Pressure monitoring method for pulsating pressure fluctuation caused by carbon dioxide and temperature of combustion chamber

Abstract

The invention discloses a pressure monitoring method for pulsating pressure fluctuation caused by carbon dioxide and temperature of a combustion chamber, and relates to the technical field of pressure monitoring, comprising the following steps: acquiring real-time combustion pulsating pressure data of different areas of the combustion chamber; re-sampling the real-time combustion pulsating pressure data by using a layered re-sampling method to obtain re-sampled combustion pulsating pressure data; a pressure anomaly detection method is used for detecting pressure anomaly conditions of different frequency bands in the combustion chamber; when it is detected that the pressure in the combustion chamber is abnormal, an alarm is given; according to the method, pressure data acquisition is performed on different areas of a combustion chamber through a grid division method; a layered resampling method combining integral multiple extraction and fractional multiple interpolation is adopted, so that the interference of temperature field fluctuation and carbon dioxide concentration change on pressure signals can be eliminated, and the accuracy of data processing is improved; the source and the property of the problem are accurately positioned, and the supervision of the combustion system is improved, so that the probability of accidents is reduced.

Description

Technical Field

[0001] The invention relates to the technical field of pressure monitoring, and in particular to a method for monitoring the pressure fluctuation of carbon dioxide and temperature-induced pulsating pressure in a combustion chamber. Background Art

[0002] Combustion pulsation pressure is an important physical phenomenon generated during the combustion process. It reflects the interaction of multiple factors such as flame propagation, fuel-air mixing, and dynamic response of the combustion chamber structure. The magnitude and frequency of combustion pulsation pressure have an important impact on the operating stability, safety, and efficiency of the equipment. Combustion pulsation exceeding the specified range in the combustion chamber of a gas turbine will accelerate the wear of hot channel components and lead to degradation of combustion performance, which may cause damage to combustion components and shutdown, and even cause irreversible damage to the hot channel. Traditional combustion pulsation pressure monitoring methods mainly rely on a single or multiple pressure sensors to measure the pressure at a specific location in the combustion chamber. However, this method has many limitations. At the same time, the temperature field in the combustion chamber will affect the pulsation pressure, causing the pulsation pressure to fluctuate. The carbon dioxide produced in the combustion chamber is a high-temperature gas. After the carbon dioxide is generated, it can cause the temperature field in the combustion chamber to change. Therefore, for the combustion chamber, both carbon dioxide and the temperature field will cause pulsation pressure fluctuations, and the influence relationship between them cannot be quantified.

[0003] For example, a Chinese patent with authorization announcement number CN113176094B discloses an online monitoring system for thermoacoustic oscillations in a gas turbine combustion chamber, including a sensor assembly, a data collector and a host computer; the sensor assembly is installed on each flame tube in the gas turbine combustion chamber, and each group of sensor assemblies includes a pressure pulsation sensor, a vibration acceleration sensor and an infrared high-temperature sensor; the data collector is used to collect electrical signals from each sensor assembly in the gas turbine combustion chamber in real time, and convert them into digital signals to obtain real-time detection data with multiple attributes and multiple states; the host computer is used to obtain and store the real-time detection data collected by the data collector, and perform multi-domain analysis and fault warning.

[0004] The above patents have the problems raised by the background technology: since the combustion process in the combustion chamber is complex and changeable, it is difficult for a single sensor to fully reflect the pressure distribution in the entire combustion chamber, and it is impossible to conduct an in-depth analysis of the frequency characteristics of the combustion pulsating pressure, ignoring the differences in abnormal pressure thresholds in different frequency bands; to solve the above problems, the present invention proposes a pressure monitoring method for the pulsating pressure fluctuations caused by carbon dioxide and temperature in the combustion chamber. Summary of the invention

[0005] In view of the shortcomings of the prior art, the main purpose of the present invention is to provide a pressure monitoring method for combustion chamber carbon dioxide and temperature-induced pulsating pressure fluctuations, which can effectively solve the problems in the background technology. The specific technical solutions of the present invention are as follows:

[0006] A pressure monitoring method for combustion chamber carbon dioxide and temperature-induced pulsating pressure fluctuations, comprising:

[0007] Obtain real-time combustion pulsation pressure data in different areas of the combustion chamber;

[0008] Resampling the real-time combustion pulsation pressure data using a layered resampling method to obtain resampled combustion pulsation pressure data;

[0009] According to the resampled combustion pulsation pressure data, using a pressure anomaly detection method to detect pressure anomalies in different frequency bands in the combustion chamber;

[0010] When abnormal pressure is detected in the combustion chamber, an alarm is sounded.

[0011] Specifically, the step of obtaining real-time combustion pulsation pressure data of different areas of the combustion chamber includes:

[0012] The combustion chamber is divided into different areas using the area division method;

[0013] Based on the different areas, real-time combustion pulsation pressure data of each area is acquired.

[0014] Specifically, the combustion chamber is divided into different areas using the area division method, including:

[0015] Divide the combustion chamber by a meshing method to obtain a plurality of mesh unit regions;

[0016] The plurality of grid unit regions are clustered using a clustering algorithm to obtain different regions.

[0017] Specifically, the real-time combustion pulsation pressure data is resampled by using a layered resampling method to obtain resampled combustion pulsation pressure data, including:

[0018] Performing windowing processing on the real-time combustion pulsation pressure data to obtain windowed pressure data;

[0019] The windowed pressure data of each region is taken as a layer of data;

[0020] The data of each layer is resampled using the dynamic resampling method to obtain the resampled data of each layer;

[0021] The resampled data of each layer are combined to form the resampled combustion pulsation pressure data.

[0022] Specifically, the method of resampling the data of each layer by using the dynamic resampling method to obtain the resampled data of each layer includes:

[0023] The data of each layer is extracted using the integer multiple extraction method to obtain the extracted data of each layer;

[0024] The fractional interpolation method is used to interpolate the extracted data of each layer to obtain the resampled data of each layer.

[0025] Specifically, the method of detecting abnormal pressure conditions in different frequency bands in the combustion chamber using a pressure anomaly detection method according to the resampled combustion pulsation pressure data includes:

[0026] Converting the resampled post-combustion pulsation pressure data into frequency domain data using Fourier transform;

[0027] Dividing the pulsating pressure data in the combustion chamber into a plurality of frequency bands, wherein the plurality of frequency bands include a low frequency band, a middle frequency band, and a high frequency band;

[0028] In each frequency band, the pressure anomaly detection method is used to detect the pressure anomaly.

[0029] Specifically, in each frequency band, the abnormal pressure situation is detected by using the abnormal pressure detection method, including:

[0030] In each frequency band, set the pre-alarm value and high alarm value respectively;

[0031] The threshold analysis method is used to provide graded warning for abnormal pulsation pressure in each frequency band.

[0032] Specifically, the threshold analysis method is used to perform graded warning on abnormal pulsation pressure in each frequency band, including:

[0033] Based on the frequency domain data, drawing a pulsating pressure change curve;

[0034] When the pressure pulsation value is higher than the pre-alarm value and lower than the high alarm value, locate the warning point in the pulsating pressure change curve and issue a warning;

[0035] When the pressure pulsation value is higher than the high alarm value, the alarm point in the pulsation pressure change curve is located and an alarm is issued.

[0036] A pressure monitoring system for implementing the pressure monitoring method of combustion chamber carbon dioxide and temperature-induced pulsating pressure fluctuations, comprising:

[0037] The data acquisition module uses multiple high-temperature pressure sensors to obtain real-time combustion pulsation pressure data in different areas of the combustion chamber;

[0038] A data resampling module, which resamples the real-time combustion pulsation pressure data using a layered resampling method to obtain resampled combustion pulsation pressure data;

[0039] An anomaly detection module, which detects pressure anomalies in different frequency bands in the combustion chamber using a pressure anomaly detection method based on the resampled combustion pulsation pressure data;

[0040] The alarm module issues a warning when it detects abnormal pressure in the combustion chamber.

[0041] A computer-readable storage medium stores a computer program for implementing the pressure monitoring method of combustion chamber carbon dioxide and temperature-induced pulsating pressure fluctuations.

[0042] Compared with the prior art, the present invention has the following beneficial effects:

[0043] The present invention collects pressure data of different areas of the combustion chamber respectively, thereby covering different areas of the combustion chamber and gaining a more comprehensive understanding of the state of the combustion process. A layered resampling method combining integer multiple extraction and fractional multiple interpolation is adopted to treat the pulsating pressure data of different areas as different layers, thereby removing redundant information in the original data while retaining key pressure fluctuation characteristics, thereby improving data processing efficiency and accuracy. Through layered processing, the interference of temperature field fluctuations and carbon dioxide concentration changes on the pressure signal can be eliminated, thereby better understanding and analyzing the pressure fluctuations in different areas. A pressure anomaly detection method is used to detect pressure anomalies in different frequency bands in the combustion chamber. By detecting pressure anomalies in different frequency bands, the source and nature of the problem can be more accurately located, thereby improving the maintenance efficiency and abnormal response speed of the staff. When a pressure anomaly is detected in the combustion chamber, the system sends an alarm to the operator through a preset alarm mechanism. By promptly reminding the operator to pay attention to the abnormal conditions in the combustion chamber, potential safety risks can be avoided, the supervision of the combustion system can be enhanced, and the probability of accidents can be reduced. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 The flowchart of the pressure monitoring method of the combustion chamber carbon dioxide and temperature-induced pulsating pressure fluctuation of the present invention;

[0045] Figure 2 It is a schematic diagram of the structure of the grid division of the cylindrical combustion chamber in Example 2 of the present invention;

[0046] Figure 3 It is a schematic structural diagram of a cylindrical combustion chamber grid cluster in Example 2 of the present invention;

[0047] Figure 4This is a schematic diagram of the structure of a pressure monitoring system in Example 3 of the present invention. DETAILED DESCRIPTION

[0048] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0049] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0050] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0051] Example 1

[0052] This embodiment provides a method for monitoring the pressure fluctuation of carbon dioxide and temperature-induced pulsating pressure in the combustion chamber. Figure 1 As shown, the pressure monitoring method of the combustion chamber carbon dioxide and temperature-induced pulsating pressure fluctuations comprises:

[0053] S101, obtaining real-time combustion pulsation pressure data of different areas of the combustion chamber;

[0054] S102, resampling the real-time combustion pulsation pressure data by using a layered resampling method to obtain resampled combustion pulsation pressure data;

[0055] S103, detecting pressure anomalies in different frequency bands in the combustion chamber using a pressure anomaly detection method according to the resampled combustion pulsation pressure data;

[0056] S104: When abnormal pressure is detected in the combustion chamber, an alarm is sounded.

[0057] In this embodiment, high-temperature pulsating pressure sensors are installed in different areas of the combustion chamber. These sensors can withstand the high temperature environment in the combustion chamber and capture the pulsating pressure signals generated during the combustion process in real time. These pulsating pressure data are collected in real time during the combustion process to provide a data basis for subsequent monitoring and analysis. By collecting pressure data from different areas of the combustion chamber, different areas of the combustion chamber can be covered to more comprehensively understand the state of the combustion process. The pulsating pressure data of different areas are treated as different levels using the layered resampling method, and resampled at each level to obtain the resampled combustion pulsating pressure data. Through layered resampling, the pulsating pressure data of different areas can be processed separately to avoid the influence between data in different areas, so as to improve the quality and reliability of the data. Through resampling, redundant information in the original data can be removed while retaining key pressure fluctuation features. The interference of temperature field fluctuations and carbon dioxide concentration changes on the pressure signal can be eliminated, the data processing efficiency and accuracy can be improved, and a more reliable data basis is provided for subsequent pressure anomaly detection. Through layered processing, the pressure fluctuations in different areas can be better understood and analyzed.

[0058] Specifically, according to the resampled combustion pulsation pressure data, the pressure anomaly detection method is used to detect the pressure anomaly in different frequency bands in the combustion chamber, which is used to detect the anomaly in the data or the deviation from the normal state. By setting the threshold in different frequency bands, the pressure anomaly in different frequency bands can be automatically detected and identified. Through the pressure anomaly monitoring, the pressure anomaly in the combustion chamber can be discovered in time, and the early warning can be provided for the safe operation of the equipment. The pressure anomaly monitoring in different frequency bands can help analyze the source and nature of specific problems. For example, high-frequency fluctuations indicate physical faults, while low-frequency fluctuations are related to the combustion state. By detecting the pressure anomaly in different frequency bands, the source and nature of the problem can be more accurately located, and the maintenance efficiency and abnormal response speed of the staff can be improved. When the pressure anomaly in the combustion chamber is detected, the system sends an alarm to the operator through the preset alarm mechanism. The alarm mechanism can warn the operator through sound, light or other means to remind them to pay attention to the abnormal situation in the combustion chamber. At the same time, the system can also record the abnormal data and related information for subsequent analysis and processing. By timely reminding the operator to pay attention to the abnormal situation in the combustion chamber, potential safety risks can be avoided, and the supervision of the combustion system can be enhanced, thereby reducing the probability of accidents.

[0059] The present invention collects pressure data of different areas of the combustion chamber respectively, thereby covering different areas of the combustion chamber and gaining a more comprehensive understanding of the state of the combustion process; a layered resampling method combining integer multiple extraction and fractional multiple interpolation is adopted to treat the pulsating pressure data of different areas as different layers, thereby removing redundant information in the original data while retaining key pressure fluctuation characteristics, thereby improving data processing efficiency and accuracy. Through layered processing, the pressure fluctuation conditions in different areas can be better understood and analyzed; a pressure anomaly detection method is utilized to detect pressure anomalies in different frequency bands in the combustion chamber. By detecting pressure anomalies in different frequency bands, the source and nature of the problem can be more accurately located, thereby improving the maintenance efficiency and abnormal response speed of the staff; when a pressure anomaly is detected in the combustion chamber, the system sends an alarm to the operator through a preset alarm mechanism. By promptly reminding the operator to pay attention to the abnormal conditions in the combustion chamber, potential safety risks can be avoided, the supervision of the combustion system can be enhanced, and the probability of accidents can be reduced.

[0060] Furthermore, the acquisition of real-time combustion pulsation pressure data of different areas of the combustion chamber includes:

[0061] S201, dividing the combustion chamber into different areas using a regional division method;

[0062] S202: Based on the different regions, obtain real-time combustion pulsation pressure data of each region.

[0063] In this embodiment, the combustion chamber is divided into different areas using a regional division method. During the combustion process, the combustion chamber is a complex space, and the combustion process inside it involves a variety of physical and chemical changes, which leads to significant differences in pressure fluctuations at different locations. Therefore, in order to more accurately monitor and analyze the pressure fluctuations in the combustion chamber, it is necessary to divide the combustion chamber into different areas. When dividing the areas, it can be based on factors such as the geometry of the combustion chamber, the characteristics of the combustion process, the distribution characteristics of the pressure fluctuations, the layout of the nozzle and the burner, etc. Specifically, the combustion chamber is divided using a grid division method. Through regional division, the pulsating pressure data of each area can be processed and analyzed separately, thereby improving the accuracy and precision of monitoring. By independently analyzing the pressure data of different areas, the characteristics of the combustion process at different locations can be more clearly revealed. When abnormal pressure fluctuations occur in a certain area, it can be quickly located and a warning can be issued, thereby improving the safety of the equipment and the abnormal response speed.

[0064] Specifically, according to the different divided areas, the real-time combustion pulsation pressure data of each area is obtained. The data acquisition system needs to be able to process the input of multiple sensors at the same time and ensure the synchronization of the data. The collected pulsation pressure data is usually presented in the form of time series, which contains rich pressure fluctuation information. Through the analysis and processing of these data, we can further understand the state and characteristics of the combustion process. By collecting the combustion pulsation pressure data of each area in real time, we can monitor the state and changes of the combustion process in real time. Based on the real-time data of each area, we can adjust the combustion parameters more finely and optimize the combustion efficiency. When the pressure data of a certain area is abnormal, the early warning mechanism can be triggered quickly, and important clues can be provided for troubleshooting. By combining regional division and partition data acquisition, it is possible to provide a detailed process of pressure changes in the combustion chamber, which helps to improve the accuracy and efficiency of monitoring, and also provides strong support for the optimization and fault diagnosis of the combustion system, thereby greatly improving the safety, reliability and efficiency of the combustion system.

[0065] Furthermore, the combustion chamber is divided into different areas by using the area division method, including:

[0066] S301, dividing the combustion chamber by a grid division method to obtain a plurality of grid unit areas;

[0067] S302: Clustering the multiple grid unit areas using a clustering algorithm to obtain different areas.

[0068] In this embodiment, the combustion chamber is divided by a grid division method to obtain a plurality of grid unit areas. The grid division method can divide a complex space or system into a plurality of small, regular or irregular grid units. In the grid division of the combustion chamber, the combustion chamber can be divided into a plurality of small grid unit areas based on its geometric shape, size and characteristics. According to actual calculation requirements, the size, shape, density and other parameters of the grid can be set to generate grid unit areas that meet the requirements. These grid unit areas can cover the entire combustion chamber to ensure that each area can be accurately monitored and analyzed. Accurate grid unit areas are generated by the grid division method to ensure that each area can be accurately monitored and analyzed. The size, shape, density and other parameters of the grid can be flexibly adjusted according to the characteristics of the combustion chamber and monitoring requirements, thereby improving the flexibility of area division. The grid unit areas generated by the grid division method are usually regular or easy to process, thereby improving data processing efficiency.

[0069] Specifically, different regions can be obtained by clustering the divided multiple grid unit areas using a clustering algorithm. The clustering algorithm usually performs calculations based on the characteristics or attributes of data points, such as distance, similarity, etc. In the regional division of the combustion chamber, clustering can be performed based on the pressure fluctuation characteristics of each grid unit area. Through the clustering algorithm, grid unit areas with similar characteristics can be divided into the same category, and the clustering results can be used as different regions; through clustering, multiple grid unit areas can be automatically divided into different categories, reducing the impact of human intervention. Clustering based on the pressure characteristics of each grid unit can obtain more accurate regional division results, reduce the amount of data for subsequent calculations, and thus improve data processing efficiency.

[0070] Furthermore, the real-time combustion pulsation pressure data is resampled by using a layered resampling method to obtain resampled combustion pulsation pressure data, including:

[0071] S401, performing windowing processing on the real-time combustion pulsation pressure data to obtain windowed pressure data;

[0072] S402, taking the windowed pressure data of each region as a layer of data;

[0073] S403, resampling the data of each layer using a dynamic resampling method to obtain resampled data of each layer;

[0074] S404, combining the resampled data of each layer as the resampled combustion pulsation pressure data.

[0075] In this embodiment, the real-time combustion pulsation pressure data of each area is windowed to obtain windowed pressure data. Windowing is a method of windowing continuous signals. In time series analysis, the data is divided into multiple small blocks by applying a sliding window to the data. Common windows include rectangular windows, triangular windows, Hanning windows, Hamming windows, Gaussian windows, etc., and a suitable window can be selected according to data characteristics and actual needs. In the processing of real-time combustion pulsation pressure data, windowing can help reduce the boundary effect of the data and improve the ability to analyze the local characteristics of the data. Through windowing, the boundaries of the data can be smoothed and the boundary effects caused by data truncation can be reduced. The windowed data can be more focused on the local time period or spatial area, thereby improving the ability to analyze the local characteristics of the combustion pulsation pressure data.

[0076] Specifically, in the layered resampling method, each layer of data represents a specific area or subset, and the windowed pressure data of each area is regarded as an independent layer for resampling. By treating the pressure data of each area as a layer, the data of different areas can be more clearly divided and processed, and the layered processing can be performed in parallel, thereby improving the overall data processing efficiency. The dynamic resampling method is used to resample the data of each layer to obtain the resampled data of each layer. The dynamic resampling method can adaptively adjust the sampling rate according to the characteristics of the data, thereby obtaining more accurate and reliable resampled data. Through resampling processing, redundant information in the original data can be removed, and the quality and availability of the data can be improved; after the generation of carbon dioxide, local high-temperature gas is formed, resulting in pressure signal baseline drift (low-frequency interference) and local pressure fluctuations (intermediate-frequency interference). Through resampling, the signal phase offset caused by the change in carbon dioxide concentration can be compensated, and the real pressure pulsation waveform can be restored; the resampled data of each layer are combined to form complete resampled combustion pulsation pressure data. By combining the resampled data of each layer, the integrity of the data can be maintained, which is convenient for the subsequent analysis of the combustion pulsation pressure.

[0077] Furthermore, the resampling of the data of each layer using the dynamic resampling method to obtain the resampled data of each layer includes:

[0078] S501, extracting the data of each layer using integer multiple extraction method to obtain the extracted data of each layer;

[0079] S502: Perform interpolation processing on each layer of extracted data using a fractional interpolation method to obtain each layer of resampled data.

[0080] In this embodiment, the data of each layer is extracted by integer multiple extraction method to obtain the extracted data of each layer. The integer multiple extraction method refers to converting the original sampling sequence into Extract a data every D-1 data to form a new sequence ,in:

[0081] ;

[0082] In the formula, , are the time serial numbers of the corresponding sequences, D is the decimation factor, and D is a positive integer. This decimation method is equivalent to reducing the data sampling frequency, that is, the spectrum period of the signal after decimation is reduced to the original 1 / D. By adjusting the decimation factor D, the data sampling rate can be adjusted to adapt to different application scenarios. Assuming that there is an original sampling sequence x(n)={1,2,3,4,5,6,7,8}, the decimation factor D=2, then the new sequence xD(m) after decimation is {1,3,5,7}; by processing the original sequence through the integer multiple decimation method, taking out the data at equal intervals and reordering it, the amount of data can be significantly reduced, while retaining the main characteristics of the signal, reducing the sampling rate to a suitable processing range, eliminating noise interference, reducing storage and computing costs, and facilitating subsequent signal processing and analysis.

[0083] Specifically, the fractional interpolation method is used to interpolate the data after each layer of extraction to obtain the resampled data of each layer. After integer multiple extraction, the sampling rate of the data is reduced. In order to increase the sampling rate of the data, the fractional interpolation method can be used. Through interpolation processing, more dense data points can be obtained, thereby more accurately describing the changes in the signal. In the fractional interpolation method, the ratio of the resampling frequency to the initial sampling frequency (i.e., the resampling multiple) needs to be converted into a coprime integer ratio, that is:

[0084] ;

[0085] In the formula, is the resampling factor, is the interpolation multiple, To extract the multiple, first Do times interpolation, and then do Multiple extraction, get the resampling sequence, for example, set the resampling multiple is 0.75, and the sampling frequency of the initial sampling sequence is , then the resampling frequency is In the resampling process, the resampling multiple 0.75 should be regularized to 3 / 4, and then the interpolation and decimation multiples I and Then, the initial sampling sequence is interpolated 3 times to obtain the sampling frequency The discrete sequence is then decimated by 4 times, and the final sampling frequency is The resampling sequence.

[0086] Specifically, the number of sampling points determines the sampling time, and the sampling time is the insertion position of the sampling value. The number of resampling points is related to the number of resampling values. Once the number of resampling values ​​is determined, the sampling time series is also determined. When , the change of the number of sampling points before and after resampling is described in two cases:

[0087] When the last point of the resampling sequence coincides with the last point of the initial sampling sequence, the number of resampling points can be calculated as follows:

[0088] ;

[0089] In the formula, is the number of initial sampling points; is the number of resampling points.

[0090] When the last point of the resampling sequence does not coincide with the last point of the initial sampling sequence, the number of resampling points can be calculated as follows:

[0091] ;

[0092] In the formula Indicates rounding down.

[0093] when When the resampling process uses the method of filling points, the number of resampling points can be calculated by the following formula:

[0094] ;

[0095] After the number of resampling points is determined, the resampled data can be expressed as:

[0096] ;

[0097] In the formula, is the time series data after resampling, is the resampling frequency, No. First, the sampling rate is reduced to a suitable processing range through integer multiple decimation filtering, while eliminating noise interference, and then the sampling rate is adjusted by fractional multiple interpolation filtering to synchronize with the rate at which data is sent to the processing end, thereby increasing the data sampling rate and making the data smoother and more continuous.

[0098] Furthermore, the method of detecting abnormal pressure conditions in different frequency bands in the combustion chamber using a pressure anomaly detection method based on the resampled combustion pulsation pressure data includes:

[0099] S601, converting the resampled combustion pulsation pressure data into frequency domain data by Fourier transform;

[0100] S602, dividing the pulsating pressure data in the combustion chamber into a plurality of frequency bands, wherein the plurality of frequency bands include a low frequency band, a middle frequency band, and a high frequency band;

[0101] S603: In each frequency band, detect the pressure anomaly using a pressure anomaly detection method.

[0102] In this embodiment, the resampled combustion pulsation pressure data is converted into frequency domain data by Fourier transform. In the combustion pulsation pressure analysis, the pressure signal that varies with time is decomposed into the sum of sine waves of different frequencies by Fourier transform, thereby revealing the frequency components in the signal. The frequency components in the signal can be intuitively displayed through frequency domain analysis. The frequency band division is based on the frequency components of the signal. In the combustion pulsation pressure analysis, the signal can be divided into a low frequency band, a medium frequency band and a high frequency band according to the frequency range. This division helps to detect pressure anomalies in different frequency ranges. Specifically, the low frequency band generally refers to a frequency band with a frequency lower than a certain threshold, for example, a frequency band lower than 30 Hz or 100 Hz is regarded as a low frequency band, and the medium frequency band refers to a frequency band with a frequency within a certain range, for example, a frequency band between 100 Hz and 1000 Hz is regarded as a medium frequency band. The high frequency band generally refers to a frequency band with a frequency higher than a certain threshold, for example, a frequency band higher than 1000 Hz is regarded as a high frequency band. The frequency band division helps to carry out targeted detection of pressure anomalies in different frequency ranges, which can improve the accuracy and efficiency of pressure anomaly detection.

[0103] Specifically, in each frequency band, the pressure anomaly detection method is used to detect the pressure anomaly. The pressure anomaly detection method can be a threshold judgment, statistical analysis, machine learning and other methods. Specifically, the threshold judgment is used to identify whether there is an abnormal pressure fluctuation in the frequency band. Assuming that in the medium frequency band (100~1000Hz), the pressure data is detected by the threshold judgment method. A threshold is set as a certain pressure value (such as 2000Pa). When the pressure data exceeds this threshold, it is considered to be abnormal. Through this method, the pressure anomaly in the medium frequency band can be discovered in time and corresponding measures can be taken to deal with it. The resampled combustion pulsating pressure data is converted into frequency domain data through Fourier transform, the pulsating pressure data in the combustion chamber is divided into multiple frequency bands, and the pressure anomaly detection method is used in each frequency band to detect the pressure anomaly. The pressure anomaly in the combustion chamber can be effectively detected and identified, which helps to ensure the stable operation of the combustion chamber and prevent potential safety hazards.

[0104] Furthermore, in each frequency band, the abnormal pressure situation is detected by using the abnormal pressure detection method, including:

[0105] S701, in each frequency band, respectively set the pre-alarm value and the high alarm value;

[0106] S702. Use a threshold analysis method to perform graded warnings on abnormal pulsation pressure conditions in each frequency band.

[0107] In this embodiment, a pre-alarm value and a high alarm value are set in each frequency band. In the pressure monitoring system, since the pressure fluctuation range and characteristics in different frequency bands are different, it is necessary to set the corresponding pre-alarm value and high alarm value according to the characteristics of each frequency band. The pre-alarm value and high alarm value are set based on the understanding of the normal pressure fluctuation range and the expectation of abnormal situations. By setting these thresholds, the system can issue an early warning before the pressure approaches or exceeds the dangerous level, thereby avoiding potential risks. It can be set according to the mean and standard deviation of normal pressure fluctuations. The formula is:

[0108] ;

[0109] In the formula, is the mean pressure in the frequency band, The first Pressure data values, is the total number of data points. The standard deviation is calculated as follows:

[0110] ;

[0111] In the formula, is the standard deviation of pressure in this frequency band. The formula for setting the pre-alarm value and high alarm value based on the mean and standard deviation is as follows:

[0112] ;

[0113] ;

[0114] In the formula, is the pre-alarm value, is the high alarm value, and It is a set multiple, which can be determined according to actual needs and safety requirements. and Typically, The value should be less than To ensure that the pre-alarm value is triggered before the high alarm value, when setting the abnormal threshold, it is necessary to consider the characteristics of the pressure data and the actual application scenario. For example, if the data fluctuates greatly, it is necessary to increase and value; if the application scenario has higher safety requirements, it is necessary to set a more stringent abnormal threshold. The setting of the abnormal threshold is a dynamic process and needs to be adjusted and optimized according to the actual situation. In practical applications, the abnormal threshold can be adjusted by observing the alarm situation, analyzing data changes, etc. to improve the accuracy and reliability of monitoring. By effectively detecting the abnormality of the combustion pulsation pressure data in each frequency band, potential pressure abnormalities can be discovered and handled in a timely manner. By setting reasonable pre-alarm values ​​and high alarm values, the stable operation and production safety of the combustion system can be guaranteed to varying degrees. By setting pre-alarm values ​​and high alarm values ​​in each frequency band and using the threshold analysis method for graded early warning, the accuracy and efficiency of pressure abnormality detection can be effectively improved.

[0115] Furthermore, the threshold analysis method is used to perform graded warning on abnormal pulsation pressure in each frequency band, including:

[0116] S801, drawing a pulsating pressure change curve based on the frequency domain data;

[0117] S802, when the pressure pulsation value is higher than the pre-alarm value and lower than the high alarm value, locate the warning point in the pulsating pressure change curve and issue a warning;

[0118] S803: When the pressure pulsation value is higher than the high alarm value, locate the alarm point in the pulsation pressure change curve and issue an alarm.

[0119] In this embodiment, based on the frequency domain data, a pulsating pressure change curve is drawn, and a curve diagram of the pulsating pressure changing with frequency is drawn according to the frequency domain data using signal processing technology. By drawing the pulsating pressure change curve, the change of the pulsating pressure in different frequency bands can be intuitively observed; the pressure abnormality is detected according to the pre-alarm value and the high alarm value. When the pulsating pressure value exceeds the pre-alarm value but does not reach the high alarm value, it is considered that the system is in a warning state and needs close attention. At this time, by locating the warning point in the pulsating pressure change curve, the specific time and frequency band of the warning can be determined. By setting the pre-alarm value and the high alarm value, a graded warning of abnormal pulsating pressure can be achieved. When the pulsating pressure value is within the warning range, the system can send a warning signal in advance to remind the operator to pay attention to the reaction in the combustion chamber and take necessary measures to avoid potential risks.

[0120] When the pulsating pressure value exceeds the high alarm value, the system is considered to be in a serious abnormal state and immediate measures need to be taken to avoid possible failures or accidents. At this time, by locating the alarm point in the pulsating pressure change curve, the specific time and frequency band of the alarm can be determined, and an alarm signal can be issued immediately. By setting the high alarm value, the severity of the pulsating pressure abnormality can be judged. When the pulsating pressure value exceeds the high alarm value, the system can immediately issue an alarm signal to remind the operator to take emergency measures to avoid more serious consequences.

[0121] Example 2

[0122] In this embodiment, if Figure 2 , a cylindrical combustion chamber with a height of 10 meters and a diameter of 5 meters, is divided into multiple hexahedral grid units using the hexahedral grid division method, such as Figure 3 , using the clustering algorithm to cluster multiple hexahedral grid cells according to the pressure data correlation of each hexahedral grid cell, the clustering results are four, that is, four regions, such as Figure 3 In the area enclosed by the dotted circle in the figure, a pulsation pressure sensor is installed in each area. When the combustion process is in progress, these sensors will collect the combustion pulsation pressure data of each area in real time. A Hanning window is added to the combustion pulsation pressure data of each area to obtain the windowed pressure data. The windowed pressure data of each area is used as a layer of data to obtain four layers of pressure data. The four layers of pressure data are resampled using the dynamic resampling method to obtain the resampled pressure data of each layer. The resampled pressure data of each layer are combined to obtain the complete resampled combustion pulsation pressure data.

[0123] According to the resampled combustion pulsation pressure data, the frequency domain data is segmented, the frequency in the range of 10-100 Hz is set as the low frequency band, the frequency in the range of 100-1000 Hz is set as the medium frequency band, and the frequency in the range of 5, 1000-2000 Hz is set as the high frequency band, and the pre-alarm value and high alarm value are set in each frequency band respectively, refer to Table 1;

[0124] Table 1 Alarm value setting table for different frequency bands

[0125]

[0126] The pressure anomaly detection method is used to detect the pressure anomalies in different frequency bands in the combustion chamber. In each frequency band, when the pressure pulsation value is lower than the pre-alarm value, no alarm is given; when the pressure pulsation value is higher than the pre-alarm value and lower than the high alarm value, an early warning is given to remind the staff to pay attention to the situation in the combustion chamber; when the pressure pulsation value is higher than the high alarm value, an alarm is given and the staff takes emergency measures, such as direct shutdown. By promptly reminding the operator to pay attention to the abnormal situation in the combustion chamber, potential safety risks can be avoided, the supervision of the combustion system can be strengthened, and the probability of accidents can be reduced.

[0127] Example 3

[0128] A pressure monitoring system, see Figure 4 , used to implement the pressure monitoring method of combustion chamber carbon dioxide and temperature-induced pulsating pressure fluctuations, comprising:

[0129] The data acquisition module uses multiple high-temperature pressure sensors to obtain real-time combustion pulsation pressure data in different areas of the combustion chamber;

[0130] A data resampling module, which resamples the real-time combustion pulsation pressure data using a layered resampling method to obtain resampled combustion pulsation pressure data;

[0131] An anomaly detection module, which detects pressure anomalies in different frequency bands in the combustion chamber using a pressure anomaly detection method based on the resampled combustion pulsation pressure data;

[0132] The alarm module issues a warning when it detects abnormal pressure in the combustion chamber.

[0133] In this embodiment, the data acquisition module includes a plurality of high-temperature pressure sensors, a data acquisition card and a data transmission line. Each sensor has high temperature resistance and can measure pressure in different areas inside the combustion chamber. The data acquisition card samples and quantifies the analog signal output by the sensor and converts it into a digital signal for subsequent data processing and analysis. The data transmission line ensures stable and high-speed transmission of pressure data from the sensor to the data acquisition card. The data resampling module includes a data processing unit and a memory. The data processing unit executes a hierarchical resampling algorithm to perform operations such as interpolation, downsampling or upsampling on the digital pressure data to optimize data quality and resolution and provide a reliable data basis for subsequent abnormality detection. The memory stores the original data and the resampled data to ensure that the data is not lost or corrupted during the data processing process. damage; the anomaly detection module includes an anomaly detection processor and an algorithm storage unit. The anomaly detection processor executes the pressure anomaly detection algorithm, performs frequency band decomposition, pattern recognition and other operations on the resampled data to detect the pressure anomalies in different frequency bands in the combustion chamber. The algorithm storage unit provides storage space for the algorithm and its required parameters to ensure the accurate execution of the anomaly detection algorithm; the alarm module includes an early warning signal generator, an alarm indicator light / buzzer, and a communication interface. The early warning signal generator generates corresponding early warning signals according to the abnormality detection results, such as sound and light alarms, network alarms, etc. The alarm indicator light / buzzer provides local alarm prompts, so that the operator can quickly notice the abnormal pressure in the combustion chamber. The communication interface realizes the remote transmission of early warning signals and communication with other systems for more extensive monitoring and management.

[0134] A computer-readable storage medium stores a computer program for implementing the pressure monitoring method of combustion chamber carbon dioxide and temperature-induced pulsating pressure fluctuations.

[0135] The above shows and describes the basic principles and main features of the present invention and the advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention to be protected. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A method for monitoring the pressure fluctuation of combustion chamber carbon dioxide and temperature-induced pulsating pressure, characterized in that: include: Obtain real-time combustion pulsation pressure data in different areas of the combustion chamber; Resampling the real-time combustion pulsation pressure data using a layered resampling method to obtain resampled combustion pulsation pressure data; According to the resampled combustion pulsation pressure data, using a pressure anomaly detection method to detect pressure anomalies in different frequency bands in the combustion chamber; When abnormal pressure is detected in the combustion chamber, an alarm is sounded.

2. The method for monitoring the pressure of combustion chamber carbon dioxide and temperature-induced pulsating pressure fluctuations according to claim 1, characterized in that: The method of obtaining real-time combustion pulsation pressure data of different areas of the combustion chamber includes: The combustion chamber is divided into different areas using the area division method; Based on the different areas, real-time combustion pulsation pressure data of each area is acquired.

3. The method for monitoring the pressure of combustion chamber carbon dioxide and temperature-induced pulsating pressure fluctuations according to claim 2, characterized in that: The combustion chamber is divided into different areas by using the area division method, including: Divide the combustion chamber by a meshing method to obtain a plurality of mesh unit regions; The plurality of grid unit regions are clustered using a clustering algorithm to obtain different regions.

4. The method for monitoring the pressure of combustion chamber carbon dioxide and temperature-induced pulsating pressure fluctuations according to claim 1, characterized in that: The method of resampling the real-time combustion pulsation pressure data by using a layered resampling method to obtain the resampled combustion pulsation pressure data includes: Performing windowing processing on the real-time combustion pulsation pressure data to obtain windowed pressure data; The windowed pressure data of each region is taken as a layer of data; The data of each layer is resampled using the dynamic resampling method to obtain the resampled data of each layer; The resampled data of each layer are combined to form the resampled combustion pulsation pressure data.

5. The method for monitoring the pressure of combustion chamber carbon dioxide and temperature-induced pulsating pressure fluctuations according to claim 4, characterized in that: The method of resampling the data of each layer by using the dynamic resampling method to obtain the resampled data of each layer includes: The data of each layer is extracted using the integer multiple extraction method to obtain the extracted data of each layer; The fractional interpolation method is used to interpolate the extracted data of each layer to obtain the resampled data of each layer.

6. The method for monitoring the pressure of combustion chamber carbon dioxide and temperature-induced pulsating pressure fluctuations according to claim 1, characterized in that: The method of detecting abnormal pressure conditions of different frequency bands in the combustion chamber using a pressure anomaly detection method according to the resampled combustion pulsation pressure data includes: Converting the resampled post-combustion pulsation pressure data into frequency domain data using Fourier transform; Dividing the pulsating pressure data in the combustion chamber into a plurality of frequency bands, wherein the plurality of frequency bands include a low frequency band, a middle frequency band, and a high frequency band; In each frequency band, the pressure anomaly detection method is used to detect the pressure anomaly.

7. The method for monitoring the pressure of combustion chamber carbon dioxide and temperature-induced pulsating pressure fluctuations according to claim 6, characterized in that: In each frequency band, the abnormal pressure situation is detected by using the abnormal pressure detection method, including: In each frequency band, set the pre-alarm value and high alarm value respectively; The threshold analysis method is used to provide graded warning for abnormal pulsation pressure in each frequency band.

8. The method for monitoring the pressure of combustion chamber carbon dioxide and temperature-induced pulsating pressure fluctuations according to claim 7, characterized in that: The threshold analysis method is used to provide a graded warning for abnormal pulsation pressure in each frequency band, including: Based on the frequency domain data, drawing a pulsating pressure change curve; When the pressure pulsation value is higher than the pre-alarm value and lower than the high alarm value, locate the warning point in the pulsating pressure change curve and issue a warning; When the pressure pulsation value is higher than the high alarm value, the alarm point in the pulsation pressure change curve is located and an alarm is issued.

9. A pressure monitoring system, characterized in that: A method for monitoring the pressure of combustion chamber carbon dioxide and temperature-induced pulsating pressure fluctuations as claimed in any one of claims 1 to 8, comprising: The data acquisition module uses multiple high-temperature pressure sensors to obtain real-time combustion pulsation pressure data in different areas of the combustion chamber; A data resampling module, which resamples the real-time combustion pulsation pressure data using a layered resampling method to obtain resampled combustion pulsation pressure data; An anomaly detection module, which detects pressure anomalies in different frequency bands in the combustion chamber using a pressure anomaly detection method based on the resampled combustion pulsation pressure data; The alarm module issues a warning when it detects abnormal pressure in the combustion chamber.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: A method for monitoring the pressure of combustion chamber carbon dioxide and temperature-induced pulsating pressure fluctuations as described in any one of claims 1 to 8.

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