A methane concentration determination method, device, electronic equipment and storage medium

Abstract

The application discloses a kind of methane concentration determination method, device, electronic equipment and storage medium.The methane concentration determination method includes: obtaining the transmission signal containing interference noise, and determining absorbance signal according to transmission signal;Empirical mode decomposition processing is carried out to absorbance signal, and determine multiple groups of intrinsic mode function;According to the fuzzy entropy of each intrinsic mode function, pre-screening is carried out, and pre-eliminated intrinsic mode function is determined;The pre-eliminated intrinsic mode function is carried out Fourier transform processing, and the first energy proportion is calculated to determine the eliminated intrinsic mode function;Signal reconstruction processing is carried out to other intrinsic mode functions except the eliminated intrinsic mode function, and the reconstructed absorbance signal is determined;According to reconstructed absorbance signal, methane concentration is determined.The application realizes the accurate suppression of interference noise, and improves the accuracy of methane concentration determination.

Description

Technical Field

[0001] This invention relates to the field of methane concentration determination technology, and more particularly to a method, apparatus, electronic device, and storage medium for determining methane concentration. Background Technology

[0002] Tunable Diode Laser Absorption Spectroscopy (TDLAS) technology has become a commonly used method for methane monitoring due to its high accuracy, high sensitivity, and high real-time performance. However, in practical systems, multiple reflections caused by optical windows, lens surfaces, or mirrors can generate multiple laser beams. At the receiving end, the superposition of these multiple laser beams produces interference fringes, affecting the transmitted signal. These interference fringes reduce the detection accuracy and sensitivity of TDLAS, thus introducing deviations in the measurement results.

[0003] In existing technologies, Empirical Mode Decomposition (EMD) is used to decompose the aliased signal carrying interference fringes into several intrinsic mode functions (IMFs) and residuals in the time domain. The interference fringes are also decomposed into one or more IMFs. By comparing the correlation coefficients of each IMF with the original signal, the IMFs caused by the interference fringes are located and removed. The reconstructed signal after removal then suppresses the interference fringes. However, existing technologies cannot accurately suppress interference noise, leading to inaccurate determination of methane concentration. Summary of the Invention

[0004] This invention provides a method, apparatus, electronic device, and storage medium for determining methane concentration, thereby achieving precise suppression of interference noise and improving the accuracy of methane concentration determination.

[0005] According to one aspect of the present invention, a method for determining methane concentration is provided, the method comprising:

[0006] Acquire the transmission signal containing interference noise, and determine the absorbance signal based on the transmission signal;

[0007] Empirical mode decomposition (EMD) is performed on the absorbance signal to determine multiple sets of intrinsic mode functions.

[0008] Pre-screening is performed based on the fuzzy entropy of each intrinsic mode function to determine the intrinsic mode functions to be eliminated.

[0009] The pre-removed intrinsic mode functions are subjected to Fourier transform processing, and the first energy ratio of the pre-removed intrinsic mode functions in the interference frequency band after Fourier transform processing is calculated. The removed intrinsic mode functions are determined based on the first energy ratio.

[0010] Signal reconstruction processing is performed on all intrinsic mode functions except those that have been removed to determine the reconstructed absorbance signal;

[0011] The methane concentration was determined based on the reconstructed absorbance signal.

[0012] Furthermore, empirical mode decomposition is performed on the absorbance signal to determine multiple sets of intrinsic mode functions, including:

[0013] Obtain the characteristic frequencies of the interference noise;

[0014] The amplitude of white noise corresponding to different decomposition levels is determined based on the characteristic frequency of the interference noise.

[0015] Based on the white noise amplitude corresponding to different decomposition levels, empirical mode decomposition is performed on the absorbance signal to determine multiple sets of intrinsic mode functions.

[0016] Furthermore, the amplitude of white noise corresponding to different decomposition levels is determined based on the characteristic frequencies of the interference noise, including:

[0017] The amplitude of white noise corresponding to different decomposition levels is determined based on the frequency amplitude corresponding to the characteristic frequency.

[0018] Furthermore, based on the white noise amplitude corresponding to different decomposition levels, empirical mode decomposition is performed on the absorbance signal to determine multiple sets of intrinsic mode functions, including:

[0019] Based on the white noise amplitude corresponding to different decomposition levels, empirical mode decomposition is performed on the absorbance signal to determine each intrinsic mode function in turn.

[0020] After confirming each intrinsic mode function, the residual signal energy ratio is calculated to control the number of decomposition layers in the empirical mode decomposition process.

[0021] Furthermore, after confirming each intrinsic mode function, the residual signal energy ratio is calculated to control the number of decomposition layers in the empirical mode decomposition process, including:

[0022] The residual signal energy ratio is compared with a first threshold, and the result of the comparison determines whether to continue generating intrinsic mode functions.

[0023] Further, the pre-removed intrinsic mode functions are subjected to Fourier transform processing, and the first energy proportion of the pre-removed intrinsic mode functions in the interference frequency band after Fourier transform processing is calculated. The removed intrinsic mode functions are then determined based on the first energy proportion, including:

[0024] The first energy percentage is compared with the second threshold, and the intrinsic mode function to be removed is determined based on the comparison result.

[0025] Furthermore, the characteristic frequencies of the interference noise are obtained, as previously included:

[0026] Under methane-free conditions, a first transmission signal and a second transmission signal containing interference noise are acquired; wherein, the first transmission signal includes the transmission signal without the optical wedge, and the second transmission signal includes the transmission signal with the optical wedge added;

[0027] The characteristic frequency of the interference noise is determined based on the first and second transmitted signals.

[0028] According to another aspect of the present invention, a methane concentration determining apparatus is provided, the methane concentration determining apparatus comprising:

[0029] The absorbance signal determination module is used to acquire the transmission signal containing interference noise and determine the absorbance signal based on the transmission signal.

[0030] The intrinsic mode function determination module is used to perform empirical mode decomposition on the absorbance signal to determine multiple sets of intrinsic mode functions;

[0031] The pre-removal intrinsic mode function determination module is used to pre-screen based on the fuzzy entropy of each intrinsic mode function to determine the intrinsic mode functions to be removed.

[0032] The module for determining the pre-removed intrinsic mode functions is used to perform Fourier transform processing on the pre-removed intrinsic mode functions, calculate the first energy proportion of the pre-removed intrinsic mode functions in the interference frequency band after Fourier transform processing, and determine the removed intrinsic mode functions based on the first energy proportion.

[0033] The reconstructed transmission signal determination module is used to perform signal reconstruction processing on intrinsic mode functions other than those that have been eliminated, and to determine the reconstructed absorbance signal.

[0034] The methane concentration determination module is used to determine the methane concentration based on the reconstructed absorbance signal.

[0035] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0036] At least one processor; and

[0037] A memory communicatively connected to the at least one processor; wherein,

[0038] The memory stores a computer program that can be executed by the at least one processor, which enables the at least one processor to perform the methane concentration determination method according to any embodiment of the present invention.

[0039] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing a processor to execute and implement the methane concentration determination method according to any embodiment of the present invention.

[0040] The methane concentration determination method provided in this invention involves performing empirical mode decomposition (EMD) on the absorbance signal to determine multiple intrinsic mode functions (IMFs). Pre-screening is then performed based on the fuzzy entropy of each IMF to identify IMFs that may contain interference noise components. Subsequently, Fourier transform processing is applied to the pre-selected IMFs, and a first energy percentage is calculated to determine the IMFs to be removed, thus accurately eliminating IMFs containing interference noise components. Finally, signal reconstruction processing is performed on the remaining IMFs to determine the reconstructed absorbance signal. This method achieves precise suppression of interference noise, thereby improving the accuracy of the methane concentration determined based on the reconstructed absorbance signal.

[0041] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0042] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0043] Figure 1 This is a flowchart of a method for determining methane concentration according to an embodiment of the present invention.

[0044] Figure 2 This is a schematic diagram of a TDLAS laser methane detection system provided according to an embodiment of the present invention.

[0045] Figure 3 This is a schematic diagram of absorbance signal decomposition according to an embodiment of the present invention.

[0046] Figure 4 This is a curve showing the correspondence between the reconstructed signal wavelength and absorbance, provided by an embodiment of the present invention.

[0047] Figure 5 This is a curve showing the relationship between a first signal wavelength and absorbance, provided by an embodiment of the present invention.

[0048] Figure 6 This is a curve showing the correspondence between the frequency and amplitude of a first signal, provided by an embodiment of the present invention.

[0049] Figure 7 This is a curve showing the relationship between the wavelength of a second signal and absorbance, provided by an embodiment of the present invention.

[0050] Figure 8 This is a curve showing the correspondence between the frequency and amplitude of a second signal, provided according to an embodiment of the present invention.

[0051] Figure 9 This is a curve showing the relationship between the frequency and amplitude of a first signal corresponding to another interference noise sample provided by an embodiment of the present invention.

[0052] Figure 10 This is a curve showing the relationship between the frequency and amplitude of a first signal corresponding to another interference noise sample provided by an embodiment of the present invention.

[0053] Figure 11 This is a curve showing the relationship between the frequency and amplitude of a first signal corresponding to another interference noise sample provided by an embodiment of the present invention.

[0054] Figure 12 This is a curve showing the relationship between the frequency and amplitude of a first signal corresponding to another interference noise sample provided by an embodiment of the present invention.

[0055] Figure 13 This is a schematic diagram of a methane concentration determination device provided according to an embodiment of the present invention.

[0056] Figure 14 A schematic diagram of an electronic device that can be used to implement embodiments of the present invention is shown.

[0057] Figure 15 This is a schematic diagram of absorbance signal decomposition in the prior art.

[0058] Figure 16 It is a curve showing the relationship between the reconstructed signal wavelength and absorbance in existing technology. Detailed Implementation

[0059] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0060] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0061] This invention provides a method for determining methane concentration. Figure 1 This is a flowchart of a method for determining methane concentration according to an embodiment of the present invention, see reference. Figure 1 Methods for determining methane concentration include:

[0062] S110. Obtain the transmission signal containing interference noise, and determine the absorbance signal based on the transmission signal.

[0063] Specifically, Figure 2 This is a schematic diagram of a TDLAS laser methane detection system according to an embodiment of the present invention. (Refer to...) Figure 2 In the process of detecting methane concentration in a certain area, the controller 4 in the TDLAS laser methane detection system controls the laser 1 to emit a laser scanning signal through the drive circuit 3. This laser scanning signal can be a triangular wave signal. The laser scanning signal emitted by the laser 1 passes through the gas to be measured, i.e., methane gas, and is received by the photoelectric converter 2. The photoelectric converter 2 converts the received laser scanning signal into an electrical signal, i.e., a transmission signal containing interference noise, and transmits the converted transmission signal to the controller 4. The controller 4 determines the absorbance signal based on the transmission signal. The absorbance signal is a curve showing the relationship between absorbance and wavelength.

[0064] Based on the Lambert-Beer law, when a laser scanning signal passes through a methane-containing gas medium, light of a specific wavelength is absorbed by the methane, and the attenuation of the transmitted light intensity is related to the methane concentration. Absorbance primarily reflects the degree of absorption of the laser scanning signal and is determined by the logarithm of the ratio of incident light intensity to transmitted light intensity. For example, the absorbance signal can be determined as follows: First, a TDLAS laser methane detection system can be used to acquire a transmitted signal containing both the target absorption wavelength (characteristic absorption peak of methane) and non-target absorption wavelengths. Then, the transmitted signal at the non-target absorption wavelength is selected; that is, with the target absorption wavelength as the center, the transmitted signals at non-target absorption wavelengths are selected on both sides of the target absorption wavelength, and a baseline is fitted to obtain the equivalent incident light intensity. Finally, the absorbance is calculated using the absorbance formula B1 = -ln(I / I0), where I is the transmitted light intensity and I0 is the incident light intensity.

[0065] S120. Perform empirical mode decomposition on the absorbance signal to determine multiple sets of intrinsic mode functions.

[0066] Specifically, the characteristic frequencies of the interference noise can be obtained first. Based on these frequencies, the amplitudes of white noise corresponding to different decomposition levels can be determined. Then, based on these white noise amplitudes, empirical mode decomposition (EMD) is performed on the absorbance signal to determine multiple sets of intrinsic mode functions. The EMD process can be Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN).

[0067] S130. Perform pre-screening based on the fuzzy entropy of each intrinsic mode function to determine the intrinsic mode functions to be eliminated.

[0068] Specifically, the fuzzy entropy value FE_k of each intrinsic mode function is calculated, where k is the decomposition level of the intrinsic mode function. For example, the specific calculation process of the fuzzy entropy value FE_k is described as follows: Let the k-th intrinsic mode function IMFk be a time series with N sampling points. Let the embedding dimension be m, the fuzziness index be n, and the similarity tolerance be r (usually 0.1-0.25 times the standard deviation of the time series). The embedding dimension m is set according to the actual situation. Then, the calculation steps of the fuzzy entropy value FE_k are as follows:

[0069] (1) Reconstruct the m-dimensional vector :

[0070] =[x(i),x(i+1),…,x(i+m−1)],i=1,2,…,N−m+1;

[0071] (2) The reconstructed m-dimensional vector is subjected to mean-removal processing to form a mean-removed m-dimensional vector. (Eliminating the effects of baseline drift):

[0072] ;

[0073] (3) Calculate the Chebyshev distance between any two mean-removed m-dimensional vectors. :

[0074] ;

[0075] (4) Calculate fuzzy similarity based on exponential membership function :

[0076] ;

[0077] (5) Calculate the global average similarity in m dimensions. :

[0078] ;

[0079] (6) Increase the embedding dimension to m+1 and repeat steps (1) to (5) above to obtain the global average similarity in m+1 dimensions. .

[0080] (7) Calculate the final fuzzy entropy value FE_k of the k-th intrinsic mode function:

[0081] .

[0082] Intrinsic mode functions (IMFs) whose fuzzy entropy value FE_k falls outside the filtering range are selected and identified as IMFs to be pre-removed. The filtering range is... , The mean of all fuzzy entropy values. denoted as the standard deviation of all fuzzy entropy values. Since fuzzy entropy can effectively characterize the nonlinearity and complexity of a signal, and intrinsic mode functions containing interference noise usually have high regularity, their fuzzy entropy values ​​generally deviate from normal signal components, thus enabling accurate screening of pre-removed intrinsic mode functions.

[0083] S140. Perform Fourier transform processing on the pre-removed intrinsic mode functions, and calculate the first energy ratio of the pre-removed intrinsic mode functions in the interference frequency band after Fourier transform processing. Determine the removed intrinsic mode functions based on the first energy ratio.

[0084] Specifically, after performing a Fourier transform on the pre-removed intrinsic mode functions, the values ​​in the interference band are calculated according to the following formula. The first energy percentage within:

[0085] ;

[0086] Where f is the frequency, For characteristic frequencies, For the interference bandwidth, Sampling frequency, The Fourier transform of the intrinsic mode functions is then performed. The first energy percentage is then compared with a preset second threshold, and the intrinsic mode functions to be removed are determined based on the comparison result.

[0087] S150. Perform signal reconstruction processing on the intrinsic mode functions other than those removed to determine the reconstructed absorbance signal.

[0088] Specifically, Figure 3 This is a schematic diagram of absorbance signal decomposition according to an embodiment of the present invention. Figure 4 This is a curve showing the correspondence between the reconstructed signal wavelength and absorbance according to an embodiment of the present invention, such as... Figure 3 and Figure 4 As shown, the decomposed IMF2 and IMF3 carry interference noise. Based on the method described above, the intrinsic mode functions (IMFs) to be removed from IMF2 and IMF3 are determined. Then, the other intrinsic mode functions (IMFs) are superimposed, i.e., signal reconstruction is performed to determine the reconstructed absorbance signal. For example, the screening method proposed in this application can effectively screen out IMFs containing interference noise. The reconstructed signal after removing the noise IMF components is as follows: Figure 4 The red signal in the middle indicates that IMF1 is the first intrinsic mode function formed after the first empirical mode decomposition (EMD), IMF2 is the second intrinsic mode function formed after the second EMD, IMF3 is the third intrinsic mode function formed after the third EMD, IMF4 is the fourth intrinsic mode function formed after the fourth EMD, and IMF5 is the fifth intrinsic mode function formed after the fifth EMD.

[0089] S160. Determine the methane concentration based on the reconstructed absorbance signal.

[0090] Specifically, the extended form of the Lambert-Beer Law is: B1 = ε × L × c, where B1 is the absorbance, ε is the molar absorptivity of methane at the target wavelength, L is the optical path length between the laser and the gas, and c is the methane concentration. When the molar absorptivity ε of methane at the target wavelength and the optical path length L between the light and the gas are determined, absorbance and concentration are linearly positively correlated, and the concentration can be inverted through this relationship. Since the molar absorptivity ε of methane at the target wavelength and the optical path length L between the light and the gas are known quantities, the absorbance peak value Amax in the reconstructed absorbance signal can be substituted into the formula B1 = ε × L × c to determine the methane concentration.

[0091] The methane concentration determination method provided in this invention involves performing empirical mode decomposition (EMD) on the absorbance signal to determine multiple intrinsic mode functions (IMFs). Pre-screening is then performed based on the fuzzy entropy of each IMF to identify IMFs that may contain interference noise components. Subsequently, Fourier transform processing is applied to the pre-selected IMFs, and a first energy percentage is calculated to determine the IMFs to be removed, thus accurately eliminating IMFs containing interference noise components. Finally, signal reconstruction processing is performed on the remaining IMFs to determine the reconstructed absorbance signal. This method achieves precise suppression of interference noise, thereby improving the accuracy of the methane concentration determined based on the reconstructed absorbance signal.

[0092] Furthermore, empirical mode decomposition is performed on the absorbance signal to determine multiple sets of intrinsic mode functions, including:

[0093] Obtain the characteristic frequencies of the interference noise;

[0094] The amplitude of white noise corresponding to different decomposition levels is determined based on the characteristic frequency of the interference noise.

[0095] Based on the white noise amplitude corresponding to different decomposition levels, empirical mode decomposition is performed on the absorbance signal to determine multiple sets of intrinsic mode functions.

[0096] The number of decomposition layers can be understood as the number of times the absorbance signal undergoes empirical mode decomposition. For example, such as... Figure 3 As shown, a decomposition level of 1 corresponds to the first empirical mode decomposition process, which forms the first intrinsic mode function (IMF1) after the first empirical mode decomposition process; a decomposition level of 2 corresponds to the second empirical mode decomposition process, which forms the second intrinsic mode function (IMF2) after the second empirical mode decomposition process.

[0097] Specifically, empirical mode decomposition (EMD) can be performed on the absorbance signal based on the white noise amplitude corresponding to different decomposition levels. Each intrinsic mode function (IMF) is determined sequentially, and after confirming an IMF, the residual signal energy ratio corresponding to that IMF is calculated. The calculated residual signal energy ratio is then used to determine whether further EMF decomposition is needed. The characteristic frequency of the interference noise is a preset characteristic frequency stored in the TDLAS laser methane detection system. For example, Figure 15 This is a schematic diagram of absorbance signal decomposition in the prior art. Figure 16 This is a curve showing the relationship between the reconstructed signal wavelength and absorbance in existing technology, for reference. Figures 3-4 as well as Figures 15-16 One sample with significant interference noise can be randomly selected, and a gas chamber filled with 1000 ppm methane gas can be used. After the methane concentration in the gas chamber stabilizes, multiple frames of transmission signals containing interference noise are acquired, and the baseline and absorbance are calculated from the transmission signals (e.g., ...). Figure 4 and Figure 16 (As shown by the black signal in the middle). For example, as... Figure 15 As shown, the traditional CEEMDAN decomposition of IMF2, IMF3, and IMF4 all carry a certain degree of interference noise and exhibits mode aliasing effects. However, as... Figure 3 As shown, the optimized CEEMDAN decomposition in this application results in IMF2 and IMF3 containing interference noise, which can be more concentrated. Comparing the reconstructed results, it can be seen that the reconstructed signal obtained by the traditional CEEMDAN algorithm still has a significant amount of residual interference fringe energy, manifested as low-frequency ripples. In contrast, the reconstructed signal obtained by the optimized CEEMDAN algorithm in this application is smoother and the peak value is slightly improved.

[0098] Furthermore, the amplitude of white noise corresponding to different decomposition levels is determined based on the characteristic frequencies of the interference noise, including:

[0099] The amplitude of white noise corresponding to different decomposition levels is determined based on the frequency amplitude corresponding to the characteristic frequency.

[0100] Specifically, the white noise amplitude corresponding to different decomposition levels can be determined using the following formula:

[0101] ;

[0102] ;

[0103] in, The initial noise amplitude corresponding to the white noise signal; For the absorbance signal at the characteristic frequency Frequency amplitude at that location; This represents the maximum frequency amplitude of the absorbance signal. It is the frequency weighting factor in the spectrum-guided noise injection strategy; The Nyquist frequency; It is the frequency index; The current decomposition order is... This is an estimate of the total order. This represents the white noise amplitude corresponding to the current decomposition order k.

[0104] Here, the decomposition order is equivalent to the number of decomposition levels. Different decomposition levels correspond to different... Different values ​​determine the white noise amplitude corresponding to different decomposition levels, i.e., determine different... The value corresponds to the white noise amplitude. Initial noise amplitude. The range is 0.1-0.3. Frequency weighting factor. Used to quantify the influence of characteristic frequency locations on the intensity of white noise injection, and Adaptive control can be achieved: when high-frequency interference occurs, the frequency weighting factor can be increased. To increase the noise amplitude; when low-frequency interference occurs, the frequency weighting factor can be reduced. To reduce noise amplitude. Frequency index This can be used as a tuning index to control frequency sensitivity. The estimated total order. This can be understood as the expected maximum number of decomposition layers. The white noise calculated using the above formula allows for the injection of strong noise in the early stages of decomposition to separate high-frequency interference, while reducing the injected noise in the later stages to protect low-frequency absorbance signals, thus avoiding the noise residue problem of traditional CEEMDAN.

[0105] Furthermore, based on the white noise amplitude corresponding to different decomposition levels, empirical mode decomposition is performed on the absorbance signal to determine multiple sets of intrinsic mode functions, including:

[0106] Based on the white noise amplitude corresponding to different decomposition levels, empirical mode decomposition is performed on the absorbance signal to determine each intrinsic mode function in turn.

[0107] After confirming each intrinsic mode function, the residual signal energy ratio is calculated to control the number of decomposition layers in the empirical mode decomposition process.

[0108] Specifically, after performing empirical mode decomposition on the absorbance signal to determine the intrinsic mode function, the residual signal energy ratio is determined according to the following formula:

[0109] ;

[0110] in, The residual signal energy ratio; This is the k-th order residual signal; The absorbance signal is used. The calculated residual signal energy ratio is compared with a first threshold, and the generation of intrinsic mode functions (IMFs) is determined based on the comparison result. If the residual signal energy ratio is less than the first threshold, the generation of IMFs is stopped; if the residual signal energy ratio is greater than or equal to the first threshold, the generation of IMFs continues. For example, the first threshold can be 0.05. Then, each IMF after empirical mode decomposition is confirmed according to the above method. For example, the decomposition process of the absorbance signal is described as follows: Figure 3 As shown, after the first empirical mode decomposition (EMD) process, IMF1 (first intrinsic mode function) and the first-order residual signal are formed. Then, the residual signal energy ratio is calculated based on the first-order residual signal. If the residual signal energy ratio is greater than or equal to a first threshold, intrinsic mode functions are generated again, i.e., the first-order residual signal undergoes a second EMD process, forming IMF2 (second intrinsic mode function) and the second-order residual signal. Then, the residual signal energy ratio is calculated based on IMF2 and the second-order residual signal. If the residual signal energy ratio is greater than or equal to the first threshold, intrinsic mode functions are generated again, i.e., the second-order residual signal undergoes a third EMD process, until the calculated residual signal energy ratio is less than the first threshold, i.e., a residual signal is formed as shown in the diagram. Figure 3 The diagram shows IMF1-IMF5 and the residual signal (the 5th-order residual signal formed by the 5th empirical mode decomposition process). The residual signal energy ratio... Used to measure how much energy remains in the residual. Residual signal energy ratio. It is the ratio of the L2 norm (energy) of the current residual signal to the L2 norm (energy) of the original signal. Wherein, The original signal is the absorbance signal containing interference noise acquired by the TDLAS laser methane detection system. Figure 3 and Figure 15 As can be seen, if the absorbance signal is processed by empirical mode decomposition according to the white noise amplitude corresponding to different decomposition layers, and multiple intrinsic mode functions (IMFs) are determined, and the residual signal energy ratio is calculated after confirming each intrinsic mode function, the number of decomposition layers after empirical mode decomposition is controlled, thereby reducing the time-domain decomposition of the CEEMDAN optimized in this application and achieving better decomposition.

[0111] Furthermore, after confirming each intrinsic mode function, the residual signal energy ratio is calculated to control the number of decomposition layers in the empirical mode decomposition process, including:

[0112] The residual signal energy ratio is compared with a first threshold, and the result of the comparison determines whether to continue generating intrinsic mode functions.

[0113] Specifically, if the residual signal energy ratio is less than the first threshold, it indicates that the absorbance signal has been completely decomposed. Compared with the existing technology that performs decomposition with a fixed number of layers, this method can decompose the absorbance signal according to the actual situation, improving the decomposition efficiency and avoiding signal distortion caused by over-decomposition of the absorbance signal.

[0114] Furthermore, the pre-removed intrinsic mode functions are subjected to Fourier transform processing, and the first energy proportion of the pre-removed intrinsic mode functions in the interference frequency band after Fourier transform processing is calculated. The removed intrinsic mode functions are then determined based on the first energy proportion, including:

[0115] The first energy percentage is compared with the second threshold, and the intrinsic mode function to be removed is determined based on the comparison result.

[0116] Specifically, when the first energy percentage is greater than the second threshold, it is confirmed that the intrinsic mode function contains the dominant component of interference noise, and thus it is identified as the intrinsic mode function to be removed, thereby avoiding the misjudgment problem of the traditional correlation coefficient method under low signal-to-noise ratio.

[0117] Furthermore, the characteristic frequencies of the interference noise are obtained, as previously included:

[0118] Under methane-free conditions, a first transmission signal and a second transmission signal containing interference noise are acquired; wherein, the first transmission signal includes the transmission signal without the optical wedge, and the second transmission signal includes the transmission signal with the optical wedge added;

[0119] The characteristic frequency of the interference noise is determined based on the first and second transmitted signals.

[0120] Specifically, such as Figure 2 As shown, under methane-free conditions, initially, no optical wedge is added between laser 1 and photoelectric converter 2. The photoelectric converter 2 detects the first transmission signal and transmits it to controller 4 to generate a first absorbance signal. Then, an optical wedge is added between laser 1 and photoelectric converter 2, and the photoelectric converter 2 detects the second transmission signal and transmits it to controller 4 to generate a second absorbance signal. For example, the optical wedge can be a wedge-shaped filter. The wedge structure causes a gradient change in the filter's film thickness, forming a continuous transmission band. When light passes through at different angles or positions, the center wavelength of the transmission dynamically shifts. The non-parallel surface disrupts the multiple reflection paths of the coherent light, effectively reducing the generation of interference fringes.

[0121] Figure 5 This is a curve showing the correspondence between a first signal wavelength and absorbance according to an embodiment of the present invention. Figure 6 This is a curve showing the correspondence between the frequency and amplitude of a first signal provided by an embodiment of the present invention, such as... Figure 5 and Figure 6 As shown, the first absorbance signal can be determined first based on the acquired first transmission signal, i.e., the relationship curve between the wavelength of the first signal and the absorbance. For example, it can be obtained from... Figure 5 It can be seen that, due to interference noise, the absorbance trend is close to sinusoidal in the absence of methane gas. Then, based on the determined relationship curve between the wavelength and absorbance of the first signal, the relationship curve between the frequency and amplitude of the first signal is determined. For example, the characteristic frequency of the interference noise in the first transmitted signal can be preliminarily determined. 2000Hz, bandwidth The frequency is 500Hz. The first signal frequency is the characteristic frequency corresponding to the first transmitted signal.

[0122] Figure 7 This is a curve showing the correspondence between the wavelength of a second signal and absorbance according to an embodiment of the present invention. Figure 8 This is a curve showing the correspondence between the frequency and amplitude of a second signal provided by an embodiment of the present invention, such as... Figure 7 and Figure 8 As shown, the second absorbance signal can be determined based on the acquired second transmission signal, i.e., the relationship curve between the second signal wavelength and absorbance. For example, such as... Figure 7 It can be seen that after adding the optical wedge, Figure 5 The sinusoidal interference fringes became less noticeable. Then, based on the established curve showing the relationship between the wavelength and absorbance of the second signal, the curve showing the relationship between the frequency and amplitude of the second signal was determined to verify the effect of adding the optical wedge. Figure 6 Whether the interference noise shown is filtered, for example, in comparison. Figure 6 and Figure 8 The signal transmitted through the optical wedge significantly suppresses signal components around 2000Hz, but introduces some other noise at higher frequencies. The second signal frequency is the characteristic frequency corresponding to the second transmitted signal.

[0123] Simultaneously, the characteristic frequencies of the interference noise can also be determined based on other interference noise samples. Verify the amplitude and its corresponding value, for example, Figures 9-12 This is a curve showing the relationship between the frequency and amplitude of a first signal corresponding to another interference noise sample, as provided in an embodiment of the present invention. Figures 9-12 As shown, the characteristic frequencies of different interference noise samples are almost the same, but the amplitudes corresponding to the characteristic frequencies of different interference noise samples fluctuate greatly. The amplitude of S1 at the characteristic frequency is approximately The amplitude of S2 at the characteristic frequency is approximately The amplitude of S3 at the characteristic frequency is less than The amplitude of S7 at the characteristic frequency is approximately .

[0124] This invention provides a methane detection interference suppression device. Figure 13 This is a schematic diagram of a methane concentration determination device according to an embodiment of the present invention. (Refer to...) Figure 13 The methane concentration determination device 200 includes:

[0125] The absorbance signal determination module 210 is used to acquire the transmission signal containing interference noise and determine the absorbance signal based on the transmission signal.

[0126] The intrinsic mode function determination module 220 is used to perform empirical mode decomposition on the absorbance signal to determine multiple sets of intrinsic mode functions;

[0127] The pre-removal intrinsic mode function determination module 230 is used to pre-screen based on the fuzzy entropy of each intrinsic mode function to determine the pre-removal intrinsic mode functions;

[0128] The module 240 for determining the pre-removed intrinsic mode function is used to perform Fourier transform processing on the pre-removed intrinsic mode function, calculate the first energy ratio of the pre-removed intrinsic mode function in the interference frequency band after Fourier transform processing, and determine the removed intrinsic mode function based on the first energy ratio.

[0129] The reconstructed transmission signal determination module 250 is used to perform signal reconstruction processing on intrinsic mode functions other than those that have been eliminated, and to determine the reconstructed absorbance signal.

[0130] The methane concentration determination module 260 is used to determine the methane concentration based on the reconstructed absorbance signal.

[0131] Furthermore, the intrinsic mode function determination module 220 includes:

[0132] The characteristic frequency acquisition unit is used to acquire the characteristic frequencies of the interference noise;

[0133] The white noise amplitude determination unit is used to determine the white noise amplitude corresponding to different decomposition levels based on the characteristic frequency of the interference noise.

[0134] The intrinsic mode function determination unit is used to perform empirical mode decomposition on the absorbance signal based on the white noise amplitude corresponding to different decomposition levels, and determine multiple sets of intrinsic mode functions.

[0135] Furthermore, the white noise amplitude determination unit is specifically used for:

[0136] The amplitude of white noise corresponding to different decomposition levels is determined based on the frequency amplitude corresponding to the characteristic frequency.

[0137] Furthermore, the intrinsic mode function determination unit includes:

[0138] The intrinsic mode functions sequentially determine the sub-units, which are used to perform empirical mode decomposition on the absorbance signal according to the white noise amplitude corresponding to different decomposition layers, and sequentially determine each intrinsic mode function;

[0139] The decomposition layer control subunit is used to calculate the residual signal energy ratio after confirming each intrinsic mode function, so as to control the number of decomposition layers in the empirical mode decomposition process.

[0140] Furthermore, the decomposition layer control subunit is specifically used for:

[0141] The residual signal energy ratio is compared with a first threshold, and the result of the comparison determines whether to continue generating intrinsic mode functions.

[0142] Furthermore, the intrinsic mode function determination module 240 is specifically used for:

[0143] The first energy percentage is compared with the second threshold, and the intrinsic mode function to be removed is determined based on the comparison result.

[0144] Furthermore, the methane concentration determining device 200 includes:

[0145] A methane-free projection signal determination module is used to acquire a first transmission signal and a second transmission signal containing interference noise under methane-free gas conditions before acquiring the characteristic frequency of interference noise; wherein, the first transmission signal includes the transmission signal without the addition of the optical wedge, and the second transmission signal includes the transmission signal with the addition of the optical wedge.

[0146] The characteristic frequency determination module is used to determine the characteristic frequency of the interference noise based on the first transmitted signal and the second transmitted signal.

[0147] The methane concentration determination device provided in the embodiments of the present invention can execute the methane concentration determination method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of executing the method.

[0148] Figure 14 A schematic diagram of an electronic device that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0149] like Figure 14As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded into the RAM 13 from storage unit 18. The RAM 13 can also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0150] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0151] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as the methane concentration determination method.

[0152] In some embodiments, the methane concentration determination method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the methane concentration determination method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the methane concentration determination method by any other suitable means (e.g., by means of firmware).

[0153] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0154] Computer programs for implementing the methane concentration determination method of the present invention can be written in any combination of one or more programming languages. These computer programs can be provided to the processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The computer programs can be executed entirely on the machine, partially on the machine, as a standalone software package partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0155] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0156] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0157] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0158] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0159] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0160] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for determining methane concentration, characterized in that, include: Acquire a transmission signal containing interference noise, and determine an absorbance signal based on the transmission signal; The absorbance signal is subjected to empirical mode decomposition to determine multiple sets of intrinsic mode functions; Pre-screening is performed based on the fuzzy entropy of each intrinsic mode function to determine the intrinsic mode functions to be eliminated; The pre-removed intrinsic mode functions are subjected to Fourier transform processing, and the first energy ratio of the pre-removed intrinsic mode functions in the interference frequency band after Fourier transform processing is calculated. The removed intrinsic mode functions are determined based on the first energy ratio. Signal reconstruction processing is performed on the intrinsic mode functions other than the eliminated intrinsic mode functions to determine the reconstructed absorbance signal; The methane concentration is determined based on the reconstructed absorbance signal.

2. The method for determining methane concentration according to claim 1, characterized in that, The absorbance signal is subjected to empirical mode decomposition (EMD) to determine multiple sets of intrinsic mode functions, including: Obtain the characteristic frequencies of the interference noise; The amplitude of white noise corresponding to different decomposition levels is determined based on the characteristic frequency of the interference noise. Based on the white noise amplitude corresponding to different decomposition levels, the absorbance signal is subjected to empirical mode decomposition to determine multiple sets of intrinsic mode functions.

3. The method for determining methane concentration according to claim 2, characterized in that, Determining the white noise amplitude corresponding to different decomposition levels based on the characteristic frequencies of the interference noise includes: The white noise amplitude corresponding to different decomposition levels is determined based on the frequency amplitude corresponding to the characteristic frequency.

4. The method for determining methane concentration according to claim 2, characterized in that, Based on the white noise amplitude corresponding to different decomposition levels, the absorbance signal is subjected to empirical mode decomposition (EMD) to determine multiple sets of intrinsic mode functions, including: Based on the white noise amplitude corresponding to different decomposition levels, the absorbance signal is subjected to empirical mode decomposition processing to determine each intrinsic mode function in sequence; After confirming each intrinsic mode function, the residual signal energy ratio is calculated to control the number of decomposition layers in the empirical mode decomposition process.

5. The method for determining methane concentration according to claim 4, characterized in that, After confirming each intrinsic mode function, the residual signal energy ratio is calculated to control the number of decomposition layers in the empirical mode decomposition process, including: The residual signal energy ratio is compared with a first threshold, and the intrinsic mode function is determined based on the comparison result.

6. The method for determining methane concentration according to claim 1, characterized in that, Performing a Fourier transform on the pre-removed intrinsic mode functions, calculating the first energy proportion of the pre-removed intrinsic mode functions within the interference frequency band after the Fourier transform, and determining the removed intrinsic mode functions based on the first energy proportion, includes: The first energy percentage is compared with the second threshold, and the elimination intrinsic mode function is determined based on the comparison result.

7. The method for determining methane concentration according to claim 2, characterized in that, To obtain the characteristic frequencies of the interference noise, the preceding steps include: Under methane-free conditions, a first transmission signal and a second transmission signal containing interference noise are acquired; wherein, the first transmission signal includes the transmission signal without the optical wedge, and the second transmission signal includes the transmission signal with the optical wedge added; The characteristic frequency of the interference noise is determined based on the first transmitted signal and the second transmitted signal.

8. A methane concentration determination device, characterized in that, include: An absorbance signal determination module is used to acquire a transmission signal containing interference noise and determine an absorbance signal based on the transmission signal. The intrinsic mode function determination module is used to perform empirical mode decomposition on the absorbance signal to determine multiple sets of intrinsic mode functions; The pre-removal intrinsic mode function determination module is used to pre-screen based on the fuzzy entropy of each intrinsic mode function to determine the pre-removal intrinsic mode functions; The module for determining the pre-removed intrinsic mode function is used to perform Fourier transform processing on the pre-removed intrinsic mode function, calculate the first energy ratio of the pre-removed intrinsic mode function in the interference frequency band after Fourier transform processing, and determine the removed intrinsic mode function based on the first energy ratio. The reconstructed transmission signal determination module is used to perform signal reconstruction processing on the intrinsic mode functions other than the eliminated intrinsic mode functions to determine the reconstructed absorbance signal; A methane concentration determination module is used to determine the methane concentration based on the reconstructed absorbance signal.

9. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor to enable the at least one processor to perform the methane concentration determination method according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the method for determining methane concentration as described in any one of claims 1-7.

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