Spectral data processing and displaying system

Abstract

The invention relates to the field of data processing display, and discloses a spectral data processing display system, which comprises a spectral data acquisition module, a data transmission module, a data preprocessing module, a data processing module, a data storage module and a display module, the data transmission module is used for transmitting spectral data among all the modules, the data preprocessing module is used for preprocessing the spectral data to eliminate the influence of environmental factors, the data processing module is used for analyzing and processing the spectral data, and the data storage module is used for storing and processing results obtained through analysis. The display module is used for controlling system operation and calling a processing result. According to the method, the spectral image is preprocessed, and the accuracy of an analysis result is ensured after the influence of various environmental factors is eliminated and then analysis processing is performed.

Description

Technical Field

[0001] The invention relates to the field of data processing and display, and in particular to a spectrum data processing and display system. Background Art

[0002] A spectrometer is a scientific instrument used to decompose complex light into spectral lines and measure the intensity of different wavelength ranges to analyze the composition, structure and properties of matter. The spectrometer separates the electromagnetic radiation of the radiation source into the required wavelength range or wavelength range area through a dispersive element (such as a prism or a diffraction grating), and measures the intensity in the selected wavelength range and finally outputs it as a spectral image. This instrument is widely used in the detection of air pollution, water pollution, food hygiene and metal industry.

[0003] Existing spectrometers only output the measured data as raw spectral images, and do not process and analyze the spectral images to eliminate the influence of environmental factors, so that testers need to analyze and process the data to obtain the desired test results.

[0004] Therefore, it is necessary to set up a spectral data processing and display system that automatically analyzes and processes the original spectral image output by the spectrometer, so as to solve the problem that the traditional spectrometer only outputs the original spectral image, resulting in the need for detection personnel to analyze and process the data by themselves to obtain the information they need. Summary of the invention

[0005] In view of this, the present invention proposes a spectral data processing and display system to solve the problem that traditional spectrometers only output raw spectral images, resulting in the need for testers to analyze and process the data themselves to obtain the information they need.

[0006] The present invention provides a spectral data processing and display system, comprising:

[0007] The spectral data acquisition module is used to collect the original spectral image, detection start time and detection end time output by the spectrometer. The detection start time and detection end time are used to mark the original spectral data, so that it is convenient to retrieve and display it according to the needs;

[0008] Data preprocessing module, which preprocesses the original spectral data to eliminate the influence of environmental factors;

[0009] A data processing module is used to analyze and process the pre-processed spectral data;

[0010] A data storage module for storing original spectral data, pre-processed spectral data and analyzed spectral data;

[0011] A display module, used to control system operation and retrieve and display the spectral data stored in the data storage module;

[0012] The data transmission module is a data transmission channel between modules and is used to transmit spectral data.

[0013] Furthermore, the display module includes:

[0014] A control panel is an external control display panel used to retrieve and display the spectral data information in the storage module and control the system operation;

[0015] A control unit, one end of which is connected to the control panel and the other end of which is connected to each functional module for controller operation, and is used to help the control panel control the system operation;

[0016] A data retrieval unit; one end of which is connected to the control panel and the other end of which is connected to the data storage module, is used to retrieve spectral data and display it on the control panel.

[0017] Furthermore, the data preprocessing module preprocesses the original spectral image by baseline correction, noise removal, and standard normal variable transformation.

[0018] Furthermore, the baseline calibration method is as follows: the data preprocessing module fits a quadratic polynomial according to the data points in the non-peak region of the spectral image to obtain the baseline, and then performs baseline subtraction on the spectral image to obtain the calibrated spectral image;

[0019] Furthermore, the noise removal method is: using wavelet transform to remove the influence of noise, the data preprocessing module performs wavelet decomposition on the spectral image, and then threshold processing is performed on the coefficients of the wavelet decomposition, a threshold is set, all wavelet coefficients are compared with the threshold, all wavelets with coefficients less than the threshold are removed, and then the processed coefficients are reconstructed by wavelet to obtain a denoised spectral image.

[0020] Furthermore, the standard normal variable transformation method is: the data preprocessing module performs a standard normal variable transformation on the spectral image to further eliminate the interference factors of the spectral data. The specific formula is as follows:

[0021]

[0022] In the formula, y represents the result of a spectrum after standard normal variable transformation, X i represents the i-th data value in this spectrum, It represents the average value of all the data of this spectrum, and n represents the number of wavelength points

[0023] Furthermore, the data processing module performs information extraction and analysis on the preprocessed spectral image through characteristic peak extraction, normalization processing and derivative spectrum generation.

[0024] Furthermore, the characteristic peak extraction is used to analyze and detect the components of the sample, including peak extraction and peak wavelength range extraction. The specific method is: the processing module divides the preprocessed spectral image into several pixel points, compares the pixel point with the two adjacent pixels, and identifies the middle pixel point higher than the two sides as the peak point. The peak point is extended to both sides to identify the lowest points on both sides. The two lowest points are the characteristic peak wavelength range, and then the wavelength and light intensity information at the peak value, as well as the wavelength range, are extracted.

[0025] Furthermore, the normalization process is used to analyze and compare the spectral images of different samples. The specific steps are as follows: the data processing module performs geometric scaling on the eigenvalues, subtracts the minimum value from the spectral data and divides it by the difference between the maximum data and the minimum data, and maps all the data to the (0, 1) interval. The normalization formula is as follows:

[0026]

[0027] Where x represents the spectral data, max represents the maximum value, and min represents the minimum value.

[0028] Furthermore, the derivative spectrum is used to show the subtle features of the spectral image, and the specific steps are: the data processing module performs derivative processing on the spectral image, so that the original graph of light intensity changing with wavelength is transformed into a graph of light intensity rate changing with wavelength.

[0029] Compared with the prior art, the beneficial effects of the present invention are as follows: by setting a data preprocessing module to preprocess the spectral image to eliminate the influence of environmental factors, and then by setting a data processing module to analyze and process the preprocessed spectral image, the accuracy of the analyzed and processed data is ensured, and at the same time, the preprocessed spectral data can be processed differently as needed to meet the needs of the detection personnel.

[0030] The present invention pre-processes the original spectral image by baseline correction, noise removal, and standard normal variable transformation, thereby eliminating most of the environmental noise influence in the original spectral image and improving data accuracy.

[0031] The present invention processes the preprocessed spectral image through peak extraction, extracts the characteristic peak value and peak wavelength range in the spectral image, which can be directly used for comparative analysis of sample material composition, greatly improving the detection speed.

[0032] The present invention also analyzes and processes the pre-processed spectral image through normalization processing, so that the spectral data sets of multiple samples are concentrated within a unified standard interval, which greatly facilitates comparative analysis of the samples.

[0033] The present invention also obtains a sample derivative spectrum by performing a derivative process on the preprocessed spectral image, thereby showing more subtle features of the spectral image and making various characteristic peaks more intuitive. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present invention. Moreover, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:

[0035] Figure 1 This is a flow chart of spectrum data processing and display system processing spectrum data according to an embodiment of the present invention;

[0036] Figure 2 This is a schematic diagram of the interior of a display module in a spectral data processing and display system according to an embodiment of the present invention;

[0037] Figure 3 Schematic diagram of a spectral data processing method in an embodiment of the present invention. DETAILED DESCRIPTION

[0038] Various exemplary embodiments of the present application will now be described in detail with reference to the accompanying drawings. It should be noted that unless otherwise specifically stated, the relative arrangement of components and steps, numerical expressions and numerical values ​​set forth in these embodiments do not limit the scope of the present application.

[0039] At the same time, it should be understood that for the convenience of description, the sizes of the various parts shown in the drawings are not drawn according to the actual proportional relationship.

[0040] The following description of at least one exemplary embodiment is merely illustrative in nature and is not intended to limit the present application, its application, or uses.

[0041] Technologies, systems, and devices known to ordinary technicians in the relevant art may not be discussed in detail, but where appropriate, the technologies, systems, and devices should be considered part of the specification.

[0042] It should be noted that like reference numerals and letters refer to similar items in the following figures, and therefore, once an item is defined in one figure, it need not be further discussed in subsequent figures.

[0043] In addition, the technical solutions between the various embodiments of the present application can be combined with each other, but it must be based on the fact that ordinary technicians in the field can implement it. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such combination of technical solutions does not exist and is not within the scope of protection required by this application.

[0044] It should be noted that all directional indications in the embodiments of the present application (such as up, down, left, right, front, back, etc.) are only used to explain the relative position relationship, movement status, etc. between the components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly.

[0045] A spectrometer is a scientific instrument used to decompose complex light into spectral lines and measure the intensity of different wavelength ranges to analyze the composition, structure and properties of a substance. The spectrometer separates the electromagnetic radiation of a radiation source into the required wavelength range or wavelength range area through a dispersive element (such as a prism or a diffraction grating), and measures the intensity in the selected wavelength range and finally outputs it as a spectral image. This instrument is widely used in the detection of air pollution, water pollution, food hygiene and metal industry. Existing spectrometers only output the measurement data as raw spectral images, and do not process and analyze the spectral images to eliminate the influence of environmental factors, so that the test personnel need to analyze and process the data to obtain the desired test results. Therefore, it is necessary to set up a spectral data processing and display system that automatically analyzes and processes the raw spectral images output by the spectrometer to solve the problem that the traditional spectrometer only outputs the raw spectral images, resulting in the need for the test personnel to analyze and process the data by themselves to obtain the information they need.

[0046] Reference Figure 1 As shown, in the embodiment provided in the present application, a spectrum data processing and display system includes: a spectrum data acquisition module, a data preprocessing module, a data processing module, a display module, and a data transmission module.

[0047] Specifically, the spectral data acquisition module is used to collect the original spectral image, detection start time and detection end time output by the spectrometer, and the detection start time and detection end time are used to mark the original spectral data for convenient retrieval and display according to needs; the data preprocessing module preprocesses the original spectral data to eliminate the influence of environmental factors; the data processing module is used to analyze and process the preprocessed spectral data; the data storage module stores the original spectral data, the preprocessed spectral data and the analyzed and processed spectral data; the display module is used to control the system operation and retrieve and display the spectral data stored in the data storage module; the data transmission module is a data transmission channel between modules and is used to transmit spectral data.

[0048] It can be understood that by setting up a data preprocessing module to preprocess the spectral image to eliminate the influence of environmental factors, and then setting up a data processing module to analyze and process the preprocessed spectral image, the accuracy of the analyzed and processed data is ensured, and the preprocessed spectral data can be processed differently as needed to meet the needs of the detection personnel.

[0049] See also Figure 2 As shown, the display module includes: a control panel, a control unit, and a data retrieval unit.

[0050] Specifically, the control panel is an external control and display panel, which is used to retrieve and display the spectral data information in the storage module and control the system operation; the control unit is connected to the control panel at one end and to each functional module at the other end to control the operation, which is used to help the control panel control the system operation; the data retrieval unit is connected to the control panel at one end and to the data storage module at the other end, which is used to retrieve the spectral data and display it on the control panel.

[0051] It is understandable that when the experimenter inputs instructions on the control panel, the control panel transmits the instructions to the control unit, and the control unit controls the system to operate according to the instructions, or starts processing or retrieving data.

[0052] See also Figure 3 As shown, the above-mentioned data preprocessing module preprocesses the original spectral image through baseline correction, noise removal, and standard normal variable transformation.

[0053] Specifically, the data preprocessing module removes the baseline offset or drift caused by the instrument, sample container or its environmental factors through baseline calibration; reduces the influence of noise in the original spectral image through noise removal; and eliminates the scattering effect caused by optical path difference through standard normal variable transformation.

[0054] It is understandable that the data preprocessing module ensures that the spectral data reflects the characteristics of the sample itself through baseline calibration; reduces the influence of noise through noise removal; and improves the accuracy of spectral data through standard normal variable transformation. And when performing subtle feature analysis, different spectral types and different samples require different preprocessing methods. Under the system default, the raw data is preprocessed by baseline correction, noise removal, and standard normal variable transformation. At the same time, the experimenter can also flexibly choose according to their own needs, or even skip the preprocessing directly.

[0055] See also Figure 2 As shown, the above baseline calibration method is: the data preprocessing module fits a quadratic polynomial according to the data points in the non-peak area of ​​the spectral image to obtain the baseline, and then performs baseline subtraction on the spectral image to obtain the calibrated spectral image.

[0056] It is understandable that during the operation of the spectrometer, due to the influence of fluorescence background, sample and surrounding blackbody radiation, the generated spectral image has a baseline, which affects the subsequent processing and analysis. The data preprocessing module fits the data points in the non-peak area into a quadratic polynomial, which represents the baseline. The baseline is then eliminated from the original spectral image, making the spectral image closer to the true spectral image of the sample.

[0057] See also Figure 2 As shown, the above noise removal method is: wavelet transform is used to remove the influence of noise, the data preprocessing module performs wavelet decomposition on the spectral image, and then threshold processing is performed on the coefficients of the wavelet decomposition, a threshold is set, all wavelet coefficients are compared with the threshold, and all wavelets with coefficients less than the threshold are removed, and then the processed coefficients are reconstructed by wavelet to obtain the denoised spectral image.

[0058] It is understandable that in the original spectral image, noise usually appears as a high-frequency part, while the real data is usually smoother and more regular, so the wavelet transform can decompose the spectral image into many wavelet structures, and then set a threshold to identify the wavelet components below this threshold as noise and remove them, and the remaining wavelet components are enriched into the spectral image to achieve noise removal in the spectral image.

[0059] See also Figure 2 As shown, the above standard normal variable transformation method is: the data preprocessing module performs standard normal variable transformation on the spectral image to further eliminate the interference factors of the spectral data. The specific formula is as follows:

[0060]

[0061] In the formula, y represents the result of a spectrum after standard normal variable transformation, X i represents the i-th data value in this spectrum, It represents the average value of all the data of this spectrum, and n represents the number of wavelength points.

[0062] It is understandable that due to factors such as optical path differences, the spectral data of different samples may be affected by scattering effects, causing the data to deviate from the true value. The standard normal variable transformation corrects the original spectral data by calculating the difference between each sample spectrum and the average spectrum of all samples, thereby eliminating this scattering effect.

[0063] See also Figure 3 As shown, the data processing module performs information extraction and analysis on the preprocessed spectral image through characteristic peak extraction, normalization processing and derivative spectrum generation.

[0064] Specifically, after receiving the preprocessed spectral image, the data processing module performs characteristic peak extraction, normalization and derivative spectrum on the preprocessed spectrum to generate characteristic peak information, characteristic peak wavelength range, normalized spectral image and derivative spectrum and other information.

[0065] It can be understood that the characteristic peak information and characteristic peak wavelength range are used to compare and analyze the sample composition. The normalization processing concentrates the spectral data sets of multiple samples into a unified standard range, which greatly facilitates the comparative analysis of samples. The derivative spectrum shows more subtle features of the spectral image, making the various characteristic peaks more intuitive.

[0066] See also Figure 2 As shown, the above-mentioned characteristic peak extraction includes peak value extraction and peak wavelength range extraction.

[0067] Specifically, the data processing module divides the preprocessed spectral image into several pixels, compares the pixel with the two adjacent pixels, identifies the middle pixel that is higher than the two sides as the peak, extends to both sides of the peak to identify the lowest points on both sides, and the two lowest points are the characteristic peak wavelength range, and then extracts the wavelength and light intensity information at the peak, as well as the wavelength range.

[0068] It is understandable that the spectral characteristics of different substances are often presented through different peaks corresponding to the properties of a certain material at a specific position in the spectral image. These peaks are called characteristic peaks. The material composition in the sample can be obtained by analyzing the characteristic peak value and the wavelength range of the characteristic peak.

[0069] See also Figure 2 As shown, the normalization processing method is as follows: the data processing module performs geometric scaling on the eigenvalues, subtracts the minimum value from the spectral data and divides it by the difference between the maximum data and the minimum data, and maps all data to the (0, 1) interval. The normalization formula is as follows:

[0070]

[0071] In the formula, max represents the maximum value of a column, and min represents the minimum value of a column.

[0072] It is understandable that different spectral images may have different spectral intensity ratios due to differences in the wavelength range and sensitivity of the spectrometer, which causes great difficulties in comparative analysis between different spectral images. Normalization processing can bring the spectral data sets of multiple samples into a unified standard range, greatly facilitating comparative analysis of samples.

[0073] See also Figure 2 As shown, the above derivative spectrum method is: the data processing module performs derivative processing on the spectrum image, so that the original graph of light intensity changing with wavelength is transformed into a graph of light intensity rate changing with wavelength.

[0074] It is understandable that when performing component analysis on complex samples, there will be many overlapping characteristic peaks in its spectral image, which causes great difficulties in the analysis. Therefore, the data processing module will perform derivative processing on the spectral image, so that the original graph of light intensity changing with wavelength is transformed into a graph of light intensity rate changing with wavelength, so that some subtle features of the spectral image are revealed, thereby clearly identifying some highly overlapping characteristic peaks.

[0075] See also Figure 1-3 As shown, the data processing module transmits the detection start time, detection end time, original spectrum graph, preprocessed spectrum image, characteristic peak value, characteristic peak wavelength range, normalized spectrum image and derivative spectrum to the data storage module through the data transmission module. The data storage module classifies and stores the original spectrum graph, preprocessed spectrum image, characteristic peak value, characteristic peak wavelength range, normalized spectrum image and derivative spectrum and labels the spectrum data according to the detection start time and the detection end time. Subsequently, the data retrieval unit retrieves the processed spectrum data and displays it on the control panel according to the type. The detection personnel can rename the label after writing the remark information for the spectrum data on the control panel.

[0076] See also Figure 3 As shown, the working process of the spectral data processing and display system of the present embodiment is as follows: first, after the spectral data processing and display system receives the original spectral image, the data preprocessing module performs noise removal, baseline calibration and standard normal variable transformation to preprocess the original spectral image to obtain a pre-processed spectral image, and any preprocessing step can be cancelled according to its own needs before preprocessing; secondly, the data processing module performs data analysis processing on the preprocessed spectral image, performs characteristic peak extraction, normalization processing and derivative processing on the preprocessed spectral image, respectively, obtains characteristic peak value, characteristic peak wavelength range, normalized spectral image and derivative spectrum, and stores them; finally, the required spectral data information is retrieved through the data retrieval module according to its own needs, and displayed on the control panel.

[0077] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0078] The present application is described with reference to flowcharts and / or block diagrams of methods, devices (systems) and computer program products according to embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0079] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0080] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0081] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A spectral data processing and display system, characterized in that: include: The spectral data acquisition module is used to collect the original spectral image, detection start time and detection end time output by the spectrometer. The detection start time and detection end time are used to mark the original spectral data, so that it is convenient to retrieve and display it according to the needs; Data preprocessing module, which preprocesses the original spectral data to eliminate the influence of environmental factors; A data processing module is used to analyze and process the pre-processed spectral data; A data storage module for storing raw spectral data, pre-processed spectral data and analyzed spectral data; A display module, used to control system operation and retrieve and display the spectral data stored in the data storage module; The data transmission module is a data transmission channel between modules and is used to transmit spectral data.

2. The spectral data processing and display system according to claim 1, characterized in that: The display module comprises: A control panel is an external control and display panel used to retrieve and display the spectral data information in the storage module and control the system operation; A control unit, one end of which is connected to the control panel and the other end of which is connected to each functional module for controller operation, and is used to help the control panel control the system operation; A data retrieval unit; one end of which is connected to the control panel and the other end of which is connected to the data storage module, is used to retrieve spectral data and display it on the control panel.

3. The spectral data processing and display system according to claim 1, characterized in that: The data preprocessing module preprocesses the original spectral image through baseline correction, noise removal, and standard normal variable transformation.

4. The spectral data processing and display system according to claim 3, characterized in that: The baseline calibration method is as follows: a data preprocessing module fits a quadratic polynomial according to data points in a non-peak region of a spectral image to obtain a baseline, and then performs baseline subtraction on the spectral image to obtain a calibrated spectral image.

5. The spectral data processing and display system according to claim 3, characterized in that: The noise removal method is as follows: the wavelet transform method is used to remove the influence of noise, the data preprocessing module performs wavelet decomposition on the spectral image, and then threshold processing is performed on the coefficients of the wavelet decomposition, a threshold is set, all wavelet coefficients are compared with the threshold, and all wavelets with coefficients less than the threshold are removed, and then the processed coefficients are subjected to wavelet reconstruction to obtain a denoised spectral image.

6. The spectral data processing and display system according to claim 3, characterized in that: The standard normal variable transformation method is: the data preprocessing module performs standard normal variable transformation on the spectral image to further eliminate the interference factors of the spectral data. The specific formula is as follows: In the formula, y represents the result of a spectrum after standard normal variable transformation, X i represents the i-th data value in this spectrum, It represents the average value of all the data of this spectrum, and n represents the number of wavelength points.

7. The spectral data processing and display system according to claim 1, characterized in that: The data processing module performs information extraction and analysis on the preprocessed spectral image through characteristic peak extraction, normalization processing and derivative spectrum generation.

8. The spectral data processing and display system according to claim 7, characterized in that: The characteristic peak extraction is used to analyze and detect the components of the sample, including peak extraction and peak wavelength range extraction. The specific method is: the processing module divides the preprocessed spectral image into several pixel points, compares the pixel point with the two adjacent pixels, and identifies the middle pixel point higher than the two sides as the peak point. The two lowest points on both sides are extended to the two sides of the peak to identify the characteristic peak wavelength range, and then the wavelength and light intensity information at the peak, as well as the wavelength range, are extracted.

9. The spectral data processing and display system according to claim 7, characterized in that: The normalization process is used to analyze and compare the spectral images of different samples. The specific steps are as follows: the data processing module performs geometric scaling on the eigenvalues, subtracts the minimum value from the spectral data and divides it by the difference between the maximum data and the minimum data, and maps all the data to the interval (0, 1). The normalization formula is as follows: In the formula, max represents the maximum value of a column, and min represents the minimum value of a column.

10. The spectral data processing and display system according to claim 7, characterized in that: The derivative spectrum is used to show the subtle features of the spectral image. The specific steps are: the data processing module performs derivative processing on the spectral image, so that the original graph of light intensity changing with wavelength is transformed into a graph of light intensity rate changing with wavelength.

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