A calibration method and device of an aero-engine core-shell type emission particulate matter photoacoustic detection system

Abstract

The application discloses a calibration method and device of an aero-engine core-shell type emission particulate matter photoacoustic detection system, and relates to the technical field of aero-engine emission detection. The method comprises the following steps: acquiring total mass of core-shell particulate matter, mass of non-volatile particulate matter in the core, and a photoacoustic response signal; calculating a reference value of the mass concentration of the non-volatile particulate matter in the core and a reference value of the mass concentration of surface volatile matter; using a multi-dimensional response signal synchronous inversion system to obtain an inversion value of the mass concentration of the non-volatile particulate matter in the core and an inversion value of the mass concentration of surface volatile matter; using the reference value as a standard value and the inversion value as an input value, using a linear correction relationship to calculate a sensitivity correction coefficient and a zero-point bias correction term, and using the two as system calibration parameters to obtain a calibrated photoacoustic detection system. The calibrated photoacoustic detection system can be used to realize high-precision correction output of the mass concentration of the non-volatile particulate matter in the core and the mass concentration of surface volatile matter.

Description

Technical Field

[0001] This application relates to the field of aero-engine emission detection technology, and in particular to a calibration method and apparatus for a core-shell type photoacoustic emission particulate matter detection system for aero-engines. Background Technology

[0002] Currently, core-shell particulate matter emissions from aero-engines mainly consist of a non-volatile core and a volatile shell. Accurate detection and system calibration of the mass concentrations of these two components have become a key research focus and an essential engineering requirement in the field of aviation emissions. Existing detection technologies mainly fall into two categories: online photoacoustic detection and offline benchmark detection via thermal desorption weighing. Conventional photoacoustic detection often employs a single-frequency, single-wavelength operating mode, which can only acquire the overall optical response signal of the particulate matter. It cannot utilize the spectral absorption differences between the core and the volatile shell to achieve signal decoupling, making it difficult to extract the multi-dimensional acoustic features corresponding to the core-shell structure, and even more difficult to construct a multi-component synchronous inversion system. Therefore, it cannot independently quantify the core and shell. Furthermore, traditional photoacoustic detection lacks authoritative benchmarks for true value comparison, lacks comprehensive error assessment, repeatability verification, and detection limit determination procedures, and lacks standardized calibration methods, resulting in low reliability and unreliable accuracy of measurement results. Although thermal desorption differential weighing technology can remove volatiles at high temperatures and achieve physical separation of two components through differential weighing, providing a traceable reference true value, it has drawbacks such as cumbersome sampling, heating, cooling, and multiple precision weighing processes, long testing cycles, and low detection efficiency. It can only achieve offline single-point testing and cannot meet the continuous and batch calibration requirements of aero-engines under a wide range of steady-state conditions from rich to lean fuel, as well as LTO dynamic cyclic conditions.

[0003] Therefore, how to standardize and calibrate the photoacoustic detection system for core-shell type particulate matter emissions from aero-engines to ensure the accuracy and reliability of the two-component concentration detection results is a technical problem that urgently needs to be solved. Summary of the Invention

[0004] The purpose of this application is to provide a calibration method and apparatus for a core-shell type photoacoustic emission particulate matter detection system for aero-engines, which can realize the calibration of the photoacoustic detection system.

[0005] To achieve the above objectives, this application provides the following solution: In a first aspect, this application provides a calibration method for a core-shell type photoacoustic emission particulate matter detection system for aero-engines, including: The total mass of core-shell particles, the mass of non-volatile core particles, and the photoacoustic response signal were obtained.

[0006] Based on the total mass of the core-shell particles and the mass of the non-volatile particles in the core, a baseline value for the mass concentration of the non-volatile particles in the core and a baseline value for the mass concentration of the surface volatiles are calculated.

[0007] Based on the photoacoustic response signal, the inversion values ​​of core non-volatile particulate matter mass concentration and surface volatile matter mass concentration are obtained by using a multidimensional response signal synchronous inversion system.

[0008] Using the reference values ​​of the core non-volatile particulate matter mass concentration and the reference values ​​of the surface volatile matter mass concentration as standard values, and the inverted values ​​of the core non-volatile particulate matter mass concentration and the inverted values ​​of the surface volatile matter mass concentration as input values, the sensitivity correction coefficient and the zero-point offset correction term are calculated using a linear correction relationship.

[0009] The sensitivity correction coefficient and zero-point offset correction term are used as system calibration parameters to obtain the calibrated photoacoustic detection system. The calibrated photoacoustic detection system is used to subsequently utilize the multidimensional response signal synchronous inversion system to obtain the inversion values ​​of core non-volatile particulate matter mass concentration and surface volatile matter mass concentration based on the photoacoustic response signal. Based on the system calibration parameters, the inversion values ​​of core non-volatile particulate matter mass concentration and surface volatile matter mass concentration are corrected to obtain the corrected core non-volatile particulate matter mass concentration and the corrected surface volatile matter mass concentration.

[0010] Secondly, this application provides a calibration device for a core-shell type photoacoustic emission particulate matter detection system for aero-engines, comprising: The device includes a thermal desorption weighing reference module, a dual-frequency multi-wavelength photoacoustic module, and a data processing module; the device has two parallel detection branches, which correspond to the thermal desorption weighing reference module and the dual-frequency multi-wavelength photoacoustic module, respectively.

[0011] The thermal desorption weighing reference module and the dual-frequency multi-wavelength photoacoustic module are used to obtain the total mass of core-shell particles, the mass of core non-volatile particles, and the photoacoustic response signal under the same sampling time window, the same gas source, and the same flow reference.

[0012] The data processing module is used to execute the method described in the first aspect, based on the total mass of the core-shell particles, the mass of the core non-volatile particles, and the photoacoustic response signal, to calibrate the photoacoustic detection system.

[0013] According to the specific embodiments provided in this application, the following technical effects are disclosed: This application provides a calibration method and apparatus for a core-shell type photoacoustic emission particulate matter detection system for aero-engines. By acquiring the total mass of core-shell particulate matter, the mass of non-volatile particulate matter in the core, and the photoacoustic response signal, it solves the problem of missing original detection data required for calibration and achieves simultaneous acquisition of multi-dimensional physical quantities of particulate matter and photoacoustic response signals. By calculating the reference values ​​of core non-volatile particulate matter mass concentration and surface volatile matter mass concentration based on the total mass of core-shell particulate matter and the mass of core non-volatile particulate matter, it solves the problem of difficulty in obtaining true reference values ​​for photoacoustic detection and achieves quantitative construction of the standard true values ​​of mass concentration of non-volatile components and surface volatile components. By using a multi-dimensional response signal synchronous inversion system based on the photoacoustic response signal to obtain the inversion values ​​of core non-volatile particulate matter mass concentration and surface volatile matter mass concentration, it solves the problem of the inability to obtain true reference values ​​for photoacoustic detection based on the photoacoustic signal. The problem of directly outputting the mass concentration of two components was solved, enabling the preliminary signal inversion output of the mass concentration of two-component particulate matter. By using two sets of reference values ​​as standard values ​​and two sets of inversion values ​​as input values, the sensitivity correction coefficient and zero-point offset correction term were calculated using a linear correction relationship, solving the problem of detection sensitivity deviation and zero-point drift in the multidimensional response signal synchronous inversion system, and realizing the quantitative solution of the system calibration parameters corresponding to the two components respectively. By using the sensitivity correction coefficient and zero-point offset correction term as system calibration parameters, the calibrated photoacoustic detection system was obtained. Subsequently, after the inversion results were output from the multidimensional response signal synchronous inversion system, the two types of inversion values ​​were corrected separately using the system calibration parameters, solving the problem of systematic error in the detection results of the two components in the photoacoustic detection system, and realizing high-precision correction output of the mass concentration of core non-volatile particulate matter and surface volatile particulate matter. Attached Figure Description

[0014] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0015] Figure 1 This is an application environment diagram of a calibration method for a core-shell type photoacoustic emission particulate matter detection system for aero-engines according to an embodiment of this application; Figure 2 A schematic flowchart illustrating a calibration method for a core-shell type photoacoustic emission particulate matter detection system for an aero-engine, provided as an embodiment of this application; Figure 3 A schematic diagram of the functional modules of a calibration device for a core-shell type photoacoustic emission particulate matter detection system for an aero-engine, provided in an embodiment of this application; Figure 4A schematic diagram of the overall architecture of a calibration device for a core-shell type photoacoustic emission particulate matter detection system for an aero-engine, provided as an embodiment of this application; Figure 5 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application.

[0016] Reference numerals: 101-Aircraft engine; 201-Core-shell particles; 301-Sampling rake; 401-First anti-adhesion particle conduit; 501-Sampling module; 601-Muffle furnace; 701-Second anti-adhesion particle conduit; 801-Precision balance; 901-First data transmission unit; 1001-Laser control unit; 1101-Multi-wavelength high-power laser unit; 1201-Dual-frequency multi-wavelength laser beam; 1301-Photoacoustic cell; 1401-High-precision microphone; 1501-Second data transmission unit; 1601-Data processing module; 1701-Internal structure of the photoacoustic cell. Detailed Implementation

[0017] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0018] Traditional photoacoustic detection systems for particulate matter and surface volatiles in aero-engines mostly employ single-frequency, single-wavelength detection methods, which can only output the overall concentration signal of particulate matter. They cannot distinguish between the core of aero-engine emission particles and the shell components of surface volatiles in a core-shell structure. They lack true reference values ​​for comparison, and measurement errors, repeatability, and detection limits cannot be quantitatively assessed. The system also lacks standardized calibration methods, making it difficult to guarantee measurement accuracy. While the traditional thermal desorption weighing reference method can achieve component separation, the sampling, heating, cooling, and multiple weighing processes are cumbersome and inefficient. It cannot meet the requirements for rapid and continuous system calibration under all operating conditions and LTO dynamic conditions, and it is difficult to balance component resolution, measurement accuracy, and detection efficiency.

[0019] This application presents a dual-frequency, multi-wavelength photoacoustic detection system for core-shell particulate matter emissions from aero-engines. It utilizes the spectral absorption differences between the particle core and the volatile shell to effectively separate photoacoustic signals. By extracting multi-dimensional acoustic features of the core-shell structure using dual characteristic frequencies, a multi-dimensional response signal synchronous inversion system is established, enabling simultaneous and accurate calculation of the mass concentrations of both the non-volatile particle core and the volatile shell. Simultaneously, it ensures consistent calibration gas sources through homogeneous sampling and obtains traceable reference values ​​using thermal desorption differential weighing. This allows for quantitative evaluation of the photoacoustic detection system's measurement errors, repeatability, and detection limits, fundamentally solving the problems of traditional photoacoustic systems lacking dedicated calibration procedures and having uncontrollable accuracy. This application overcomes the limitations of traditional single-frequency, single-wavelength photoacoustic systems in separating the two components, achieving simultaneous and independent measurement of the particle core and surface volatiles. While retaining the high precision advantage of the weighing reference, it leverages the real-time, continuous, and rapid measurement characteristics of the photoacoustic detection system. After multi-condition calibration and solidification of correction coefficients, the photoacoustic detection system can stably and accurately measure the mass concentrations of the aero-engine particle core and volatile shell over a long period.

[0020] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, this application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0021] The calibration method for the photoacoustic detection system of core-shell type particulate matter emissions from aero-engines provided in this application embodiment can be applied to, for example... Figure 1In the application environment shown, terminal 102 communicates with server 104 via a network. A data storage system can store the data that server 104 needs to process. The data storage system can be set up independently, integrated into server 104, or placed in the cloud or on other servers. Terminal 102 can send the total mass of core-shell particles, the mass of non-volatile core particles, and the photoacoustic response signal to be processed to server 104. After receiving the total mass of core-shell particles, the mass of non-volatile core particles, and the photoacoustic response signal, server 104 calculates the core non-volatile particle mass concentration benchmark value and the surface volatile matter mass concentration benchmark value based on the total mass of core-shell particles and the mass of non-volatile core particles; based on the photoacoustic response signal, it uses multi-dimensional response signals to synchronously reflect... The system is inverted to obtain the inverted values ​​of the core non-volatile particulate matter mass concentration and the surface volatile matter mass concentration. Using the core non-volatile particulate matter mass concentration reference value and the surface volatile matter mass concentration reference value as standard values, and the core non-volatile particulate matter mass concentration inversion value and the surface volatile matter mass concentration inversion value as input values, the sensitivity correction coefficient and the zero-point offset correction term are calculated using a linear correction relationship. The sensitivity correction coefficient and the zero-point offset correction term are used as system calibration parameters to obtain the calibrated photoacoustic detection system. The server 104 can feed back the obtained system calibration parameters to the terminal 102. The calibrated photoacoustic detection system is used to subsequently utilize a multi-dimensional response signal synchronous inversion system. After obtaining the inversion values ​​of core non-volatile particulate matter mass concentration and surface volatile matter mass concentration based on the photoacoustic response signal, the inversion values ​​of core non-volatile particulate matter mass concentration and surface volatile matter mass concentration are corrected based on the system calibration parameters to obtain the corrected core non-volatile particulate matter mass concentration and the corrected surface volatile matter mass concentration. Furthermore, in some embodiments, the calibration method for the photoacoustic detection system of aero-engine core-shell type emission particulate matter can also be implemented independently by the server 104 or the terminal 102. For example, the terminal 102 can directly process the total mass of core-shell particulate matter, the mass of core non-volatile particulate matter, and the photoacoustic response signal to be processed. Alternatively, the server 104 can obtain the total mass of core-shell particulate matter, the mass of core non-volatile particulate matter, and the photoacoustic response signal from the data storage system and process them accordingly.

[0022] The terminal 102 can be, but is not limited to, various desktop computers, laptops, smartphones, and tablets. The server 104 can be implemented using a standalone server or a server cluster consisting of multiple servers, or it can be a cloud server.

[0023] In one exemplary embodiment, such as Figure 2 As shown, a calibration method for a photoacoustic detection system for particulate matter emissions from a core-shell type aero-engine is provided. This method is executed by computer equipment, specifically by a terminal or server alone, or by both a terminal and a server. In this embodiment, the method is applied to... Figure 1 Taking server 104 as an example, the following steps are taken: S11 to S15: S11, acquire the total mass of core-shell particles, the mass of non-volatile core particles, and the photoacoustic response signal.

[0024] S12, based on the total mass of the core-shell particles and the mass of the core non-volatile particles, calculate the baseline value of the core non-volatile particle mass concentration and the baseline value of the surface volatile matter mass concentration.

[0025] S13, based on the photoacoustic response signal, the inversion values ​​of the core non-volatile particulate matter mass concentration and the surface volatile matter mass concentration are obtained by using a multi-dimensional response signal synchronous inversion system.

[0026] S14, using the reference value of the core non-volatile particulate matter mass concentration and the reference value of the surface volatile matter mass concentration as standard values, and the inverted value of the core non-volatile particulate matter mass concentration and the inverted value of the surface volatile matter mass concentration as input values, the sensitivity correction coefficient and the zero-point offset correction term are calculated using the linear correction relationship.

[0027] S15, the sensitivity correction coefficient and zero-point offset correction term are used as system calibration parameters to obtain the calibrated photoacoustic detection system; the calibrated photoacoustic detection system is used to subsequently utilize the multidimensional response signal synchronous inversion system, and after obtaining the inversion values ​​of the core non-volatile particulate matter mass concentration and the surface volatile matter mass concentration based on the photoacoustic response signal inversion, the inversion values ​​of the core non-volatile particulate matter mass concentration and the surface volatile matter mass concentration are corrected based on the system calibration parameters to obtain the corrected core non-volatile particulate matter mass concentration and the corrected surface volatile matter mass concentration.

[0028] By implementing steps S11 to S15 above, this application constructs a true reference value for the mass concentration of two components by collecting relevant mass parameters of core-shell particulate matter and photoacoustic response signals. It then obtains the concentration inversion result by combining the multidimensional response signal synchronous inversion system. Furthermore, it completes the system calibration by solving the sensitivity correction coefficient and zero-point offset correction term based on the linear correction relationship. This solves the system error problem of sensitivity deviation and zero-point drift in the mass concentration inversion results of core non-volatile particulate matter and surface volatile matter in photoacoustic detection, and realizes the synchronous and high-precision quantitative detection of the mass concentration of the two types of particulate matter components.

[0029] As an optional implementation, the multidimensional response signal synchronous inversion system specifically includes the following: Let the photoacoustic detection system be at the... i modulation frequency and the j laser wavelength The photoacoustic response signal obtained below is Then its response relationship can be expressed as: (1); in, This represents the overall gain coefficient of the photoacoustic detection system at the corresponding frequency and wavelength. The incident laser power, This is either a background signal or a zero-air baseline signal. and These represent the core non-volatile particulate matter and surface volatile matter at different wavelengths. The mass absorption coefficient below, and The modulation frequency represents the difference between core non-volatile particulate matter and surface volatile matter. Thermoacoustic response factor under the given conditions and These represent the concentrations of non-volatile particulate matter in the core and the mass concentrations of volatile matter on the surface, respectively. This is for measuring noise and model error terms.

[0030] After background subtraction and optical power normalization of the photoacoustic response signal, we can obtain: (2); Combining all the normalized response signals obtained under dual characteristic frequencies and multiple laser wavelengths into an observation vector can be written in matrix form: (3); in, It is a multidimensional photoacoustic response vector; It is a multidimensional response matrix composed of absorption coefficients of different wavelengths and thermoacoustic response factors of different frequencies; This is the model error vector; Let be the mass concentration vector to be inverted.

[0031] The mass concentrations of non-volatile particulate matter in the kernel and the surface volatile matter can be solved simultaneously using the least squares or regularized least squares method. The expression for the solution is: (4); in, For regularization parameters; It is the identity matrix; , and These represent the mass concentrations of core non-volatile particulate matter and surface volatile matter obtained through inversion, respectively. Using the aforementioned multidimensional response signal synchronous inversion system, the synchronous and quantitative separation of the mass concentrations of core non-volatile particulate matter and surface volatile matter in aviation emissions can be achieved.

[0032] As an optional implementation, the formula for calculating the reference value of the core non-volatile particulate matter mass concentration is as follows: (5); The formula for calculating the baseline value of surface volatile matter mass concentration is as follows: (6); in, This serves as the baseline value for the mass concentration of non-volatile particulate matter in the core area. Sampling flow rate; Sampling time; For the mass of non-volatile particulate matter in the core; The total mass of core-shell particles; This is the baseline value for the mass concentration of surface volatiles.

[0033] As an optional implementation, in S14, using the reference value of the core non-volatile particulate matter mass concentration and the reference value of the surface volatile matter mass concentration as standard values, and using the inverted value of the core non-volatile particulate matter mass concentration and the inverted value of the surface volatile matter mass concentration as input values, the sensitivity correction coefficient and the zero-point offset correction term are calculated using a linear correction relationship, specifically including the following: Based on the core non-volatile particulate matter mass concentration benchmark value and the baseline value of surface volatile matter mass concentration The standard value is the value retrieved from the photoacoustic system. , Establish a linear correction relationship for the input values: (7); (8); In the formula, and These are the corrected core mass concentration and surface volatile mass concentration, respectively. , This is the sensitivity correction factor. , This is the zero-point offset correction term.

[0034] If there is a cross-response between the kernel and shell signals, a matrix correction relationship can be further established: (9); in, This is the cross-sensitivity correction matrix. This is the bias correction vector. This correction relationship can correct the effects of spectral absorption crossover, differences in thermal relaxation response, and system gain drift on the photoacoustic inversion results.

[0035] As an optional implementation, the calibration method for the aero-engine core-shell type particulate matter photoacoustic detection system further includes steps S21-S27: S21, repeatedly obtain the core non-volatile particulate matter mass concentration baseline value, the surface volatile matter mass concentration baseline value, and the corresponding core non-volatile particulate matter mass concentration inversion value and surface volatile matter mass concentration inversion value.

[0036] S22, based on the sensitivity correction coefficient and the zero-point offset correction term, correct the inversion value of the core non-volatile particulate matter mass concentration and the inversion value of the surface volatile matter mass concentration, respectively, to obtain the corrected core non-volatile particulate matter mass concentration and the corrected surface volatile matter mass concentration.

[0037] S23, based on the reference value of the core non-volatile particulate matter mass concentration, the reference value of the surface volatile matter mass concentration, and the corrected core non-volatile particulate matter mass concentration and the corrected surface volatile matter mass concentration at the corresponding time, the relative error and repeatability index of the photoacoustic detection system are calculated; the relative error includes the relative error of the core non-volatile particulate matter mass concentration, the relative error of the surface volatile matter mass concentration, and the relative error of the total mass concentration.

[0038] S24, calculate the detection limit and quantitation limit of the photoacoustic detection system after introducing the sensitivity correction coefficient and the zero-point offset correction term.

[0039] S25, determine whether the relative error, the repeatability index, the detection limit index, and the quantitation limit index have reached preset thresholds respectively, and obtain the first judgment result.

[0040] S26, if the first judgment result is yes, then the sensitivity correction coefficient and the zero-point offset correction term are used as system calibration parameters to obtain the calibrated photoacoustic detection system.

[0041] S27, if the first judgment result is negative, return to the step "obtain the total mass of core-shell particles, the mass of core non-volatile particles, and the photoacoustic response signal".

[0042] Specifically, the relative error in calculating the mass concentration of non-volatile particulate matter in the core and the mass concentration of volatile matter on the surface is as follows: (10); (11); Simultaneously calculate the relative error of the total mass concentration: (12); in, This represents the relative error in the mass concentration of non-volatile particulate matter in the core. This represents the corrected mass concentration of non-volatile particulate matter in the core. This serves as the baseline value for the mass concentration of non-volatile particulate matter in the core area. This represents the relative error in the mass concentration of surface volatiles. This is the corrected surface volatile matter mass concentration; This serves as a baseline value for the mass concentration of surface volatiles. This represents the relative error of the total mass concentration. This is the baseline value for the total mass concentration of core-shell particulate matter.

[0043] The above error results can be used to evaluate the photoacoustic detection system's ability to simultaneously quantify non-volatile particulate matter in the core and volatile matter on the surface of aviation emissions.

[0044] To evaluate system repeatability, at least [number] tests were conducted under the same particle generation conditions, the same dilution ratio, and the same sampling time. n Repeated measurements were performed, and the average value and relative standard deviation of the mass concentration of particle cores and surface volatiles measured by the photoacoustic detection system were calculated respectively. The repeatability index can be expressed as: (13); (14); in, This serves as a repeatability indicator for photoacoustic detection systems of non-volatile particulate matter in the kernel. for n The average mass concentration of non-volatile particulate matter in the kernel obtained from repeated measurements; for n The standard deviation of the mass concentration of non-volatile particulate matter in the core obtained from repeated measurements; This serves as a repeatability indicator for surface volatiles in photoacoustic systems. for n The average mass concentration of surface volatiles obtained from repeated measurements; for n The standard deviation of surface volatile mass concentration obtained from repeated measurements.

[0045] Repeatability analysis is used to determine the level of measurement fluctuation of the system under stable input conditions.

[0046] Furthermore, the background noise and low-concentration response capability of the photoacoustic detection system after introducing the sensitivity correction coefficient and zero-point offset correction term were tested using zero-particle pure carrier gas and low-concentration standard particulate sample gas, respectively. First, the output signal of the photoacoustic detection system after introducing the sensitivity correction coefficient and zero-point offset correction term was continuously acquired under zero-particle conditions, and the standard deviation of the background noise was calculated. Subsequently, the sensitivity of the photoacoustic detection system after introducing a sensitivity correction coefficient and a zero-point offset correction term was obtained through a standard particle gradient concentration experiment. S This refers to the calibration slope between the photoacoustic response and the mass concentration. The expression for the detection limit index of the photoacoustic detection system after introducing the sensitivity correction coefficient and the zero-point offset correction term is: (15); The expression for the limit of quantitation index is: (16); in, The lowest mass concentration used to characterize a system that can reliably distinguish particle signals from background noise. This is used to characterize the lowest mass concentration at which the system can be stably and quantitatively measured. The mass concentrations of core non-volatile particulate matter and surface volatile matter can be used to establish corresponding detection limits for core non-volatile particulate matter. Detection limit of surface volatile matter concentration Limits on the quantification of non-volatile particulate matter mass concentration in the core and the quantitative limit index of surface volatile matter mass concentration .

[0047] Finally, the corrected measurement results are compared with the baseline results again. If the relative error, repeatability, and detection limit of the corrected core mass concentration, surface volatile mass concentration, and total mass concentration all meet the preset requirements, then the photoacoustic detection system is determined to have the ability to synchronously detect the core and surface volatile mass concentrations of aero-engine emission particles online. The sensitivity coefficient, zero-point offset, and detection limit are used as the detection method parameters for subsequent full-condition engine testing.

[0048] In one exemplary embodiment, such as Figure 3 As shown, a calibration device for a photoacoustic detection system for particulate matter emissions from an aero-engine core-shell type is provided. The device includes a thermal desorption weighing reference module, a dual-frequency multi-wavelength photoacoustic module, and a data processing module. The device has two parallel detection branches, which correspond to the thermal desorption weighing reference module and the dual-frequency multi-wavelength photoacoustic module, respectively.

[0049] The thermal desorption weighing reference module and the dual-frequency multi-wavelength photoacoustic module are used to obtain the total mass of core-shell particles, the mass of core non-volatile particles, and the photoacoustic response signal under the same sampling time window, the same gas source, and the same flow reference.

[0050] The data processing module is used to execute the method described above, based on the total mass of the core-shell particles, the mass of the core non-volatile particles, and the photoacoustic response signal, to calibrate the photoacoustic detection system.

[0051] As an optional implementation, the thermal desorption weighing reference module specifically includes: a muffle furnace, a balance, and a first data transmission unit.

[0052] The muffle furnace is used to remove volatile substances from the core-shell particles to obtain non-volatile particles from the core.

[0053] The balance is used to weigh the total mass of the core-shell particles and the mass of the non-volatile core particles obtained by muffle furnace treatment.

[0054] The first data transmission unit is used to transmit the total mass of core-shell particles and the mass of non-volatile core particles to the data processing module.

[0055] As an optional implementation, the dual-frequency multi-wavelength photoacoustic module specifically includes: a laser control unit, a multi-wavelength high-power laser unit, a photoacoustic cell, a second data transmission unit, and a microphone.

[0056] The laser control unit is used to control the multi-wavelength high-power laser unit to emit dual-frequency lasers, and to pass the dual-frequency lasers into the photoacoustic cell to generate photoacoustic signals in the photoacoustic cell.

[0057] The microphone is used to measure the photoacoustic signal to obtain a photoacoustic response signal.

[0058] The second data transmission unit is used to transmit the photoacoustic response signal to the data processing module.

[0059] It should be noted that the photoacoustic detection system includes a dual-frequency, multi-wavelength photoacoustic module and a data processing module. This system utilizes the spectral absorption difference between the core and surface volatile shell layers of aviation emission particles to achieve effective separation of photoacoustic signals. By extracting multidimensional acoustic features corresponding to the core-shell structure through dual characteristic frequencies and multiple laser wavelengths, a multidimensional response signal synchronous inversion system is established. Based on the photoacoustic response signal and relying on the constructed multidimensional response signal synchronous inversion system, the mass concentrations of non-volatile particulate matter in the core and surface volatiles of aviation emission particles are calculated synchronously and accurately.

[0060] In one exemplary embodiment, such as Figure 4As shown, this application provides a calibration device for an integrated photoacoustic detection system for particulate matter emissions from a core-shell type aero-engine. This application requires first performing high-temperature pretreatment on a high-temperature resistant quartz fiber filter membrane and then performing pre-precision weighing using a precision balance 801. The filter membrane is then placed in a sampling device 501. The device is then activated, and the combustion of the aero-engine 101 generates core-shell structured carbon soot particles 201. The exhaust gas is collected by a sampling rake 301 and sent to the sampling module 501. The sample gas particles are captured by the filter membrane within 501. After sampling, the filter membrane is removed, sealed, and weighed again in the precision balance 801 to obtain the total mass of the core-shell particles. Subsequently, the filter membrane containing the particles is sent to a muffle furnace 601 through a first anti-adhesion particle pipe 401. After being heated at 400℃ for 2 hours to remove surface volatiles, it is cooled and sent again through a second anti-adhesion particle pipe 701 to the precision balance 801 for weighing to obtain the mass of the non-volatile core particles. The difference between the two weighings is the mass of the surface volatiles. The entire set of baseline weighing data is transmitted via a first data transmission unit 901 to a data processing module 1601 for conversion into two components. The mass concentration reference value is obtained; simultaneously, another source sample gas is split off from 501 and sent into the photoacoustic cell 1301 through the first anti-adhesion particle pipe 401. In the optical path, the laser control unit 1001 regulates the multi-wavelength high-power laser unit 1101 to output a dual-frequency multi-wavelength laser beam 1201, which is injected into the internal structure 1701 of the photoacoustic cell 1301. The core and shell particles are excited by the laser to generate photoacoustic signals. The photoacoustic signals are completely collected by the high-precision microphone 1401 to obtain the photoacoustic response signal. The photoacoustic response signal is synchronously transmitted to the data processing module 1601 through the second data transmission unit 1501. The data processing module 1601 synchronously receives the thermal desorption weighing reference data and the photoacoustic response signal, and synchronously calculates the mass concentration of non-volatile particles in the core and the mass concentration of volatiles on the surface through the inversion algorithm. Then, a linear correction relationship is established based on the reference value, and the sensitivity correction coefficient and zero-point offset correction term are calculated as system calibration parameters to obtain the calibrated photoacoustic detection system.

[0061] It should be noted that the aero-engine 101 is used to generate core-shell particles; the core-shell particles 201 are the measurement object of this application; the sampling rake 301 is used to collect the core-shell particles emitted by the aero-engine; the sampling module 501 is used to acquire the core-shell particles; the first anti-adhesion particle pipe 401 is used to pass the acquired core-shell particles into the precision balance 801 and the muffle furnace 601; the muffle furnace 601 is used to remove volatile substances from the core-shell particles to obtain non-volatile core particles; the second anti-adhesion particle pipe 701 is used to pass the non-volatile core particles after the removal of volatile substances into the precision balance 801; the precision balance 801 is used to weigh the total mass of the core-shell particles and the non-volatile core particles obtained after treatment in the muffle furnace. The system comprises: a mass unit 901 for transmitting the total mass of core-shell particulate matter and the mass of non-volatile core particulate matter to a data processing module; a laser control unit 1001 for controlling a multi-wavelength high-power laser unit 1101 to emit lasers with dual specific modulation frequencies; a multi-wavelength high-power laser unit 1101 for emitting dual-frequency multi-wavelength lasers; a dual-frequency multi-wavelength laser beam 1201, which is an integrated dual-frequency multi-wavelength laser beam, used to generate photoacoustic signals by passing it into a photoacoustic cell 1301; a high-precision microphone 1401 for measuring the photoacoustic signals and obtaining photoacoustic response signals; a second data transmission unit 1501 for transmitting the photoacoustic response signals to a data processing module; and a data processing module 1601 for processing data and studying emission patterns.

[0062] Specifically, under the control of 1001 (laser control unit), 1101 (multi-wavelength high-power laser unit) generates a dual-frequency multi-wavelength laser beam with specific wavelength, modulation frequency and power; Particles generated by 101 (aircraft engine) enter 501 (sampling module) through 301 (sampling rake). The particles are then passed through 401 (first anti-adhesion particle pipe) to 601 (muffle furnace), 801 (precision balance), and 1301 (photoacoustic cell) for processing and measurement. The obtained data is transmitted to 1601 (data processing module) by 901 (first data transmission unit) and 1501 (second data transmission unit) for detecting the mass concentration of aviation emission particles and surface volatiles, as well as for system calibration.

[0063] In an exemplary embodiment, the specific implementation process of the detection and calibration method of this application is described below in conjunction with the photoacoustic detection and calibration device for core-shell type particulate matter emissions from aero-engines: S31 extracts sample gas from the same physical point of the aircraft engine exhaust, and divides it into two paths through the sampling module, which are respectively connected to the dual-frequency multi-wavelength photoacoustic module and the thermal desorption weighing reference module.

[0064] S32, after high-temperature pretreatment and precise weighing, the high-temperature resistant quartz fiber filter membrane is placed in the reference module sampling device to collect sample gas, and the total mass of core-shell particulate matter is obtained by sealing and weighing.

[0065] S33, the filter membrane is treated in a muffle furnace at 400℃ for 2 hours to remove volatiles. After cooling, the mass of the core non-volatile particulate matter is weighed to obtain the mass concentration benchmark value of the core non-volatile particulate matter and the mass concentration benchmark value of the surface volatile matter.

[0066] S34, while performing sampling and weighing of the S32 and S33 reference systems, simultaneously starts the dual-frequency multi-wavelength photoacoustic module. It utilizes the spectral absorption difference between the core of the aerospace emission particles and the surface volatile shell layer of the core-shell particles to achieve effective separation of photoacoustic signals. By extracting the multidimensional acoustic features corresponding to the core-shell structure through dual characteristic frequencies and multiple laser wavelengths, the photoacoustic response signal is obtained.

[0067] S35, the photoacoustic response signal is transmitted to the data processing module. Relying on the constructed multi-dimensional response signal synchronous inversion system, the inversion values ​​of the core non-volatile particulate matter mass concentration and the surface volatile matter mass concentration are calculated synchronously and accurately. At the same time, the inversion values ​​are synchronously compared with the reference values ​​to establish the error evaluation, repeatability evaluation, detection limit determination, quantitation limit determination, and linear correction relationship of the photoacoustic detection system. The sensitivity correction coefficient and zero-point offset correction term are calculated using the linear correction relationship. The sensitivity correction coefficient and zero-point offset correction term are used as system calibration parameters to obtain the calibrated photoacoustic detection system.

[0068] S36 controls the engine to execute a complete LTO cycle, adjusts the air-fuel ratio to set a wide-range steady-state test point covering rich to lean combustion, and after each operating condition stabilizes, starts the dual-frequency multi-wavelength photoacoustic module and the thermal desorption weighing reference module to obtain the mass concentration value under the same operating condition. Based on error evaluation, repeatability evaluation, detection limit determination, and quantitation limit determination, the calibration results are verified to be correct and the photoacoustic detection system is further revised to complete the efficient detection and calibration of the mass concentration of particulate matter and surface volatiles emitted by aero-engines.

[0069] This application introduces a dual-frequency excitation + multi-wavelength coupled photoacoustic detection method, utilizing the spectral absorption difference between the core and volatile shell layers of core-shell particles to achieve photoacoustic signal decoupling and separation. By extracting multidimensional acoustic features corresponding to the core-shell structure through dual characteristic frequencies, a multidimensional response signal synchronous inversion system is established, enabling synchronous and accurate quantitative measurement of the mass concentration of the core and volatile shell layers of aero-engine particles. Simultaneously, a co-source heated split sampling method is adopted to ensure consistent calibration sampling gas source conditions. The thermal desorption differential weighing result is used as a traceable reference true value to quantitatively evaluate the measurement error, repeatability, and detection limit of the photoacoustic detection system, and to correct the inversion value. This effectively solves the shortcomings of traditional photoacoustic detection methods, such as the lack of standardized calibration procedures and difficulty in controlling measurement accuracy, significantly improving the accuracy of independent detection of two components. After being calibrated under all operating conditions and having its correction coefficients solidified, the photoacoustic system can output stable and accurate concentration data of both non-volatile particulate matter in the particle core and volatile matter on the surface for a long period of time. It eliminates the need for frequent recalibration, balancing detection accuracy and operational efficiency, and enables simultaneous, accurate, and efficient online detection of the mass concentration of particulate matter and volatile matter emitted by aero-engines.

[0070] In one exemplary embodiment, a computer device is provided, which may be a server or a terminal, and its internal structure diagram may be as follows. Figure 5 As shown, the computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The database stores data used in the calibration process of an aero-engine core-shell particulate matter photoacoustic detection system. The I / O interfaces are used for information exchange between the processor and external devices. The communication interface is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements a calibration method for an aero-engine core-shell particulate matter photoacoustic detection system.

[0071] Understandable. Figure 5 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0072] In one exemplary embodiment, a computer device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the above-described method embodiments.

[0073] In one exemplary embodiment, a computer-readable storage medium is provided storing a computer program that, when executed by a processor, implements the above-described method embodiments.

[0074] In one exemplary embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the above-described method embodiments.

[0075] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of related data must comply with relevant regulations and be authorized by the owner of the corresponding device.

[0076] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

[0077] The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0078] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0079] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A calibration method for a core-shell type photoacoustic emission particulate matter detection system for aero-engines, characterized in that, The method includes: Acquire the total mass of core-shell particles, the mass of non-volatile core particles, and the photoacoustic response signal; Based on the total mass of the core-shell particles and the mass of the non-volatile particles in the core, calculate the baseline value of the mass concentration of the non-volatile particles in the core and the baseline value of the mass concentration of the volatiles on the surface. Based on the photoacoustic response signal, the inversion values ​​of the core non-volatile particulate matter mass concentration and the surface volatile matter mass concentration are obtained by using a multidimensional response signal synchronous inversion system. Using the reference values ​​of the core non-volatile particulate matter mass concentration and the reference values ​​of the surface volatile matter mass concentration as standard values, and the inverted values ​​of the core non-volatile particulate matter mass concentration and the inverted values ​​of the surface volatile matter mass concentration as input values, the sensitivity correction coefficient and the zero-point offset correction term are calculated using the linear correction relationship. The sensitivity correction coefficient and zero-point offset correction term are used as system calibration parameters to obtain the calibrated photoacoustic detection system. The calibrated photoacoustic detection system is used to subsequently utilize the multidimensional response signal synchronous inversion system to obtain the inversion values ​​of core non-volatile particulate matter mass concentration and surface volatile matter mass concentration based on the photoacoustic response signal. Based on the system calibration parameters, the inversion values ​​of core non-volatile particulate matter mass concentration and surface volatile matter mass concentration are corrected to obtain the corrected core non-volatile particulate matter mass concentration and the corrected surface volatile matter mass concentration.

2. The calibration method for the photoacoustic detection system for core-shell type particulate matter emissions from aero-engines according to claim 1, characterized in that, The method further includes: Repeatedly obtain the core non-volatile particulate matter mass concentration baseline value, the surface volatile matter mass concentration baseline value, and the corresponding core non-volatile particulate matter mass concentration inversion value and surface volatile matter mass concentration inversion value at the corresponding time. The inverted values ​​of the core non-volatile particulate matter mass concentration and the surface volatile matter mass concentration are corrected based on the sensitivity correction coefficient and the zero-point bias correction term, respectively, to obtain the corrected core non-volatile particulate matter mass concentration and the corrected surface volatile matter mass concentration. Based on the reference values ​​of core non-volatile particulate matter mass concentration, surface volatile matter mass concentration, and the corrected core non-volatile particulate matter mass concentration and corrected surface volatile matter mass concentration at the corresponding time, the relative error and repeatability index of the photoacoustic detection system are calculated; the relative error includes the relative error of core non-volatile particulate matter mass concentration, the relative error of surface volatile matter mass concentration, and the relative error of total mass concentration. Calculate the detection limit and quantitation limit of the photoacoustic detection system after introducing the sensitivity correction coefficient and the zero-point offset correction term; Determine whether the relative error, the repeatability index, the detection limit index, and the quantitation limit index have reached preset thresholds respectively, and obtain a first determination result; If the first judgment result is yes, then the sensitivity correction coefficient and the zero-point offset correction term are used as system calibration parameters to obtain the calibrated photoacoustic detection system; If the first judgment result is negative, then return to the step "obtain the total mass of core-shell particles, the mass of core non-volatile particles, and the photoacoustic response signal".

3. The calibration method for the photoacoustic detection system for core-shell type particulate matter emissions from aero-engines according to claim 1, characterized in that, The expression for the linear correction relationship is: ； ； in, This represents the corrected mass concentration of non-volatile particulate matter in the core. This is the corrected surface volatile matter mass concentration; , This is the zero-point offset correction term; , This is the sensitivity correction factor; This represents the inversion value of the mass concentration of non-volatile particulate matter in the core. This represents the inversion value of the surface volatile matter mass concentration.

4. The calibration method for the photoacoustic detection system for core-shell type particulate matter emissions from aero-engines according to claim 1, characterized in that, The formula for calculating the baseline value of the core non-volatile particulate matter mass concentration is as follows: ； The formula for calculating the baseline value of surface volatile matter mass concentration is as follows: ； in, This serves as the baseline value for the mass concentration of non-volatile particulate matter in the core area. Sampling flow rate; Sampling time; For the mass of non-volatile particulate matter in the core; The total mass of core-shell particles; This serves as a baseline value for the mass concentration of surface volatiles. The expression for the multidimensional response signal synchronous inversion system is: ； ； ； ； in, It is a photoacoustic response signal; This represents the overall gain coefficient of the system at the corresponding frequency and wavelength. The incident laser power; For non-volatile particulate matter in the core at wavelength The mass absorption coefficient below; For non-volatile particulate matter in the core at the modulation frequency Thermoacoustic response factor under; This refers to the mass concentration of non-volatile particulate matter in the core. For surface volatiles at wavelength Mass absorption coefficient at the specified depth; For surface volatiles at modulation frequency Thermoacoustic response factor under; This refers to the mass concentration of surface volatiles. For measuring noise; Model error term; To obtain the processed photoacoustic response signal after background subtraction and optical power normalization; This is the multidimensional photoacoustic response vector corresponding to the processed photoacoustic response signal; It is a multidimensional response matrix composed of absorption coefficients of different wavelengths and thermoacoustic response factors of different frequencies; for Transpose of; The mass concentration vector to be inverted; This is the model error vector; For regularization parameters, It is an identity matrix.

5. The calibration method for the photoacoustic detection system for core-shell type particulate matter emissions from aero-engines according to claim 2, characterized in that, The formula for calculating the relative error of the mass concentration of non-volatile particulate matter in the core is as follows: ； The formula for calculating the relative error of the surface volatile mass concentration is: ； The formula for calculating the relative error of total mass concentration is: ； in, This represents the relative error in the mass concentration of non-volatile particulate matter in the core. This represents the corrected mass concentration of non-volatile particulate matter in the core. This serves as the baseline value for the mass concentration of non-volatile particulate matter in the core area. This represents the relative error in the mass concentration of surface volatiles. This is the corrected surface volatile matter mass concentration; This serves as a baseline value for the mass concentration of surface volatiles. This represents the relative error of the total mass concentration. This is the baseline value for the total mass concentration of core-shell particulate matter.

6. The calibration method for the photoacoustic detection system for core-shell type particulate matter emissions from aero-engines according to claim 2, characterized in that, The expression for the repeatability index is: ； ； in, This serves as a repeatability indicator for photoacoustic detection systems of non-volatile particulate matter in the kernel. The average mass concentration of non-volatile particulate matter in the kernel obtained from several repeated measurements; The standard deviation of the mass concentration of non-volatile particulate matter in the core obtained from several repeated measurements; This serves as a repeatability indicator for surface volatiles in photoacoustic systems. This represents the average mass concentration of surface volatiles obtained from several repeated measurements. The standard deviation of the surface volatile mass concentration obtained from several repeated measurements is denoted as .

7. The calibration method for the photoacoustic detection system for core-shell type particulate matter emissions from aero-engines according to claim 2, characterized in that, The detection limit index The expression is: ； The limit of quantitation index The expression is: ； in, The lowest mass concentration used to characterize a system that can reliably distinguish particulate signals from background noise; The lowest mass concentration used to characterize the system so that it can be stably and quantitatively measured; The standard deviation of background noise; To obtain the sensitivity of the photoacoustic system through a standard particle gradient concentration experiment.

8. A calibration device for a photoacoustic detection system for particulate matter emissions from a core-shell type aero-engine, characterized in that, The device includes: a thermal desorption weighing reference module, a dual-frequency multi-wavelength photoacoustic module, and a data processing module; the device is provided with two parallel detection branches, which correspond to the thermal desorption weighing reference module and the dual-frequency multi-wavelength photoacoustic module, respectively. The thermal desorption weighing reference module and the dual-frequency multi-wavelength photoacoustic module are used to obtain the total mass of core-shell particles, the mass of non-volatile core particles, and the photoacoustic response signal under the same sampling time window, the same gas source, and the same flow reference. The data processing module is used to perform the method described in any one of claims 1-7 to calibrate the photoacoustic detection system based on the total mass of the core-shell particles, the mass of the non-volatile particles in the core, and the photoacoustic response signal.

9. The calibration device for the photoacoustic detection system for core-shell type particulate matter emissions from aero-engines according to claim 8, characterized in that, The thermal desorption weighing reference module specifically includes: a muffle furnace, a balance, and a first data transmission unit; The muffle furnace is used to remove volatile substances from the core-shell particulate matter to obtain non-volatile particulate matter in the core. The balance is used to weigh the total mass of the core-shell particles and the mass of the non-volatile core particles obtained by muffle furnace treatment; The first data transmission unit is used to transmit the total mass of core-shell particles and the mass of non-volatile core particles to the data processing module.

10. The calibration device for the photoacoustic detection system of core-shell type particulate matter emissions from aero-engines according to claim 8, characterized in that, The dual-frequency multi-wavelength photoacoustic module specifically includes: a laser control unit, a multi-wavelength high-power laser unit, a photoacoustic cell, a second data transmission unit, and a microphone; The laser control unit is used to control the multi-wavelength high-power laser unit to emit dual-frequency laser, and to pass the dual-frequency laser into the photoacoustic cell to generate photoacoustic signals in the photoacoustic cell. The microphone is used to measure the photoacoustic signal to obtain a photoacoustic response signal; The second data transmission unit is used to transmit the photoacoustic response signal to the data processing module.

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