Online calibration method of dry laser analyzer and related equipment

Abstract

The invention discloses an online calibration method of a dry laser analyzer and related equipment, relates to the field of steel production, and mainly aims to solve the problem that the calibration method of the existing dry laser analyzer depends on labor and is low in efficiency. The method comprises the following steps: determining first flue gas component data and second flue gas component data; obtaining the deviation between the first flue gas component data and the second flue gas component data; the laser analyzer is calibrated by a calibration algorithm based on the deviation. The online calibration device is used for the online calibration process of the dry laser analyzer.

Description

Technical Field

[0001] The present invention relates to the field of steel production, and particularly to an online calibration method and related equipment for a dry laser analyzer. Background Art

[0002] During the steel production process, accurately monitoring the components in the flue gas is of great significance for process control and environmental protection. A mass spectrometer and a laser analyzer, as two important monitoring instruments at the hot end of the converter and the cold end of the primary dedusting respectively, are widely used in the production line.

[0003] However, due to the different working environments and measurement principles of the mass spectrometer and the laser analyzer, it is usually necessary to calibrate them regularly to ensure their measurement accuracy. Traditional calibration methods usually rely on external standard gases or regular manual calibration, which are complex to operate and have high maintenance costs. Summary of the Invention

[0004] In view of the above problems, the present invention provides an online calibration method and related equipment for a dry laser analyzer, mainly aiming to solve the problem of low efficiency of the current calibration method for the dry laser analyzer relying on manual labor.

[0005] To solve the above-mentioned at least one technical problem, in a first aspect, the present invention provides an online calibration method for a dry laser analyzer, the method comprising:

[0006] Determine first flue gas component data and second flue gas component data;

[0007] Obtain the deviation between the first flue gas component data and the second flue gas component data;

[0008] Calibrate the laser analyzer based on the deviation through a calibration algorithm.

[0009] Optionally, the determining the first flue gas component data and the first flue gas component data includes:

[0010] Obtain the first flue gas component data based on a mass spectrometer, wherein the mass spectrometer is arranged at the hot end of the converter,

[0011] and obtain the second flue gas component data based on a laser analyzer, wherein the laser analyzer is arranged at the cold end of the dry dedusting.

[0012] Optionally, the calibrating the laser analyzer based on the deviation through a calibration algorithm includes:

[0013] Calibrate the measurement result of the laser analyzer based on the deviation through a calibration algorithm, wherein the measurement result is used for data analysis and process control.

[0014] Optionally, obtaining the deviation between the first flue gas component data and the second flue gas component data includes:

[0015] D(t) = M(t) - L(t)

[0016] where D(t) is the deviation, M(t) is the first flue gas component data, and L(t) is the second flue gas component data.

[0017] Optionally, calibrating the laser analyzer based on the deviation through a calibration algorithm includes:

[0018] Constructing a calibration model:

[0019] Lc(t) = L(t) + k·D(t)

[0020] where L(t) is the second flue gas component data, k is the calibration coefficient, and D(t) is the deviation.

[0021] Optionally, calibrating the laser analyzer based on the deviation through a calibration algorithm includes:

[0022] Calibrating the laser analyzer based on the output result of the calibration model.

[0023] Optionally, the above method further includes:

[0024] Determining the calibration coefficient by least squares fitting according to historical data.

[0025] In a second aspect, an embodiment of the present invention further provides an on-line calibration device for a dry laser analyzer, including:

[0026] A determination unit for determining first flue gas component data and second flue gas component data;

[0027] An acquisition unit for acquiring the deviation between the first flue gas component data and the second flue gas component data;

[0028] A calibration unit for calibrating the laser analyzer based on the deviation through a calibration algorithm.

[0029] To achieve the above object, according to a third aspect of the present invention, there is provided a computer-readable storage medium, the computer-readable storage medium including a stored program, wherein when the above program is executed by a processor, the steps of the on-line calibration method for the dry laser analyzer are implemented.

[0030] To achieve the above object, according to the fourth aspect of the present invention, an electronic device is provided, including at least one processor and at least one memory connected to the processor; wherein, the processor is configured to call program instructions in the memory and execute the steps of the online calibration method of the dry laser analyzer described above.

[0031] By means of the above technical solution, for the problem of low efficiency of the current calibration method of the dry laser analyzer that relies on manual operation, the present invention determines the first flue gas component data and the second flue gas component data; obtains the deviation between the first flue gas component data and the second flue gas component data; and corrects the laser analyzer based on the deviation through a calibration algorithm. In the above solution, through two-party data and based on the linkage calibration method of the mass spectrometer and the laser analyzer, automatic and real-time calibration can be achieved, reducing manual intervention and improving production efficiency and equipment stability.

[0032] Correspondingly, the online calibration device, equipment, and computer-readable storage medium of the dry laser analyzer provided by the embodiments of the present invention also have the above technical effects.

[0033] The above description is only an overview of the technical solution of the present invention. In order to be able to understand the technical means of the present invention more clearly, it can be implemented according to the content of the specification. And in order to make the above and other objects, features, and advantages of the present invention more obvious and understandable, the specific embodiments of the present invention are specifically exemplified below. Description of the Drawings

[0034] By reading the detailed description of the preferred embodiments below, various other advantages and benefits will become clear to those of ordinary skill in the art. The drawings are only for the purpose of showing the preferred embodiments and are not considered to be a limitation of the present invention. Moreover, throughout the drawings, the same reference numerals are used to represent the same components. In the drawings:

[0035] Figure 1 A flowchart showing an online calibration method of a dry laser analyzer provided by an embodiment of the present invention is shown;

[0036] Figure 2 A schematic block diagram showing the composition of an online calibration device of a dry laser analyzer provided by an embodiment of the present invention is shown;

[0037] Figure 3 A schematic block diagram showing the composition of an online calibration electronic device of a dry laser analyzer provided by an embodiment of the present invention is shown. Detailed Embodiments

[0038] Exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present invention are shown in the drawings, it should be understood that the present invention can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided so that the present invention can be more thoroughly understood and the scope of the present invention can be completely conveyed to those skilled in the art.

[0039] In order to solve the problem that the current calibration method of dry laser analyzers relies on manual labor and has low efficiency, an online calibration method for dry laser analyzers is provided in an embodiment of the present invention. As Figure 1 shown, the method includes:

[0040] S101. Determine first flue gas component data and second flue gas component data;

[0041] In one embodiment, the first flue gas component data is obtained based on a mass spectrometer, wherein the mass spectrometer is disposed at the hot end of a converter,

[0042] and the second flue gas component data is obtained based on a laser analyzer, wherein the laser analyzer is disposed at the cold end of dry dust removal.

[0043] Considering that currently, a mass spectrometer and a laser analyzer are usually used separately to monitor flue gas components, but they work independently and lack a linkage calibration mechanism. The mass spectrometer is mainly used for component analysis at the high-temperature end of the converter, while the laser analyzer is used for component monitoring at the cold end of dry dust removal. The calibration of the mass spectrometer can be directly performed with a multi-component calibration gas. The calibration of the laser analyzer requires removing the transmitting end and the receiving end, using an offline LAG optical path adjuster, and then calibrating with a calibration gas. It can only be carried out during maintenance and shutdown times, which is time-consuming and laborious.

[0044] Therefore, the present application proposes a linkage calibration method based on a mass spectrometer and a laser analyzer, which can achieve automatic and real-time calibration, reduce manual intervention, and improve production efficiency and equipment stability.

[0045] Exemplarily, the flue gas component data is collected in real time by the mass spectrometer installed at the hot end of the converter in the present application. The flue gas component data is synchronously collected by the laser analyzer installed at the cold end of dry dust removal.

[0046] Specifically, first, the mass spectrometer is calibrated with a standard gas (calibration gas) to ensure the accuracy of its measurement data. This step corrects the reference value of the mass spectrometer by introducing the standard gas, enabling it to reliably perform real-time flue gas data analysis. After the calibration of the mass spectrometer is completed, the component data of the flue gas is analyzed in real time. This data provides an accurate reference value for the subsequent calibration of the laser analyzer.

[0047] S102. Obtain the deviation between the first flue gas component data and the second flue gas component data;

[0048] Exemplarily, the flue gas composition data obtained by mass spectrometer analysis is transmitted to the central control system through the network and compared and analyzed with the data of the laser analyzer.

[0049] Based on the above solution, the present application transmits the first flue gas composition data and the second flue gas composition data of the mass spectrometer and the laser analyzer to the central control unit through a wired network.

[0050] In one embodiment,

[0051] D(t) = M(t) - L(t)

[0052] where D(t) is the deviation, M(t) is the first flue gas composition data, and L(t) is the second flue gas composition data.

[0053] Exemplarily, the reference data of the mass spectrometer is M(t), representing the true concentration value at time t. The measurement data of the laser analyzer is L(t), representing the measured concentration value of the laser analyzer at time t. The corrected data of the laser analyzer is Lc(t).

[0054] S103. Calibrate the laser analyzer based on the deviation through a calibration algorithm.

[0055] Exemplarily, after the central control unit receives the data of the mass spectrometer, it calculates the reference component concentration value and compares and analyzes it with the data of the laser analyzer in real time. The present application uses the data of the mass spectrometer as a reference and corrects the deviation of the measurement result of the laser analyzer through a built-in calibration algorithm. According to the analysis result, the present application automatically adjusts the calibration parameters of the laser analyzer to ensure the measurement accuracy. If obvious abnormalities or equipment failures are found in the measurement data, the system will automatically send an alarm signal and record the relevant data for subsequent analysis.

[0056] Based on the above solution, according to the real-time reference data provided by the mass spectrometer, the laser analyzer is automatically calibrated through a calibration algorithm. The calibration algorithm calculates the measurement deviation of the laser analyzer and corrects it based on the reference data of the mass spectrometer.

[0057] It should be noted that the calibration algorithm continuously monitors and adjusts the measurement result of the laser analyzer to ensure the accuracy of its output data. The system continuously adjusts and corrects the parameters of the laser analyzer according to the data of the mass spectrometer.

[0058] It can be understood that the present application provides a user-friendly display interface to display real-time data, calibration status and historical records, facilitating the operation and maintenance personnel to monitor and maintain.

[0059] In one embodiment, the measurement result of the laser analyzer is corrected by a calibration algorithm based on the deviation, where the measurement result is used for data analysis and process control.

[0060] Specifically, measurement data within the same time period is synchronously collected from a mass spectrometer and a laser analyzer. The deviation between the measurement data of the laser analyzer and the reference data of the mass spectrometer is calculated. An error model is established, and the measurement error is used as the algorithm input. The measurement result of the laser analyzer is corrected for real-time deviation through the established error model and calibration formula.

[0061] Exemplarily, the core idea of the above calibration algorithm is to use the data of the mass spectrometer as a reference, identify the systematic error in the measurement of the laser analyzer by comparing the measurement results of the mass spectrometer and the laser analyzer, and perform real-time correction.

[0062] In one embodiment, a correction model is constructed:

[0063] Lc(t) = L(t) + k·D(t)

[0064] where L(t) is the second flue gas component data, k is the correction coefficient, and D(t) is the deviation.

[0065] In one embodiment, the above method further includes:

[0066] Determining the correction coefficient by fitting through the least squares method based on historical data.

[0067] Exemplarily, to perform deviation correction on the measurement result of the laser analyzer in this application, a correction model needs to be adopted, and the deviation D(t) is incorporated into the calculation. According to different requirements and error distributions, the correction model can be a simple linear correction or a more complex non-linear model. For the linear correction model, we assume that the deviation D(t) is a constant or a linear function that changes with time. The calibration formula can be expressed as:

[0068] Lc(t) = L(t) + k·D(t)

[0069] where k is the correction coefficient, which can be determined by fitting through the least squares method or other statistical methods based on historical data.

[0070] In one embodiment, the laser analyzer is corrected based on the output result of the correction model.

[0071] The following shows a specific calibration process:

[0072] Step 1: Obtain the real-time data of the mass spectrometer and the laser analyzer.

[0073] Step 2: Calculate the deviation D(t) = M(t) - L(t) at the current time point.

[0074] Step 3: Calculate the corrected value Lc(t) = L(t) + k·D(t) using a preset correction model.

[0075] Step 4: Use the corrected data Lc(t) for subsequent data analysis and process control.

[0076] Through the data analysis results of the mass spectrometer, the laser analyzer is automatically calibrated to ensure the accuracy of its measurement. After calibration, the laser analyzer can accurately detect the components of the flue gas. If the system detects abnormal measurement or equipment failure, it will trigger an alarm to prompt the operator to conduct further inspection or maintenance. The automatic and real-time calibration of the mass spectrometer and the laser analyzer is realized, significantly improving the measurement accuracy of the equipment, reducing the manual maintenance and calibration costs, enhancing the production efficiency, providing a perfect feedback and alarm mechanism, and enhancing the reliability and safety of the system.

[0077] By means of the above technical solution, for the problem of low efficiency of the current calibration method of the dry laser analyzer relying on manual labor, the online calibration method of the dry laser analyzer provided by the present invention determines the first flue gas component data and the second flue gas component data; obtains the deviation between the first flue gas component data and the second flue gas component data; and corrects the laser analyzer based on the deviation through a calibration algorithm. In the above solution, through the two-party data, based on the linkage calibration method of the mass spectrometer and the laser analyzer, automatic and real-time calibration can be realized, reducing manual intervention and improving production efficiency and equipment stability.

[0078] Further, as an implementation of the above Figure 1 shown method, the embodiment of the present invention also provides an online calibration device for a dry laser analyzer, which is used to implement the above Figure 1 shown method. This device embodiment corresponds to the foregoing method embodiment. For the convenience of reading, the details of the foregoing method embodiment will not be repeated one by one in this device embodiment, but it should be clear that the device in this embodiment can correspondingly implement all the contents of the foregoing method embodiment. As Figure 2 shown, the device includes: a determination unit 21, an acquisition unit 22, and a correction unit 23, where

[0079] The determination unit 21 is configured to determine the first flue gas component data and the second flue gas component data;

[0080] The acquisition unit 22 is configured to acquire the deviation between the first flue gas component data and the second flue gas component data;

[0081] The correction unit 23 is configured to correct the laser analyzer based on the deviation through a calibration algorithm.

[0082] The processor contains a kernel, and the kernel retrieves corresponding program units from the memory. One or more kernels can be set, and by adjusting the kernel parameters, an online calibration method for a dry laser analyzer can be implemented, which can solve the problem that the current calibration method of the dry laser analyzer depends on manual labor and has low efficiency.

[0083] An embodiment of the present invention provides a computer-readable storage medium. The above computer-readable storage medium includes a stored program, and when the program is executed by a processor, the online calibration method of the dry laser analyzer is implemented.

[0084] An embodiment of the present invention provides a processor. The processor is used to run a program, and when the program runs, the online calibration method of the dry laser analyzer is executed.

[0085] An embodiment of the present invention provides an electronic device. The above electronic device includes at least one processor and at least one memory connected to the processor; wherein, the above processor is used to call program instructions in the above memory and execute the online calibration method of the dry laser analyzer as described above

[0086] An embodiment of the present invention provides an electronic device 30, as Figure 3 shown, the electronic device includes at least one processor 301, at least one memory 302 connected to the processor, and a bus 303; wherein, the processor 301 and the memory 302 complete communication with each other through the bus 303; the processor 301 is used to call program instructions in the memory to execute the online calibration method of the dry laser analyzer as described above.

[0087] The intelligent electronic device herein can be a PC, a PAD, a mobile phone, etc.

[0088] The present application also provides a computer program product. When executed on a process management electronic device, it is suitable for executing a program initialized with the steps of the online calibration method of the dry laser analyzer as described above.

[0089] It should be noted that in the above embodiments, the descriptions of each embodiment have their own emphases. For parts not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0090] Those skilled in the art should understand that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk memories, CD-ROMs, optical memories, etc.) containing computer-usable program codes.

[0091] This application is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram, as well as the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded computer, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in one flow Figure 1 one flow or multiple flows and / or blocks Figure 1 or multiple blocks.

[0092] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory generate a manufactured article including instruction means that implement the functions specified in one flow Figure 1 one flow or multiple flows and / or blocks Figure 1 or multiple blocks.

[0093] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one flow Figure 1 one flow or multiple flows and / or blocks Figure 1 or multiple blocks.

[0094] Embodiments of the present application also provide a computer program product that includes computer software instructions. When the computer software instructions run on a processing device, the processing device is caused to execute the process of controlling the memory as in Figure 1 the corresponding embodiment.

[0095] A computer program product includes one or more computer instructions. When the computer instructions are loaded and executed on a computer, the processes or functions according to the embodiments of the present application are all or partially generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from a website, a computer, a server, or a data center to another website, a computer, a server, or a data center in a wired manner (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or a wireless manner (such as infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be stored by a computer or a data storage device such as a server or a data center that includes one or more integrated available media. The available medium can be a magnetic medium (such as a floppy disk, a hard disk, a magnetic tape), an optical medium (such as a DVD), or a semiconductor medium (such as a solid state disk (SSD)), etc.

[0096] Those skilled in the art can clearly understand that for the convenience and conciseness of description, the specific working processes of the above-described systems, devices, and units can refer to the corresponding processes in the foregoing method embodiments, and will not be described herein again.

[0097] In several embodiments provided in the present application, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of units is only a logical function division, and there can be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be indirect couplings or communication connections through some interfaces, devices, or units, and can be in an electrical, mechanical, or other form.

[0098] The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they can be located in one place, or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0099] In addition, in each embodiment of the present application, each functional unit can be integrated into a processing unit, can exist separately physically for each unit, or two or more units can be integrated into one unit. The above integrated unit can be implemented in the form of hardware or in the form of a software functional unit.

[0100] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods in each embodiment of the present application. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs that can store program codes.

[0101] The above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than limiting them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of each embodiment of the present application.

Claims

1. An online calibration method for a dry laser analyzer, characterized in that, Including: Determine the first flue gas component data and the second flue gas component data; Obtain the deviation between the first flue gas component data and the second flue gas component data; Calibrate the laser analyzer based on the deviation through a calibration algorithm.

2. The method according to claim 1, wherein The determining the first flue gas component data and the first flue gas component data includes: Obtain the first flue gas component data based on a mass spectrometer, wherein the mass spectrometer is arranged at the hot end of a converter, and obtain the second flue gas component data based on a laser analyzer, wherein the laser analyzer is arranged at the cold end of dry dust removal.

3. The method according to claim 1, wherein The calibrating the laser analyzer based on the deviation through a calibration algorithm includes: Calibrate the measurement result of the laser analyzer based on the deviation through a calibration algorithm, wherein the measurement result is used for data analysis and process control.

4. The method according to claim 1, characterized in that The obtaining the deviation between the first flue gas component data and the second flue gas component data includes: D(t) = M(t) - L(t) where D(t) is the deviation, M(t) is the first flue gas component data, and L(t) is the second flue gas component data.

5. The method according to claim 4, wherein The calibrating the laser analyzer based on the deviation through a calibration algorithm includes: Construct a calibration model: Lc(t) = L(t) + k·D(t) where L(t) is the second flue gas component data, k is a calibration coefficient, and D(t) is the deviation.

6. The method according to claim 5, characterized in that, The calibrating the laser analyzer based on the deviation through a calibration algorithm includes: Calibrate the laser analyzer based on the output result of the calibration model.

7. The method according to claim 5, characterized in that, It further includes: Determine the calibration coefficient by least squares fitting according to historical data.

8. An on-line calibration device for a dry laser analyzer, characterized in that, It further includes: A determining unit for determining the first flue gas component data and the second flue gas component data; An obtaining unit for obtaining the deviation between the first flue gas component data and the second flue gas component data; A calibrating unit for calibrating the laser analyzer based on the deviation through a calibration algorithm.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored program, wherein when the program is executed by a processor, the steps of the online calibration method of the dry laser analyzer as described in any one of claims 1 to 7 are implemented.

10. An electronic device, characterized in that, The electronic device includes at least one processor and at least one memory connected to the processor; wherein the processor is used to call the program instructions in the memory and execute the steps of the online calibration method of the dry laser analyzer as described in any one of claims 1 to 7.

Images