. For those of ordinary skill in the art, the specific meanings of the above terms can be understood according to specific circumstances.

[0039] 1. Theoretical Analysis of Automatic Calibration

[0040] Based on the β-ray principle, the present invention proposes a device capable of automatically calibrating a continuous monitoring instrument for light-scattering soot concentration in-situ. The basic idea is as Figure 1 shown. First, install the β-ray calibration equipment and the light-scattering continuous monitoring instrument at the flue gas sampling port of the same emission flue to ensure the homology of the sampled soot. Subsequently, automatically calibrate the light-scattering soot continuous monitoring instrument regularly. Therefore, it is necessary to first understand the basic principle of measuring soot concentration by β-ray and analyze the advantages and disadvantages of this method.

[0041] The basic principle of measuring soot concentration by β-ray is as Figure 2 shown. When measuring soot concentration by the β-ray method, first obtain the β-ray intensity I 1 passing through the clean filter membrane before sampling soot through the detector; then sample the flue gas to make the soot adhere to the filter membrane. After a period of time, end the soot sampling, record the sampling volume V, and then use the detector again to obtain the β-ray intensity I 2 passing through the dust-containing filter membrane after dust extraction; finally, calculate the measured soot concentration value ρ Δm (mg / m 3 ), as shown in the formula:

[0042]

[0043] where r is the effective radiation radius of the measured soot, and μ m is the mass absorption coefficient.

[0044] In summary, when the filter membrane, β-ray source, and sampling volume are determined, μ m , r, and V in formula (1) are all determined, and the soot concentration measurement is related to the logarithm ln(I 1 / I 2 ) of the intensity ratio of the β-ray source passing through the filter membrane before and after sampling.

[0045] After analyzing the basic principle of measuring soot concentration by beta-ray method, it is found that to achieve automatic calibration of soot concentration, two key problems must be solved: First, the humidity of the sampled flue gas is relatively high, and humidity will affect the transmittance of beta-rays, resulting in inaccurate measurement results of soot concentration; Second, the soot concentration measured by beta-ray method is based on the average value within a period of time, while the optical scattering method monitors the real-time continuous soot concentration value. Therefore, how to achieve calibration between the average value and the real-time continuous value becomes the key to automatic calibration.

[0046] 2. Development of Dehumidification Mechanism

[0047] After investigation, the relative humidity of the discharged flue gas is about 70 - 95%RH. During the process of the flue gas flowing through the extraction pipeline, due to the high humidity of the flue gas, it is easy to condense on the pipeline wall and filter paper, and finally the moisture is adsorbed on the filter paper. This will not only make the measured soot concentration of the flue gas on the high side, but may even cause the filter paper to get damp, reducing its toughness, and thus it is easy to break during the transmission process, affecting the normal operation of the equipment. Therefore, it is necessary to develop a soot dehumidification mechanism to reduce the influence of high humidity on the measurement of soot concentration.

[0048] First, according to the sampling flow rate of 16.7L / min and the tensile force requirement of the roll paper system, a filter paper tape with a filtration efficiency greater than 99.9% (for dust particles above 0.3μm), a tensile strength of 32N, a tensile strength of 800 - 900N / m longitudinally and 600 - 700N / m transversely, and a thickness of 0.26 - 0.3mm was selected. Then, an experimental study on the influence of humidity on the measurement of soot concentration was carried out, providing a basis for the design of the dehumidification mechanism.

[0049] 2.1. Research on the Influence of Humidity on Soot Measurement

[0050] During the sampling process, the high humidity flue gas will moisten the filter paper tape, resulting in some adverse consequences, mainly manifested as: First, the intensity value of beta-rays passing through the filter paper tape (i.e., the pulse value obtained by the detector per unit time) decreases; Second, the tensile strength of the filter paper tape decreases. Therefore, it is necessary to carry out relevant experimental studies to deeply understand the specific influence of humidity on the measurement of soot concentration.

[0051] 2.1.1. Experiment on the Influence of Filter Paper Tape Wetting on Soot Measurement

[0052] The experimental steps are as follows:

[0053] a. Prepare five dry filter paper tapes, and place them respectively in Figure 2 the filter membrane position, and then make marks, and record the beta-ray pulse value passing through the filter paper tape within 10 seconds;

[0054] b. Take out the filter paper tape and soak it completely with pure water;

[0055] c. Take out the wetted filter paper strips separately again and put them back into Figure 2 the filter membrane position. Ensure that the positions where the filter paper strips are put in twice are the same according to the marks, and record the β-ray pulse values passing through the wet filter paper strips within 10 seconds again;

[0056] d. Use a tensiometer to test the tensile strength of the filter paper strips before and after drying and wetting respectively.

[0057] The test results are shown in Table 1.

[0058] Table 1 Data table of the influence of wetting the filter paper strip on the β-ray pulse value

[0059]

[0060] As shown in Table 1, after the filter paper strip is wetted, the number of pulses of β-rays passing through the filter paper strip decreases significantly, indicating that the filter paper strip is greatly affected by wetting and interferes with the measurement of dust concentration. In addition, through the test with a tensiometer, it is found that after the filter paper strip is wetted, its tensile strength drops from 32 N to 10 N, and it is very easy to be broken during the operation of the paper winding system. Therefore, it is necessary to consider introducing a drying device to dry the wetted filter paper strip to improve the stability and measurement accuracy of the system.

[0061] 2.1.2. Influence test of the filter paper strip on dust measurement after wetting and drying

[0062] The test steps are as follows:

[0063] Steps a and b are the same as the previous test, the difference is that 12 dry filter paper strips need to be prepared;

[0064] c. Take out the wetted filter paper strips separately again, dry them with a semiconductor heating sheet, and use a temperature sensor feedback control to control the drying temperature at 40 °C, 50 °C, 60 °C, and 70 °C respectively, and the drying time for each group is 1 hour;

[0065] d. Take out the dried filter paper strips and put them back into Figure 2 the filter membrane position. Ensure that the positions where the filter paper strips are put in twice are the same according to the marks, and record the β-ray pulse values passing through the dried filter paper strips within 10 seconds again;

[0066] e. Use a tensiometer to test the tensile strength of the filter paper strips before and after drying respectively.

[0067] The test results are shown in Table 2.

[0068] Table 2 Data table of the influence of the filter paper strip on the β-ray pulse value after wetting and drying

[0069]

[0070]

[0071] As shown in Table 2, after the filter paper tape is wetted and dried, the β-ray pulse value passing through the filter paper tape decreases by 0.58 - 1.36%. When drying at a relatively low temperature (40 °C), the reduction amplitude of the pulse value is small. Therefore, the filter paper tape can be dried by means of constant-temperature heating to eliminate the influence of humidity on the measurement of soot concentration, thereby improving the measurement accuracy and reliability.

[0072] 2.2. Design of the dehumidification mechanism

[0073] Based on the above test conclusions, first, a drying device needs to be set in the dehumidification mechanism, and the drying temperature is set at 40 °C to effectively eliminate the influence of high humidity on the detection of the filter paper tape; second, since the flue gas temperature is usually between 40 - 60 °C, to prevent the flue gas from condensing on the inner wall of the extraction pipe, a dynamic heating device needs to be wrapped around the outer wall of the extraction pipe, and the heating temperature is set at 65 °C. As Figure 3 shown, it is a schematic diagram of the dehumidification mechanism in the automatic calibration equipment.

[0074] 3. Development of the automatic calibration equipment

[0075] After completing the design of the dehumidification mechanism, the automatic calibration device will be further developed. As its internal structure is Figure 4 shown, the device is sequentially configured with a drying position, a sampling position, and a detection position from left to right. Among them, the position where the drying device 11 is located is the drying position, the position below the extraction pipe wrapped by the dynamic heating system 1 is the sampling position, and the middle position where the receiver 2 and the radiation sources 2, 3 are located is the β-ray intensity detection position.

[0076] The soot concentration measurement process of the automatic calibration equipment is as follows: First, the filter paper 4 is accurately moved to the drying position through the sliding table 9 for drying the filter paper 4; subsequently, the filter paper 4 is moved to the detection position, and the β-ray intensity is measured through a clean filter paper; then, the filter paper is moved to the sampling position, and the sampling pump 8 is started to introduce the flue gas. During this process, the dynamic heating system 1 heats the extraction pipe to ensure that the soot particles can be effectively intercepted on the filter paper. After sampling, the sliding table 9 moves the dust-containing filter paper to the drying position and the detection position again for drying treatment and β-ray intensity measurement respectively. Finally, the soot concentration to be measured is calculated through the measured data such as β-ray intensity and sampling flow rate.

[0077] 4. Research on the automatic calibration algorithm

[0078] According to HJ 76 - 2017 "Technical Requirements and Testing Methods for Continuous Emission Monitoring Systems of Flue Gas (SO 2 , NO x , Particulate Matter) from Stationary Pollution Sources", the acquisition interval of the soot concentration data needs to reach at least 5 seconds to meet the high real-time requirements of continuous monitoring.

[0079] The development of the active calibration equipment for continuous monitoring of soot concentration has been completed in the previous text. Next, an automatic calibration algorithm will be established to meet the requirements of high real-time performance and accuracy for continuous monitoring of soot concentration.

[0080] To meet the high real-time performance of monitoring and the adaptability to on-site fluctuations, through comparative analysis of various algorithms, it is found that the least mean square algorithm, with its advantages of simple structure, high computational efficiency, good stability, and wide application, can well meet the monitoring requirements. Therefore, based on the least mean square algorithm theory, an automatic calibration algorithm for soot concentration is designed in the present invention.

[0081] However, since the optical scattering continuous monitoring instrument usually provides one monitoring data per second, while the β-ray automatic calibration equipment requires at least 30 seconds to obtain the average value within a time interval, there are significant differences in the data between the two in terms of time and they cannot be directly calibrated correspondingly. This time inconsistency becomes the key problem that the calibration algorithm needs to solve.

[0082] To make the data of the two corresponding in the same time period, it is assumed that m optical scattering continuous monitoring data are obtained within the unit time T, and then the average value is denoted as G j , and after n unit times T, multiple data G 1 , G 2 , …, G n are obtained; at the same time, the data β 1 , β 2 , …, β n of the automatic calibration equipment within this period are obtained.

[0083] Calculate the comparison coefficient D j , as shown in Equation (2):

[0084]

[0085] where 1 ≤ j ≤ n.

[0086] Based on the least mean square algorithm, establish an automatic calibration algorithm for soot concentration, as shown in Equation (3):

[0087]

[0088] where is the calibration coefficient, is the calibration offset value. G m is the calibrated optical scattering continuous monitoring concentration value; G' is the real-time soot concentration value of the optical scattering continuous monitoring; f j is the slope direction coefficient. If D j ≥ 0, then f j = 1, otherwise f j = -1; f d is the trend direction coefficient. If f d = 1, otherwise f d = -1; m j is the slope direction coefficient after calibration. If G j -G j-1 ≥β j , then m j = 1, otherwise m j = -1; m k is the slope direction coefficient after calibration. If then m k = 1, otherwise m k = -1.

[0089] 5. Experiment

[0090] Next, the dehumidification effect of the automatic calibration equipment and the accuracy of the algorithm are experimentally verified to evaluate its performance and reliability in actual applications.

[0091] 5.1. Experiment Preparation

[0092] To verify the performance of the automatic calibration equipment, a representative coal-fired power plant is selected as the test site. The equipment is installed at a position 15 m away from the chimney, 10 m away from the outlet of the dust removal system, and about 15 m above the ground. The schematic diagram of the on-site installation is as Figure 5 shown.

[0093] Flue gas parameters at the installation point: Temperature: 40 - 60 °C; Relative humidity: 70 - 90% RH.

[0094] Environmental parameters at the installation point: Temperature: -20 - 60 °C; Relative humidity: 20 - 99% RH.

[0095] At the same time, a dust sampler and an analytical balance with a precision of one in a hundred thousand are prepared for the standard equipment used in the dust concentration comparison test verification.

[0096] 5.2. Experiment Verification of Dehumidification Effect

[0097] After a period of test operation, the dust concentration automatic calibration device performs stably and reliably. Observing the dehumidification of the filter paper tape, no abnormal phenomena such as breakage or wrinkles are found, and the filter paper tape can collect dust particles evenly and stably.

[0098] Then, the dust sampler is used to take manual samples multiple times within a period of time, and the filter membrane of the manual sample is treated at a constant temperature of 25 °C for 24 hours at low temperature; then, the treated dust-containing filter membrane is weighed using a balance, and the dust concentration value of the manual sample is calculated and used as the standard value. Finally, the measured value of the β-ray automatic calibration equipment and the standard value in the same time period are compared, and the error data is as Figure 6 shown.

[0099] Subsequently, the smoke sampler was used to perform manual sampling multiple times in different time periods. After sampling, the filter membrane was placed in a constant temperature environment of 25°C for 24 hours, and then weighed using a balance to calculate the smoke concentration value of the manual sampling, which was used as the standard value. Finally, the measured value of the β-ray automatic calibration equipment in the same time period was compared and analyzed with the standard value. The error data is shown in the figure. Figure 6 As shown, the manual weighing value of the sampler is used as the standard. After dehumidification, the measurement error of the automatic calibration equipment is 9.23%. The results show that the developed dehumidification mechanism has a good effect and can ensure stable and reliable measurement of smoke concentration.

[0100] 5.3. Test verification of calibration algorithm accuracy

[0101] exist Figure 5 In the experiment shown, the manual weighing value of the sampler is also used as the standard. Over a period of time, two sets of measurement data of the light scattering continuous monitoring instrument are obtained under the conditions of no calibration algorithm and with calibration algorithm. The error comparison results of the two sets of data and the standard value are shown in Figure 7 shown.

[0102] like Figure 7 The maximum measurement error of the light scattering continuous monitoring instrument with the calibration algorithm is 10.65%, and the maximum measurement error without the calibration algorithm is 19.12%. It can be seen that after adding the calibration algorithm of the automatic calibration equipment, the measurement error of the light scattering continuous monitoring instrument is small, and the error fluctuation is small; while without the calibration algorithm of the automatic calibration equipment, the measurement error of the light scattering continuous monitoring instrument is large, the error fluctuation is also large, and the measurement reliability is poor.

[0103] like Figure 7 As shown in the figure, the maximum measurement error of the light scattering continuous monitoring instrument with automatic calibration algorithm is 10.65%, while the maximum error without calibration algorithm is 19.12%. It can be seen that the calibration algorithm with automatic calibration equipment significantly reduces the measurement error of the light scattering continuous monitoring instrument, and the error fluctuation is small; in contrast, the instrument without automatic calibration equipment has a large measurement error and more violent fluctuations, resulting in a decrease in measurement reliability.

[0104] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the purpose and scope of the technical solution, which should be included in the scope of the claims of the present invention.

Claims

1. An automatic calibration device for continuous monitoring of smoke concentration, characterized in that: The device comprises a drying device (11), a dynamic heating system (1), a receiver (2) and a radiation source (3); the device comprises a drying position, a sampling position and a detection position from left to right; wherein the position where the drying device (11) is located is the drying position, the position below the exhaust pipe wrapped by the dynamic heating system (1) is the sampling position, and the position between the receiver (2) and the radiation source (3) is the β-ray intensity detection position; The smoke concentration measurement process of the automatic calibration device is as follows: first, the filter paper (4) is moved to the drying position to dry the filter paper (4); then, the filter paper (4) is moved to the detection position to measure the beta ray intensity through the clean filter paper; then, the filter paper is moved to the sampling position to introduce smoke; during this process, the dynamic heating system (1) heats the exhaust pipe to ensure that the smoke particles can be effectively retained on the filter paper; after the sampling is completed, the dust-containing filter paper is moved to the drying position and the detection position again to perform drying treatment and beta ray intensity measurement respectively; finally, the smoke concentration to be measured is calculated by measuring the beta ray intensity and the sampling flow rate.

2. The automatic calibration device according to claim 1, characterized in that: The device also includes a slide table (9) for accurately moving the filter paper (4) to a drying position.

3. The automatic calibration device according to claim 1, characterized in that: The device also includes a sampling pump (8) for introducing smoke.

4. The automatic calibration device according to claim 1, characterized in that: The device also includes a flow sensor (6) for collecting gas flow.

5. The automatic calibration device according to claim 1, characterized in that: The device also includes an encoder (10) for recording the movement track of the filter paper.

6. The automatic calibration device according to claim 1, characterized in that: The device also comprises a paper roll system (5) for fixing and storing filter paper.

7. The automatic calibration device according to claim 1, characterized in that: When the smoke concentration to be measured is calculated, the smoke concentration automatic calibration algorithm is used for calibration. Specifically, it is assumed that m continuous light scattering monitoring data are obtained within a unit time T, and then the average is calculated and recorded as G j After n unit time T, multiple data G1, G2, ..., G n ; At the same time, the β-ray intensity data β1, β2, ..., β of the automatic calibration device during this period are obtained n ; Calculate the contrast coefficient D j , as shown below: Among them, 1≤j≤n; Based on the least mean square algorithm, an automatic calibration algorithm for smoke concentration is established, as shown in the following formula: in, is the calibration factor, is the calibration offset value; G m is the calibrated light scattering continuous monitoring concentration value; G' is the real-time smoke concentration value of light scattering continuous monitoring; f j is the slope direction coefficient, if D j ≥0, then f j =1, otherwise f j = -1; f d is the trend direction coefficient, if f d =1, otherwise f d = -1; m j is the slope direction coefficient after calibration, if G j -G j-1 ≥β j , then m j =1, otherwise m j =-1; m k is the slope direction coefficient after calibration, if Then m k =1, otherwise m k =-1.

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