Chromatographic peak automatic identification method and device based on dynamic threshold value and electronic equipment

Abstract

The invention provides a chromatographic peak automatic identification method and device based on a dynamic threshold value and electronic equipment, and relates to the technical field of analytical chemistry and data processing. The chromatographic peak automatic identification method based on the dynamic threshold value comprises the following steps: acquiring a combustion pulse signal collected by a pulse flame photometric detector; determining a dynamic threshold value of the combustion pulse signal based on statistical data of different local signals in the combustion pulse signal; determining a sudden change signal point of the combustion pulse signal according to difference data between the dynamic threshold value and a differential signal of the combustion pulse signal; and performing characteristic analysis on each signal segment where the abrupt change signal points after de-weighting are located to obtain chromatographic peak characteristic data of the combustion pulse signal.

Description

Technical Field

[0001] The present invention relates to the field of analytical chemistry and data processing technology, and in particular to a method, device and electronic equipment for automatic identification of chromatographic peaks based on dynamic thresholds. Background Art

[0002] The pulsed flame photometric detector (PFPD) is a highly sensitive detector widely used in gas chromatography for detecting compounds containing sulfur, phosphorus, and other specific elements. The PFPD uses the spectral emission signal of a pulsed flame for element-selective detection, with the detection signal output in the form of pulses. Chromatographic peak characteristics (such as peak height, peak area, and half-width) are core data for qualitative and quantitative analysis of compounds and are directly related to the accuracy and reliability of test results. Therefore, efficient and accurate identification and processing of pulsed signals is essential. Summary of the Invention

[0003] In view of this, the present invention provides a method, device and electronic equipment for automatic identification of chromatographic peaks based on dynamic thresholds.

[0004] According to the first aspect of the present invention, a method for automatic identification of chromatographic peaks based on dynamic thresholds is provided, comprising: obtaining a combustion pulse signal collected by a pulse flame photometric detector; determining the dynamic threshold of the combustion pulse signal based on statistical data of different local signals in the combustion pulse signal; determining the mutation signal point of the combustion pulse signal based on difference data between the dynamic threshold and the differential signal of the combustion pulse signal; and performing feature analysis on each signal segment where the mutation signal point is located after deduplication to obtain chromatographic peak feature data of the combustion pulse signal.

[0005] According to an embodiment of the present invention, based on the statistical data of different local signals in the combustion pulse signal, determining the dynamic threshold of the combustion pulse signal includes: calculating the local mean and local standard deviation of the combustion pulse signal under a preset sliding window; and determining the dynamic threshold based on the local mean and local standard deviation in each window.

[0006] According to an embodiment of the present invention, determining the dynamic threshold according to the local mean and local standard deviation in each window includes: adding the local mean to the product of the local standard deviation and a preset sensitivity coefficient to obtain the dynamic threshold of the combustion pulse signal.

[0007] According to an embodiment of the present invention, determining the mutation signal point in the combustion pulse signal based on the difference data between the dynamic threshold and the differential signal of the combustion pulse signal includes: calculating the first-order differential data between two adjacent sampling signals in the combustion pulse signal as the differential signal; comparing the difference between each first-order differential data and the dynamic threshold, and marking the signal point corresponding to the first-order differential data being greater than the dynamic threshold as a mutation signal point.

[0008] According to an embodiment of the present invention, before performing feature analysis on each signal segment where the deduplicated mutation signal point is located, the automatic chromatographic peak identification method also includes: extracting mutation signals in the mutation signal point whose sampling time interval is greater than the preset minimum time interval to obtain the deduplicated mutation signal point.

[0009] According to an embodiment of the present invention, a feature analysis is performed on each signal segment where the mutation signal point after deduplication is located to obtain the chromatographic peak characteristic data of the combustion pulse signal, including: detecting the first light peak, the second light peak and the light valley between the first light peak and the second light peak appearing in each signal segment, and determining the amplitude and time corresponding to the first light peak, the second light peak and the light valley; at the half-peak height between the first light peak and the second light peak, searching for the nearest intersection point from the second light peak to the left and right, respectively, to determine the left and right boundaries of the half peak, and calculating the time difference between the left and right boundaries to obtain the half-peak width; calculating the area of the signal curve between the moment of the light valley and the cutoff moment of the signal segment to obtain the peak area; extracting the amplitude, half-peak width and peak area of the second light peak to obtain the chromatographic peak characteristic data.

[0010] According to an embodiment of the present invention, performing feature analysis on each signal segment where the mutation signal point is located after deduplication includes: according to the index of the mutation signal point, intercepting each signal segment where the mutation signal point is located after deduplication, and storing them as independent mutation signal units for subsequent feature analysis.

[0011] According to an embodiment of the present invention, obtaining a combustion pulse signal collected by a pulse flame photometric detector includes: obtaining a combustion light signal collected by a pulse flame photometric detector; converting the combustion light signal into an electrical signal using a photomultiplier tube, amplifying the electrical signal output by the photomultiplier tube, and converting the amplified electrical signal into a digital signal using an analog-to-digital converter; receiving the digital signal using a data acquisition card and transmitting it to a computer or storage device to obtain a combustion pulse signal.

[0012] The second aspect of the present invention provides a chromatographic peak automatic identification device based on a dynamic threshold, comprising: a signal acquisition module for acquiring a combustion pulse signal collected by a pulse flame photometer; a first determination module for determining the dynamic threshold of the combustion pulse signal based on statistical data of different local signals in the combustion pulse signal; a second determination module for determining the mutation signal point of the combustion pulse signal based on the difference data between the dynamic threshold and the differential signal of the combustion pulse signal; a feature analysis module for performing feature analysis on each signal segment where the mutation signal point is located after deduplication to obtain chromatographic peak feature data of the combustion pulse signal.

[0013] The third aspect of the present invention provides an electronic device comprising: one or more processors; a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors execute the method in any one of the above embodiments.

[0014] According to the dynamic threshold-based automatic chromatographic peak identification method, device and electronic equipment of the embodiments of the present invention, a dynamic threshold algorithm is adopted, which effectively combines local statistical data to accurately set the signal threshold. It can efficiently and accurately identify the mutation characteristics of PFPD pulse signals in a dynamically changing environment, and significantly improve the recognition accuracy and robustness of chromatographic peaks. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The above contents and other objects, features and advantages of the present invention will become more apparent through the following description of the embodiments of the present invention with reference to the accompanying drawings, in which:

[0016] Figure 1 The flowchart of the method for automatic identification of chromatographic peaks based on dynamic threshold according to one embodiment of the present invention is schematically shown;

[0017] Figure 2 Schematically showing a combustion pulse signal collected according to an embodiment of the present invention;

[0018] Figure 3 Schematically shows the Figure 2 The mutation signal point detected by the combustion pulse signal;

[0019] Figure 4 Schematically shows the Figure 3 The pulse signal fragment extracted from the mutation signal point;

[0020] Figure 5 Schematically shows a flow chart of a method for automatic chromatographic peak recognition based on dynamic threshold according to another embodiment of the present invention;

[0021] Figure 6The following schematically shows a structural block diagram of a chromatographic peak automatic identification device based on a dynamic threshold according to an embodiment of the present invention;

[0022] Figure 7 The block diagram of an electronic device suitable for implementing a method for automatic chromatographic peak identification based on a dynamic threshold according to an embodiment of the present invention is schematically shown. DETAILED DESCRIPTION

[0023] Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the present invention. In the following detailed description, for ease of explanation, many specific details are set forth to provide a comprehensive understanding of embodiments of the present invention. However, it is apparent that one or more embodiments may also be implemented without these specific details. In addition, in the following description, descriptions of known structures and technologies are omitted to avoid unnecessary confusion of the concept of the present invention.

[0024] The terms used herein are only for describing specific embodiments and are not intended to limit the present invention. The terms "comprise," "include," etc. used herein indicate the presence of features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0025] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those skilled in the art unless otherwise defined. It should be noted that the terms used herein should be interpreted as having a meaning consistent with the context of this specification and should not be interpreted in an idealized or overly rigid manner.

[0026] When expressions such as "at least one of A, B, and C, etc." are used, they should generally be interpreted in accordance with the meaning commonly understood by those skilled in the art (for example, "a system having at least one of A, B, and C" should include but is not limited to a system having A alone, B alone, C alone, A and B, A and C, B and C, and / or A, B, C, etc.).

[0027] In order to realize the chromatographic peak recognition of combustion pulse signals, technicians in this field have conducted various studies and explorations. For example, in 2005, Vivo-Truyols G et al. proposed an automated peak recognition method that can efficiently and accurately identify chromatographic peaks in complex overlapping situations. However, in the process of chromatographic recognition, thresholds need to be manually specified to distinguish between signals and noise, which is a great challenge for operators. In order to solve the limitations of manual threshold setting in traditional methods, Lin Lianfeng et al. proposed an automatic chromatogram analysis method based on image recognition in 2021, which realized the automated analysis of chromatograms. However, this scheme relies on high-quality template libraries and large-scale sample training, and still has certain limitations when processing dynamically changing pulse signals.

[0028] In view of the obvious deficiencies in the efficiency and adaptability of chromatographic peak recognition in the prior art, the present invention provides a method for automatic chromatographic peak recognition based on a dynamic threshold, including: obtaining a combustion pulse signal collected by a pulse flame photometric detector; determining the dynamic threshold of the combustion pulse signal based on the statistical data of different local signals in the combustion pulse signal; determining the mutation signal point of the combustion pulse signal according to the difference data between the dynamic threshold and the differential signal of the combustion pulse signal; performing feature analysis on each signal segment where the mutation signal point is located after deduplication to obtain the chromatographic peak characteristic data of the combustion pulse signal. The method for automatic chromatographic peak recognition based on a dynamic threshold provided in this embodiment adopts a dynamic threshold algorithm, effectively combines local statistical data, and accurately sets the signal threshold. It can efficiently and accurately identify the mutation characteristics of the PFPD pulse signal in a dynamically changing environment, and significantly improve the recognition accuracy and robustness of the chromatographic peak. The following is combined with Figures 1 to 5 This method is further explained.

[0029] Figure 1 The flowchart of the method for automatic identification of chromatographic peaks based on dynamic threshold according to one embodiment of the present invention is schematically shown.

[0030] like Figure 1 As shown, the method for automatic chromatographic peak identification based on dynamic threshold value of this embodiment includes operations S110 to S140.

[0031] In operation S110 , a combustion pulse signal collected by a pulse flame photometric detector is acquired.

[0032] In some embodiments, a combustion light signal collected by a pulsed flame photometric detector can be first acquired. A photomultiplier tube (PMT) is then used to convert the combustion light signal into an electrical signal. The electrical signal output by the PMT is amplified and then converted into a digital signal using an analog-to-digital converter (ADC). A data acquisition card (DAQ) then receives the digital signal and transmits it to a computer or storage device to obtain a combustion pulse signal. The digital signal is stored in a computer or storage device, facilitating subsequent data analysis, modeling, and long-term storage. By utilizing components such as PMTs, signal amplifiers, and ADCs, the entire process of acquiring combustion pulse signals can be automated, reducing human intervention and improving detection efficiency and accuracy, making it suitable for industrial or laboratory environments.

[0033] The sampling frequency (which can be recorded as fs) can be reasonably set according to actual needs. For example, the sampling frequency fs can be set to 10000, and the collected combustion pulse signal can be as follows Figure 2 shown. Figure 2 The horizontal axis represents the sampling point, and the vertical axis represents the amplitude of the pulse signal. Then, operation S120 can be performed.

[0034] In operation S120 , a dynamic threshold of the combustion pulse signal is determined based on statistical data of different local signals in the combustion pulse signal.

[0035] In some embodiments, operation S120 may include calculating the local mean and local standard deviation of the combustion pulse signal within a preset sliding window; and determining a dynamic threshold based on the local mean and local standard deviation within each window. The size of the sliding window can be appropriately set based on practical needs and is not specifically limited in this invention. The mean and standard deviation of the local signal can be calculated using the following formula:

[0036]

[0037]

[0038] Among them, μ local represents the local mean, σ local Represents the local standard deviation, N represents the number of signal sampling points of the local signal where the window is located, x i Represents the amplitude of the i-th sampling point in the local signal.

[0039] This embodiment uses a sliding window and dynamic threshold algorithm, effectively combining the local mean and standard deviation to accurately set the signal threshold, thereby efficiently and accurately identifying the mutation characteristics of PFPD pulse signals in a dynamically changing environment, significantly improving the recognition accuracy and robustness of chromatographic peaks.

[0040] In some embodiments, the dynamic threshold of the combustion pulse signal can be obtained by adding the local mean to the product of the local standard deviation and the preset sensitivity coefficient. The dynamic threshold can be calculated according to the following formula:

[0041]

[0042] Among them, T dynamic represents the dynamic threshold, and k represents the sensitivity coefficient. k can be set according to actual needs, for example, it can be set to 3, but the present invention is not limited to this. By adjusting the preset sensitivity coefficient, it can be applied to the detection of combustion signals of different intensities. The dynamic threshold can be automatically adjusted according to the local characteristics of the signal (such as the mean and standard deviation), adapting to changes in the signal and avoiding misjudgments or missed judgments that may be caused by fixed thresholds. By calculating the dynamic threshold through the mean and standard deviation of the local signal and the sensitivity coefficient, it can effectively improve the accuracy, anti-interference ability and adaptability of combustion pulse signal detection, and is suitable for signal processing requirements in complex environments. Operation S130 can then be performed.

[0043] In operation S130 , a sudden change signal point of the combustion pulse signal is determined based on difference data between the dynamic threshold and the differential signal of the combustion pulse signal.

[0044] Combustion signals are often non-stationary. Differential signals can highlight local variations in the signal, avoiding subtle changes that might be overlooked when directly analyzing the original signal, and improving sensitivity to sudden changes. Combustion signals combined with dynamic thresholding can better adapt to dynamic signal changes and enhance detection robustness.

[0045] In some embodiments, operation S130 may include: calculating first-order differential data between two adjacent sample signals in the combustion pulse signal as a differential signal; comparing the difference between each first-order differential data and a dynamic threshold, and marking the signal point corresponding to the first-order differential data being greater than the dynamic threshold as a sudden change signal point. The differential signal may be calculated according to the following formula:

[0046]

[0047] in, Represents the amplitude x of two adjacent signals i+1 、x i The absolute value of the difference between the two is the first-order differential data. With dynamic threshold T dynamic By comparison, the points exceeding the dynamic threshold are marked as mutation points. In this way, the mutation points in the combustion pulse signal can be identified quickly and accurately, and have high noise resistance and adaptability.

[0048] Before feature analysis, the mutation points obtained in operation S130 can be deduplicated to avoid duplicate markings. In some embodiments, mutation signal points whose sampling intervals exceed a preset minimum interval can be extracted to obtain deduplicated mutation signal points. The minimum interval min_interval (in sampling points) can be adjusted based on data characteristics and is not specifically limited in this invention.

[0049] As an example, corresponding to the above example where the sampling frequency fs is set to 10000, the minimum time interval min_interval can be set to 2000. Figure 2 The combustion pulse signal collected is detected Figure 2 The mutation point in Figure 3 As shown, the location of the mutation signal point is Figure 3 Marked with a circle.

[0050] For the detected mutation point, a certain range of signal fragments before and after it can be intercepted and stored as independent signal units for subsequent analysis. Figure 3 The detected mutation points and the extracted pulse signal fragments can be Figure 4 As shown. Figure 4 As shown in Figure 2, the extracted pulse signal has two light peaks. The first light peak ( Figure 4 The middle position 1) is attributed to the light spike generated when the pulse flame background passes through the light collection window, and the second light peak ( Figure 4 Position 3) is produced by a chemical reaction of sulfur (phosphorus) compounds in the combustion gas. These sulfur (phosphorus) compounds are oxidized in the pulsed flame and produce a characteristic light signal. The amplitude of the second light peak is greater than that of the first light peak. Then, proceed to step S140.

[0051] In operation S140 , feature analysis is performed on each signal segment where the mutation signal point after deduplication is located to obtain chromatographic peak feature data of the combustion pulse signal.

[0052] Chromatographic peak characteristics may include, for example, peak height, peak width, peak area, etc. Figure 4 As shown, the first light peak (position 1), second light peak (position 3), and light valley (position 2) between the first and second light peaks in each signal segment can be detected to determine the amplitude and time corresponding to each of the first and second light peaks. The second light peak, i.e., the highest point of the characteristic light signal generated by sulfur- or phosphorus-containing compounds, can be defined as the peak height, and its corresponding signal value and position are recorded as the core characteristics of the chromatographic peak:

[0053]

[0054] Among them, Hpeak is the peak height, signal is the extracted pulse signal segment, max() is the maximum amplitude in the pulse signal segment, t first_peak is the moment when the first light peak is detected, t end is the upper limit of the time of the extracted pulse signal. Figure 4 As shown, t first_peak is the time corresponding to position 1, t end is 25ms.

[0055] Then, at the half-peak height between the first and second light peaks, search for the nearest intersection point from the second light peak to the left and right, determine the left and right boundaries of the half-peak, calculate the time difference between the left and right boundaries, and obtain the half-peak width. The half-peak height can be calculated according to the following formula:

[0056]

[0057] Among them, H half-max is the half-peak height, H valley is the amplitude of the valley between the two light peaks, that is, the position where the second light peak starts ( Figure 4 Position 2 in the ).

[0058] At the half-peak height, search for the nearest intersection point from the peak point to the left and right to determine the left and right boundaries of the peak. The half-peak width can be calculated according to the following formula:

[0059]

[0060] Among them, W peak is the half-peak width, t left is the left boundary time, t right Right boundary time.

[0061] Next, calculate the area of the signal curve between the time of the light valley and the cutoff time of the signal segment to obtain the peak area. For example, you can use numerical integration (trapezoidal integration method) to calculate the peak area:

[0062]

[0063] Among them, A peak is the peak area of the characteristic light signal generated by sulfur or phosphorus compounds, t valley is the starting time of the second light peak, which is also the time corresponding to the light valley.

[0064] Finally, extract the amplitude H of the second light peak peak , half-peak width W peak , peak area A peak , that is, the chromatographic peak characteristic data is obtained.

[0065] Figure 5 The flowchart of the method for automatic identification of chromatographic peaks based on dynamic threshold according to another embodiment of the present invention is schematically shown.

[0066] like Figure 5 As shown, the method for automatic chromatographic peak recognition based on dynamic threshold provided in this embodiment may include the following steps:

[0067] The first step is to load the combustion pulse signal data and parameters: the parameters can be initialized according to the actual situation, such as sampling frequency, sliding window size, sensitivity coefficient and minimum time interval.

[0068] The second step is to calculate the dynamic threshold: a sliding window can be used to calculate the local mean and standard deviation at each position of the signal, and the dynamic threshold is calculated based on these statistical values.

[0069] The third step is to calculate the differential signal: the mutation in the signal can be detected by calculating the absolute value of the differential signal.

[0070] The fourth step is to detect the mutation point: the differential signal can be compared with the dynamic threshold to identify the mutation point that exceeds the dynamic threshold.

[0071] Step 5: Deduplication: Repeatedly detected mutation points can be removed based on the minimum time interval.

[0072] Step 6: Extract the mutation signal segment: The mutation signal segment can be extracted according to the index of the mutation point and stored in an array.

[0073] Step 7: Feature analysis: For each mutation signal segment, its peak value, half-peak width and peak area can be calculated to obtain the chromatographic peak feature data.

[0074] It should be noted that the order and number of steps 1 to 7 described above are merely examples and do not constitute further limitations of the present invention. Without changing the overall technical solution, those skilled in the art may combine or adjust the steps according to actual circumstances. For example, the dynamic threshold calculation in step 2 and the differential signal calculation in step 3 may be performed simultaneously. For another example, the differential signal in step 3 may be calculated first, followed by the dynamic threshold in step 2, and then the sudden change in the signal may be detected based on the difference between the differential signal and the dynamic threshold.

[0075] Based on the above-mentioned multiple embodiments, the present invention proposes a dynamic threshold algorithm based on a sliding window, which calculates the dynamic threshold of the signal by the local mean and standard deviation, can adapt to the dynamic changes of complex background signals, and effectively identify mutation points. The present invention proposes a method for extracting signal fragments from detected mutation points, and designs a calculation algorithm for peak height, peak width and peak area based on dynamic thresholds to ensure the accuracy and robustness of feature extraction. By analyzing the light peak characteristics of the PFPD signal, a dual-peak structure is used to correspond to the pulse background and the target compound reaction signal respectively, and the dynamic threshold method is combined to achieve high-precision pulse signal recognition. This technical solution is suitable for the analysis of sulfur-containing and phosphorus-containing compounds in PFPD signals, and can be widely used in data processing scenarios of chemical analysis instruments.

[0076] Compared with the method using fixed thresholds in the prior art, the present invention realizes adaptive analysis of local characteristics of the signal through a dynamic threshold algorithm. It can flexibly adapt to different signal characteristics based on the calculation of the local mean and standard deviation in the sliding window without manually setting the threshold. The present invention does not need to rely on high-quality template libraries or large-scale sample training, and directly analyzes in dynamic signals. It is applicable to a variety of chemical environments and experimental conditions. The present invention is particularly optimized for the signal characteristics of the pulse flame photometer, distinguishing between background signals and characteristic signals of sulfur-containing and phosphorus-containing compounds, ensuring the accuracy of multi-element analysis. The effects presented by the technology can be, for example, Figure 2 、 Figure 3 and Figure 4 As shown, no further details are given here.

[0077] Based on the above-mentioned chromatographic peak automatic identification method based on dynamic threshold, the present invention also provides a chromatographic peak automatic identification device based on dynamic threshold. Figure 6 The device is described in detail.

[0078] Figure 6 The structure block diagram of the apparatus for automatic identification of chromatographic peaks based on dynamic threshold according to an embodiment of the present invention is schematically shown.

[0079] like Figure 6 As shown, the chromatographic peak automatic identification device 600 based on dynamic threshold value of this embodiment includes a signal acquisition module 610 , a first determination module 620 , a second determination module 630 and a feature analysis module 640 .

[0080] The signal acquisition module 610 is used to acquire the combustion pulse signal collected by the pulse flame photometric detector. In one embodiment, the signal acquisition module 610 can be used to perform the operation S110 described above, which will not be described in detail here.

[0081] The first determination module 620 is configured to determine a dynamic threshold of the combustion pulse signal based on statistical data of different local signals in the combustion pulse signal. In one embodiment, the first determination module 620 may be configured to perform the operation S120 described above, which will not be described in detail herein.

[0082] The second determination module 630 is configured to determine a sudden change point of the combustion pulse signal based on the difference data between the dynamic threshold and the differential signal of the combustion pulse signal. In one embodiment, the second determination module 630 may be configured to perform the operation S130 described above, which will not be further described here.

[0083] The feature analysis module 640 is used to perform feature analysis on each signal segment where the mutation signal point is located after deduplication to obtain chromatographic peak feature data of the combustion pulse signal. In one embodiment, the feature analysis module 640 can be used to perform the operation S140 described above, which will not be repeated here.

[0084] According to an embodiment of the present invention, signal acquisition module 610 can also be used to acquire a combustion light signal collected by a pulsed flame photometer; convert the combustion light signal into an electrical signal using a photomultiplier tube; amplify the electrical signal output by the photomultiplier tube; and convert the amplified electrical signal into a digital signal using an analog-to-digital converter; receive the digital signal using a data acquisition card and transmit it to a computer or storage device to obtain a combustion pulse signal. For details, please refer to the previous section and will not be repeated here.

[0085] According to an embodiment of the present invention, the first determination module 620 is further configured to calculate the local mean and local standard deviation of the combustion pulse signal within a preset sliding window; and determine a dynamic threshold based on the local mean and local standard deviation within each window. For details, please refer to the previous section and will not be repeated here.

[0086] According to an embodiment of the present invention, the second determination module 630 is further configured to calculate first-order difference data between two adjacent sampled signals in the combustion pulse signal as a differential signal; compare the difference between each first-order difference data and a dynamic threshold; and mark the signal point corresponding to the first-order difference data being greater than the dynamic threshold as a sudden change signal point. For details, please refer to the previous section and will not be repeated here.

[0087] According to an embodiment of the present invention, the dynamic threshold-based automatic chromatographic peak identification device 600 may further include a deduplication module (not shown). The deduplication module is configured to extract mutation signal points whose sampling intervals are greater than a preset minimum interval, thereby obtaining deduplicated mutation signal points. For details, please refer to the previous section and will not be further elaborated here.

[0088] According to an embodiment of the present invention, the feature analysis module 640 can also be used to detect the first light peak, the second light peak, and the light valley between the first and second light peaks in each signal segment, determine the amplitude and time corresponding to each of the first light peak, the second light peak, and the light valley; at the half-peak height between the first and second light peaks, search for the nearest intersection point from the second light peak to the left and right, determine the left and right boundaries of the half-peak, calculate the time difference between the left and right boundaries, and obtain the half-peak width; calculate the area of the signal curve from the time of the light valley to the cutoff time of the signal segment to obtain the peak area; and extract the amplitude, half-peak width, and peak area of the second light peak to obtain chromatographic peak characteristic data. For details of the relevant content, please refer to the previous text and will not be repeated here.

[0089] According to an embodiment of the present invention, feature analysis module 640 may also be configured to extract each signal segment containing a mutation signal point after deduplication based on its index, and store the segment as a separate mutation signal unit for subsequent feature analysis. For details, please refer to the previous section and will not be repeated here.

[0090] According to embodiments of the present invention, any multiple modules among the signal acquisition module 610, the first determination module 620, the second determination module 630, and the feature analysis module 640 may be combined into a single module, or any one of these modules may be split into multiple modules. Alternatively, at least part of the functionality of one or more of these modules may be combined with at least part of the functionality of other modules and implemented in a single module. According to embodiments of the present invention, at least one of the signal acquisition module 610, the first determination module 620, the second determination module 630, and the feature analysis module 640 may be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on a chip, a system on a substrate, a system on a package, an application-specific integrated circuit (ASIC), or may be implemented in hardware or firmware through any other reasonable means of circuit integration or packaging, or implemented in any one of software, hardware, and firmware, or any suitable combination of these. Alternatively, at least one of the signal acquisition module 610 , the first determination module 620 , the second determination module 630 and the feature analysis module 640 may be at least partially implemented as a computer program module, which may perform corresponding functions when executed.

[0091] Figure 7 The block diagram of an electronic device suitable for implementing a method for automatic chromatographic peak identification based on a dynamic threshold according to an embodiment of the present invention is schematically shown.

[0092] like Figure 7As shown, an electronic device 700 according to an embodiment of the present invention includes a processor 701, which can perform various appropriate actions and processes based on programs stored in a read-only memory (ROM) 702 or programs loaded from a storage unit 708 into a random access memory (RAM) 703. The processor 701 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or related chipsets and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 701 may also include onboard memory for caching purposes. The processor 701 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present invention.

[0093] The RAM 703 stores various programs and data required for the operation of the electronic device 700. The processor 701, ROM 702, and RAM 703 are connected to each other via a bus 704. The processor 701 executes the programs in the ROM 702 and / or RAM 703 to perform the various operations of the method flow according to the embodiment of the present invention. It should be noted that the programs may also be stored in one or more memories other than the ROM 702 and RAM 703. The processor 701 may also execute the programs stored in one or more memories to perform the various operations of the method flow according to the embodiment of the present invention.

[0094] According to an embodiment of the present invention, electronic device 700 may further include an input / output (I / O) interface 705, which is also connected to bus 704. Electronic device 700 may also include one or more of the following components connected to I / O interface 705: an input section 706 including a keyboard, mouse, etc.; an output section 707 including devices such as a cathode ray tube (CRT), liquid crystal display (LCD), and speakers; a storage section 708 including a hard disk; and a communication section 709 including a network interface card such as a LAN card or modem. Communication section 709 performs communication processing via a network such as the Internet. A drive 710 is also connected to I / O interface 705 as needed. Removable media 711, such as a magnetic disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed in drive 710 as needed, so that computer programs read from the removable media can be installed into storage section 708 as needed.

[0095] The present invention also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments, or may exist independently and not incorporated into the device / apparatus / system. The computer-readable storage medium carries one or more programs, which, when executed, implement the method according to the embodiments of the present invention.

[0096] According to an embodiment of the present invention, a computer-readable storage medium may be a non-volatile computer-readable storage medium, and may include, for example, but not limited to: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. For example, according to an embodiment of the present invention, a computer-readable storage medium may include the ROM 702 and / or RAM 703 described above, and / or one or more memories other than ROM 702 and RAM 703.

[0097] Embodiments of the present invention also include a computer program product comprising a computer program containing program code for executing the method shown in the flowchart. When the computer program product is executed in a computer system, the program code causes the computer system to implement the method for automatic chromatographic peak identification based on dynamic thresholds provided in embodiments of the present invention.

[0098] The computer program executes the above functions defined in the system / device of the embodiment of the present invention when the computer program is executed by the processor 701. According to the embodiment of the present invention, the system, device, module, unit, etc. described above can be implemented by a computer program module.

[0099] In one embodiment, the computer program may be stored on a tangible storage medium such as an optical storage device or a magnetic storage device. In another embodiment, the computer program may be transmitted and distributed in the form of a signal on a network medium, downloaded and installed via the communication portion 709, and / or installed from a removable medium 711. The program code contained in the computer program may be transmitted using any appropriate network medium, including but not limited to wireless, wired, or any suitable combination thereof.

[0100] In such an embodiment, the computer program can be downloaded and installed from a network via the communication section 709 and / or installed from the removable medium 711. When the computer program is executed by the processor 701, the above-described functions defined in the system of the embodiment of the present invention are performed. According to the embodiment of the present invention, the systems, devices, means, modules, units, etc. described above can be implemented by computer program modules.

[0101] According to an embodiment of the present invention, the program code for executing the computer program provided by the embodiment of the present invention can be written in any combination of one or more programming languages. Specifically, these computer programs can be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages include, but are not limited to, languages such as Java, C++, Python, "C" or similar programming languages. The program code can be executed entirely on the user computing device, partially on the user device, partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (for example, using an Internet service provider to connect via the Internet).

[0102] The flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present invention. In this regard, each box in the flowchart or block diagram can represent a module, program segment, or a part of code, and the above-mentioned module, program segment, or a part of code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0103] It will be understood by those skilled in the art that the features described in the various embodiments of the present invention may be combined and / or coupled in various ways, even if such combinations or couplings are not explicitly described in the present invention. In particular, the features described in the various embodiments of the present invention may be combined and / or coupled in various ways without departing from the spirit and teachings of the present invention. All such combinations and / or couplings fall within the scope of the present invention.

[0104] The above describes embodiments of the present invention. However, these embodiments are for illustrative purposes only and are not intended to limit the scope of the present invention. Although each embodiment has been described separately above, this does not mean that the measures in each embodiment cannot be advantageously used in combination. Without departing from the scope of the present invention, those skilled in the art may make various substitutions and modifications, which should all fall within the scope of the present invention.

Claims

1. A method for automatic identification of chromatographic peaks based on dynamic threshold, characterized in that: include: Obtaining a combustion pulse signal collected by a pulse flame photometric detector; determining a dynamic threshold of the combustion pulse signal based on statistical data of different local signals in the combustion pulse signal; determining a mutation signal point of the combustion pulse signal according to difference data between the dynamic threshold and a differential signal of the combustion pulse signal; A characteristic analysis is performed on each signal segment where the mutation signal point is located after deduplication to obtain chromatographic peak characteristic data of the combustion pulse signal.

2. The method for automatic identification of chromatographic peaks according to claim 1, characterized in that: Determining the dynamic threshold of the combustion pulse signal based on statistical data of different local signals in the combustion pulse signal includes: Calculating the local mean and local standard deviation of the combustion pulse signal within a preset sliding window; The dynamic threshold is determined according to the local mean and the local standard deviation in each window.

3. The method for automatic identification of chromatographic peaks according to claim 2, characterized in that: Determining the dynamic threshold according to the local mean and the local standard deviation in each window includes: The local mean is added to the product of the local standard deviation and a preset sensitivity coefficient to obtain the dynamic threshold of the combustion pulse signal.

4. The method for automatic identification of chromatographic peaks according to claim 1, characterized in that: Determining the mutation signal point in the combustion pulse signal according to the difference data between the dynamic threshold and the differential signal of the combustion pulse signal includes: Calculating first-order difference data between two adjacent sampling signals in the combustion pulse signal as the differential signal; The difference between each of the first-order differential data and the dynamic threshold is compared, and the signal point corresponding to the first-order differential data being greater than the dynamic threshold is marked as the mutation signal point.

5. The method for automatic identification of chromatographic peaks according to claim 1, characterized in that: Before performing feature analysis on each signal segment where the mutation signal point is located after deduplication, the automatic chromatographic peak recognition method further includes: Extract the mutation signal points whose sampling time interval is greater than the preset minimum time interval from the mutation signal points to obtain the mutation signal points after duplication removal.

6. The method for automatic identification of chromatographic peaks according to claim 1 or 5, characterized in that: The characteristic analysis of each signal segment where the mutation signal point is located after deduplication to obtain the chromatographic peak characteristic data of the combustion pulse signal includes: detecting a first light peak, a second light peak, and a light valley between the first light peak and the second light peak in each of the signal segments, and determining amplitudes and times corresponding to the first light peak, the second light peak, and the light valley; At the half-peak height between the first light peak and the second light peak, searching for the nearest intersection point from the second light peak to the left and right, respectively, determining the left and right boundaries of the half-peak, calculating the time difference between the left and right boundaries, and obtaining the half-peak width; Calculating the area of the signal curve between the moment of the light valley and the cutoff moment of the signal segment to obtain the peak area; The amplitude, the half-peak width, and the peak area of the second light peak are extracted to obtain the chromatographic peak characteristic data.

7. The method for automatic identification of chromatographic peaks according to claim 1, characterized in that: The feature analysis of each signal segment where the mutation signal point is located after deduplication includes: According to the index of the mutation signal point, each signal segment where the mutation signal point is located after deduplication is intercepted and stored as a separate mutation signal unit for subsequent feature analysis.

8. The method for automatic identification of chromatographic peaks according to claim 1, characterized in that: The obtaining of the combustion pulse signal collected by the pulse flame photometric detector comprises: Obtaining a combustion light signal collected by the pulse flame photometry detector; A photomultiplier tube is used to convert the combustion light signal into an electrical signal, the electrical signal output by the photomultiplier tube is amplified, and an analog-to-digital converter is used to convert the amplified electrical signal into a digital signal; A data acquisition card is used to receive the digital signal and transmit it to a computer or storage device to obtain the combustion pulse signal.

9. A chromatographic peak automatic identification device based on dynamic threshold, characterized in that: include: A signal acquisition module is used to acquire the combustion pulse signal collected by the pulse flame photometric detector; a first determining module, configured to determine a dynamic threshold of the combustion pulse signal based on statistical data of different local signals in the combustion pulse signal; a second determining module, configured to determine a mutation signal point of the combustion pulse signal according to difference data between the dynamic threshold and a differential signal of the combustion pulse signal; The feature analysis module is used to perform feature analysis on each signal segment where the mutation signal point is located after deduplication, so as to obtain the chromatographic peak feature data of the combustion pulse signal.

10. An electronic device, characterized in that: include: one or more processors; a storage device for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors are enabled to execute the method according to any one of claims 1 to 8.

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