Combustion chamber combustion oscillation on-line monitoring system based on intelligent sensing element

Abstract

The invention discloses an online monitoring system for combustion oscillation of a combustion chamber based on an intelligent sensing element. The online monitoring system comprises an acquisition imaging unit, a conversion unit, a speed measurement unit, a dynamic fusion unit and a path analysis unit, the acquisition imaging unit is constructed based on a microphone array and is used for acquiring and processing combustion acoustic signals of a combustion chamber and calculating sound wave propagation time delay by using a cross-correlation function to obtain a time delay data set; the conversion unit can convert the time delay data set into a dynamic pressure field matrix for displaying the cross section of the combustion chamber; the speed measurement unit emits continuous wave signals through microwave probes installed at the head and the middle of a combustion chamber, and measures local instantaneous speed values of ionized particles in flames through difference frequency signals generated through scattering. Through cooperative work of the non-intrusive acquisition imaging unit and the speed measurement unit, omnibearing monitoring of dynamic characteristics of the combustion chamber is realized, and meanwhile, deep coupling of a speed field and a pressure field is realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of combustion chamber state monitoring, and in particular to a combustion chamber combustion oscillation online monitoring system based on intelligent sensing elements. BACKGROUND

[0002] In modern industrial combustion equipment, the combustion stability of the combustion chamber is the basis for efficient energy utilization. When the fuel and air in the combustion chamber are fully mixed and stably burned, the chemical energy can be maximally converted into heat energy, thereby improving energy utilization and reducing production costs. When combustion oscillation occurs in the combustion chamber, the shape and position of the flame will change dramatically, causing the fuel to burn unevenly, and some of the fuel may be discharged without being completely burned, which not only wastes energy resources but also increases the emission of pollutants. Therefore, it is necessary to monitor the combustion oscillation of the combustion chamber in real time online to conveniently and accurately obtain the combustion state information in the combustion chamber, and once signs of combustion oscillation are found, appropriate control measures can be taken quickly.

[0003] For example, a combustion chamber combustion oscillation online monitoring method, device and storage medium with Chinese publication number CN 119469785 A disclose a method for obtaining time-domain vibration signals and pulsating pressure signals of a combustion chamber during operation of a combustion engine through a vibration acceleration sensor and a pulsating pressure sensor. This method facilitates subsequent improvement of the monitoring rate of combustion oscillation, makes the monitoring range wider, provides support for accurate and reliable combustion mode adjustment and combustion engine protection for gas turbines, and improves the service life of the combustion chamber.

[0004] However, the invasive sensors of most current combustion chamber combustion oscillation online monitoring systems change the flow field of the combustion chamber, are easily ablated by high temperatures, and can only provide single-point information, making it impossible to capture the oscillation mode of the entire cross section. At the same time, real-time fusion of speed fluctuation data and pressure field distribution information leads to inaccurate positioning of the oscillation source, and thus it is difficult to construct a complete oscillation feedback mechanism. SUMMARY

[0005] Therefore, the present application provides a combustion chamber combustion oscillation online monitoring system based on intelligent sensing elements to solve the problems in the prior art.

[0006] To achieve the above-mentioned purpose, the present application provides the following technical solutions:

[0007] A combustion chamber combustion oscillation online monitoring system based on intelligent sensing elements, comprising an acquisition imaging unit, a conversion unit, a speed measurement unit, a dynamic fusion unit and a path analysis unit.

[0008] The acquisition imaging unit is constructed based on a microphone array, used for acquiring and processing combustion acoustic signals of the combustion chamber, and calculating time delay of sound wave propagation by using cross-correlation function to obtain a time delay dataset;

[0009] The conversion unit is capable of converting the time delay dataset into a dynamic pressure field matrix of the combustion chamber cross section;

[0010] The velocity measurement unit emits continuous wave signals by microwave probes installed at the head and middle of the combustion chamber, and measures local instantaneous velocity values of ionized particles in the flame by using difference frequency signals generated by scattering ;

[0011] The calculation formula of the local instantaneous velocity value is as follows:

[0012]

[0013] wherein, is a microwave wavelength, is a difference frequency signal, is an angle between a beam and a velocity vector;

[0014] The dynamic fusion unit is capable of synchronously processing the dynamic pressure field distribution data and the local instantaneous velocity value , and calculating a correlation coefficient of a pressure change rate of each node and a velocity field , screening out key path nodes with a correlation coefficient >0.7;

[0015] The path analysis unit is capable of calculating a pressure difference of the key path nodes , and visualizing all oscillation energy propagation paths by a topological atlas.

[0016] Further, the cross-correlation function is used to calculate time delay of sound wave propagation between two microphones; the formula of the cross-correlation function is as follows:

[0017]

[0018] wherein, is a time delay variable, is a current time, is a microphone signal, is another microphone signal.

[0019] Further, the specific content of the conversion unit is as follows:

[0020] 1) discretizing the combustion chamber cross section into a regular grid of 200x200, with a grid size of 2cmx2cm;

[0021] 2) According to the local gas composition and temperature , the sound speed is converted into a dynamic pressure field ;

[0022] 3) The output dynamic pressure field data is stored in a 200x200 matrix form, and each matrix element corresponds to the dynamic pressure amplitude at a specific position on the cross section.

[0023] Further, the difference frequency signal is the frequency difference between the scattered wave frequency received by the microwave probe and the transmission frequency .

[0024] Further, the dynamic fusion unit can diffuse the local instantaneous velocity value to the grid points in the entire 200x200 regular grid , forming a continuously distributed velocity disturbance field, and the diffusion formula is as follows:

[0025]

[0026] wherein, is the local instantaneous velocity value, is the Euclidean distance from the microwave probe to the grid point , is the standard deviation, is the total number of microwave probes. Further, the correlation coefficient

[0027] is the relationship value of the pressure change rate at each grid node in the velocity disturbance field and the corresponding velocity disturbance field, and the correlation coefficient of the correlation coefficient is calculated as follows:

[0028]

[0029] wherein, is the pressure change rate, is the standard deviation of the pressure change rate, is the standard deviation of the velocity value in the velocity disturbance field.

[0030] Further, the path analysis unit includes a construction subunit and a path extraction subunit;

[0031] The construction subunit can regard each key path node in the 200x200 grid as a vertex in the network, and the connection relationship between the nodes as an edge.

[0032] ​The path extraction subunit can calculate the pressure difference between the two endpoints at each connection edge. According to the pressure difference The direction of energy transfer is determined by the location of the interval.

[0033] Furthermore, the pressure difference The calculation formula is as follows:

[0034]

[0035] in, For nodes Pressure fluctuation difference, For nodes The pressure fluctuation difference.

[0036] Furthermore, the pressure difference When the value falls within the interval [-π / 2, π / 2], it is determined that the energy originates from the node. To the node For positive propagation; when When the value falls within the interval [π / 2, 3π / 2], it is determined that the energy originates from the node. To the node This is a reverse propagation.

[0037] This invention has the following advantages: Through the coordinated operation of a non-invasive acquisition and imaging unit and a velocity measurement unit, it achieves comprehensive monitoring of the dynamic characteristics of the combustion chamber. The acquisition and imaging unit employs four sets of MEMS microphones in a cross-shaped configuration to acquire acoustic signals in the 1kHz-8kHz frequency band at a 10kHz sampling frequency. This effectively avoids the damage to the flow field structure and the risk of high-temperature ablation caused by traditional invasive sensors. The continuous wave scattering velocity data measured by the microwave probe diffuses across the entire cross-section grid, forming a continuous velocity disturbance field, improving the accuracy of oscillation source positioning. The coordinated operation of these two components constructs a complete combustion chamber state sensing network, providing a reliable data foundation for dynamic equilibrium assessment.

[0038] Meanwhile, through correlation coefficient analysis of the dynamic fusion unit and pressure difference determination of the path analysis unit, deep coupling of velocity field and pressure field is achieved, which significantly improves the positioning accuracy of vibration source and can clearly identify key features such as red vibration source area and blue main path, thus constructing a complete online monitoring and feedback system and providing accurate basis for combustion stability control.

[0039] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. Attached Figure Description

[0040] To more intuitively illustrate the prior art and the present application, exemplary drawings are given below. It should be understood that the specific shapes, configurations shown in the drawings should not be considered as limiting conditions in the implementation of the present application; for example, based on the technical concepts and exemplary drawings disclosed in the present application, those skilled in the art can easily make routine adjustments or further optimizations to the increase / decrease / assignment of certain units (components), specific shapes, positional relationships, connection methods, size ratio relationships, etc.

[0041] Figure 1 An implementation flowchart of a combustion chamber combustion oscillation online monitoring system based on intelligent sensing elements. DETAILED DESCRIPTION

[0042] The embodiments of the present application are described below by specific specific embodiments, and those skilled in the art can easily understand other advantages and effects of the present application from the disclosed content. Obviously, the described embodiments are part of the embodiments of the present application, not all. It should be understood that these embodiments are only to further illustrate the present application, and cannot be understood as limiting the scope of protection of the present application. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0043] Please refer to Figure 1 A combustion chamber combustion oscillation online monitoring system based on intelligent sensing elements includes an acquisition imaging unit, a conversion unit, a speed measurement unit, a dynamic fusion unit and a path analysis unit.

[0044] The acquisition imaging unit is used to acquire and process combustion acoustic signals of the combustion chamber, and uses cross-correlation function to calculate the time delay of sound wave propagation to obtain a time delay data set.

[0045] The acquisition imaging unit is constructed based on a microphone array. Each microphone array is composed of four MEMS microphones in a cross-shaped configuration, which is used to receive combustion acoustic signals of a specific frequency band, facilitating the acquisition of sound pressure data at different positions in the combustion chamber at the same time. The sampling frequency is set to 10 kHz. The microphone uses high-temperature-resistant packaging to ensure stable operation in the combustion chamber environment.

[0046] The acoustic signal processing includes preprocessing the raw acoustic signal using a bandpass filter with a passband frequency range of 1 kHz to 8 kHz, covering the main characteristic frequency components of combustion oscillations. The filter is implemented using a multi-feedback loop circuit composed of operational amplifiers, maintaining a flat amplitude-frequency response within the passband and a stopband attenuation of -40 dB / decathlon. During filtering, flow noise below 1 kHz and sensor resonant frequencies above 8 kHz are effectively suppressed, while retaining the critical combustion oscillation signal near the 5 kHz center frequency. This processing ensures that subsequent cross-correlation delay calculations are unaffected by low-frequency turbulence noise and high-frequency electrical interference.

[0047] By calculating the signals from the two microphones and cross-correlation function The peak position corresponds to the sound wave propagation delay, thus determining the propagation delay of the sound wave between different microphones, ultimately obtaining the time delay dataset. Cross-correlation function. The formula is as follows:

[0048]

[0049] in, For time delay variables, This refers to the current moment.

[0050] The conversion unit can transform time-delay datasets into a dynamic pressure field matrix displaying the cross-section of the combustion chamber. This conversion unit provides dynamic pressure field distribution data of the combustion chamber cross-section, facilitating its use as input for subsequent oscillation analysis.

[0051] First, the combustion chamber cross-section is discretized into a regular grid of 200×200 pixels, with a grid size of 2cm×2cm. Then, the sound velocity distribution is solved by minimizing the following objective function; the formula for the objective function is as follows:

[0052]

[0053] in, The sound wave path matrix, The sound speed vector For time delay variables, For grid size, The parameter is denoted as . This optimization problem is solved iteratively using the conjugate gradient method until the residual converges.

[0054] Based on local gas composition and temperature speed of sound Converted into a dynamic pressure field Dynamic pressure field The calculation formula is as follows:

[0055]

[0056] where, is the local gas density. The local gas density is calculated as follows:

[0057]

[0058] where is the static pressure, is the gas molar mass, is the universal gas constant.

[0059] The final output dynamic pressure field data is stored in a 200x200 matrix form, with each matrix element corresponding to the dynamic pressure amplitude at a specific location on the cross-section, providing input data for subsequent oscillation mode analysis.

[0060] The velocity measurement unit transmits continuous wave signals through microwave probes installed at the head and middle of the combustion chamber, and measures the local instantaneous velocity value of ionized particles in the flame by using the difference frequency signal generated by scattering . For providing a velocity signal synchronized with an acoustic signal.

[0061] The microwave probe transmits a continuous wave electromagnetic signal at a frequency of 38 GHz. When the continuous wave electromagnetic signal propagates in the combustion chamber, it interacts with ionized particles present in the flame, producing a scattering effect. The microwave probe simultaneously receives the echo signal scattered by moving particles. When the scattering body moves at a velocity relative to the probe, the frequency of the received scattered wave differs from the transmission frequency by a difference frequency signal , the calculation formula of the difference frequency signal is as follows:

[0062]

[0063] When the received signal passes through the mixer, the mixer receives the signal and mixes it with the local oscillation signal to extract the difference frequency signal , and the local instantaneous velocity value along the beam direction is calculated in real time, the calculation formula of the local instantaneous velocity value is as follows:

[0064]

[0065] where, is the microwave wavelength, is the angle between the beam and the velocity vector.

[0066] The dynamic fusion unit can utilize hardware-level timestamp technology to enable the processing of dynamic pressure field distribution data and local instantaneous velocity values ​​at a sampling frequency of 10kHz. Synchronous data acquisition is performed, and an absolute time stamp is attached to each data frame. This allows for data acquisition at any given time. Local instantaneous velocity value Both can achieve spatiotemporal consistency mapping with the dynamic pressure field distribution data of the combustion chamber cross-section. The acquisition and imaging unit and the velocity measurement unit are equipped with high-precision clock units.

[0067] Then take the local instantaneous velocity value Grid points diffused throughout the entire 200×200 regular grid. Above, each local instantaneous velocity value The value, centered on its spatial location, influences surrounding grid nodes according to a distance-attenuation law, forming a continuously distributed velocity perturbation field. The diffusion formula is as follows:

[0068]

[0069] in, For the first A local instantaneous velocity value, For the first Microwave probe to grid point Euclidean distance, Standard deviation This represents the total number of microwave probes.

[0070] Then, the correlation coefficient between the pressure change rate and the corresponding velocity disturbance field at each grid node was calculated. This ensures that the complete oscillation cycle can be captured. Correlation coefficient The calculation formula is as follows:

[0071]

[0072] in, The rate of change of pressure, The standard deviation of the rate of change of pressure. Let be the standard deviation of the velocity values ​​in the velocity disturbance field.

[0073] Then, key areas are filtered using preset thresholds, and the correlation coefficients are... Grid nodes with a value >0.7 are marked as critical path nodes for oscillatory energy transfer, facilitating the subsequent construction of a complete oscillatory energy transfer topology network.

[0074] The path analysis unit can calculate the pressure difference between critical path nodes. , for determining the energy transmission direction, and all oscillation energy propagation paths are visualized by the topology atlas, realizing the visual expression of the oscillation energy flow direction in the combustion chamber and improving the monitoring ability of the system for the combustion chamber.

[0075] The path analysis unit includes a construction subunit and a path extraction subunit. The construction subunit can regard each key path node in the 200*200 grid as a vertex in the network and the connection relationship between the nodes as an edge.

[0076] The path extraction subunit can calculate the pressure difference of the two end nodes on each connection edge , determine the energy transmission direction according to the interval of the pressure difference : when falls in the interval [-π / 2, π / 2], it is determined that the energy is transmitted in the positive direction from the node to the node ; when falls in the interval [π / 2, 3π / 2], it is determined that the energy is transmitted in the reverse direction from the node to the node . The calculation formula of the pressure difference is as follows:

[0077]

[0078] wherein is the pressure fluctuation difference of the node , and is the pressure fluctuation difference of the node .

[0079] All propagation paths are determined according to the interval range of the pressure difference . The propagation paths include positive paths and reverse paths, and all the final propagation paths are presented in the form of color coding in the topology atlas, so as to clearly show the complete transmission path of the monitored oscillation energy in the combustion chamber and improve the monitoring effect.

[0080] For example, the red hot spot represents a high-sensitivity vibration source, the blue channel indicates the main energy propagation path, and the green buffer zone is a low-impact marginal zone.

[0081] The application realizes all-around monitoring of dynamic characteristics of the combustion chamber through the cooperative work of the non-invasive acquisition imaging unit and the velocity measurement unit. The acquisition imaging unit adopts four groups of MEMS microphones in cross-shaped configuration, acquires acoustic signals in the frequency band of 1kHz-8kHz under the sampling frequency of 10kHz, effectively avoids the damage of the traditional invasive sensor to the flow field structure and the high-temperature ablation risk, diffuses the continuous wave scattering velocity data measured by the microwave probe to the full cross-section grid, forms a continuous velocity disturbance field, improves the positioning accuracy of the oscillation source, and the two intelligent sensing elements (microphone array and microwave probe) cooperatively work to build a complete combustion chamber state perception network, which provides a reliable data basis for dynamic balance evaluation.

[0082] Meanwhile, through the correlation coefficient analysis of the dynamic fusion unit and the pressure difference determination of the path analysis unit, the depth coupling of the velocity field and the pressure field is realized, the positioning accuracy of the vibration source is significantly improved, the key features such as the red vibration source area and the blue main path can be clearly identified, and a complete online monitoring and feedback system is built, which provides accurate basis for combustion stability control.

[0083] The above only describes the preferred embodiments of the application and is not intended to limit the application. Any modification, equivalent replacement and improvement made within the spirit and principle of the application shall be included in the protection scope of the application.

Claims

1. A system for online monitoring of combustion oscillations in a combustion chamber based on intelligent sensing elements, characterized in that, The application comprises a collection imaging unit, a conversion unit, a speed measurement unit, a dynamic fusion unit and a path analysis unit. The collection imaging unit is constructed based on a microphone array, used for collecting and processing combustion acoustic signals of the combustion chamber, and calculating the sound wave propagation time delay by using the cross-correlation function to obtain a time delay data set; The conversion unit can convert the time delay data set into a dynamic pressure field matrix showing the cross section of the combustion chamber; The velocity measuring unit emits continuous wave signals by microwave probes installed at the head and middle of the combustion chamber, and measures the local instantaneous velocity value of ionized particles in the flame by using the difference frequency signals generated by scattering ; local instantaneous velocity value The formula for calculating the local instantaneous velocity value is as follows: ； wherein, is the microwave wavelength, is the difference frequency signal, is the angle between the beam and the velocity vector; The dynamic fusion unit can process dynamic pressure field distribution data and local instantaneous velocity values. Synchronization processing was performed, and the correlation coefficient between the pressure change rate and the velocity field at each node was calculated. Filter out the correlation coefficient Critical path nodes >0.7; The path analysis unit can calculate a stress difference of a critical path node All oscillation energy propagation paths can be visualized by a topology map.

2. The system according to claim 1, wherein the system is characterized by: The cross-correlation function is used to calculate the time delay of the sound wave propagating between the two microphones; cross-correlation function The formula is as follows: ； wherein is a time delay variable, is a current time instant, is a microphone signal, is another microphone signal.

3. The system according to claim 1, wherein the system further comprises a sensor for detecting the pressure of the combustion chamber. The specific content of the conversion unit is as follows: 1) Discretize the cross section of the combustion chamber into a regular grid of 200x200, with a grid size of 2cmx2cm; 2) according to local gas composition and temperature Converts the sound velocity into a dynamic pressure field ; 3) The output dynamic pressure field data is stored in the form of a 200x200 matrix, and each matrix element corresponds to the dynamic pressure amplitude at a specific position on the cross section.

4. The system for online monitoring of combustion oscillations in a combustion chamber based on an intelligent sensor element according to claim 1, characterized in that The difference frequency signal The frequency difference between the frequency of the scattered wave received by the microwave probe And the transmission frequency Between the transmission frequency 5. The system for online monitoring of combustion oscillations in a combustion chamber based on an intelligent sensor element according to claim 1, characterized in that The dynamic fusion unit can diffuse the local instantaneous velocity values to the grid points in the entire 200x200 regular grid , forming a continuously distributed velocity disturbance field, and the diffusion formula is as follows: ； in, For the first A local instantaneous velocity value, For the first Microwave probe to grid point Euclidean distance, Standard deviation, This represents the total number of microwave probes.

6. The system for online monitoring of combustion oscillations in a combustion chamber based on an intelligent sensor element according to claim 1, characterized in that The correlation coefficient The correlation coefficient is a value of the relationship between the rate of change of pressure at each grid node in the velocity disturbance field and the corresponding velocity disturbance field. The correlation coefficient The calculation formula of the correlation coefficient is as follows: ； wherein is the rate of pressure change, is the standard deviation of the rate of pressure change, is the standard deviation of the velocity values in the velocity perturbation field.

7. The system for online monitoring of combustion oscillations in a combustion chamber based on an intelligent sensor element according to claim 1, characterized in that The path analysis unit comprises a construction subunit and a path extraction subunit; The construction subunit can regard each key path node in the 200x200 grid as a vertex in the network, and the connection relationship between the nodes as an edge. The path extraction subunit can calculate the pressure difference of both end nodes on each connection edge According to the pressure difference The interval where the pressure difference is located determines the energy transmission direction.

8. The online combustion oscillation monitoring system of a combustion chamber based on intelligent sensing elements according to claim 7, characterized in that, The pressure difference The calculation formula is as follows: ； wherein is the pressure fluctuation difference of the node is the pressure fluctuation difference of the node is the pressure fluctuation difference of the node is the pressure fluctuation difference of the node 9. The online combustion oscillation monitoring system of a combustion chamber based on intelligent sensing elements according to claim 7, characterized in that, said when the pressure difference falls in the interval [-π / 2, π / 2], it is determined that the energy is transmitted from the node to the node in the forward direction; when falls in the interval [π / 2, 3π / 2], it is determined that the energy is transmitted from the node to the node in the backward direction.

Images