Automatic peak identification method, device, and electronic equipment based on dynamic threshold

Abstract

This invention provides a method, apparatus, and electronic device for automatic chromatographic peak identification based on dynamic thresholds, relating to the fields of analytical chemistry and data processing technology. The method for automatic chromatographic peak identification based on dynamic thresholds includes: acquiring a combustion pulse signal collected by a pulsed flame photometric detector; determining a dynamic threshold for the combustion pulse signal based on statistical data of different local signals in the combustion pulse signal; identifying abrupt change signal points in the combustion pulse signal based on the difference data between the dynamic threshold and the differential signal of the combustion pulse signal; and performing feature analysis on each signal segment containing the deduplicated abrupt change signal points to obtain chromatographic peak feature data of the combustion pulse signal.

Description

Technical Field

[0001] This invention relates to the fields of analytical chemistry and data processing technology, and specifically to a method, apparatus, and electronic device for automatic identification of chromatographic peaks based on dynamic thresholds. Background Technology

[0002] A pulsed flame photometric detector (PFPD) is a highly sensitive detector widely used in gas chromatography for the detection of sulfur- and phosphorus-containing compounds, as well as other specific elements. The PFPD performs element-selective detection through the spectral emission signal of a pulsed flame, outputting the detection signal in pulse form. Chromatographic peak characteristics (such as peak height, peak area, and half-maximum width at half-maximum) are core data for qualitative and quantitative analysis of compounds, directly affecting the accuracy and reliability of the detection results. Therefore, efficient and accurate identification and processing of the pulse signal is essential. Summary of the Invention

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

[0004] According to a first aspect of the present invention, an automatic peak identification method based on dynamic threshold is provided, comprising: acquiring a combustion pulse signal collected by a pulsed 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 abrupt change signal points of the combustion pulse signal based on the difference data between the dynamic threshold and the differential signal of the combustion pulse signal; and performing feature analysis on each signal segment containing the deduplicated abrupt change signal points to obtain chromatographic peak feature data of the combustion pulse signal.

[0005] According to an embodiment of the present invention, 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 under a preset sliding window; and determining the dynamic threshold according to the local mean and local standard deviation in each window.

[0006] According to an embodiment of the present invention, determining the dynamic threshold based on 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 abrupt change signal points 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 difference data between two adjacent sampled signals in the combustion pulse signal as the differential signal; comparing the difference between each first-order difference data and the dynamic threshold, and marking the signal points corresponding to the first-order difference data being greater than the dynamic threshold as abrupt change signal points.

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

[0009] According to an embodiment of the present invention, feature analysis is performed on each signal segment containing the deduplicated mutation signal point to obtain chromatographic peak feature data of the combustion pulse signal, including: detecting the first peak, the second peak, and the valley between the first and second peaks in each signal segment, and determining the amplitude and time corresponding to the first peak, the second peak, and the valley; at the half-peak height between the first and second peaks, searching for the nearest intersection points to the left and right from the second peak to determine the left and right boundaries of the half-peak, 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 time of the valley and the cutoff time of the signal segment to obtain the peak area; and extracting the amplitude, half-peak width, and peak area of ​​the second peak to obtain chromatographic peak feature data.

[0010] According to an embodiment of the present invention, feature analysis of each signal segment containing the deduplicated mutation signal point includes: according to the index of the mutation signal point, each signal segment containing the deduplicated mutation signal point is extracted and stored as an independent mutation signal unit for subsequent feature analysis.

[0011] According to an embodiment of the present invention, acquiring the combustion pulse signal collected by the pulse flame photometric detector includes: acquiring the combustion light signal collected by the 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; and receiving the digital signal using a data acquisition card and transmitting it to a computer or storage device to obtain the combustion pulse signal.

[0012] A second aspect of the present invention provides an automatic chromatographic peak identification device based on a dynamic threshold, comprising: a signal acquisition module for acquiring a combustion pulse signal collected by a pulsed flame photometric detector; a first determination module for determining a 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 abrupt change signal points of the combustion pulse signal based on difference data between the dynamic threshold and the differential signal of the combustion pulse signal; and a feature analysis module for performing feature analysis on each signal segment containing the deduplicated abrupt change signal points to obtain chromatographic peak feature data of the combustion pulse signal.

[0013] A third aspect of the present invention provides an electronic device comprising: one or more processors; and 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 perform the method in any of the above embodiments.

[0014] The automatic chromatographic peak identification method, apparatus, and electronic device based on dynamic threshold according to embodiments of the present invention employ a dynamic threshold algorithm, effectively combining local statistical data to accurately set signal thresholds, enabling efficient and accurate identification of abrupt changes in PFPD pulse signals under dynamically changing environments, and significantly improving the identification accuracy and robustness of chromatographic peaks. Attached Figure Description

[0015] The above-described features, other objects, and advantages of the present invention will become clearer from the following description of embodiments of the invention with reference to the accompanying drawings, in which:

[0016] Figure 1 A flowchart illustrating an automatic chromatographic peak identification method based on a dynamic threshold according to an embodiment of the present invention is shown.

[0017] Figure 2 The illustration schematically shows a combustion pulse signal acquired according to an embodiment of the present invention;

[0018] Figure 3 Schematic illustration of the Figure 2 Abrupt signal points detected by the combustion pulse signal;

[0019] Figure 4 Schematic illustration of from Figure 3 Pulse signal fragments extracted from mutation signal points;

[0020] Figure 5 A flowchart illustrating an automatic chromatographic peak identification method based on dynamic thresholds according to another embodiment of the present invention is shown.

[0021] Figure 6The schematic diagram illustrates the structure of an automatic chromatographic peak identification device based on a dynamic threshold according to an embodiment of the present invention;

[0022] Figure 7 A block diagram of an electronic device suitable for implementing an automatic chromatographic peak identification method based on dynamic thresholds according to an embodiment of the present invention is shown schematically. Detailed Implementation

[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 invention. In the following detailed description, numerous specific details are set forth to provide a thorough understanding of the embodiments of the invention for ease of explanation. However, it will be apparent that one or more embodiments may be practiced without these specific details. Furthermore, descriptions of well-known structures and techniques are omitted in the following description to avoid unnecessarily obscuring the concept of the invention.

[0024] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the invention. The terms “comprising,” “including,” etc., as 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 are to be interpreted in a manner consistent with the context of this specification, and not in an idealized or overly rigid way.

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

[0027] To achieve chromatographic peak identification of combustion pulse signals, various studies and explorations have been conducted by those skilled in the art. For example, in 2005, Vivo-Truyols G et al. proposed an automated peak identification method that could efficiently and accurately identify chromatographic peaks under complex overlapping conditions. However, the chromatographic identification process requires manually specifying thresholds to distinguish between signal and noise, which is a significant challenge for operators. To address 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, achieving automated chromatogram analysis. However, this approach relies on high-quality template libraries and large-scale sample training, and still has certain limitations when processing dynamically changing pulse signals.

[0028] Given the significant shortcomings of existing technologies in terms of efficiency and adaptability for chromatographic peak identification, this invention provides an automatic chromatographic peak identification method based on dynamic thresholds. The method includes: acquiring a combustion pulse signal collected by a pulsed flame photometric detector (PFPD); determining a dynamic threshold for the combustion pulse signal based on statistical data of different local signals within the combustion pulse signal; identifying abrupt change points in the combustion pulse signal based on the difference data between the dynamic threshold and the differential signal of the combustion pulse signal; and performing feature analysis on each signal segment containing the deduplicated abrupt change points to obtain chromatographic peak feature data of the combustion pulse signal. The automatic chromatographic peak identification method based on dynamic thresholds provided in this embodiment employs a dynamic threshold algorithm, effectively combining local statistical data to accurately set signal thresholds. This enables efficient and accurate identification of abrupt change features in PFPD pulse signals under dynamically changing environments, significantly improving the accuracy and robustness of chromatographic peak identification. The following is a continuation of this discussion. Figures 1-5 The method will be further explained.

[0029] Figure 1 A flowchart illustrating an automatic chromatographic peak identification method based on a dynamic threshold according to an embodiment of the present invention is shown.

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

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

[0032] In some embodiments, the combustion light signal acquired by a pulsed flame photometric detector can be obtained first. Then, a photomultiplier tube (PMT) is used to convert the combustion light signal into an electrical signal. After amplifying the electrical signal output by the PMT, an analog-to-digital converter (ADC) is used to convert the amplified electrical signal into a digital signal. A data acquisition card (DAQ) is then used to receive the digital signal and transmit it to a computer or storage device to obtain the combustion pulse signal. The digital signal is stored in the computer or storage device, facilitating subsequent data analysis, modeling, and long-term preservation. The entire process of acquiring the combustion pulse signal using devices such as photomultiplier tubes, signal amplifiers, and analog-to-digital converters 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 denoted as fs) can be set appropriately according to actual needs. For example, the sampling frequency fs can be set to 10000, and the acquired combustion pulse signal can be... Figure 2 As 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, the dynamic threshold of the combustion pulse signal is determined based on the 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 in each window. The size of the sliding window can be reasonably set according to actual needs, and this invention does not impose specific limitations. The mean and standard deviation of the local signal can be calculated using the following formula:

[0036]

[0037]

[0038] Where, μ local σ represents the local mean. local The standard deviation is represented by N, which represents the number of signal sampling points in the local signal within the window. i This represents the amplitude of the i-th sampling point in the local signal.

[0039] This embodiment employs a sliding window and dynamic threshold algorithm, effectively combining local mean and standard deviation to precisely set signal thresholds. This enables efficient and accurate identification of abrupt changes in PFPD pulse signals under dynamically changing environments, significantly improving the accuracy and robustness of chromatographic peak identification.

[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 a preset sensitivity coefficient. The dynamic threshold can be calculated according to the following formula:

[0041]

[0042] Among them, T dynamic The dynamic threshold is represented by k, and the sensitivity coefficient is represented by k. k can be set according to actual needs, for example, it can be set to 3, but this 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 mean and standard deviation) to adapt to changes in the signal and avoid misjudgment or missed judgment that may be caused by a fixed threshold. The dynamic threshold is calculated by using the mean and standard deviation of the local signal and the sensitivity coefficient, which can effectively improve the accuracy, anti-interference ability and adaptability of combustion pulse signal detection, and is suitable for signal processing needs in complex environments. Then, operation S130 can be performed.

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

[0044] Combustion signals typically exhibit non-stationary characteristics. Differential signals can highlight local variations in the signal, avoiding subtle changes that might be overlooked when directly analyzing the original signal, thus improving sensitivity to abrupt changes. Combining differential signals with dynamic thresholding can better adapt to dynamic signal changes, enhancing detection robustness.

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

[0046]

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

[0048] Before feature analysis, the mutation points obtained through operation S130 can be deduplicated to avoid duplicate labeling. In some embodiments, mutation signals with sampling time intervals greater than a preset minimum time interval can be extracted from the mutation signal points to obtain deduplicated mutation signal points. The minimum time interval min_interval (in units of sampling points) can be adjusted according to the data characteristics, and this invention does not impose specific limitations.

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

[0050] For detected abrupt changes, signal segments within a certain range before and after the abrupt change can be extracted and stored as independent signal units for later analysis. Figure 3 The detected mutation points and the extracted pulse signal fragments can be used as follows: Figure 4 As shown. Figure 4 As shown, the extracted pulse signal has two optical peaks. The first optical peak ( Figure 4 Position 1 is attributed to the light spike generated when the pulsed flame background passes through the light collection window, and the second light peak ( Figure 4 Position 3) is generated by a chemical reaction of sulfur (phosphorus) compounds in the gas during combustion. These sulfur (phosphorus) compounds are oxidized in the pulsed flame and produce characteristic light signals. The amplitude of the second light peak is greater than that of the first light peak. Then, operation S140 can be performed.

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

[0052] Chromatographic peak characteristics can include, for example, peak height, peak width, and peak area. Figure 4 As shown, we can first detect the first peak (position 1), the second peak (position 3), and the valley between the first and second peaks (position 2) in each signal segment to determine the amplitude and timing of each peak and valley. The second peak, which is the highest point of the characteristic light signal produced 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 this chromatographic peak.

[0053]

[0054] Among them, Hpeak The peak height is given by t, signal is the extracted pulse signal segment, max() is the maximum amplitude value in the pulse signal segment, and t is the maximum amplitude value in the pulse signal segment. first_peak To determine the moment when the first light peak is detected, t end This represents the upper limit of the extracted pulse signal time. For example... Figure 4 As shown, t first_peak For the time corresponding to position 1, t end It takes 25ms.

[0055] Then, at the half-peak height between the first and second light peaks, the nearest intersection points are searched to the left and right of the second light peak to determine the left and right boundaries of the half-peak. The time difference between the left and right boundaries is calculated to obtain the half-peak width. The half-peak height can be calculated using the following formula:

[0056]

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

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

[0059]

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

[0061] Next, the area under the signal curve between the moment of the peak and the moment of the signal segment's cutoff is calculated to obtain the peak area. For example, numerical integration (trapezoidal rule) can be used to calculate the peak area:

[0062]

[0063] Among them, A peak The peak area of ​​the characteristic optical signal produced by sulfur- or phosphorus-containing compounds, t valley This marks the start of the second light peak, which is also the time corresponding to the light valley.

[0064] Finally, the amplitude H of the second light peak is extracted. peak Half-peak width W peak Peak area A peak This yields chromatographic peak characteristic data.

[0065] Figure 5 A flowchart illustrating an automatic chromatographic peak identification method based on dynamic thresholds according to another embodiment of the present invention is shown.

[0066] like Figure 5 As shown, the automatic peak identification method 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: 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 location of the signal, and the dynamic threshold can be calculated based on these statistics.

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

[0070] The fourth step is to detect abrupt change points: the differential signal can be compared with a dynamic threshold to identify abrupt change points that exceed the dynamic threshold.

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

[0072] Step 6: Extract mutation signal segments: The mutation signal segments can be extracted based on the index of the mutation point and stored in an array.

[0073] Step 7, Feature Analysis: For each abrupt signal segment, its peak value, half-width at half-maximum, and peak area can be calculated to obtain chromatographic peak characteristic data.

[0074] It should be noted that the order and number of steps one through seven described above are merely examples and do not constitute a further limitation on the present invention. Without altering the overall technical solution, those skilled in the art can combine or adjust the steps according to the actual situation. For example, the dynamic threshold calculation in step two and the differential signal calculation in step three can be performed simultaneously. As another example, the differential signal in step three can be calculated first, followed by the dynamic threshold in step two, and then abrupt changes in the signal can be detected based on the difference between the differential signal and the dynamic threshold.

[0075] Based on the aforementioned embodiments, this invention proposes a dynamic thresholding algorithm based on a sliding window. This algorithm calculates the dynamic threshold of the signal using local mean and standard deviation, enabling it to adapt to dynamic changes in complex background signals and effectively identify abrupt changes. This invention also proposes a method for extracting signal segments from detected abrupt changes and designs algorithms for calculating peak height, peak width, and peak area based on the dynamic threshold, ensuring the accuracy and robustness of feature extraction. By analyzing the peak characteristics of the PFPD signal, a bimodal structure is used to correspond to the pulse background and the target compound reaction signal, respectively. Combined with the dynamic thresholding method, high-precision pulse signal identification is achieved. This technical solution is applicable to the analysis of sulfur- and phosphorus-containing compounds in PFPD signals and can be widely applied in data processing scenarios of chemical analysis instruments.

[0076] Compared to existing technologies that use fixed thresholds, this invention achieves adaptive analysis of local signal characteristics through a dynamic threshold algorithm. Calculated based on the local mean and standard deviation within a sliding window, it flexibly adapts to different signal characteristics without requiring manual threshold setting. This invention does not rely on high-quality template libraries or large-scale sample training; it analyzes directly within dynamic signals and is suitable for various chemical environments and experimental conditions. Specifically, this invention optimizes the signal characteristics of pulsed flame photometric detectors, distinguishing background signals from characteristic signals of sulfur- and phosphorus-containing compounds, ensuring the accuracy of multi-element analysis. The effects presented by this technology can be, for example, as shown in... Figure 2 , Figure 3 and Figure 4 As shown, it will not be elaborated further here.

[0077] Based on the above-described automatic chromatographic peak identification method based on dynamic thresholds, this invention also provides an automatic chromatographic peak identification device based on dynamic thresholds. The following will be combined with... Figure 6 The device is described in detail.

[0078] Figure 6 A schematic diagram of a dynamic threshold-based automatic chromatographic peak identification device according to an embodiment of the present invention is shown.

[0079] like Figure 6 As shown, the automatic chromatographic peak identification device 600 based on dynamic threshold in 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 repeated here.

[0081] The first determining module 620 is used to determine the 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 determining module 620 can be used to perform the operation S120 described above, which will not be repeated here.

[0082] The second determining module 630 is used to determine the abrupt change 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. In one embodiment, the second determining module 630 can be used to perform the operation S130 described above, which will not be repeated here.

[0083] The feature analysis module 640 is used to perform feature analysis on each signal segment containing the deduplicated mutation signal point 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, the signal acquisition module 610 can also be used to acquire the combustion light signal collected by the pulse flame photometric detector; a photomultiplier tube is used to convert the combustion light signal into an electrical signal; after amplifying the electrical signal output by the photomultiplier tube, 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. For details regarding this, please refer to the preceding text; it will not be repeated here.

[0085] According to an embodiment of the present invention, the first determining module 620 is further configured to calculate the local mean and local standard deviation of the combustion pulse signal under a preset sliding window; and determine a dynamic threshold based on the local mean and local standard deviation in each window. Details of the relevant content can be found above and will not be repeated here.

[0086] According to an embodiment of the present invention, the second determining module 630 is further configured to calculate the first-order difference data between two adjacent sampled signals in the combustion pulse signal, as a difference 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 regarding this, please refer to the preceding text, which will not be repeated here.

[0087] According to an embodiment of the present invention, the automatic chromatographic peak identification device 600 based on dynamic thresholds may further include a deduplication module (not shown in the figure). The deduplication module is used to extract the mutation signal points whose sampling time interval is greater than a preset minimum time interval, thereby obtaining the deduplicated mutation signal points. For details of the relevant content, please refer to the preceding text, which will not be repeated here.

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

[0089] According to an embodiment of the present invention, the feature analysis module 640 can also be used to extract each signal segment containing the deduplicated mutation signal point based on the index of the mutation signal point, and store them as independent mutation signal units for subsequent feature analysis. For details regarding this, please refer to the preceding text; it will not be repeated here.

[0090] According to embodiments of the present invention, any plurality of 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 one module, or any one of these modules may be split into multiple modules. Alternatively, at least a portion of the functionality of one or more of these modules may be combined with at least a portion of the functionality of other modules and implemented in one 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 hardware circuitry, 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-package, an application-specific integrated circuit (ASIC), or any other reasonable means of integrating or packaging the circuitry, or implemented in software, hardware, or firmware, or in any one of the three implementation methods or a suitable combination of any of them. 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 implemented at least partially as a computer program module, which can perform corresponding functions when the computer program module is run.

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

[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 according to a program stored in a read-only memory (ROM) 702 or a program loaded from a storage portion 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 an associated chipset 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] RAM 703 stores various programs and data required for the operation of electronic device 700. Processor 701, ROM 702, and RAM 703 are interconnected via bus 704. Processor 701 executes various operations of the method flow according to embodiments of the present invention by executing programs in ROM 702 and / or RAM 703. It should be noted that programs may also be stored in one or more memories other than ROM 702 and RAM 703. Processor 701 may also execute various operations of the method flow according to embodiments of the present invention by executing programs stored in one or more memories.

[0094] According to an embodiment of the present invention, the electronic device 700 may further include an input / output (I / O) interface 705, which is also connected to a bus 704. The electronic device 700 may also include one or more of the following components connected to the input / output (I / O) interface 705: an input section 706 including a keyboard, mouse, etc.; an output section 707 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 708 including a hard disk, etc.; and a communication section 709 including a network interface card such as a LAN card, modem, etc. The communication section 709 performs communication processing via a network such as the Internet. A drive 710 is also connected to the input / output (I / O) interface 705 as needed. A removable medium 711, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on the drive 710 as needed so that computer programs read from it can be installed into the 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 it may exist independently and not assembled 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 embodiments of the present invention, a computer-readable storage medium may be a non-volatile computer-readable storage medium, such as including, but not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. For example, according to embodiments of the present invention, a computer-readable storage medium may include ROM 702 and / or RAM 703 and / or one or more memories other than ROM 702 and RAM 703 described above.

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

[0098] When the computer program is executed by the processor 701, it performs the functions defined in the system / apparatus of this invention. According to embodiments of the invention, the systems, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0099] In one embodiment, the computer program may rely on a tangible storage medium such as an optical storage device or a magnetic storage device. In another embodiment, the computer program may also be transmitted and distributed in the form of signals over a network medium, and may be downloaded and installed via the communication section 709, and / or installed from a removable medium 711. The program code contained in the computer program can be transmitted using any suitable network medium, including but not limited to: wireless, wired, etc., 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, it performs the functions defined in the system of this embodiment of the invention. According to embodiments of the invention, the systems, devices, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0101] According to embodiments of the present invention, program code for executing the computer programs provided in the embodiments of the present invention can be written in any combination of one or more programming languages. Specifically, these computational 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's computing device, partially on the user's device, partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0102] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

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

[0104] The embodiments of the present invention have been described above. However, these embodiments are merely illustrative and not intended to limit the scope of the invention. Although various embodiments have been described above, this does not mean that the measures in the various embodiments cannot be used advantageously in combination. Various substitutions and modifications can be made by those skilled in the art without departing from the scope of the invention, and all such substitutions and modifications should fall within the scope of the invention.

Claims

1. A method for automatic identification of chromatographic peaks based on dynamic thresholds, characterized in that, include: Acquire the combustion pulse signal collected by the pulse flame photometric detector; Based on statistical data of different local signals in the combustion pulse signal, the dynamic threshold of the combustion pulse signal is determined, including: calculating the local mean and local standard deviation of the combustion pulse signal under a preset sliding window; 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; Based on the difference data between the dynamic threshold and the differential signal of the combustion pulse signal, the abrupt change signal point of the combustion pulse signal is determined; Feature analysis is performed on each signal segment containing the deduplicated mutation signal point to obtain the chromatographic peak feature data of the combustion pulse signal.

2. The automatic peak identification method according to claim 1, characterized in that, The step of determining the abrupt change 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: Calculate the first-order difference data between two adjacent sampled signals in the combustion pulse signal, and use it as the difference signal; Compare the difference between each of the first-order difference data and the dynamic threshold, and mark the signal points corresponding to the first-order difference data being greater than the dynamic threshold as the mutation signal points.

3. The automatic peak identification method according to claim 1, characterized in that, Before performing feature analysis on each signal segment containing the deduplicated mutation signal point, the automatic peak identification method further includes: Extract the mutation signals from the mutation signal points whose sampling time interval is greater than a preset minimum time interval to obtain the duplicated mutation signal points.

4. The automatic peak identification method according to claim 1 or 3, characterized in that, The step of performing feature analysis on each signal segment containing the deduplicated mutation signal point to obtain the chromatographic peak feature data of the combustion pulse signal includes: Detect the first light peak, the second light peak, and the valley between the first light peak and the second light peak in each of the signal segments, and determine the amplitude and time corresponding to the first light peak, the second light peak, and the valley respectively; At the half-peak height between the first and second light peaks, the nearest intersection points are searched to the left and right from the second light peak to determine the left and right boundaries of the half-peak. The time difference between the left and right boundaries is calculated to obtain the half-peak width. Calculate the area of ​​the signal curve between the time of the optical valley and the cutoff time of the signal segment to obtain the peak area; The amplitude of the second peak, the half-peak width, and the peak area are extracted to obtain the chromatographic peak characteristic data.

5. The automatic peak identification method according to claim 1, characterized in that, The feature analysis of each signal segment containing the deduplicated mutation signal point includes: Based on the index of the mutation signal point, each signal segment containing the deduplicated mutation signal point is extracted and stored as its own independent mutation signal unit for subsequent feature analysis.

6. The automatic peak identification method according to claim 1, characterized in that, The acquisition of the combustion pulse signal collected by the pulse flame photometric detector includes: Acquire the combustion light signal collected by the pulse flame photometric detector; The combustion light signal is converted into an electrical signal using a photomultiplier tube. After the electrical signal output by the photomultiplier tube is amplified, an analog-to-digital converter is used to convert the amplified electrical signal into a digital signal. The digital signal is received by a data acquisition card and transmitted to a computer or storage device to obtain the combustion pulse signal.

7. An automatic chromatographic peak identification device based on dynamic threshold, characterized in that, include: The signal acquisition module is used to acquire the combustion pulse signal collected by the pulse flame photometric detector; The first determining module is used to determine the dynamic threshold of the combustion pulse signal based on statistical data of different local signals in the combustion pulse signal; the first determining module is also used to calculate the local mean and local standard deviation of the combustion pulse signal under a preset sliding window; the dynamic threshold of the combustion pulse signal is obtained by adding the local mean to the product of the local standard deviation and a preset sensitivity coefficient. The second determining module is used to determine the abrupt change 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; The feature analysis module is used to perform feature analysis on each signal segment where the deduplicated mutation signal point is located, and to obtain the chromatographic peak feature data of the combustion pulse signal.

8. An electronic device, characterized in that, include: One or more processors; 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 perform the method according to any one of claims 1 to 6.

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