Photoacoustic cell resonance characteristic measurement and classification method based on frequency sweep modulation

Abstract

The invention discloses a photoacoustic cell resonance characteristic measurement classification method based on frequency sweep modulation, and relates to the technical field of photoacoustic cells, and the method comprises the following steps: collecting photoacoustic signal data, and transmitting the data to a data management center, the photoacoustic signal data comprising historical data and real-time data, the collected photoacoustic signal data is preprocessed and analyzed, resonance characteristic interference factors are extracted, the resonance characteristic interference factors comprise a temperature interference factor, a humidity interference factor and an electromagnetic interference factor, and the change curve of the resonance amplitude and the resonance frequency of the photoacoustic cell is analyzed. By measuring and calibrating the temperature in real time, the resonance characteristics of the photoacoustic cell at different temperatures can be accurately reflected, so that the accuracy and stability of measurement are improved, the photoacoustic spectrum system can stably operate under wider environmental conditions, and the reliability and durability of the photoacoustic spectrum system in practical application are improved.

Description

Technical Field

[0001] The invention relates to the technical field of photoacoustic cells, and in particular to a photoacoustic cell resonance characteristic measurement and classification method based on frequency sweep modulation. Background Art

[0002] Photoacoustic spectroscopy is a gas detection technology based on the photoacoustic effect. Its core component is the photoacoustic cell. The design and processing and assembly effect of the photoacoustic cell directly determine the accuracy and detection limit of gas detection. The swept frequency modulation technology is a method of measuring the system response by changing the frequency of the modulation signal. In the measurement of the resonance characteristics of the photoacoustic cell based on swept frequency modulation, the swept frequency sine signal is used to modulate the intensity of the laser output by the laser. This modulation method can make the output light intensity of the laser change with the frequency of the swept frequency sine signal, thereby realizing the excitation of the photoacoustic cell. This technology is also used in the detection technology of dissolved gas in transformer oil. As the insulation and cooling medium of power transformers, the performance of transformer oil is directly related to the stability and safe operation of the power system. Due to overload or manufacturing defects, the transformer may have faults such as discharge and overheating. These faults will cause the hydrocarbon molecular bonds in the insulating oil to break, and produce small molecular characteristic gases dissolved in the oil. The concentration and type of these characteristic gases are different. By analyzing the type and concentration of dissolved gas in the oil, the operating status and aging status of the transformer can be judged.

[0003] In the prior art, the photoacoustic cell and its measurement system may be disturbed by external factors such as environmental noise and vibration, resulting in a decrease in the accuracy of the measurement results. For example, temperature changes, humidity changes, electromagnetic interference, etc. will have an adverse effect on the resonance characteristics of the photoacoustic cell and affect the measurement results. When its resonance characteristics change, the accuracy of its prediction of the target parameters will also be greatly reduced. Therefore, reducing the interference of external factors and improving the accuracy of measurement are the problems we need to solve now. For this purpose, a photoacoustic cell resonance characteristic measurement classification method based on swept frequency modulation is proposed. Summary of the invention

[0004] The present invention aims to provide a method for measuring and classifying resonance characteristics of a photoacoustic cell based on swept frequency modulation to solve the problems raised in the above background technology.

[0005] In order to solve the above technical problems, the technical solution adopted by the present invention is:

[0006] A method for measuring and classifying resonance characteristics of a photoacoustic cell based on frequency sweep modulation, step 1, collecting photoacoustic signal data, and transmitting the data to a data management center to ensure the security and real-time performance of data transmission, wherein the photoacoustic signal data includes historical data and real-time data;

[0007] Step 2, preprocessing and analyzing the collected photoacoustic signal data, extracting the resonance characteristic interference factors, wherein the resonance characteristic interference factors include temperature interference factors, humidity interference factors and electromagnetic interference factors, and analyzing the resonance amplitude and resonance frequency change curve of the photoacoustic cell;

[0008] Step 3, analyzing the pre-processed photoacoustic signal data and combining the resonance interference factor, establishing a resonance characteristic analysis model, and obtaining the temperature interference index, humidity interference index and electromagnetic interference index, and quantifying the influence of each factor on the resonance characteristics of the photoacoustic cell;

[0009] Step 4, based on the temperature interference index, humidity interference index, electromagnetic interference index and historical data, analyze the factors affecting the resonance characteristics of the photoacoustic pool, generate an abnormal factor analysis list, list the potential impact of each factor, and obtain the abnormal evaluation coefficient of the photoacoustic pool, evaluate the health of the current state of the photoacoustic pool, and quantify the deviation degree of the performance of the photoacoustic pool;

[0010] Step 5, input the real-time data into the resonance characteristic analysis model, analyze the change curve and influence law of the resonance characteristic, and obtain the analysis results. At the same time, combined with the value of the abnormal evaluation coefficient of the photoacoustic pool, output the corresponding correction and compensation plan, such as adjusting the temperature, humidity control parameters or electromagnetic shielding measures.

[0011] A further improvement of the technical solution of the present invention is that in step 1, the photoacoustic signal data collection process is:

[0012] Step 101, deploying and debugging the photoacoustic signal acquisition equipment, including sensors, amplifiers, data acquisition and photoacoustic detector cards, etc., to ensure that their sensitivity and accuracy meet the experimental requirements. At the same time, according to the experimental requirements, set the sampling rate, sampling depth and signal gain parameters to collect photoacoustic signals in real time. The sampling rate should be set according to the signal frequency characteristics, the sampling depth should be sufficient to record the complete waveform of the signal, and the signal gain should be adjusted to an appropriate level to ensure that the signal is clear and not overloaded;

[0013] Step 102, setting a time interval for the photoacoustic signal acquisition device, automatically recording the photoacoustic signal data, and dividing the collected photoacoustic signal data into historical data and real-time data, wherein the historical data is usually used for subsequent data analysis, model training, etc., and the real-time data is used for real-time monitoring and decision support;

[0014] Step 103, establish a data transmission channel, encrypt the collected photoacoustic signal data and transmit it to the data management center, and monitor the status of data transmission in real time to ensure the integrity and real-time performance of the data;

[0015] Step 104, the data management center stores the transmitted acoustic signal data, and classifies, marks and indexes the photoacoustic signal data, including classification by time, experimental conditions, signal type, etc., to facilitate subsequent data retrieval and analysis, and regularly backs up and restores the data to ensure data reliability and security.

[0016] A further improvement of the technical solution of the present invention is that in step 2, the advance process of the resonance characteristic interference factor is:

[0017] Step 201, performing data cleaning, noise reduction, signal enhancement and standardization processing on the collected photoacoustic signal data to highlight the tissue structure information and reduce the influence of noise; wherein, noise reduction can apply low-pass, high-pass or band-pass filters to remove high-frequency noise or low-frequency background signals, retain the signal in the frequency band of interest, and use wavelet transform to perform multi-scale analysis to separate and enhance the useful components in the signal, and at the same time, according to the statistical characteristics of the signal and noise, adaptively adjust the filter parameters to achieve better noise reduction effect;

[0018] Step 202, using spectrum analysis technology to identify the resonance frequency of the photoacoustic signal, determining the resonance frequency by observing the peak value in the spectrum diagram, and measuring the amplitude of the signal at the resonance frequency to obtain the resonance amplitude, which reflects the response intensity of the photoacoustic cell at the resonance frequency.

[0019] Step 203, extracting features from the pre-processed historical data, performing feature extraction on the temperature condition, humidity condition and electromagnetic condition respectively, and obtaining a temperature interference factor, a humidity interference factor and an electromagnetic interference factor;

[0020] Step 204, based on the extracted resonance amplitude and resonance frequency, respectively draw curves of the resonance amplitude and resonance frequency changing with the temperature interference factor, humidity interference factor and electromagnetic interference factor, analyze the trend of the corresponding curve and output the analysis results, such as whether the resonance amplitude decreases with increasing temperature, or whether the resonance frequency shifts with increasing humidity, etc., summarize the influence of the temperature interference factor, humidity interference factor and electromagnetic interference factor on the resonance amplitude and resonance frequency, such as the negative correlation of temperature on the resonance amplitude, the positive offset effect of humidity on the resonance frequency, etc., to understand the influence of these factors on the resonance amplitude.

[0021] A further improvement of the technical solution of the present invention is that in step 3, the process of obtaining the temperature interference index, the humidity interference index and the electromagnetic interference index is as follows:

[0022] Step 301, using a spectrum analysis tool to perform spectrum analysis on the preprocessed photoacoustic signal data, obtain a spectrum diagram of the photoacoustic signal data, identify the resonance frequency in the spectrum diagram, and measure the resonance amplitude; wherein the resonance amplitude is measured by observing and analyzing the frequency distribution of the signal in the spectrum diagram, finding obvious peaks or resonance points, using a peak detection algorithm or a manual marking method to determine the resonance frequency, and recording each resonance frequency and its corresponding resonance amplitude;

[0023] Step 302, combining the analysis results of the resonance frequency, the resonance amplitude and the resonance interference factor, establishing a resonance characteristic analysis model, which will take into account the influence of temperature, humidity and electromagnetic interference on the resonance characteristics of the photoacoustic cell, and integrate the associated data of the temperature interference factor, the humidity interference factor and the electromagnetic interference factor in the pre-processed historical data to form a unified data set;

[0024] Step 303, dividing the integrated data set into a training set, a validation set and a test set, using the training set data to train the resonance characteristic analysis model, and using the validation set and the test set data to verify the trained resonance characteristic analysis model, and evaluating the performance of the resonance characteristic analysis model;

[0025] Step 304, based on the constructed resonance characteristic analysis model, calculate the temperature interference index, humidity interference index and electromagnetic interference index, analyze the influence degree and trend of different interference indexes on the resonance characteristic, and explore the relationship between the interference index and factors such as experimental conditions and equipment performance.

[0026] A further improvement of the technical solution of the present invention is that the calculation formula of the temperature interference index is:

[0027]

[0028] Among them, TI is the temperature interference index, T is the current temperature, T std is the standard temperature, σ T is the temperature standard deviation, is the derivative of the resonant frequency with temperature, indicating the degree of influence of temperature on the resonant frequency, ΔT is the temperature change, Δf res is the change in resonant frequency;

[0029] The calculation formula of the humidity interference index is:

[0030]

[0031] Among them, HI is the humidity interference index, H is the current humidity, and H opt For the optimal humidity, H range is the humidity variation range, indicating the degree of humidity fluctuation, f res (H) is the resonant frequency at the current humidity, fres,std is the resonant frequency at standard humidity;

[0032] The calculation formula of the electromagnetic interference index is:

[0033]

[0034] Among them, EI is the electromagnetic interference index, E is the current electromagnetic field strength, and E thresh is the electromagnetic interference threshold, ΔA res is the change in resonance amplitude, A res,std is the resonance amplitude in the absence of electromagnetic interference.

[0035] A further improvement of the technical solution of the present invention is that in step 4, the process of obtaining the abnormal evaluation coefficient of the photoacoustic pool is:

[0036] Step 401, traversing the pre-processed historical data, combining the temperature interference index, the humidity interference index, and the electromagnetic interference index, and analyzing the correlation between the photoacoustic cell resonance characteristics and the temperature interference index, the humidity interference index, and the electromagnetic interference index;

[0037] Step 402, based on the temperature interference index, humidity interference index, electromagnetic interference index and historical data, classify and organize to establish an abnormal factor analysis list, and list the factors that affect the resonance characteristics of the photoacoustic pool, including temperature, humidity, electromagnetic interference, etc., and analyze each factor separately, including possible influencing mechanisms such as temperature increase may cause the photoacoustic pool material to expand, affecting the resonance frequency; humidity increase may cause water condensation inside the photoacoustic pool, affecting the photoacoustic conversion efficiency; electromagnetic interference may cause resonance signal distortion, etc.;

[0038] Step 403, assigning different weights to the temperature interference index, the humidity interference index, and the electromagnetic interference index, performing weighted calculations on them, and obtaining a photoacoustic cell abnormality assessment coefficient;

[0039] Step 404, according to the pre-processed historical data matching abnormal factor analysis list, analyze the degree of deviation of the photoacoustic cell performance, and determine different deviation levels, such as slight deviation level, moderate deviation level, severe deviation level, etc.;

[0040] Step 405, matching the determined different deviation levels with the result of the photoacoustic pool abnormality assessment coefficient, setting corresponding deviation thresholds for different deviation levels, and judging the health of the current state of the photoacoustic pool.

[0041] A further improvement of the technical solution of the present invention is that the calculation formula of the abnormal evaluation coefficient of the photoacoustic cell is:

[0042]

[0043] Among them, PA is the photoacoustic pool anomaly assessment coefficient, TI is the temperature interference index, which indicates the degree of influence of temperature on the resonance characteristics of the photoacoustic pool, HI is the humidity interference index, which indicates the degree of influence of humidity on the resonance characteristics of the photoacoustic pool, EI is the electromagnetic interference index, which indicates the degree of influence of electromagnetic interference on the resonance characteristics of the photoacoustic pool, T std is the standard temperature of the temperature interference index, H std is the standard humidity of humidity interference index, E std It is the standard value of electromagnetic interference index.

[0044] A further improvement of the technical solution of the present invention is that: the multiple deviation levels correspond to multiple deviation thresholds, wherein the deviation thresholds include an upper threshold and a lower threshold;

[0045] The plurality of deviation levels and the plurality of deviation thresholds satisfy the following relationship:

[0046] Slight deviation from level 0 <PA≤P1;

[0047] Moderate deviation level P1 <PA≤P2;

[0048] Severe deviation level P2 <PA<1;

[0049] Among them, PA is the photoacoustic pool abnormality assessment coefficient, P1 is the upper threshold corresponding to the slight deviation level and the lower threshold corresponding to the moderate deviation level, and P2 is the upper threshold corresponding to the moderate deviation level and the lower threshold corresponding to the severe deviation level.

[0050] A further improvement of the technical solution of the present invention is that in step 5, the process of outputting the corresponding correction and compensation solution is:

[0051] Step 501, input the pre-processed real-time data into the resonance characteristic analysis model, calculate the temperature interference index, humidity interference index, and electromagnetic interference index respectively, and generate a change curve to analyze the stability of the resonance frequency and observe whether there is a frequency drift phenomenon. Frequency drift may mean a slight change in the internal structure of the photoacoustic cell or interference from the external environment;

[0052] Step 502, combining the calculated temperature interference index, humidity interference index and electromagnetic interference index to obtain the photoacoustic pool abnormality assessment coefficient, and determining the deviation level of the current photoacoustic pool according to a preset deviation threshold, and evaluating the current state of the photoacoustic pool;

[0053] Step 503, according to the deviation level of the current photoacoustic pool state, output the corresponding compensation plan and report, implement the correction and compensation plan, continuously monitor the resonance characteristics of the photoacoustic pool, ensure the correction effect, re-evaluate the performance of the photoacoustic pool according to the real-time data after correction, and adjust the correction plan to ensure long-term stable operation.

[0054] Due to the adoption of the above technical solution, the present invention has the following technical advances compared with the prior art:

[0055] 1. The present invention provides a classification method for measuring the resonance characteristics of a photoacoustic pool based on frequency sweep modulation. By continuously scanning the photoacoustic signal within the frequency range, the resonance frequency of the photoacoustic pool and its related characteristics can be accurately captured, thereby avoiding measurement errors caused by improper frequency selection and significantly improving the measurement accuracy. At the same time, the resonance frequency changes of the photoacoustic pool can be tracked in real time. Even when external factors such as temperature and humidity change, the measurement parameters can be quickly adjusted to ensure the stability of the measurement.

[0056] 2. The present invention provides a classification method for measuring the resonance characteristics of a photoacoustic cell based on swept frequency modulation. By continuously scanning the photoacoustic signal within a frequency range, the resonance characteristic curve of the photoacoustic cell can be accurately captured, and modulation can be performed within a wider frequency range, thereby providing a more comprehensive understanding of the resonance behavior of the photoacoustic cell. This not only improves the measurement accuracy, but also significantly shortens the measurement time, making the calibration and calibration process of the photoacoustic cell more efficient.

[0057] 3. The present invention provides a method for measuring and classifying the resonance characteristics of a photoacoustic cell based on swept frequency modulation. By measuring and calibrating the temperature in real time, the resonance characteristics of the photoacoustic cell at different temperatures can be accurately reflected, thereby improving the accuracy and stability of the measurement, enabling the photoacoustic spectroscopy system to operate stably under a wider range of environmental conditions, thereby improving its reliability and durability in practical applications. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0059] Figure 1 is a flow chart of the present invention;

[0060] Figure 2 The present invention is a flow chart for obtaining the temperature interference factor, humidity interference factor and electromagnetic interference factor;

[0061] Figure 3 The present invention is a flowchart for obtaining the abnormal evaluation coefficient of the photoacoustic cell. DETAILED DESCRIPTION

[0062] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0063] Embodiment 1, as Figure 1-3 As shown, the present invention provides a method for measuring and classifying resonance characteristics of a photoacoustic cell based on swept frequency modulation, comprising the following steps:

[0064] Step 1, collect photoacoustic signal data, and transmit the data to the data management center to ensure the security and real-time performance of data transmission, wherein the photoacoustic signal data includes historical data and real-time data; the photoacoustic signal data collection process is: deploy photoacoustic signal collection equipment and debug and calibrate, including sensors, amplifiers, data collection and photoacoustic detector cards, etc., to ensure that their sensitivity and accuracy meet the experimental requirements, and set the sampling rate, sampling depth and signal gain parameters according to the experimental requirements, and collect photoacoustic signals in real time. The sampling rate should be set according to the signal frequency characteristics, the sampling depth should be sufficient to record the complete waveform of the signal, and the signal gain should be adjusted to an appropriate level to ensure that the signal is clear and not overloaded, and the time interval is set for the photoacoustic signal collection equipment. The photoacoustic signal data is automatically recorded at intervals, and the collected photoacoustic signal data is divided into historical data and real-time data. The historical data is usually used for subsequent data analysis, model training, etc.; the real-time data is used for real-time monitoring and decision support. The established data transmission channel encrypts the collected photoacoustic signal data and transmits it to the data management center. At the same time, the status of data transmission is monitored in real time to ensure the integrity and real-time nature of the data. The data management center stores the transmitted acoustic signal data and classifies, marks and indexes the photoacoustic signal data, including classification by time, experimental conditions, signal type, etc., to facilitate subsequent data retrieval and analysis, and regularly backs up and restores the data to ensure the reliability and security of the data.

[0065] Step 2, preprocessing and analyzing the collected photoacoustic signal data, extracting the resonance characteristic interference factors, wherein the resonance characteristic interference factors include temperature interference factors, humidity interference factors and electromagnetic interference factors, and analyzing the resonance amplitude of the photoacoustic pool and the change curve of the resonance frequency; the advance process of the resonance characteristic interference factors is: data cleaning, noise reduction, signal enhancement and standardization of the collected photoacoustic signal data to highlight the tissue structure information and reduce the influence of noise; wherein, noise reduction can apply low-pass, high-pass or band-pass filters to remove high-frequency noise or low-frequency background signals, retain the signals in the frequency band of interest, and use wavelet transform Multi-scale analysis is performed to separate and enhance the useful components in the signal. At the same time, according to the statistical characteristics of the signal and noise, the filter parameters are adaptively adjusted to achieve better noise reduction effects. The spectrum analysis technology is used to identify the resonant frequency of the photoacoustic signal. The resonant frequency is determined by observing the peak value in the spectrum diagram, and the amplitude of the signal is measured at the resonant frequency to obtain the resonance amplitude. The resonance amplitude reflects the response intensity of the photoacoustic cell at the resonance frequency. Features are extracted from the pre-processed historical data. Feature extraction is performed for temperature conditions, humidity conditions, and electromagnetic conditions to obtain temperature interference factors, humidity interference factors, and electromagnetic interference factors; each factor The acquisition process is as follows: the temperature interference factor changes the temperature of the experimental environment, observes and records the changes in the resonant frequency and resonant amplitude of the photoacoustic signal at different temperatures, and uses statistical methods to analyze the correlation between temperature and resonance characteristics, thereby extracting the temperature interference factor. The extraction of the temperature interference factor, by changing the humidity of the experimental environment, observes and records the changes in the resonant frequency and resonant amplitude of the photoacoustic signal under different humidity, and uses statistical methods to analyze the correlation between humidity and resonance characteristics, thereby extracting the humidity interference factor. The electromagnetic interference factor can simulate different electromagnetic interference environments and observe how the resonant characteristics of the photoacoustic signal change. By comparing the data under different electromagnetic interference conditions, the electromagnetic interference factor is extracted; according to the extracted resonance amplitude and resonance frequency, the curves of the resonance amplitude and resonance frequency changing with the temperature interference factor, humidity interference factor and electromagnetic interference factor are drawn respectively, and the trend of the corresponding curve is analyzed and the analysis results are output, such as whether the resonance amplitude decreases with increasing temperature, or whether the resonance frequency shifts with increasing humidity, etc., and the influence of the temperature interference factor, humidity interference factor and electromagnetic interference factor on the resonance amplitude and resonance frequency are summarized, such as the negative correlation of temperature on the resonance amplitude, the positive shift effect of humidity on the resonance frequency, etc., to understand the influence of these factors on the resonance amplitude;

[0066] Step 3, analyze the pre-processed photoacoustic signal data and combine it with the resonance interference factor, establish a resonance characteristic analysis model, and obtain the temperature interference index, humidity interference index and electromagnetic interference index, and quantify the influence of each factor on the resonance characteristics of the photoacoustic pool; the acquisition process of the temperature interference index, humidity interference index and electromagnetic interference index is: use a spectrum analysis tool to perform spectrum analysis on the pre-processed photoacoustic signal data, obtain a spectrum diagram of the photoacoustic signal data, identify the resonance frequency in the spectrum diagram, and measure the resonance amplitude; wherein, the resonance amplitude is measured by observing and analyzing the frequency distribution of the signal in the spectrum diagram, looking for obvious peaks or resonance points, using a peak detection algorithm or a manual marking method to determine the resonance frequency, recording each resonance frequency and its corresponding resonance amplitude, combining the resonance frequency, resonance amplitude and resonance interference Based on the analysis results of the interference factors, a resonance characteristic analysis model is established. The model will consider the influence of temperature, humidity and electromagnetic interference on the resonance characteristics of the photoacoustic pool, and integrate the associated data of the temperature interference factor, humidity interference factor and electromagnetic interference factor in the pre-processed historical data to form a unified data set. The integrated data set is divided into a training set, a validation set and a test set. The resonance characteristic analysis model is trained using the training set data, and the trained resonance characteristic analysis model is verified using the validation set and the test set data. The performance of the resonance characteristic analysis model is evaluated. According to the constructed resonance characteristic analysis model, the temperature interference index, humidity interference index and electromagnetic interference index are calculated, the influence degree and trend of different interference indices on the resonance characteristics are analyzed, and the relationship between the interference index and experimental conditions, equipment performance and other factors is explored;

[0067] Step 4, based on the temperature interference index, humidity interference index, electromagnetic interference index and historical data, analyze the factors affecting the resonance characteristics of the photoacoustic pool, generate an abnormal factor analysis list, list the potential impact of each factor, and obtain the abnormal evaluation coefficient of the photoacoustic pool at the same time, evaluate the health of the current state of the photoacoustic pool, and quantify the degree of deviation of the performance of the photoacoustic pool; the process of obtaining the abnormal evaluation coefficient of the photoacoustic pool is as follows: traverse the pre-processed historical data, combine the temperature interference index, humidity interference index, and electromagnetic interference index, analyze the correlation between the resonance characteristics of the photoacoustic pool and the temperature interference index, humidity interference index, and electromagnetic interference index, and classify and organize the abnormal factor analysis list based on the temperature interference index, humidity interference index, electromagnetic interference index and historical data, and list the factors affecting the resonance characteristics of the photoacoustic pool, including temperature, humidity, and electromagnetic interference. Magnetic interference, etc., analyze each factor separately, including possible influencing mechanisms such as temperature increase may cause the photoacoustic pool material to expand and affect the resonance frequency; humidity increase may cause water condensation inside the photoacoustic pool and affect the photoacoustic conversion efficiency; electromagnetic interference may cause resonance signal distortion, etc., assign different weights to the temperature interference index, humidity interference index, and electromagnetic interference index, perform weighted calculations on them, and obtain the photoacoustic pool abnormality assessment coefficient. According to the pre-processed historical data matching abnormal factor analysis list, analyze the degree of deviation of the photoacoustic pool performance, and determine different deviation levels, such as slight deviation level, moderate deviation level, severe deviation level, etc., match the determined different deviation levels with the results of the photoacoustic pool abnormality assessment coefficient, set corresponding deviation thresholds for different deviation levels, and judge the health of the current state of the photoacoustic pool;

[0068] Step 5, input the real-time data into the resonance characteristic analysis model, analyze the change curve and influence law of the resonance characteristic, and obtain the analysis results. At the same time, combined with the value of the abnormal evaluation coefficient of the photoacoustic pool, the corresponding correction and compensation scheme is output, such as adjusting the temperature and humidity control parameters or electromagnetic shielding measures, etc. The process of outputting the corresponding correction and compensation scheme is as follows: input the pre-processed real-time data into the resonance characteristic analysis model, calculate the temperature interference index, humidity interference index, and electromagnetic interference index respectively, and generate a change curve, analyze the stability of the resonance frequency, and observe whether there is a frequency drift phenomenon. Frequency drift may mean a slight change in the internal structure of the photoacoustic pool or interference from the external environment. The calculated temperature interference index, humidity interference index, and electromagnetic interference index are combined to obtain the abnormal evaluation coefficient of the photoacoustic pool, and the deviation level of the current photoacoustic pool is determined according to the preset deviation threshold, and the current state of the photoacoustic pool is evaluated. According to the deviation level of the current photoacoustic pool state, the corresponding compensation scheme and report are output, and the correction and compensation scheme is implemented, the resonance characteristics of the photoacoustic pool are continuously monitored to ensure the correction effect, and the performance of the photoacoustic pool is re-evaluated according to the corrected real-time data, and the correction scheme is adjusted to ensure long-term stable operation, including Adjust working environment parameters such as temperature and humidity to reduce interference, or fine-tune the working parameters of the photoacoustic pool to improve performance. Corrective measures include: Environmental control: If the abnormal evaluation coefficient indicates that temperature and humidity are the main reasons, adjust the environmental conditions to approach the optimal working point; Electromagnetic shielding: If electromagnetic interference is the main problem, strengthen electromagnetic shielding measures; Compensation schemes include algorithm compensation: According to the change curve and influence law of the resonance characteristics, develop or adjust the algorithm to compensate for the impact of environmental changes on the photoacoustic signal; Hardware adjustment: When necessary, replace or adjust the hardware components of the photoacoustic pool, such as sensors, optical elements, etc., to improve the resonance characteristics.

[0069] Embodiment 2, as Figure 1-3 As shown, based on Example 1, the present invention provides a technical solution: Preferably, the calculation formula of the temperature interference index is:

[0070]

[0071] Among them, TI is the temperature interference index, T is the current temperature, T std is the standard temperature, σ T is the temperature standard deviation, is the derivative of the resonant frequency with temperature, indicating the degree of influence of temperature on the resonant frequency, ΔT is the temperature change, Δf res is the change in resonant frequency;

[0072] The calculation formula of humidity interference index is:

[0073]

[0074] Among them, HI is the humidity interference index, H is the current humidity, H opt is the optimal humidity, H range is the humidity change range, indicating the degree of humidity fluctuation, f res (H) is the resonance frequency at the current humidity, f res,std is the resonance frequency under standard humidity;

[0075] The calculation formula for the electromagnetic interference index is:

[0076]

[0077] Among them, EI is the electromagnetic interference index, E is the current electromagnetic field intensity, E thresh is the electromagnetic interference threshold, ΔA res is the change amount of the resonance amplitude, A res,std is the resonance amplitude without electromagnetic interference;

[0078] The calculation formula for the photoacoustic cell anomaly evaluation coefficient is:

[0079]

[0080] Among them, PA is the photoacoustic cell anomaly evaluation coefficient, TI is the temperature interference index, indicating the degree of influence of temperature on the resonance characteristics of the photoacoustic cell, HI is the humidity interference index, indicating the degree of influence of humidity on the resonance characteristics of the photoacoustic cell, EI is the electromagnetic interference index, indicating the degree of influence of electromagnetic interference on the resonance characteristics of the photoacoustic cell, T std is the standard temperature of the temperature interference index, H std is the standard humidity of the humidity interference index, E std is the standard value of the electromagnetic interference index;

[0081] Multiple deviation levels correspond to multiple deviation thresholds. Among them, the deviation thresholds include upper limit thresholds and lower limit thresholds;

[0082] The multiple deviation levels and the multiple deviation thresholds satisfy the following relationship:

[0083] For the slight deviation level 0 < PA ≤ P1; the compensation measures are to regularly check and record the changes in temperature, humidity, and electromagnetic interference, slightly adjust the environmental conditions, such as finely tuning the temperature and humidity control systems, and strengthening the daily maintenance and cleaning of the photoacoustic cell

[0084] For the moderate deviation level P1 < PA ≤ P2; the compensation measures are to implement stricter environmental control to ensure that the temperature and humidity are maintained within the optimal working range, strengthen electromagnetic shielding measures to reduce external electromagnetic interference, conduct a detailed inspection and diagnosis of the photoacoustic cell, identify and repair possible fault sources, and consider adjusting the working parameters of the photoacoustic cell, such as laser power, modulation frequency, etc., to optimize the resonance characteristics;

[0085] Severe deviation level P2 < PA < 1; the compensation measures are to immediately stop using the photoacoustic cell, conduct a comprehensive fault diagnosis and repair, replace damaged components such as sensors, optical elements, etc., recalibrate and verify the photoacoustic cell to ensure its performance is restored. Before the problem is solved, the photoacoustic cell should not be used for any important measurements or experiments. Consider upgrading the hardware or software of the photoacoustic cell to improve its anti-interference ability and stability;

[0086] Among them, PA is the abnormal evaluation coefficient of the photoacoustic cell, P1 is the upper threshold corresponding to the minor deviation level and the lower threshold corresponding to the moderate deviation level, and P2 is the upper threshold corresponding to the moderate deviation level and the lower threshold corresponding to the severe deviation level.

[0087] The above is only the specific implementation manner of this application, but the protection scope of this application is not limited thereto. Any person skilled in the art within the technical scope disclosed in this application can easily think of changes or substitutions, which should all be covered within the protection scope of this application. Therefore, the protection scope of this application shall be subject to the protection scope of the claims.

Claims

1. A method for measuring and classifying resonance characteristics of a photoacoustic cell based on frequency sweep modulation, characterized in that: The following steps are involved: Step 1, collecting photoacoustic signal data and transmitting the data to a data management center, wherein the photoacoustic signal data includes historical data and real-time data; Step 2, preprocessing and analyzing the collected photoacoustic signal data, extracting the resonance characteristic interference factors, wherein the resonance characteristic interference factors include temperature interference factors, humidity interference factors and electromagnetic interference factors, and analyzing the resonance amplitude and resonance frequency change curve of the photoacoustic cell; Step 3, analyzing the preprocessed photoacoustic signal data and combining the resonance interference factor, establishing a resonance characteristic analysis model, and obtaining the temperature interference index, humidity interference index and electromagnetic interference index; Step 4, based on the temperature interference index, humidity interference index, electromagnetic interference index and historical data, analyze the factors affecting the resonance characteristics of the photoacoustic pool, generate an abnormal factor analysis list, and obtain the abnormal evaluation coefficient of the photoacoustic pool, evaluate the health of the current state of the photoacoustic pool, and quantify the deviation degree of the performance of the photoacoustic pool; Step 5, input the real-time data into the resonance characteristic analysis model, analyze the change curve and influence law of the resonance characteristic, and obtain the analysis results. At the same time, combined with the value of the photoacoustic pool abnormality assessment coefficient, output the corresponding correction and compensation plan.

2. The method for measuring and classifying the resonance characteristics of a photoacoustic cell based on swept frequency modulation according to claim 1, characterized in that: In step 1, the photoacoustic signal data collection process is: Step 101, deploying a photoacoustic signal acquisition device and debugging and calibrating it, and setting the sampling rate, sampling depth and signal gain parameters according to the experimental requirements to collect photoacoustic signals in real time; Step 102, setting a time interval for the photoacoustic signal acquisition device, automatically recording the photoacoustic signal data, and dividing the collected photoacoustic signal data into historical data and real-time data; Step 103, establishing a data transmission channel, encrypting the collected photoacoustic signal data and transmitting it to the data management center, and monitoring the status of data transmission in real time; Step 104: The data management center stores the transmitted acoustic signal data, classifies, marks and indexes the photoacoustic signal data, and regularly backs up and restores the data.

3. The method for measuring and classifying the resonance characteristics of a photoacoustic cell based on frequency sweep modulation according to claim 2, characterized in that: In step 2, the advance process of the resonance characteristic interference factor is: Step 201, performing data cleaning, noise reduction, signal enhancement and standardization processing on the collected photoacoustic signal data to highlight the tissue structure information and reduce the influence of noise; Step 202, using spectrum analysis technology to identify the resonant frequency of the photoacoustic signal, and measuring the amplitude of the signal at the resonant frequency to obtain the resonant amplitude, which reflects the response intensity of the photoacoustic cell at the resonant frequency: Step 203, extracting features from the pre-processed historical data, performing feature extraction on the temperature condition, humidity condition and electromagnetic condition respectively, and obtaining a temperature interference factor, a humidity interference factor and an electromagnetic interference factor; Step 204, based on the extracted resonance amplitude and resonance frequency, respectively draw curves of the resonance amplitude and resonance frequency changing with the temperature interference factor, humidity interference factor and electromagnetic interference factor, analyze the trend of the corresponding curves and output the analysis results, and summarize the influence of the temperature interference factor, humidity interference factor and electromagnetic interference factor on the resonance amplitude and resonance frequency.

4. The method for measuring and classifying resonance characteristics of a photoacoustic cell based on frequency sweep modulation according to claim 3, characterized in that: In step 3, the process of obtaining the temperature interference index, humidity interference index and electromagnetic interference index is as follows: Step 301, using a spectrum analysis tool to perform spectrum analysis on the preprocessed photoacoustic signal data to obtain a spectrum graph of the photoacoustic signal data, identify the resonance frequency in the spectrum graph, and measure the resonance amplitude; Step 302, combining the analysis results of the resonance frequency, the resonance amplitude and the resonance interference factor, establishing a resonance characteristic analysis model, and integrating the associated data of the temperature interference factor, the humidity interference factor and the electromagnetic interference factor in the pre-processed historical data to form a unified data set; Step 303, dividing the integrated data set into a training set, a validation set and a test set, using the training set data to train the resonance characteristic analysis model, and using the validation set and the test set data to verify the trained resonance characteristic analysis model, and evaluating the performance of the resonance characteristic analysis model; Step 304 , calculating the temperature interference index, humidity interference index and electromagnetic interference index according to the constructed resonance characteristic analysis model, and analyzing the influence degree and trend of different interference indexes on the resonance characteristic.

5. The method for measuring and classifying resonance characteristics of a photoacoustic cell based on swept frequency modulation according to claim 4, characterized in that: The calculation formula of the temperature interference index is: Among them, TI is the temperature interference index, T is the current temperature, T std is the standard temperature, σ T is the temperature standard deviation, is the derivative of the resonant frequency with temperature, ΔT is the temperature change, Δf res is the change in resonant frequency; The calculation formula of the humidity interference index is: Among them, HI is the humidity interference index, H is the current humidity, and H op t is the optimal humidity, H range is the humidity variation range, f res (H) is the resonant frequency at the current humidity, f res，std is the resonant frequency at standard humidity; The calculation formula of the electromagnetic interference index is: Among them, EI is the electromagnetic interference index, E is the current electromagnetic field strength, and E thresh is the electromagnetic interference threshold, ΔA res is the change in resonance amplitude, A res，std is the resonance amplitude in the absence of electromagnetic interference.

6. The method for measuring and classifying resonance characteristics of a photoacoustic cell based on swept frequency modulation according to claim 5, characterized in that: In step 4, the process of obtaining the photoacoustic cell abnormality assessment coefficient is as follows: Step 401, traversing the pre-processed historical data, combining the temperature interference index, the humidity interference index, and the electromagnetic interference index, and analyzing the correlation between the photoacoustic cell resonance characteristics and the temperature interference index, the humidity interference index, and the electromagnetic interference index; Step 402, based on the temperature interference index, humidity interference index, electromagnetic interference index and historical data, classify and organize to establish an abnormal factor analysis list, list the factors that affect the resonance characteristics of the photoacoustic cell, and analyze each factor separately; Step 403, assigning different weights to the temperature interference index, the humidity interference index, and the electromagnetic interference index, performing weighted calculations on them, and obtaining a photoacoustic cell abnormality assessment coefficient; Step 404, matching the abnormal factor analysis list according to the pre-processed historical data, analyzing the degree of deviation of the photoacoustic cell performance, and determining different deviation levels; Step 405, matching the determined different deviation levels with the result of the photoacoustic pool abnormality assessment coefficient, setting corresponding deviation thresholds for different deviation levels, and judging the health of the current state of the photoacoustic pool.

7. The method for measuring and classifying resonance characteristics of a photoacoustic cell based on swept frequency modulation according to claim 6, characterized in that: The calculation formula of the photoacoustic cell abnormality assessment coefficient is: Among them, PA is the photoacoustic pool anomaly assessment coefficient, TI is the temperature interference index, HI is the humidity interference index, EI is the electromagnetic interference index, T std is the standard temperature of the temperature interference index, H std is the standard humidity of humidity interference index, E std It is the standard value of electromagnetic interference index.

8. The method for measuring and classifying resonance characteristics of a photoacoustic cell based on swept frequency modulation according to claim 7, characterized in that: The plurality of deviation levels correspond to the plurality of deviation thresholds, wherein the deviation thresholds include an upper threshold and a lower threshold; The plurality of deviation levels and the plurality of deviation thresholds satisfy the following relationship: Slight deviation from level 0 <PA≤P1; Moderate deviation level P1 <PA≤P2; Severe deviation level P2 <PA<1; Among them, PA is the photoacoustic pool abnormality assessment coefficient, P1 is the upper threshold corresponding to the slight deviation level and the lower threshold corresponding to the moderate deviation level, and P2 is the upper threshold corresponding to the moderate deviation level and the lower threshold corresponding to the severe deviation level.

9. The method for measuring and classifying resonance characteristics of a photoacoustic cell based on frequency sweep modulation according to claim 8, characterized in that: In step 5, the process of outputting the corresponding correction and compensation scheme is: Step 501, input the pre-processed real-time data into the resonance characteristic analysis model, calculate the temperature interference index, humidity interference index, and electromagnetic interference index respectively, and generate a change curve to analyze the stability of the resonance frequency and observe whether there is a frequency drift phenomenon. Frequency drift may mean a slight change in the internal structure of the photoacoustic cell or interference from the external environment; Step 502, combining the calculated temperature interference index, humidity interference index and electromagnetic interference index to obtain the photoacoustic pool abnormality assessment coefficient, and determining the deviation level of the current photoacoustic pool according to a preset deviation threshold, and evaluating the current state of the photoacoustic pool; Step 503, according to the deviation level of the current photoacoustic cell state, output the corresponding compensation plan and report, implement the correction and compensation plan, re-evaluate the performance of the photoacoustic cell according to the corrected real-time data, and adjust the correction plan to ensure long-term stable operation.

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