An on-line monitoring method and system for monitoring particulate matter in a gas

Abstract

The application discloses an online monitoring method and system for monitoring particulate matters in gas, and relates to the technical field of dust detection. The target light power is determined by acquiring the working condition parameters; the measuring chamber is cleaned and its optical state is detected before measurement; the sampled flue dust is heated and dried and then is transported to the measuring chamber at a constant speed; the laser is controlled to emit laser at the target light power, the flue dust scattering light signal is collected, and the flue dust particle concentration is calculated after calibration. Through the light power dynamic adjustment based on the working condition parameters and the heating and drying treatment, the interference of water in the wet flue gas on the scattering signal is eliminated, the low-concentration signal is avoided from being too weak or the high-concentration signal from being saturated, the high signal-to-noise ratio of the detector signal is ensured, and the online monitoring precision and stability of the flue dust after wet dedusting are significantly improved.

Description

Technical Field

[0001] This invention relates to the technical field of dust detection, and specifically to an online monitoring method and system for monitoring particulate matter in gas. Background Technology

[0002] In the treatment of flue gas from coal-fired boilers, wet desulfurization and wet dust removal have become common environmental protection processes. After wet treatment, the particulate matter concentration in the flue gas is significantly reduced, often reaching a low level. However, wet processes introduce a large amount of moisture, placing the flue gas in a high-humidity or even saturated state. Particulate matter readily absorbs moisture, expands, and clumps together, even forming tiny droplets in some cases. These changes not only alter the particle size distribution but also significantly affect its optical properties, posing a significant challenge to online monitoring.

[0003] While existing laser scattering dust monitoring technology is widely used, it has significant shortcomings in the aforementioned operating conditions. Firstly, traditional systems often employ fixed optical power parameters, failing to dynamically adjust to changes in actual conditions. When dust concentration is low, a fixed optical power may result in an excessively weak detector output signal, approaching noise levels; conversely, occasional high concentration fluctuations may lead to signal saturation, both affecting the accuracy of concentration calculations. Secondly, the large amount of moisture in wet flue gas causes abnormal changes in the scattering characteristics of particulate matter. The optical signal not only includes light scattered by particles but also superimposed interference light generated by water droplets or wet films, resulting in measurement results that are either too high or fluctuate abnormally. These problems collectively limit the effectiveness of existing technologies in monitoring low-concentration dust after wet desulfurization and wet dust removal processes. Summary of the Invention

[0004] The purpose of this invention is to solve the problem of insufficient monitoring accuracy mentioned in the background art, and to propose an online monitoring method and system for monitoring particulate matter in gas.

[0005] A first aspect of this invention provides an online monitoring method for monitoring particulate matter in a gas, the method comprising:

[0006] Obtain operating parameters and determine the target optical power based on the operating parameters;

[0007] The measurement chamber is cleaned, and the cleanliness is tested using the target optical power.

[0008] The sampled flue gas is heated to obtain dried flue gas, which is then transported to the measuring chamber.

[0009] The laser is controlled to emit a target laser beam based on the target optical power, which then enters the measurement chamber.

[0010] By acquiring the light signal scattered by the smoke and dust particles, the scattered photoelectric signal is obtained;

[0011] The concentration of smoke particles is calculated based on the scattered photoelectric signal and the target optical power.

[0012] Optionally, the operating parameters include boiler load, dust collector operating status, and desulfurization tower operating status; determining the target optical power based on the operating parameters includes:

[0013] If the dust collector and desulfurization tower are operating normally, the predicted dust concentration after dust removal is obtained based on the historical data of boiler load matching.

[0014] The first optical power is calculated based on the predicted smoke and dust concentration and the detector's saturation threshold.

[0015] The second optical power is calculated based on the predicted smoke and dust concentration and the effective signal strength of the detector.

[0016] The target optical power is determined based on the first optical power and the second optical power; the target optical power is less than the first optical power and greater than the second optical power.

[0017] Optionally, the cleaning detection using the target optical power includes:

[0018] Clean gas is supplied to the measurement chamber to establish a clean environment;

[0019] In a clean environment, the laser is incident with the target optical power, and the scattered light signal at this time is collected and recorded as the first zero-point reference signal.

[0020] The first zero-point reference signal is compared with the preset original zero-point reference signal to determine whether the optical path in the measurement chamber is in a clean state; the original zero-point reference signal is the zero-point signal measured when the optical path is in a standard clean state.

[0021] If the optical path is clean, the first zero-point reference signal is determined as the background reference signal for zero-point calibration in subsequent measurements.

[0022] Optionally, calculating the concentration of smoke particles based on the scattered photoelectric signal and the target optical power includes:

[0023] Subtracting the background reference signal from the scattered photoelectric signal yields the calibrated scattered photoelectric signal, which is denoted as the first electrical signal.

[0024] The first electrical signal is discretely averaged to obtain the average value of the electrical signal, and the average value of the electrical signal is converted into the intensity of scattered light;

[0025] Based on the scattered light intensity and the target optical power, the concentration of smoke particles is calculated:

[0026] ;

[0027] Where C is the concentration of smoke particles; It is the intensity of the scattered light; is the target optical power; K and n are empirical fitting constants.

[0028] Optionally, the step of heating the sampled flue dust to obtain dried flue dust, and then conveying the dried flue dust to the measuring chamber includes:

[0029] During the transport process, the flow rate of the smoke and dust is controlled at a constant velocity to ensure a constant sampling airflow speed.

[0030] A second aspect of the present invention provides an online monitoring system for monitoring particulate matter in gas, the system comprising:

[0031] The parameter determination module is used to acquire operating parameters and determine the target optical power based on the operating parameters.

[0032] The optical path cleaning module is used to clean the measurement chamber and to perform cleaning detection using the target optical power.

[0033] The high-temperature heat tracing module is used to heat the sampled flue gas to obtain dry flue gas, and then transport the dry flue gas to the measurement chamber;

[0034] A laser incident module is used to control the laser to emit target laser light according to the target optical power and to shoot it into the measurement chamber;

[0035] The scattered light receiving module is used to acquire the light signal scattered by the smoke and dust particles and obtain the scattered photoelectric signal;

[0036] The concentration analysis module is used to calculate the concentration of smoke particles based on the scattered photoelectric signal and the target optical power.

[0037] Optionally, the operating parameters include boiler load, dust collector operating status, and desulfurization tower operating status; the parameter determination module includes:

[0038] The concentration estimation module is used to obtain the predicted value of the flue dust concentration after dust removal based on the historical data of boiler load matching if the operating status of the dust collector and the desulfurization tower are normal.

[0039] The upper limit estimation module is used to calculate the first optical power based on the predicted smoke and dust concentration and the saturation threshold of the detector.

[0040] The lower limit estimation module is used to calculate the second optical power based on the predicted smoke and dust concentration and the effective signal strength of the detector;

[0041] A power determination module is used to determine a target optical power based on the first optical power and the second optical power; the target optical power is less than the first optical power and greater than the second optical power.

[0042] Optionally, the optical path cleaning module includes:

[0043] The gas supply control module is used to deliver clean gas to the measurement chamber to establish a clean environment;

[0044] The zero-point detection module is used to collect the scattered light signal when the laser is incident with the target optical power in a dust-free environment, and record it as the first zero-point reference signal.

[0045] The cleanliness judgment module is used to compare the first zero-point reference signal with the preset original zero-point reference signal to determine whether the optical path in the measurement chamber is in a clean state; the original zero-point reference signal is the zero-point signal measured when the optical path is in a standard clean state.

[0046] The background determination module is used to determine the first zero-point reference signal as a background reference signal if the optical path is in a clean state, for use in zero-point calibration of subsequent measurements.

[0047] Optionally, the concentration analysis module includes:

[0048] The signal calibration module is used to subtract the background reference signal from the scattered photoelectric signal to obtain the calibrated scattered photoelectric signal, which is denoted as the first electrical signal.

[0049] The signal smoothing module is used to discretely average the first electrical signal to obtain the average value of the electrical signal, and then convert the average value of the electrical signal into the intensity of scattered light.

[0050] The concentration calculation module is used to calculate the concentration of smoke particles based on the scattered light intensity and the target light power.

[0051] ;

[0052] Where C is the concentration of smoke particles; It is the intensity of the scattered light; is the target optical power; K and n are empirical fitting constants.

[0053] Optionally, the high-temperature heat tracing module includes a constant-velocity sampling module, used to control the flow rate of the smoke and dust during the transportation process so as to keep the sampling airflow speed constant.

[0054] The beneficial effects of this invention are:

[0055] By dynamically adjusting the laser power based on operating parameters and combining this with the heating and drying process for the flue gas, the interference of moisture in the flue gas on the particulate matter scattering signal is effectively eliminated. At the same time, the problem of weak signals at low concentrations or saturation at high concentrations is avoided, ensuring that the detector signal maintains a high signal-to-noise ratio. This significantly improves the accuracy and stability of online monitoring of low-concentration flue gas after wet dust removal. Attached Figure Description

[0056] Figure 1 A flowchart of an online monitoring method for monitoring particulate matter in gas provided by an embodiment of the present invention;

[0057] Figure 2 This is an architecture diagram of an online monitoring system for monitoring particulate matter in gas, provided as an embodiment of the present invention. Detailed Implementation

[0058] To further illustrate the technical means and effects of the present invention in achieving its intended purpose, the following detailed description of the specific implementation methods, structures, features, and effects of the present invention, in conjunction with the accompanying drawings and preferred embodiments, is provided below.

[0059] This invention provides an online monitoring method for monitoring particulate matter in gas. See also... Figure 1 , Figure 1 This is a flowchart illustrating an online monitoring method for particulate matter in gas, provided as an embodiment of the present invention. The method employs forward scattering for concentration monitoring and includes the following steps:

[0060] S101: Obtain operating parameters and determine the target optical power based on the operating parameters.

[0061] S102, clean the measurement chamber and perform cleaning detection using the target optical power.

[0062] S103 heats the sampled flue dust to obtain dry flue dust, and then transports the dry flue dust to the measurement chamber.

[0063] S104 controls the laser to emit the target laser according to the target optical power, which then enters the measurement chamber.

[0064] S105, acquire the light signal scattered by the smoke and dust particles, and obtain the scattered photoelectric signal.

[0065] S106, calculate the concentration of smoke particles based on the scattered photoelectric signal and the target light power.

[0066] Based on the online monitoring method for monitoring particulate matter in gas provided by the embodiments of the present invention, the laser power is dynamically adjusted by the operating parameters, and combined with the heating and drying treatment of flue gas, the interference of moisture in wet flue gas on the scattering signal of particulate matter is effectively eliminated. At the same time, the problem of weak low-concentration signal or saturation of high-concentration signal is avoided, so that the detector signal maintains a high signal-to-noise ratio, thereby significantly improving the online monitoring accuracy and stability of low-concentration flue gas after wet dust removal.

[0067] In one embodiment, the operating parameters include boiler load, dust collector operating status, and desulfurization tower operating status.

[0068] In step S101, determining the target optical power based on the operating parameters includes:

[0069] Step 1: If the dust collector and desulfurization tower are operating normally, then the predicted dust concentration after dust removal is obtained based on the historical data of boiler load matching.

[0070] Step 2: Calculate the first optical power based on the predicted smoke and dust concentration and the detector's saturation threshold.

[0071] Step 3: Calculate the second optical power based on the predicted smoke and dust concentration and the effective signal strength of the detector.

[0072] Step 4: Determine the target optical power based on the first optical power and the second optical power; the target optical power is less than the first optical power and greater than the second optical power.

[0073] The saturation threshold and effective signal strength are determined by the detector's rated parameters. The saturation threshold refers to the maximum measurable output signal that the photodetector can produce when receiving a light signal. Exceeding this threshold, the detector's output will no longer change linearly with increasing light intensity, and may even become distorted. The effective signal strength refers to the minimum signal strength at which the detector can stably and reliably identify and calculate particulate matter concentration. Below this value, the signal may be overwhelmed by noise, leading to inaccurate or unmeasurable measurements.

[0074] This embodiment predicts dust concentration by combining operating parameters such as boiler load, dust collector and desulfurization tower operation status, and dynamically determines the laser target light power based on the detector's saturation threshold and effective signal strength. This ensures that the light power is neither too high, causing detector saturation, nor too low, causing weak signal, thus maintaining a high signal-to-noise ratio signal. As a result, it achieves intelligent online particulate matter monitoring with high measurement accuracy, stable signal, and adaptability to concentration fluctuations.

[0075] In one implementation, laser irradiation of smoke and dust is performed using an empirical formula: Fitting the intensity of scattered light from particles The mapping relationship between the particulate matter concentration C and the particulate matter concentration C. Here, K is the incident light intensity, K is a calibration coefficient related to particle size, refractive index, detector geometry, etc., and n is the fitting exponent. Both K and n are derived from fitting experimental data. In low-concentration scenarios, n can be taken as 1, i.e., the particle scattered light intensity. There is an approximately linear relationship with the particulate matter concentration C: .

[0076] Furthermore, because the laser beam typically maintains a constant beam cross-section A (constant) within the measurement chamber, meaning the optical power is directly proportional to the optical intensity: Therefore, optical power can be directly substituted into the calculation. ,Will ,get This formula is an empirical fitting formula; only numerical values ​​are substituted for calculation. Therefore, when the... , When any two of C are given, the other factor value can be obtained by substituting them into the formula.

[0077] In one implementation, the average of the first optical power and the second optical power can be used as the target optical power, thereby achieving simple, stable, and dynamically adaptive optical power control while ensuring signal effectiveness and detector safety, which is convenient for long-term online particulate matter monitoring.

[0078] In one embodiment, step S102, performing cleaning detection using target optical power, includes:

[0079] Step 1: Deliver clean gas into the measurement chamber to establish a clean environment;

[0080] Step 2: In a dust-free environment, use the target optical power to incident the laser and collect the scattered light signal at this time, which is recorded as the first zero-point reference signal.

[0081] Step 3: Compare the first zero-point reference signal with the preset original zero-point reference signal to determine whether the optical path in the measurement chamber is clean.

[0082] Step four: If the optical path is clean, the first zero-point reference signal is determined as the background reference signal for zero-point calibration in subsequent measurements.

[0083] The original zero-point reference signal is the zero-point signal measured when the optical path is in a standard clean state.

[0084] This embodiment establishes a clean environment in the measurement chamber and collects scattered signals. These signals are then compared with a standard zero-point reference signal to determine whether the optical path is clean. If clean, the signal is used as a background reference signal for zero-point calibration, thereby achieving pre-measurement cleaning and automatic calibration, ensuring the accuracy and reliability of particulate matter concentration measurement.

[0085] In one implementation, multiple zero-point signals are continuously acquired, the average value is calculated, and then compared with a standard value. The absolute difference between the two can be calculated and compared with a set tolerance threshold (e.g., 3 times the standard deviation, calculated by acquiring zero-point signals multiple times under standard cleaning conditions and calculating the standard deviation). Alternatively, the relative deviation (the percentage of the absolute difference relative to the standard value) can be calculated; if the relative deviation is less than a preset percentage (e.g., 5%), the system is considered clean.

[0086] In one embodiment, step S103, heating the sampled flue dust to obtain dried flue dust, and conveying the dried flue dust to the measuring chamber, includes:

[0087] During the transport process, the flow rate of the flue gas is controlled at a constant velocity using a flow meter and a proportional valve to ensure that the sampling airflow speed remains constant.

[0088] Maintaining a constant flow rate in the sampling tube ensures that the dust is heated evenly during the drying process, avoiding localized overheating or stagnation. It also ensures a stable number of particles entering the measuring chamber per unit time, thereby improving measurement accuracy and enhancing the reliability of the online monitoring system.

[0089] In one embodiment, calculating the concentration of smoke particles based on the scattered photoelectric signal and the target optical power includes:

[0090] Step 1: Subtract the background reference signal from the scattered photoelectric signal to obtain the calibrated scattered photoelectric signal, which is denoted as the first electrical signal.

[0091] Step 2: Discretely average the first electrical signal to obtain the average value of the electrical signal, and then convert the average value of the electrical signal into the intensity of scattered light.

[0092] Step 3: Calculate the concentration of smoke particles based on the intensity of scattered light and the target light power.

[0093] This embodiment suppresses instantaneous noise and signal fluctuations by discretely averaging the calibrated first electrical signal, resulting in a more stable and reliable average value. This average value is then converted into scattered light intensity for concentration calculation, thereby significantly improving the accuracy of smoke particle concentration measurement.

[0094] This invention provides an online monitoring system for monitoring particulate matter in gas. See also... Figure 2 , Figure 2 This is an architectural diagram of an online monitoring system for monitoring particulate matter in gas, provided as an embodiment of the present invention. The system includes:

[0095] The parameter determination module is used to acquire operating parameters and determine the target optical power based on the operating parameters.

[0096] The optical path cleaning module is used to clean the measurement chamber and perform cleaning detection using the target optical power.

[0097] The high-temperature heat tracing module is used to heat the sampled flue gas to obtain dry flue gas, and then transport the dry flue gas to the measurement chamber.

[0098] The laser incident module is used to control the laser to emit the target laser according to the target optical power and then shoot it into the measurement chamber.

[0099] The scattered light receiving module is used to acquire the light signal scattered by the smoke and dust particles and obtain the scattered photoelectric signal.

[0100] The concentration analysis module is used to calculate the concentration of smoke particles based on the scattered photoelectric signal and the target light power.

[0101] An online monitoring system for monitoring particulate matter in gas, based on an embodiment of the present invention, effectively eliminates the interference of moisture in wet flue gas on the scattering signal of particulate matter by dynamically adjusting the laser power through operating parameters and combining it with the heating and drying treatment of flue gas. At the same time, it avoids the problem of weak signals at low concentrations or saturation at high concentrations, and keeps the detector signal at a high signal-to-noise ratio, thereby significantly improving the accuracy and stability of online monitoring of low-concentration flue gas after wet dust removal.

[0102] In one embodiment, the parameter determination module includes:

[0103] The concentration estimation module is used to obtain the predicted value of the flue dust concentration after dust removal based on historical data of boiler load matching if the dust collector and desulfurization tower are operating normally.

[0104] The upper limit estimation module is used to calculate the first optical power based on the predicted smoke and dust concentration and the detector's saturation threshold.

[0105] The lower limit estimation module is used to calculate the second optical power based on the predicted smoke and dust concentration and the effective signal strength of the detector.

[0106] The power determination module is used to determine the target optical power based on the first optical power and the second optical power.

[0107] In one embodiment, the optical path cleaning module includes:

[0108] The gas supply control module is used to deliver clean gas to the measurement chamber to establish a clean environment.

[0109] The zero-point detection module is used to collect the scattered light signal when the laser is incident with the target optical power in a dust-free environment, and record it as the first zero-point reference signal.

[0110] The cleanliness judgment module is used to compare the first zero-point reference signal with the preset original zero-point reference signal to determine whether the optical path in the measurement chamber is in a clean state; the original zero-point reference signal is the zero-point signal measured when the optical path is in a standard clean state.

[0111] The background determination module is used to determine the first zero-point reference signal as the background reference signal if the optical path is clean, for use in zero-point calibration of subsequent measurements.

[0112] In one embodiment, the concentration analysis module includes:

[0113] The signal calibration module is used to subtract the background reference signal from the scattered photoelectric signal to obtain the calibrated scattered photoelectric signal, which is denoted as the first electrical signal.

[0114] The signal smoothing module is used to discretely average the first electrical signal to obtain the average value of the electrical signal, and then convert the average value of the electrical signal into the intensity of scattered light.

[0115] The concentration calculation module is used to calculate the concentration of dust particles based on the intensity of scattered light and the target light power.

[0116] In one embodiment, the high-temperature heat tracing module includes a constant-velocity sampling module for controlling the flow rate of smoke and dust during the conveying process to keep the sampling airflow velocity constant.

[0117] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall fall within the scope of the present invention.

Claims

1. An online monitoring method for monitoring particulate matter in gas, characterized in that, The method includes: Obtain operating parameters and determine the target optical power based on the operating parameters; The measurement chamber is cleaned, and the cleanliness is tested using the target optical power. The sampled flue gas is heated to obtain dried flue gas, which is then transported to the measuring chamber. The laser is controlled to emit a target laser beam based on the target optical power, which then enters the measurement chamber. By acquiring the light signal scattered by the smoke and dust particles, the scattered photoelectric signal is obtained; The concentration of smoke particles is calculated based on the scattered photoelectric signal and the target optical power; The operating parameters include boiler load, dust collector operating status, and desulfurization tower operating status; determining the target optical power based on the operating parameters includes: If the dust collector and desulfurization tower are operating normally, the predicted dust concentration after dust removal is obtained based on the historical data of boiler load matching. The first optical power is calculated based on the predicted smoke and dust concentration and the detector's saturation threshold. The second optical power is calculated based on the predicted smoke and dust concentration and the effective signal strength of the detector. The target optical power is determined based on the first optical power and the second optical power; the target optical power is less than the first optical power and greater than the second optical power.

2. The online monitoring method for monitoring particulate matter in gas according to claim 1, characterized in that, The cleaning detection using the target optical power includes: Clean gas is supplied to the measurement chamber to establish a clean environment; In a clean environment, the laser is incident with the target optical power, and the scattered light signal at this time is collected and recorded as the first zero-point reference signal. The first zero-point reference signal is compared with the preset original zero-point reference signal to determine whether the optical path in the measurement chamber is in a clean state; the original zero-point reference signal is the zero-point signal measured when the optical path is in a standard clean state. If the optical path is clean, the first zero-point reference signal is determined as the background reference signal for zero-point calibration in subsequent measurements.

3. The online monitoring method for monitoring particulate matter in gas according to claim 2, characterized in that, The calculation of dust particle concentration based on the scattered photoelectric signal and the target optical power includes: Subtracting the background reference signal from the scattered photoelectric signal yields the calibrated scattered photoelectric signal, which is denoted as the first electrical signal. The first electrical signal is discretely averaged to obtain the average value of the electrical signal, and the average value of the electrical signal is converted into the intensity of scattered light; Based on the scattered light intensity and the target optical power, the concentration of smoke particles is calculated: ； Where C is the concentration of smoke particles; It is the intensity of the scattered light; is the target optical power; K and n are empirical fitting constants.

4. The online monitoring method for monitoring particulate matter in gas according to claim 1, characterized in that, The step of heating the sampled flue dust to obtain dried flue dust and then conveying the dried flue dust to the measuring chamber includes: During the transportation process, the flow rate of the smoke and dust is controlled at a constant velocity to keep the sampling airflow speed constant.

5. An online monitoring system for monitoring particulate matter in gas, characterized in that, The system includes: The parameter determination module is used to acquire operating parameters and determine the target optical power based on the operating parameters. The optical path cleaning module is used to clean the measurement chamber and to perform cleaning detection using the target optical power. The high-temperature heat tracing module is used to heat the sampled flue gas to obtain dry flue gas, and then transport the dry flue gas to the measurement chamber; A laser incident module is used to control the laser to emit target laser light according to the target optical power and to shoot it into the measurement chamber; The scattered light receiving module is used to acquire the light signal scattered by the smoke and dust particles and obtain the scattered photoelectric signal; The concentration analysis module is used to calculate the concentration of smoke particles based on the scattered photoelectric signal and the target optical power; The operating parameters include boiler load, dust collector operating status, and desulfurization tower operating status; the parameter determination module includes: The concentration estimation module is used to obtain the predicted value of the flue dust concentration after dust removal based on the historical data of boiler load matching if the operating status of the dust collector and the desulfurization tower are normal. The upper limit estimation module is used to calculate the first optical power based on the predicted smoke and dust concentration and the saturation threshold of the detector. The lower limit estimation module is used to calculate the second optical power based on the predicted smoke and dust concentration and the effective signal strength of the detector; A power determination module is used to determine a target optical power based on the first optical power and the second optical power; the target optical power is less than the first optical power and greater than the second optical power.

6. The online monitoring system for monitoring particulate matter in gas according to claim 5, characterized in that, The optical path cleaning module includes: The gas supply control module is used to deliver clean gas to the measurement chamber to establish a clean environment; The zero-point detection module is used to collect the scattered light signal when the laser is incident with the target optical power in a dust-free environment, and record it as the first zero-point reference signal. The cleanliness judgment module is used to compare the first zero-point reference signal with the preset original zero-point reference signal to determine whether the optical path in the measurement chamber is in a clean state; the original zero-point reference signal is the zero-point signal measured when the optical path is in a standard clean state. The background determination module is used to determine the first zero-point reference signal as a background reference signal if the optical path is in a clean state, for use in zero-point calibration of subsequent measurements.

7. The online monitoring system for monitoring particulate matter in gas according to claim 6, characterized in that, The concentration analysis module includes: The signal calibration module is used to subtract the background reference signal from the scattered photoelectric signal to obtain the calibrated scattered photoelectric signal, which is denoted as the first electrical signal. The signal smoothing module is used to discretely average the first electrical signal to obtain the average value of the electrical signal, and then convert the average value of the electrical signal into the intensity of scattered light. The concentration calculation module is used to calculate the concentration of smoke particles based on the scattered light intensity and the target light power. ； Where C is the concentration of smoke particles; It is the intensity of the scattered light; is the target optical power; K and n are empirical fitting constants.

8. The online monitoring system for monitoring particulate matter in gas according to claim 5, characterized in that, The high-temperature heat tracing module includes a constant-velocity sampling module, which is used to control the flow rate of the smoke and dust during the transportation process so as to keep the sampling airflow speed constant.

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