Dust concentration monitoring method and system based on scattered light measurement

Abstract

The invention discloses a dust concentration monitoring method and system based on scattered light measurement, and relates to the field of dust concentration monitoring. The method comprises the following steps: S1, in a range point detection stage, turning off an emitter to implement zero point detection to obtain a zero point value, and generating a range point detection result; s2, collecting an optical signal and a temperature signal, obtaining basic scattering intensity based on demodulation and zero value deduction, and generating an analog output current; s3, on-line correction is carried out on the basic scattering intensity through the correction coefficient and the temperature correction coefficient which are calculated in real time, and the optical scattering intensity is obtained; and S4, calibrating by simulating output current and weighing method concentration, solving a current coefficient vector and converting the current coefficient vector into a regression coefficient, and generating dust concentration by directly using optical scattering intensity and the regression coefficient when equipment runs online. Through real-time correction, intelligent dark baseline compensation, temperature correction and Tikhonov regularization methods, the measurement accuracy and the equipment stability and reliability are improved, and high-precision real-time monitoring is ensured.

Description

Technical Field

[0001] This invention relates to the field of dust concentration monitoring, specifically to a dust concentration monitoring method and system based on scattered light measurement. Background Technology

[0002] This invention relates to a dust concentration monitoring method based on scattered light measurement. With the continuous development of industry and environmental protection, the requirements for air quality monitoring and control are becoming increasingly stringent, especially for dust concentration monitoring. Traditional dust concentration monitoring typically relies on physicochemical analysis methods, such as gravimetric methods, to accurately measure dust concentration. However, gravimetric methods have drawbacks such as cumbersome operation, long processing time, and delayed results; they cannot provide real-time feedback on changes in dust concentration and are highly sensitive to environmental conditions.

[0003] In recent years, dust concentration monitoring methods based on the principle of optical scattering have been widely used. This method calculates the dust concentration by measuring the intensity of light scattered by dust particles. The scattered light measurement method has advantages such as fast response speed, simple operation, and strong real-time performance, and can well meet the needs of industrial sites for rapid and real-time detection of dust concentration.

[0004] However, existing methods for monitoring dust concentration using scattered light measurement still have certain shortcomings. For example, optical signals are affected by environmental factors such as temperature, humidity, and pollutants, leading to errors in the measurement results. Furthermore, in existing methods, the calculation of regression coefficients usually relies on manually set or empirical parameters, lacking an effective correction mechanism, resulting in low monitoring accuracy and difficulty in adapting to dust concentration monitoring needs under different environmental conditions.

[0005] To overcome the above problems, this invention proposes a dust concentration monitoring method based on scattered light measurement. By rationally designing the various operation procedures of the monitoring system, accurate acquisition and correction of optical scattering signals are achieved, thereby improving the accuracy and reliability of dust concentration measurement. Summary of the Invention

[0006] In view of the shortcomings of the prior art described above, the purpose of this invention is to provide a dust concentration monitoring method and system based on scattered light measurement to solve the above-mentioned technical problems.

[0007] To achieve the above objectives, the present invention provides the following technical solution: a dust concentration monitoring method based on scattered light measurement, comprising: S1: During the range point detection stage, zero point detection is performed by turning off the transmitter to obtain the zero point value and generate the range point detection result; S2: Collect the optical and temperature signals output by the dust detection probe. Based on the optical signal, after demodulation and zero-point value subtraction, the basic scattering intensity is obtained, and then the analog output current is generated. S3: The basic scattering intensity is corrected online by using the real-time calculated correction coefficient and temperature correction coefficient to obtain the optical scattering intensity; S4: By calibrating based on the simulated output current and the concentration by weighing, the current coefficient vector is solved and converted into regression coefficients. When the equipment is running online, the dust concentration is directly generated using the optical scattering intensity and the regression coefficients.

[0008] The present invention is further configured such that S1 includes: After turning off the emitting diode, the optical signal is collected by the detection probe and the in-phase and positive communication channels are obtained by ADC phase-locked demodulation. The amplitude is synthesized by combining the digital quantities of in-phase and positive traffic channels and marked as the zero-point value; Adjust the output light intensity of the emitting diode drive current to a specified ratio of the preset standard reference value, acquire the optical signal collected by the detection probe again, process it and output the composite amplitude; The composite amplitude is compared with the standard reference value to obtain the deviation amplitude; Range point detection results are generated based on the deviation amplitude. The range point detection results include two states: normal and error. If the deviation amplitude is less than the specified range, the result is judged as normal; otherwise, it is judged as error.

[0009] The present invention is further configured such that S2 includes: Optical and temperature signals in flue gas are collected using a detection probe. The collected optical signals are demodulated by an ADC to obtain in-phase and positive cross-channel digital signals, and the amplitude is synthesized as the original scattering signal. The phase angle is extracted based on the digital quantities of the in-phase channel and the digital quantities of the positive-phase channel. The phase angle is compared with the preset reference phase. Combined with the preset phase tolerance width, a signal confidence level between zero and one is generated by a Gaussian function.

[0010] The present invention is further configured such that when the signal confidence level is continuously lower than a set threshold, an automatic re-examination mechanism is triggered. If the confidence level still cannot be recovered after re-examination, the flue environment is determined to be abnormal, and an abnormality notification signal is output to indicate that maintenance is required. When the signal confidence level is greater than or equal to the set confidence threshold, the difference between the original scattered signal and the zero point value is calculated. If the difference is less than the specified ratio, it is determined to be a dust-free or near-dust-free environment, and the dust concentration is set to zero. If the difference is greater than or equal to a specified ratio, an intelligent dark baseline is generated by combining the zero-point value, a preset forgetting factor, and the original scattering signal.

[0011] The present invention is further configured to subtract the intelligent dark baseline from the original scattering signal to generate a preliminary basic scattering intensity, perform non-negative constraint processing on the preliminary basic scattering intensity, set it to zero when the preliminary basic scattering intensity is less than zero, and finally obtain the basic scattering intensity. The basic scattering intensity is sampled when the driving current of the emitting diode is at its maximum value, and this basic scattering intensity is set as the full-scale scattering intensity. Substituting the basic scattering intensity, the preset current output zero point, and the full-scale scattering intensity into the linear mapping formula generates an analog current output signal.

[0012] The present invention is further configured such that S3 includes: Before the end of the range point detection phase, the basic scattering intensity is collected and set as the instantaneous intensity of the current detection phase; Before the system was put into use, the basic scattering intensity and zero-point value of the factory environment were collected synchronously under clean conditions and set as the intensity reference value and dark baseline reference value, respectively. Difference 1 is calculated based on instantaneous intensity combined with intelligent dark baseline, and difference 2 is calculated based on intensity reference value combined with dark baseline reference value; The correction coefficient is constructed based on the ratio of difference one to difference two, and is limited to a specified range by a constraint function; By using a correction coefficient to compensate for the instantaneous scattering intensity, the pollution-compensated scattering intensity is obtained.

[0013] The present invention is further configured to calculate a temperature correction coefficient based on the difference between the temperature signal and a preset reference temperature by combining a pre-calibrated temperature sensitivity coefficient and a temperature index. The pollution compensation scattering intensity is corrected using a temperature correction factor to obtain the final corrected optical scattering intensity.

[0014] The present invention is further configured such that S4 includes: Dust concentration calculation is divided into two stages: Calibration and coefficient calculation stage: During the initial operation of the equipment, the simulated output current of the equipment is used as the independent variable and the simultaneously measured gravimetric concentration value is used as the dependent variable to construct a quadratic polynomial regression model. By collecting multiple sets of data pairs to construct the involved matrix and observation vector, the data pairs include: simulated output current and gravimetric concentration value; The normal equations are processed using the Tikhonov regularization method. Regularization coefficients and a scaling matrix are introduced to ensure numerical stability, and the current coefficient vector based on the current signal is solved. The obtained current coefficient vector is converted into regression coefficients based on optical scattering intensity for direct use within the device through a preset mathematical formula, and then stored in the device.

[0015] The present invention is further configured such that, in the online concentration calculation stage: when the equipment is running online, the concentration value is calculated in real time by combining the optical scattering intensity and the regression coefficients from the calibration and coefficient solving stage, and then the final output dust concentration value is obtained after adaptive filtering.

[0016] The present invention also provides a dust concentration monitoring system based on scattered light measurement, the system comprising: Functional testing and calibration module: During the range point testing phase, zero point testing is performed by turning off the transmitter to obtain the zero point value and generate the range point testing result; Data acquisition module: Acquires optical and temperature signals output by the dust detection probe, obtains the basic scattering intensity based on the optical signal after demodulation and zero-point subtraction, and further generates the analog output current; Environmental and pollution compensation module: The basic scattering intensity is corrected online by real-time calculation of correction coefficients and temperature correction coefficients to obtain the optical scattering intensity; Concentration calculation module: By calibrating based on simulated output current and gravimetric concentration, the current coefficient vector is solved and converted into regression coefficients. When the equipment is running online, the dust concentration is directly generated using optical scattering intensity and regression coefficients.

[0017] This invention provides a dust concentration monitoring method and system based on scattered light measurement. The method comprises: S1: In the range point detection stage, zero-point detection is performed by turning off the transmitter to obtain a zero-point value and generate a range point detection result; S2: Optical and temperature signals output by the dust detection probe are acquired, and the basic scattering intensity is obtained after demodulation and zero-point value subtraction based on the optical signal, further generating a simulated output current; S3: The basic scattering intensity is corrected online using real-time calculated correction coefficients and temperature correction coefficients to obtain the optical scattering intensity; S4: Calibration is performed using the simulated output current and weighing concentration as benchmarks, the current coefficient vector is solved, and it is converted into regression coefficients. When the device is running online, the dust concentration is directly generated using the optical scattering intensity and regression coefficients. The beneficial effects include: Real-time accurate dust concentration measurement: This invention solves the problem of environmental changes interfering with measurement accuracy in traditional scattered light measurement methods by combining real-time correction of optical scattering signals with dynamic compensation for environmental factors such as temperature and pollution. Through intelligent dark baseline compensation and temperature correction, the accuracy and reliability of dust concentration measurement can be effectively improved, ensuring high-precision real-time monitoring under different operating conditions.

[0018] Improving equipment operational stability and reliability: The range point detection and zero-point correction mechanism proposed in this invention, combined with intelligent dark baseline and dynamic correction coefficient, effectively avoids measurement deviations in scattered signals caused by equipment aging or environmental changes, ensuring the stability and reliability of dust concentration monitoring equipment during long-term operation. Furthermore, the introduction of a temperature correction coefficient enables the equipment to adapt to different ambient temperature changes, improving the system's environmental adaptability.

[0019] Improving the accuracy of regression coefficients through Tikhonov regularization: This invention employs the Tikhonov regularization method to address numerical instability in the calculation of regression coefficients, and combines the scaling matrix and regularization coefficients to ensure the stability of the regression model. This innovative method not only improves the accuracy of dust concentration calculation, but also, through mathematical modeling and data calibration, makes the regression coefficients more accurate and adaptive, further enhancing the system's performance under various operating conditions.

[0020] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. In the drawings: Figure 1 A flowchart illustrating a dust concentration monitoring method based on scattered light measurement, as an exemplary embodiment of the present invention; Figure 2 This is a schematic diagram of a dust concentration monitoring system based on scattered light measurement, which is an exemplary embodiment of the present invention. Detailed Implementation

[0022] The embodiments of the present invention will be described below with reference to the accompanying drawings and preferred embodiments. 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, and 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 understood that the preferred embodiments are only for illustrating the present invention and not for limiting the scope of protection of the present invention.

[0023] It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. Therefore, the drawings only show the components related to the present invention and are not drawn according to the actual number, shape and size of the components in the actual implementation. In the actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0024] In the following description, numerous details are explored to provide a more thorough explanation of embodiments of the invention. However, it will be apparent to those skilled in the art that embodiments of the invention may be practiced without these specific details. In other embodiments, well-known structures and devices are shown in block diagram form rather than in detail to avoid obscuring embodiments of the invention.

[0025] Example 1: A dust concentration monitoring method based on scattered light measurement, such as Figure 1 As shown, it includes: S1: During the range point detection stage, zero point detection is performed by turning off the transmitter to obtain the zero point value and generate the range point detection result; S2: Collect the optical and temperature signals output by the dust detection probe. Based on the optical signal, after demodulation and zero-point value subtraction, the basic scattering intensity is obtained, and then the analog output current is generated. S3: The basic scattering intensity is corrected online by using the real-time calculated correction coefficient and temperature correction coefficient to obtain the optical scattering intensity; S4: By calibrating based on the simulated output current and the concentration by weighing, the current coefficient vector is solved and converted into regression coefficients. When the equipment is running online, the dust concentration is directly generated using the optical scattering intensity and the regression coefficients.

[0026] The present invention is further configured such that S1 includes: After turning off the emitting diode, the optical signal is collected by the detection probe and the in-phase and positive communication channels are obtained by ADC phase-locked demodulation. The amplitude is synthesized by combining the digital quantities of in-phase and positive traffic channels and marked as the zero-point value; Adjust the output light intensity of the emitting diode drive current to a specified ratio of the preset standard reference value, acquire the optical signal collected by the detection probe again, process it and output the composite amplitude; The composite amplitude is compared with the standard reference value to obtain the deviation amplitude; Range point detection results are generated based on the deviation amplitude. These results include two states: normal and error. If the deviation amplitude is less than a specified range, the result is considered normal; otherwise, it is considered error. Specifically, before starting range point detection, the emitting diode is first turned off to ensure that, in the absence of a light source, the system can only detect ambient noise and the background signal from the probe itself. At this time, the signal acquired by the probe is the "zero-point value," i.e., the basic signal without scattered light. To obtain this value, ADC phase-locked demodulation technology is used to process the acquired optical signal. After ADC phase-locked demodulation, the in-phase and positive-path digital quantities are extracted separately. These two digital quantities represent the signal amplitudes of different phase channels after signal demodulation. Since these two signals are related to the original optical signal, they can accurately reflect the system's operating state. The in-phase and positive-path digital quantities are synthesized to obtain a composite amplitude value, which represents the optical signal intensity in the absence of a light source. This composite amplitude is the "zero-point value," which will be used as a calibration reference point to determine the scattered light intensity under actual operating conditions in subsequent work. The driving current of the emitting diode is adjusted to ensure that the output light intensity meets the specified ratio of the preset standard reference value. At this stage, the repeatability of the measurement results is ensured by precisely controlling the output light intensity of the emitting diode. The adjusted light intensity serves as the optical signal source for the detection probe to acquire. After adjusting the emitted light intensity, the scattered light signal is acquired again by the probe. This time, the signal acquired by the probe is processed to obtain a new composite amplitude, representing the amplitude of the scattered signal under known light source intensity conditions. The acquired composite amplitude is compared with the preset standard reference value, and the deviation amplitude between the two is calculated. The purpose of this step is to check the degree of deviation between the current system's optical signal and the reference standard value. If the deviation amplitude is within the predetermined range, the system is working normally; if the deviation amplitude exceeds the specified range, it indicates that the system is abnormal and requires maintenance or adjustment. Based on the magnitude of the deviation amplitude, a range point detection result is generated. If the deviation amplitude is less than the specified range, the detection result is judged to be normal; if the deviation amplitude is greater than the specified range, it is judged to be an error, and a corresponding fault warning signal is issued.

[0027] The present invention is further configured such that S2 includes: Optical and temperature signals in flue gas are collected using a detection probe. The collected optical signals are demodulated by an ADC to obtain in-phase and positive cross-channel digital signals, and the amplitude is synthesized as the original scattering signal. The phase angle is extracted based on the digital quantities of the in-phase channel and the digital quantities of the positive-phase channel. The phase angle is compared with the preset reference phase. Combined with the preset phase tolerance width, a signal confidence level between zero and one is generated by a Gaussian function. When the signal confidence level remains below the set threshold, an automatic re-examination mechanism is triggered. If the confidence level still cannot be recovered after re-examination, the flue environment is determined to be abnormal, and an abnormality notification signal is output, indicating that maintenance is required. When the signal confidence level is greater than or equal to the set confidence threshold, the difference between the original scattered signal and the zero point value is calculated. If the difference is less than the specified ratio, it is determined to be a dust-free or near-dust-free environment, and the dust concentration is set to zero. If the difference is greater than or equal to a specified ratio, an intelligent dark baseline is generated by combining the zero-point value, a preset forgetting factor, and the original scattering signal. The intelligent dark baseline is subtracted from the original scattering signal to generate the preliminary basic scattering intensity. The preliminary basic scattering intensity is subjected to non-negative constraint processing. When the preliminary basic scattering intensity is less than zero, it is set to zero, and the basic scattering intensity is finally obtained. The basic scattering intensity is sampled when the driving current of the emitting diode is at its maximum value, and this basic scattering intensity is set as the full-scale scattering intensity. Substituting the basic scattering intensity, the preset current output zero point, and the full-scale scattering intensity into the linear mapping formula generates an analog current output signal. Specifically, firstly, an optical signal and a temperature signal are simultaneously acquired using a probe in the flue gas. The probe converts the optical signal into a digital signal, and the temperature data is acquired in real time by a temperature sensor. These signals provide raw data for subsequent processing. The acquisition and conversion of the digital signal is the same as the method used to construct the "zero point value" in the preceding step S1. The difference is that the zero point value is set as a reference value, a baseline value acquired by the system in a dark environment, while here the real-time environmental value in the flue is acquired during system operation. The amplitude marker obtained from the post-processing of this acquisition is used as the raw scattering signal. Based on the demodulated in-phase channel digital quantity and the positive-mode channel digital quantity, the phase angle is extracted. The phase angle is compared with the preset reference phase to generate a signal confidence level. The generation of the signal confidence level depends on the phase tolerance width and is calculated using a Gaussian function, resulting in a value between zero and one. If the signal confidence level is detected to be continuously lower than the set threshold, an automatic re-detection mechanism is triggered. After retesting, if the signal confidence level still cannot be restored to the set threshold, the system will determine that the flue environment is abnormal and issue an abnormality notification signal, prompting the user to perform maintenance operations. When the signal confidence level is greater than or equal to the set confidence level threshold, further processing is performed: 1. Calculate the difference between the original scattered signal and the zero-point value; 2. If the difference is less than a specified proportion, the system will determine that it is a dust-free or near-dust-free environment and set the dust concentration to zero; 3. If the difference is greater than or equal to a specified proportion, it is considered that there is dust in the flue environment, and subsequent calculations continue. When the difference is greater than a specified proportion, a smart dark baseline is generated by combining the zero-point value, the preset forgetting factor, and the original scattered signal. The generation process of the smart dark baseline reduces the influence of optical equipment drift and background noise by weighting historical data. The generated smart dark baseline is subtracted from the original scattered signal to obtain the preliminary basic scattered intensity; subsequently, the preliminary basic scattered intensity is subjected to non-negative constraint processing, that is: when the preliminary basic scattered intensity is less than zero, it is set to zero to ensure the accuracy and rationality of subsequent data. When the emitting diode's drive current output reaches its maximum value, the baseline scattering intensity is acquired and set as the full-scale scattering intensity. This process ensures that the system can correctly calibrate the maximum output intensity under different operating conditions and dynamically adjust it according to actual conditions. Finally, by substituting the baseline scattering intensity, the preset current output zero point, and the full-scale scattering intensity into the linear mapping formula, a corresponding analog current output signal is generated. This analog signal reflects the real-time dust concentration and is ultimately used for feedback control or display.

[0028] The present invention is further configured such that S3 includes: Before the end of the range point detection phase, the basic scattering intensity is collected and set as the instantaneous intensity of the current detection phase; Before the system was put into use, the basic scattering intensity and zero-point value of the factory environment were collected synchronously under clean conditions and set as the intensity reference value and dark baseline reference value, respectively. Difference 1 is calculated based on instantaneous intensity combined with intelligent dark baseline, and difference 2 is calculated based on intensity reference value combined with dark baseline reference value; The correction coefficient is constructed based on the ratio of difference one to difference two, and is limited to a specified range by a constraint function; The pollution-compensated scattering intensity is obtained by compensating the instantaneous scattering intensity using a correction coefficient. Based on the difference between the temperature signal and the preset reference temperature, the temperature correction coefficient is calculated by combining the pre-calibrated temperature sensitivity coefficient and temperature index. The pollution compensation scattering intensity is corrected using a temperature correction coefficient to obtain the final corrected optical scattering intensity. Specifically, this step uses a precise scattering intensity correction method, combined with intelligent dark baseline, pollution compensation, and temperature correction, to achieve accurate optical scattering intensity calculation under dynamically changing operating conditions, thereby enabling accurate measurement of dust concentration. By comparing the instantaneous intensity with the reference value, correcting the temperature signal, and compensating for other external factors, a stable and reliable corrected optical scattering intensity signal is finally obtained. Instantaneous baseline scattering intensity acquisition involves collecting the instantaneous baseline scattering intensity of the current detection stage before the end of the range point detection stage. The purpose of this step is to record the instantaneous signal of the environment at the current stage. This signal will then be used for subsequent pollution compensation calculations. Optical signals in the flue are collected in real time by the detection probe to generate astigmatic optical scattering intensity data. This optical intensity data is set as the baseline scattering intensity and stored in the value system for easy retrieval later. The acquisition method of this process is consistent with the aforementioned steps, so it will not be described again here. Before system operation or maintenance, the equipment should be calibrated under clean environmental conditions. The collected baseline scattering intensity is used for subsequent pollution compensation and correction. This process can be performed using known environmental conditions. The collected scattering intensity is set as the intensity reference value, and the zero-point value is set as the dark baseline reference value. Using the real-time data obtained in the aforementioned steps, instantaneous calculations are performed. The intelligent dark baseline plays a crucial role here, dynamically compensating the signal based on historical environmental data or preset algorithms, thereby effectively filtering noise in the real-time environment. Difference 1 is calculated by combining the instantaneous scattering intensity and the intelligent dark baseline; Difference 2 is calculated by combining the intensity reference value and the dark baseline reference value. A correction coefficient is constructed based on the ratio of Difference 1 to Difference 2. The ratio calculation method can use simple weighted averaging or linear interpolation, etc., and is adaptively adjusted according to the equipment's operating environment. To ensure the rationality of the signal, the correction coefficient is limited to a specified range by constraint functions. Overcompensation is avoided by setting an effective range for the calculation results. Based on the difference between the temperature signal and a preset reference temperature, a temperature correction coefficient is calculated. This coefficient compensates for the impact of temperature changes on optical scattering intensity. Compensation is achieved using empirical data or theoretical models, combined with the known relationship between temperature change curves and scattering intensity. This process can be implemented using existing temperature correction formulas or machine learning algorithms. Finally, the pollution-compensated scattering intensity is corrected using the temperature correction coefficient to obtain the final corrected optical scattering intensity. This final temperature correction ensures that the scattering intensity signal remains accurate under varying temperature conditions, thereby improving the accuracy of dust concentration calculation. This process considers multiple factors, including temperature and environmental pollution. The final corrected optical scattering intensity will be used for real-time dust concentration calculation.

[0029] The present invention is further configured such that S4 includes: Dust concentration calculation is divided into two stages: Calibration and coefficient calculation stage: During the initial operation of the equipment, the simulated output current of the equipment is used as the independent variable and the simultaneously measured gravimetric concentration value is used as the dependent variable to construct a quadratic polynomial regression model. By collecting multiple sets of data pairs to construct the involved matrix and observation vector, the data pairs include: simulated output current and gravimetric concentration value; The normal equations are processed using the Tikhonov regularization method. Regularization coefficients and a scaling matrix are introduced to ensure numerical stability, and the current coefficient vector based on the current signal is solved. The obtained current coefficient vector is converted into regression coefficients based on optical scattering intensity for direct use within the device through a preset mathematical formula, and then stored in the device. Online concentration calculation stage: When the equipment is running online, the concentration value is calculated in real time using a preset formula, combining the optical scattering intensity and the regression coefficients from the calibration and coefficient solving stages. This value is then processed through adaptive filtering to obtain the final output dust concentration value. Specifically, the dust concentration calculation is divided into two stages: the calibration and coefficient solving stage and the online concentration calculation stage.

[0030] The calibration and coefficient calculation phase requires the following steps: During initial equipment operation, the simulated output current of the equipment is collected, and the concentration value is obtained by weighing using the gravity measurement method according to EN13284 and the reverse-current measurement method. The weighing concentration value is used as the dependent variable to construct a quadratic polynomial regression model. Next, based on the collected simulated output current and weighing concentration value, a design matrix and observation vector are constructed. The design matrix should include the quadratic term, first-order term, and constant term of the simulated output current to ensure sufficient features are included for solving the regression model.

[0031] The design matrix is ​​used as input to the regression model. The Tikhonov regularization method is applied to process the regression equation, incorporating regularization coefficients and a scaling matrix to ensure numerical stability, reduce the impact of noise in the data, and prevent overfitting. The regularization coefficients can be adjusted based on the actual data characteristics through cross-validation or empirical setting. This method is used to calculate the current coefficient vector based on the current signal.

[0032] Then, based on the physical relationship between current and scattered light intensity, the current coefficient vector is converted into regression coefficients based on optical scattering intensity, and the regression coefficients are stored in the device for subsequent use.

[0033] The online concentration calculation phase requires the following steps: During online operation, the device collects optical scattering intensity signals and combines them with regression coefficients obtained during calibration and coefficient solving. Using optical scattering intensity as a substitute input for analog current, the device performs multiplication based on pre-calculated regression coefficients to calculate and feed back the current dust concentration in real time. To further improve the accuracy of dust concentration calculation, the device applies an adaptive filtering algorithm to process the concentration calculation results. Kalman filtering or other suitable filtering algorithms are used to process the dust concentration data, ensuring high accuracy and stability of the output data. This reduces interference from instantaneous fluctuations and measurement noise, improving the stability and reliability of concentration measurement. This invention does not limit the filtering algorithm; any algorithm can be used to assist in the implementation of this invention.

[0034] Example 2: Please see Figure 2 This exemplary dust concentration monitoring system based on scattered light measurement includes: Functional testing and calibration module: During the range point testing phase, zero point testing is performed by turning off the transmitter to obtain the zero point value and generate the range point testing result; Data acquisition module: Acquires optical and temperature signals output by the dust detection probe, obtains the basic scattering intensity based on the optical signal after demodulation and zero-point subtraction, and further generates the analog output current; Environmental and pollution compensation module: The basic scattering intensity is corrected online by real-time calculation of correction coefficients and temperature correction coefficients to obtain the optical scattering intensity; Concentration calculation module: By calibrating based on simulated output current and gravimetric concentration, the current coefficient vector is solved and converted into regression coefficients. When the equipment is running online, the dust concentration is directly generated using optical scattering intensity and regression coefficients.

[0035] It should be noted that the dust concentration monitoring system based on scattered light measurement provided in the above embodiments and the dust concentration monitoring method based on scattered light measurement provided in the above embodiments belong to the same concept. The specific operation methods of each module and unit have been described in detail in the method embodiments and will not be repeated here. In practical applications, the dust concentration monitoring system based on scattered light measurement provided in the above embodiments can be assigned to different functional modules as needed, that is, the internal structure of the system can be divided into different functional modules to complete all or part of the functions described above. This is not a limitation here.

[0036] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A dust concentration monitoring method based on scattered light measurement, characterized by, Comprise: S1: in the range point detection stage, by closing the transmitter to implement zero point detection to obtain zero point value, generate range point detection results; S2: collect the optical signal and temperature signal output by the dust detection probe, and obtain the basic scattering intensity by demodulating the optical signal and deducting the zero point value, and further generate the analog output current; S3: by real-time calculation of correction coefficient and temperature correction coefficient, the basic scattering intensity is corrected online to obtain the optical scattering intensity; S4: by taking the analog output current and the concentration of weighing method as the benchmark to calibrate, the current coefficient vector is solved, and it is converted into regression coefficient, and when the equipment is running online, the optical scattering intensity and the regression coefficient are used to generate dust concentration.

2. The dust concentration monitoring method based on scattered light measurement according to claim 1, characterized in that, The S1 comprises: After closing the emitting diode, the optical signal is collected by the detection probe, and the in-phase and quadrature channel digital quantities are obtained by ADC phase demodulation; By synthesizing the amplitudes of the in-phase and quadrature channel digital quantities, the zero point value is marked; Adjust the driving current output of the emitting diode to be a specified proportion of the preset standard reference value, and acquire the optical signal collected by the detection probe again, and output the synthesized amplitude after processing; Compare the synthesized amplitude with the standard reference value to obtain the deviation amplitude; Generate the range point detection result based on the deviation amplitude, and the range point detection result includes two states of normal and error, if the deviation amplitude is less than the specified range, the result is normal, otherwise, it is judged as error.

3. The dust concentration monitoring method based on scattered light measurement according to claim 1, characterized in that, The S2 comprises: The optical signal and temperature signal in the flue gas are collected by the detection probe, the in-phase and quadrature channel digital quantities are obtained by ADC phase demodulation, and the synthesized amplitude is used as the original scattering signal; Based on the in-phase channel digital quantity and the quadrature channel digital quantity, the phase angle is extracted, the phase angle is compared with the preset reference phase, the phase tolerance width is combined, and a signal confidence degree between zero and one is generated by Gaussian function.

4. The dust concentration monitoring method based on scattering light measurement according to claim 3, wherein When the signal confidence degree is continuously lower than the set threshold, the automatic reinspection mechanism is triggered, if the confidence degree cannot be restored after reinspection, it is judged that the flue environment is abnormal, and an abnormal notification signal is output to prompt maintenance; When the signal confidence degree is greater than or equal to the set confidence threshold, the difference between the original scattering signal and the zero point value is calculated, if the difference is less than the specified proportion, it is judged that there is no dust or the environment is close to no dust, and the dust concentration is set to zero; If the difference is greater than or equal to the specified proportion, the intelligent dark baseline is generated by combining the zero point value, the preset forgetting factor and the original scattering signal.

5. The dust concentration monitoring method based on scattering light measurement according to claim 4, wherein The intelligent dark baseline is deducted from the original scattering signal to generate the preliminary basic scattering intensity, the non-negative constraint processing is performed on the preliminary basic scattering intensity, and when the preliminary basic scattering intensity is less than zero, it is set to zero, and finally the basic scattering intensity is obtained; The basic scattering intensity is collected when the maximum value of the driving current output of the emitting diode is collected, and the basic scattering intensity at this time is set as the full-scale scattering intensity. The base scattering intensity, the preset current output zero point and the full range scattering intensity are substituted into the linear mapping formula to generate an analog current output signal.

6. The dust concentration monitoring method based on scattered light measurement according to claim 1, characterized in that, The S3 comprises: The base scattering intensity is collected before the end of the range point detection stage and is set as the instantaneous intensity of the current detection stage; The synchronous base scattering intensity and zero point value are collected under clean conditions in the factory environment before the system is put into use and are set as the intensity reference value and the dark baseline reference value respectively; Difference one is calculated based on the instantaneous intensity and the intelligent dark baseline, and difference two is calculated based on the intensity reference value and the dark baseline reference value; The correction coefficient is constructed based on the ratio of difference one to difference two and is limited in a specified range through a constraint function; The instantaneous scattering intensity is compensated by using the correction coefficient to obtain the pollution compensation scattering intensity.

7. The dust concentration monitoring method based on scattering light measurement according to claim 6, characterized in that, The temperature correction coefficient is calculated by combining the temperature sensitive coefficient and the temperature index pre-calibrated based on the difference between the temperature signal and the preset reference temperature; The pollution compensation scattering intensity is corrected by using the temperature correction coefficient to obtain the final corrected optical scattering intensity.

8. The dust concentration monitoring method based on scattered light measurement according to claim 1, characterized in that, The S4 comprises: The dust concentration calculation is divided into two stages: The calibration and coefficient solving stage: a quadratic polynomial regression model is constructed with the analog output current of the device as the independent variable and the synchronous measured concentration value by the weighing method as the dependent variable when the device is initially operated; A plurality of data pairs are collected to constitute a matrix and an observation vector, and the data pairs include the analog output current and the concentration value by the weighing method; The normal equation is processed by using the Tikhonov regularization method, the regularization coefficient and the scale matrix are introduced to ensure numerical stability, and the current coefficient vector based on the current signal is solved; The obtained current coefficient vector is converted into the regression coefficient based on the optical scattering intensity used directly in the device through a preset mathematical relationship and is stored in the device.

9. The dust concentration monitoring method based on scattering light measurement according to claim 8, characterized in that, The online concentration calculation stage: the concentration value is calculated in real time by using the optical scattering intensity and the regression coefficient of the calibration and coefficient solving stage through a preset formula when the device is operated online, and the final output dust concentration value is obtained after adaptive filtering processing.

10. A dust concentration monitoring system based on scattered light measurement for implementing a dust concentration monitoring method based on scattered light measurement according to any one of claims 1 to 9, characterized in that It comprises: The function detection and calibration module: the zero point value is obtained by closing the transmitter to implement zero point detection in the range point detection stage, and the range point detection result is generated; The data acquisition module: the optical signal and the temperature signal output by the dust detection probe are collected, the base scattering intensity is obtained based on the optical signal after demodulation and zero point deduction, and the analog output current is further generated; The environment and pollution compensation module: the base scattering intensity is corrected online by using the correction coefficient and the temperature correction coefficient calculated in real time to obtain the optical scattering intensity; The concentration calculation module: the current coefficient vector is solved by calibrating based on the analog output current and the concentration by the weighing method, and the regression coefficient is converted, and the dust concentration is directly generated by using the optical scattering intensity and the regression coefficient when the device is operated online.

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