Multi-component gas detection and analysis system and method for waste incineration power plant

Abstract

The invention discloses a multi-component gas detection and analysis system and method for a waste incineration power plant, and relates to the technical field of waste incineration and flue gas detection, the system comprises a sampling module, a spectrum analysis module, a detection module, a processing module and a processing module, the sampling module is used for synchronously collecting multi-component flue gas samples containing heavy metal components at specified sampling points of the waste incineration power plant; the spectrum analysis module is used for performing real-time component concentration measurement on the flue gas sample collected by the sampling module, and the simulation and prediction module is used for simulating and predicting temperature fields and heavy metal volatilization conditions at different positions in the furnace based on a component concentration measurement result of the spectrum analysis module; according to the multi-component gas detection and analysis system and method for the waste incineration power plant, the accuracy and robustness of data acquisition are enhanced; the simulation and prediction module provides dynamic visualization of a temperature field and heavy metal volatilization, and is convenient for an operator to monitor and optimize operation. The whole system is modularized in design and easy to maintain and upgrade.

Description

Technical Field

[0001] The present invention relates to the technical field of waste incineration and flue gas detection, and particularly relates to a multi-component gas detection and analysis system and method for a waste incineration power plant. Background Art

[0002] In a waste incineration power plant, flue gas detection and analysis is an important means to ensure the stability and environmental protection of the incineration process. The existing detection technologies mainly focus on the sampling analysis of flue gas components and the detection by fixed-position sensors. These methods can monitor the main components and contents of flue gas to a certain extent. However, due to the complex distribution of the flue gas flow field in the incinerator, the existing technologies have insufficient detection coverage of the overall flow field, and it is difficult to accurately reflect the local gas component and temperature change conditions.

[0003] In particular, in local areas of the incinerator, the volatility of heavy metals may increase due to high temperatures, and the occurrence of this phenomenon is characterized by suddenness and locality. The fixed detection methods or off-line analysis in the existing technologies cannot effectively identify and timely adjust the local high-temperature areas. As a result, the volatilization amount of heavy metals may increase, which may have an adverse impact on environmental emissions. In addition, the dynamic feedback ability of the existing detection means is insufficient, making it difficult for operators to timely adjust the operating parameters of the incinerator to cope with the changes in gas components, further affecting the incineration efficiency and the achievement of emission standards. Summary of the Invention

[0004] The purpose of the present invention is to provide a multi-component gas detection and analysis system and method for a waste incineration power plant, which detects and feedbacks the distribution characteristics of the flue gas flow field in the furnace to solve the problem of increased volatility of heavy metals caused by local high temperatures.

[0005] To achieve the above purpose, the present invention provides the following technical solution: A multi-component gas detection and analysis system for a waste incineration power plant, the system includes:

[0006] A sampling module, which is used to synchronously collect multi-component flue gas samples containing heavy metal components at designated sampling points in a waste incineration power plant;

[0007] A spectral analysis module connected to the sampling module, including for real-time determination of the component concentrations of the flue gas samples collected by the sampling module;

[0008] A simulation and prediction module connected to the spectral analysis module, which is used to simulate and predict the temperature field and heavy metal volatilization conditions at different positions in the furnace based on the component concentration determination results of the spectral analysis module;

[0009] A feedback and optimization module connected to the simulation and prediction module, which is used to perform targeted detection on specific areas in the incinerator based on the results of the simulation and prediction module and feedback and optimize the flue gas treatment process to reduce the excessive volatilization of heavy metals caused by local high temperatures.

[0010] Preferably, the sampling module synchronously collects multi-component flue gas samples containing heavy metal components at designated sampling points in the waste incineration power plant, including modeling the concentration of flue gas components and analyzing the relationship between sampling time and concentration uniformity.

[0011] Preferably, the spectral analysis module is used to measure the real-time component concentration of the flue gas samples collected by the sampling module, including using a laser-induced breakdown spectrometer to detect the spectrum of the flue gas samples, recording the characteristic waves of metal components, and correcting the wavelength shift caused by the flow field velocity.

[0012] Preferably, the simulation prediction module is used to simulate and predict the temperature field and heavy metal volatilization at different positions in the furnace based on the component concentration measurement results of the spectral analysis module, including:

[0013] Simulating the temperature field distribution inside the incinerator;

[0014] Outputting the temperature field distribution map and volatilization data, providing a basis for the feedback optimization module.

[0015] Preferably, the feedback optimization module, based on the results of the simulation prediction module, conducts targeted detection on specific areas inside the incinerator and feeds back to optimize the flue gas treatment process to reduce the excessive volatilization of heavy metals caused by local high temperatures, including inputting the results output by the simulation prediction module into the feedback optimization module and calculating the marginal benefit of local high temperature regulation.

[0016] Preferably, the sampling module includes multiple sampling devices, which are respectively arranged at different positions of the incinerator to synchronously collect multi-point flue gas samples, thereby improving the representativeness and accuracy of detection.

[0017] Preferably, the spectral analysis module includes a laser-induced breakdown spectrometer, which is used to analyze the heavy metal components in the flue gas samples in real time through laser technology and generate accurate concentration data.

[0018] Preferably, the spectral analysis module further includes a data filtering device, which is used to process the noise in the detection signal.

[0019] Preferably, the simulation prediction module includes a temperature field dynamic display device, which is used to visually display the temperature distribution and high-temperature areas inside the incinerator in real time.

[0020] A multi-component gas detection and analysis method for a waste incineration power plant, using the multi-component gas detection and analysis system for a waste incineration power plant as described above, the method includes:

[0021] S1. Synchronously collect multi-component flue gas samples containing heavy metal components at designated sampling points in the waste incineration power plant;

[0022] S2. Perform real-time component concentration measurement on the collected flue gas samples using a laser-induced breakdown spectrometer;

[0023] S3. Use a computational fluid dynamics model to simulate and predict the temperature field and heavy metal volatilization at different positions in the furnace based on the component concentration measurement results;

[0024] S4. Based on the simulation and prediction results, conduct targeted detection on specific areas and feedback to optimize the flue gas treatment process to reduce excessive heavy metal volatilization caused by local high temperatures.

[0025] As can be seen from the above technical solutions, the present invention has the following beneficial effects:

[0026] This multi-component gas detection and analysis system and method for a waste incineration power plant realizes the synchronous collection and real-time analysis of multi-component flue gas samples in the incinerator by combining a sampling module and a spectral analysis module. It can not only detect the conventional components in the flue gas but also accurately quantify the heavy metal component concentrations. Compared with the methods of fixed sampling or off-line analysis in the prior art, the present invention can cover multiple positions in the incinerator, improving the representativeness and accuracy of flue gas detection. It dynamically simulates the temperature field at different positions in the incinerator and combines the concentration measurement data of the spectral analysis module to accurately predict the volatilization path and concentration distribution of heavy metals. This prediction ability solves the problem in the prior art that it is impossible to identify local high-temperature areas and changes in heavy metal volatility, thus providing an important basis for optimizing the incineration process. Through the feedback optimization module for real-time adjustment based on the PID control algorithm, it can adjust the operating parameters of the incinerator according to the results provided by the simulation and prediction module, thereby effectively reducing excessive heavy metal volatilization caused by local high temperatures. Compared with the prior art, this solution has significant advantages in terms of dynamic adjustment ability and response speed, ensuring the stability and environmental protection of the incineration process. By combining the real-time data of the spectral analysis module and the simulation and prediction module, it realizes the comprehensive monitoring of the flue gas flow field and heavy metal volatilization in the incinerator, can quickly take optimization measures at the initial stage of the high-temperature area formation, reduce heavy metal emissions, significantly improve the flue gas emission quality, and thus effectively reduce the impact of waste incineration on the environment. The sampling module is designed as multiple sampling devices, and the sampling points can be flexibly arranged according to the scale and structure of the incinerator, improving the system applicability; the spectral analysis module introduces a laser-induced breakdown spectrometer and combines it with a data filtering device, enhancing the accuracy and robustness of data collection; the simulation and prediction module provides dynamic visualization of the temperature field and heavy metal volatilization, facilitating operators to monitor and optimize the operation. The overall system design is modular, making it easy to maintain and upgrade. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 It is a schematic diagram of the connection of the system modules of the present invention;

[0028] Figure 2This is the flowchart of the method of the present invention. Detailed implementation manners

[0029] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0030] As Figure 1 shown, the present invention provides a technical solution: a multi-component gas detection and analysis system for a waste incineration power plant, and the system includes:

[0031] A sampling module, configured to synchronously collect multi-component flue gas samples containing heavy metal components at specified sampling points in the waste incineration power plant;

[0032] A spectral analysis module connected to the sampling module, including being used for performing real-time component concentration measurement on the flue gas samples collected by the sampling module;

[0033] A simulation and prediction module connected to the spectral analysis module, configured to simulate and predict the temperature field and heavy metal volatilization conditions at different positions in the furnace based on the component concentration measurement results of the spectral analysis module;

[0034] A feedback and optimization module connected to the simulation and prediction module, configured to perform targeted detection on specific areas in the incinerator based on the results of the simulation and prediction module and feedback to optimize the flue gas treatment process to reduce the excessive volatilization of heavy metals caused by local high temperatures.

[0035] In the above embodiment, the sampling module collects multi-component flue gas samples in real time through designated sampling points set in the waste incineration power plant, using high-precision sampling probes and adsorption devices to ensure the representativeness of the sampling points and the integrity of multiple components during the sampling process. The collected flue gas samples are transmitted through pipelines to the spectral analysis module, which rapidly determines the concentrations of heavy metal components (such as lead, mercury, cadmium, etc.) in the flue gas based on analysis techniques such as ultraviolet, infrared, or Raman spectroscopy. The measurement results are transmitted in real time to the simulation prediction module, which uses built-in calculation models (such as numerical simulation, neural network models, etc.), combined with the structural parameters and operating conditions of the incinerator, to deduce the temperature field distribution in different regions of the furnace and evaluate the volatilization behavior of heavy metals under high-temperature conditions. According to the prediction results, the feedback optimization module analyzes the temperature anomalies and excessive heavy metal volatilization in specific regions and automatically adjusts the operating parameters of the incinerator, such as optimizing the oxygen supply in the furnace or adjusting the fuel distribution, to inhibit heavy metal volatilization and improve the flue gas treatment efficiency. This embodiment realizes the precise detection and dynamic control of the flue gas components in the waste incineration power plant by integrating four major modules: sampling, spectral analysis, simulation prediction, and feedback optimization. Specifically, the present invention can monitor the heavy metal concentration in the flue gas in real time, predict its volatilization behavior, and optimize the incineration process according to the feedback, solving the problem of excessive heavy metal volatilization caused by local high temperatures in traditional incineration processes. Compared with the prior art, this system significantly improves the safety and environmental protection of flue gas treatment, and at the same time reduces the operating cost by optimizing the operating parameters.

[0036] The sampling module synchronously collects multi-component flue gas samples containing heavy metal components at designated sampling points in the waste incineration power plant, including modeling the concentration of flue gas components and analyzing the relationship between sampling time and concentration uniformity. The specific formula is:

[0037] where C represents the concentration of a certain component in the flue gas, t represents time, D represents the diffusion coefficient, represents the second-order spatial derivative of the concentration.

[0038] In the above embodiment, the sampling module uses precise sampling equipment to synchronously collect flue gas samples at designated sampling points in the waste incineration power plant. By dynamically modeling the concentration of the collected flue gas components, the system analyzes the time-evolution characteristics of the flue gas components based on the diffusion equation The diffusion coefficient D is determined according to the physical and chemical properties of the flue gas (such as temperature, pressure, and interactions between components), which describes the concentration diffusion rate. In the formula, It represents the changing trend of the flue gas concentration in the spatial distribution, and its value is obtained through numerical calculation methods. Through this modeling method, the system can accurately predict the changes in the concentration distribution of each component in the flue gas (such as heavy metal vapors and other pollutants) over time and space. This analysis result can provide more accurate input data for the simulation prediction module, further improving the prediction accuracy of the temperature field in the furnace and the heavy metal volatilization behavior. In this embodiment, by establishing a time and space variation model of the flue gas component concentration, the dynamic monitoring and analysis of the multi-component concentration distribution in the flue gas of the waste incineration power plant are realized. Compared with the traditional method based on single-point concentration detection, this system can accurately describe the diffusion law of the component concentration in the flue gas, help optimize the incineration process, and further reduce the emission of harmful components. In addition, the use of mathematical modeling methods significantly improves the understanding of the complex behavior of the flue gas and can provide more reliable basic data for the subsequent simulation prediction and feedback optimization links.

[0039] The spectral analysis module is used to measure the real-time component concentration of the flue gas sample collected by the sampling module, including using a laser-induced breakdown spectrometer to perform spectral detection on the flue gas sample, recording the characteristic waves of metal components, and correcting the wavelength shift caused by the flow field velocity. The specific formula is:

[0040]

[0041] Among them, λ′ represents the measured wavelength, λ0 represents the theoretical wavelength, v represents the gas velocity, and c represents the speed of light.

[0042] In the above embodiment, the spectral analysis module uses laser-induced breakdown spectroscopy technology to perform real-time detection on the flue gas sample transmitted by the sampling module. The LIBS technology excites the components in the flue gas sample through high-power laser pulses to form a plasma, and analyzes the radiation spectrum of the plasma to obtain the characteristic wavelengths of the metal components in the flue gas sample. Due to the existence of flow velocity in the flue gas of the waste incineration power plant, the spectral signal may be affected by the Doppler effect, resulting in wavelength shift. To ensure the accuracy of component concentration measurement, in this embodiment, according to the formula corrects the measured wavelength λ′, where v is the gas flow velocity, c is the speed of light, and λ 0 is the theoretical wavelength of a specific component. By matching the corrected wavelength value with the standard spectral library, the concentration of each component in the flue gas sample is determined. The correction process includes: measuring the flow velocity v of the flue gas in real time, which can be achieved through the built-in gas flow sensor; calculating the wavelength shift caused by the Doppler effect according to the measured flow velocity v; converting the measured wavelength value λ′ into the corrected wavelength value λ 0, ensuring the accuracy of the detection results. In this embodiment, by combining laser-induced breakdown spectroscopy technology and Doppler effect correction algorithm, high-precision detection of heavy metal components in the flue gas of waste incineration power plants is achieved. Compared with traditional spectral analysis methods, the accuracy and real-time performance of detection are significantly improved in this system. Especially for high-speed flowing flue gas samples, this embodiment effectively eliminates the wavelength shift caused by the flow field velocity, ensuring the reliability of concentration measurement. At the same time, the rapid detection of trace components such as heavy metals by this method improves the control ability of the incineration process and helps to reduce the emission of harmful substances.

[0043] A simulation prediction module, used to simulate and predict the temperature field and heavy metal volatilization conditions at different positions in the furnace based on the component concentration measurement results of the spectral analysis module, including:

[0044] Simulate the temperature field distribution inside the incinerator, and the specific formula is:

[0045] where T represents temperature, t represents time, k represents thermal conductivity, represents the second-order spatial derivative of temperature;

[0046] Output the temperature field distribution map and volatilization data, providing a basis for the feedback optimization module.

[0047] In the above embodiment, the simulation prediction module establishes a mathematical model of the temperature field and heavy metal volatilization behavior in the incinerator based on the component concentration measurement results of the spectral analysis module. Through the heat conduction equation This module dynamically simulates the temperature field distribution in the furnace. Among them, the thermal conductivity k depends on the thermal physical properties of the combustion materials in the furnace, such as fuel type, flue gas composition, and incineration conditions, etc. The specific simulation process is as follows: collect the flue gas composition concentration data detected by the spectral analysis module, and combine the structural parameters in the furnace (such as furnace dimensions, flame distribution) as the initial conditions; use the heat conduction equation to calculate the temperature field distribution at different positions in the furnace over time; after obtaining the temperature field distribution, combine the volatilization characteristic curves of heavy metals (such as the temperature-volatilization rate relationship) to calculate the volatilization amounts of heavy metals in different regions; output the calculation results as the temperature field distribution map and volatilization amount data, providing data support for the feedback optimization module to help optimize the operation parameters in the furnace. Through this simulation prediction module, it is possible to accurately locate the possible local high-temperature regions in the furnace and quantify the heavy metal volatilization behavior in these regions, providing a scientific basis for subsequent process optimization. In this embodiment, the dynamic simulation of the temperature field and heavy metal volatilization in the incinerator is realized through the simulation prediction module, significantly improving the system's control ability for the incineration process. Compared with the traditional empirical adjustment method, this module is based on the heat conduction equation and multi-component concentration data for accurate calculation, and can effectively discover and predict local high-temperature phenomena and the resulting heavy metal volatilization problems, thereby optimizing the incineration process and reducing pollutant emissions. In addition, the temperature field and volatilization amount data provided by this module can provide a scientific basis for the subsequent feedback optimization module, making the overall system more intelligent and environmentally friendly.

[0048] Based on the results of the simulation prediction module, the feedback optimization module conducts targeted detection on specific areas in the incinerator and provides feedback to optimize the flue gas treatment process to reduce the excessive volatilization of heavy metals caused by local high temperatures, including inputting the results output by the simulation prediction module into the feedback optimization module to calculate the marginal benefit of local high-temperature adjustment. The specific formula is: A = X / Y;

[0049] Among them, A represents the marginal benefit, X represents the emission reduction amount, and Y represents the adjustment cost.

[0050] In the above embodiment, the feedback optimization module detects local high-temperature areas that may exist in the incinerator by receiving the temperature field distribution and heavy metal volatilization data output by the simulation prediction module, and adjusts the incineration process parameters. The module first analyzes the temperature level and heavy metal volatilization amount in the high-temperature area, and calculates the marginal benefit A based on the emission reduction amount X and the adjustment cost Y. The specific steps include: data input, inputting the temperature field and volatilization distribution data generated by the simulation prediction module into the feedback optimization module; marginal benefit calculation, according to the heavy metal emission reduction amount X that can be achieved by adjusting the temperature parameter (such as reducing the oxygen supply or adjusting the fuel distribution), combined with the cost Y of the adjustment operation, using the formula A = X / Y to calculate the marginal benefit; parameter optimization, through the result analysis of the marginal benefit A, select an optimization plan with low adjustment cost and significant emission reduction effect, and adjust the oxygen supply method, fuel injection or flue gas treatment operation in the incinerator; feedback implementation, apply the optimized process parameters to the actual operation of the incinerator, and continuously monitor the adjustment effect to ensure that the heavy metal emission level meets the environmental protection requirements while reducing the adjustment cost. Through the feedback optimization function of this module, the incineration process parameters can be dynamically adjusted, effectively avoiding the problem of excessive heavy metal volatilization caused by local high temperature. In this embodiment, by calculating the adjustment marginal benefit A = X / Y, it provides a quantitative basis for the optimization of the incineration process, avoiding the inefficiency or cost waste caused by the lack of accurate evaluation in the traditional process adjustment. Compared with the adjustment method that only relies on empirical judgment, this module can achieve data-driven intelligent feedback optimization, ensuring the maximum reduction of heavy metal emissions at the lowest adjustment cost. In addition, dynamically adjusting the incineration parameters can effectively improve the operation efficiency of the incineration system, extend the service life of the equipment, and significantly reduce environmental pollution.

[0051] The sampling module includes multiple sampling devices, which are respectively arranged at different positions of the incinerator to synchronously collect multi-point flue gas samples, thereby improving the representativeness and accuracy of detection. In the above embodiment, the sampling module is composed of multiple sampling devices, and these sampling devices are reasonably arranged at different key positions of the incinerator (such as the furnace inlet, the middle of the furnace, the flue gas outlet, etc.). Each sampling device can collect the flue gas sample at its location in real time through a high-precision sampling probe and an adsorption device, and transmit the sample to the spectral analysis module through a gas pipeline for centralized detection. By synchronously collecting multi-point flue gas samples, the flue gas composition and concentration distribution characteristics at different positions in the incinerator can be comprehensively reflected. For example, by obtaining the flue gas in the high-temperature area in the middle of the furnace through the sampling device, the preliminary volatilization behavior of heavy metal components can be analyzed; by analyzing the outlet flue gas sample, the overall effect of flue gas treatment can be evaluated. The results of multi-point synchronous sampling provide a more accurate and comprehensive data basis for subsequent simulation prediction and feedback optimization, and help to improve the overall detection and control capabilities of the system. This embodiment realizes multi-point synchronous sampling by arranging multiple sampling devices at different positions of the incinerator, significantly improving the representativeness and accuracy of detection. Compared with the traditional single-point sampling method, this system can capture the spatial distribution characteristics of the flue gas components in the furnace more comprehensively, avoiding systematic misjudgment caused by single-point sample deviation. At the same time, multi-point synchronous sampling provides high-quality data for subsequent spectral analysis, temperature field simulation and feedback optimization, can significantly improve the intelligent level of the incineration process, and reduce heavy metal volatilization or other pollutant emissions caused by local anomalies. In addition, the synchronous sampling design of this embodiment can also shorten the detection time and provide technical support for real-time adjustment of process parameters.

[0052] The spectral analysis module includes a laser-induced breakdown spectrometer, which is used to perform real-time analysis on the heavy metal components in the flue gas sample through laser technology and generate accurate concentration data. In the above embodiment, the spectral analysis module adopts laser-induced breakdown spectroscopy (LIBS) technology. A high-power pulsed laser acts on the flue gas sample transmitted by the sampling module to excite the heavy metal components in the sample to form a plasma. During the attenuation process of the plasma, light signals of specific wavelengths are released, and the spectrometer analyzes the types and concentrations of heavy metal components (such as lead, mercury, cadmium, etc.) in the flue gas sample based on these light signals. The spectral analysis process includes the following steps: exciting the plasma, where the high-power laser emits pulsed laser, acting on the flue gas sample to rapidly heat up and ionize the heavy metal components to form a plasma; spectral detection, using an optical detection device (such as a grating spectrometer and a photodetector) to decompose and detect the spectrum radiated by the plasma, and extract the characteristic wavelength signals of specific metal components; data analysis, by comparing with the standard spectral library, generating the concentration data of the heavy metal components in real time and transmitting the analysis results to the simulation prediction module and the feedback optimization module. The LIBS technology has the characteristics of fast response, high sensitivity, and no need for sample pretreatment, and can monitor the concentration of heavy metal components in the flue gas in real time, meeting the requirements of the waste incineration power plant for accurate detection of pollutants. In this embodiment, the real-time analysis of the heavy metal components in the flue gas sample by the laser-induced breakdown spectrometer significantly improves the detection speed and accuracy. Compared with traditional analysis methods (such as chemical wet analysis or atomic absorption spectrometry), the LIBS technology has the advantages of no need for sample pretreatment, wide detection range, and simultaneous detection of multiple elements, and is suitable for rapid on-line monitoring of complex flue gas during the waste incineration process. In addition, by generating accurate concentration data in real time, it provides high-precision input data for the simulation prediction module, thereby improving the accuracy of temperature field and heavy metal volatilization prediction, and at the same time providing reliable basic data for the feedback optimization module, which helps to better control the incineration process and reduce the heavy metal emission level.

[0053] The spectral analysis module also includes a data filtering device for processing the noise in the detection signal. In the above embodiment, the data filtering device in the spectral analysis module effectively reduces the noise interference generated during the analysis of laser-induced breakdown spectroscopy (LIBS) through various signal processing methods, ensuring the accuracy of the detection results. The noise may come from electromagnetic interference during the laser excitation process, background light signals, and random noise of the photodetector. The data filtering device processes the spectral detection signal by combining hardware and algorithms. The specific steps are as follows: Noise identification and separation, by analyzing the time domain or frequency domain of the detection signal, identifying and separating noise signals, such as random noise and background signals; Signal smoothing, using a smoothing algorithm to remove high-frequency noise in the signal while retaining the characteristic waveform of the signal; Signal enhancement, using methods such as wavelet transform or Fourier transform to extract and enhance the useful signal from the background noise; Output of cleaned data, transferring the high-quality data after filtering processing to subsequent modules (such as the simulation prediction module) to ensure the detection accuracy and reliability of the entire system. The data filtering device can adapt to the complex situations of different noise types and dynamically adjust the filtering parameters according to actual needs, thereby minimizing the noise interference while maximizing the retention of the key features of the signal. This embodiment effectively reduces the signal distortion problem caused by noise interference during the spectral detection process by integrating a data filtering device into the spectral analysis module. Compared with the traditional unprocessed data, this system can output more accurate and stable spectral detection results, ensuring the detection accuracy of the heavy metal component concentration in multi-component flue gas. In addition, the real-time signal processing function of the filtering device improves the reliability of spectral analysis, reduces the risk of misjudgment or missed judgment caused by noise, provides higher-quality data input for the simulation prediction module and the feedback optimization module, and thus optimizes the effect of the overall flue gas treatment process in the waste incineration power plant.

[0054] The simulation and prediction module includes a temperature field dynamic display device for visualizing in real time the temperature distribution and high-temperature areas inside the incinerator. In the above embodiment, the temperature field dynamic display device in the simulation and prediction module presents in a graphical manner in real time the temperature distribution inside the incinerator based on the temperature field calculation results. The specific working process is as follows: data collection and calculation, using the flue gas concentration data provided by the spectral analysis module and combining with the heat conduction equation and the convective diffusion model to calculate the temperature field distribution inside the incinerator; data conversion, converting the temperature field calculation results into a visual data format to generate a three-dimensional distribution map or a two-dimensional sectional view; dynamic update, through the dynamic display function, updating in real time the temperature field distribution and its change over time, and highlighting the local high-temperature areas to facilitate quick identification by the operator; interface display, presenting the temperature distribution map on a display screen or a human-machine interaction terminal, providing a color gradient identifier (such as blue representing low temperature and red representing high temperature) to help users intuitively understand the temperature condition inside the incinerator. The temperature field dynamic display device can provide real-time data at a refresh rate of seconds, helping to monitor the high-temperature abnormal areas during the operation of the incinerator, thereby providing a reliable basis for the subsequent feedback optimization module. In this embodiment, through the temperature field dynamic display device, the complex temperature distribution data is presented in a visual form, enabling the operator to grasp in real time the temperature condition inside the incinerator. Compared with the traditional text or table data display method, the dynamic display is more intuitive, can help quickly identify and locate the high-temperature areas, thereby improving the timeliness and accuracy of the incineration process control. In addition, the real-time temperature distribution map can be used as a reference for evaluating the operating conditions of the incinerator, providing effective auxiliary information for the control of heavy metal volatilization, thereby reducing the emission of harmful substances and improving the safety and environmental protection performance of the incineration system.

[0055] As Figure 2 shown, there is also provided a method for detecting and analyzing multi-component gases in a waste incineration power plant. Using the multi-component gas detection and analysis system for a waste incineration power plant, the method includes:

[0056] S1. Synchronously collect multi-component flue gas samples containing heavy metal components at designated sampling points in the waste incineration power plant;

[0057] S2. Perform real-time component concentration determination on the collected flue gas samples through a laser-induced breakdown spectrometer;

[0058] S3. Use a computational fluid dynamics model to simulate and predict the temperature field and heavy metal volatilization conditions at different positions inside the furnace based on the component concentration determination results;

[0059] S4. Based on the simulation and prediction results, perform targeted detection on specific areas and feedback to optimize the flue gas treatment process to reduce excessive heavy metal volatilization caused by local high temperatures.

[0060] In this embodiment, an efficient flue gas analysis and control system for a waste incineration power plant is constructed by combining multi-point sampling, laser spectroscopy analysis, CFD simulation prediction, and feedback optimization operations. Compared with traditional detection methods, this method realizes real-time and accurate analysis of flue gas components, dynamic prediction of temperature fields, and intelligent optimization of incineration processes, and has the following remarkable advantages: improving the accuracy and representativeness of flue gas analysis, being able to comprehensively reflect the distribution and volatilization of heavy metal components during the incineration process; dynamically controlling incineration process parameters through simulation prediction and feedback optimization to reduce pollutant emissions and meet environmental protection requirements; providing visual displays of real-time temperature fields and volatilization conditions, facilitating operators to quickly grasp the working conditions and make timely adjustments; optimizing adjustment costs, improving the operating efficiency of the incineration system, and reducing equipment wear and pollutant emissions caused by local high temperatures.

[0061] Although the embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention, and the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A multi-component gas detection and analysis system for a waste incineration power plant, characterized in that: The system comprises: The sampling module is used to simultaneously collect multi-component flue gas samples containing heavy metal components at designated sampling points in waste incineration power plants; A spectrum analysis module connected to the sampling module includes a module for measuring the concentration of components of the smoke sample collected by the sampling module in real time; A simulation prediction module connected to the spectrum analysis module is used to simulate and predict the temperature field and heavy metal volatilization conditions at different positions in the furnace based on the component concentration measurement results of the spectrum analysis module; The feedback optimization module connected to the simulation prediction module is used to carry out targeted detection of specific areas in the incinerator and to provide feedback to optimize the flue gas treatment process based on the results of the simulation prediction module, so as to reduce excessive volatilization of heavy metals caused by local high temperatures.

2. A multi-component gas detection and analysis system for a waste incineration power plant according to claim 1, characterized in that: The sampling module synchronously collects multi-component flue gas samples containing heavy metal components at designated sampling points in the waste incineration power plant, including modeling the concentration of flue gas components and analyzing the relationship between sampling time and concentration uniformity.

3. A multi-component gas detection and analysis system for a waste incineration power plant according to claim 1, characterized in that: The spectrum analysis module is used to measure the real-time component concentration of the flue gas sample collected by the sampling module, including using a laser induced breakdown spectrometer to perform spectrum detection on the flue gas sample, record characteristic waves of metal components, and correct wavelength deviation caused by flow field velocity.

4. A multi-component gas detection and analysis system for a waste incineration power plant according to claim 1, characterized in that: The simulation prediction module is used to simulate and predict the temperature field and heavy metal volatilization conditions at different positions in the furnace based on the component concentration measurement results of the spectrum analysis module, including: Simulate the temperature field distribution inside the incinerator; Output temperature field distribution diagram and volatilization data to provide basis for feedback optimization module.

5. A multi-component gas detection and analysis system for a waste incineration power plant according to claim 1, Features: Based on the results of the simulation prediction module, the feedback optimization module implements targeted detection on specific areas in the incinerator and feedback optimizes the flue gas treatment process to reduce excessive volatilization of heavy metals caused by local high temperature, including inputting the results output by the simulation prediction module into the feedback optimization module to calculate the marginal benefit of local high temperature regulation.

6. A multi-component gas detection and analysis system for a waste incineration power plant according to claim 1, characterized in that: The sampling module includes a plurality of sampling devices, which are arranged at different positions of the incinerator respectively, so as to synchronously collect multi-point flue gas samples, thereby improving the representativeness and accuracy of the detection.

7. A multi-component gas detection and analysis system for a waste incineration power plant according to claim 1, characterized in that: The spectrum analysis module includes a laser induced breakdown spectrometer, which is used to perform real-time analysis of heavy metal components in the flue gas sample through laser technology and generate accurate concentration data.

8. The multi-component gas detection and analysis system for a waste incineration power plant according to claim 1 is characterized by: The spectrum analysis module also includes a data filtering device for processing the noise in the detection signal.

9. A multi-component gas detection and analysis system for a waste incineration power plant according to claim 1, characterized in that: The simulation prediction module includes a temperature field dynamic display device for real-time visualization of the temperature distribution and high-temperature areas in the incinerator.

10. A method for detecting and analyzing multi-component gases in a waste incineration power plant, using the multi-component gas detection and analysis system for a waste incineration power plant according to any one of claims 1 to 9, characterized in that: The method comprises: S1. Collect multi-component flue gas samples containing heavy metal components simultaneously at designated sampling points in waste incineration power plants; S2. Real-time component concentration measurement of the collected flue gas samples by laser induced breakdown spectrometry; S3. Using the computational fluid dynamics model to simulate and predict the temperature field and heavy metal volatilization at different locations in the furnace based on the component concentration measurement results; S4. Based on the simulation prediction results, targeted detection is carried out in specific areas and feedback is provided to optimize the flue gas treatment process to reduce excessive volatilization of heavy metals caused by local high temperatures.

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