Method and system for measuring thickness of pool bottom of glass kiln based on radar

Abstract

The invention belongs to the technical field of glass manufacturing, and discloses a radar-based glass kiln bottom thickness measuring method and system.The radar-based glass kiln bottom thickness measuring method comprises the steps that firstly, according to different kiln bottom materials, the propagation speed of radar waves in the kiln bottom materials is corrected, and then the propagation speed of the radar waves in the kiln bottom materials is corrected; according to the structure of the glass kiln, the most appropriate radar installation position is calibrated, the accuracy of a measurement result is ensured, then, a radar wave compensation coefficient is obtained according to different temperatures of the kiln, and finally, the thickness of the pool bottom is calculated by combining a propagation speed correction coefficient, the radar wave compensation coefficient and collected radar wave parameters. The device can achieve the quick and accurate measurement in the operation state of the kiln, and is remarkable in economic benefit and practical value.

Description

Technical Field

[0001] The present invention belongs to the technical field of glass manufacturing, and particularly relates to a method and system for measuring the thickness of the bottom of a glass furnace based on radar. Background Technique

[0002] In the process of glass production, as the core equipment, the operating conditions of the glass furnace directly affect the quality and production efficiency of the glass. The thickness of the bottom of the furnace is a key parameter. With the long-term use of the furnace, the refractory material at the bottom will gradually become thinner due to factors such as high-temperature erosion and glass liquid scouring. If the bottom thickness is too thin, it may cause liquid leakage in the furnace, trigger serious production accidents, increase energy consumption, and reduce production efficiency.

[0003] Currently, there are many drawbacks in the traditional methods for measuring the thickness of the bottom of a glass furnace. For example, the manual measurement method is not only inefficient but also needs to be carried out when the furnace is out of production, affecting production continuity; some measurement methods based on contact sensors have short sensor life and difficult-to-guarantee measurement accuracy due to the high-temperature and highly corrosive environment inside the glass furnace. Therefore, the present invention proposes a method and system for measuring the thickness of the bottom of a glass furnace based on radar. Summary of the Invention

[0004] The purpose of the present invention is to provide a method and system for measuring the thickness of the bottom of a glass furnace based on radar to solve the problems faced in the above background technique.

[0005] The purpose of the present invention can be achieved by the following technical solutions:

[0006] A method for measuring the thickness of the bottom of a glass furnace based on radar, the method comprising the following steps:

[0007] Step S1, construct a thickness measurement system, the system comprising: a radar transmitting device, a radar receiving device, a data processing module and a display and storage module;

[0008] Step S2, calibrate the measurement system using a standard sample with a known thickness to obtain the propagation speed correction coefficient of the radar wave in the bottom material of the furnace;

[0009] Step S3, set up the radar-based measurement system, install the radar transmitting device and the radar receiving device at appropriate positions on the outer wall corresponding to the bottom of the furnace, and calibrate the installation position of the radar transmitting device;

[0010] Step S4, in the normal operation state of the glass furnace, start the radar transmitting device and transmit high-frequency radar wave signals to the bottom according to the set parameters;

[0011] Step S5: Analyze the parameter characteristics of the reflected signal, and combine with the propagation speed of the radar wave in the bottom material of the pool. Use a specific algorithm to calculate the thickness values at different positions of the bottom of the pool;

[0012] Step S6: The data processing module transmits the calculated bottom thickness value of the pool to the display and storage module, and displays it in an intuitive graphical or numerical form.

[0013] As a further description of the technical solution of the present invention, the specific process of step S2 includes:

[0014] Step S21: Construct a calibration mathematical model: Wherein, v is the propagation speed of the radar wave in the object to be measured, Δt is the time difference between the transmitted signal and the received reflected signal, and k is the propagation speed correction coefficient;

[0015] Step S22: Select a standard sample with a known thickness as the calibration target;

[0016] Step S23: Assemble the calibration target and set the transmission frequency and pulse width parameters of the radar wave;

[0017] Step S24: Start the radar transmitting device and collect the time difference between the transmitted signal and the received reflected signal;

[0018] Step S25: Obtain the propagation speed of the radar wave in the calibration target, and substitute it into the calibration mathematical model to obtain the propagation speed correction coefficient.

[0019] As a further description of the technical solution of the present invention, the specific process of step S3 includes:

[0020] Step S31: According to the geometric shape and size of the bottom of the kiln furnace, divide the bottom of the pool into multiple regular measurement areas;

[0021] Step S32: Place the standard sample with a known thickness in different measurement areas at the bottom of the pool;

[0022] Step S33: Based on the propagation characteristics of the radar wave and the measurement accuracy requirements, select 10 best theoretical positions to install the radar transmitting device respectively;

[0023] Step S34: Start the radar transmitting device and collect the parameters at 10 best theoretical positions respectively;

[0024] Step S35: Substitute the 10 groups of collected data and the thickness of the standard sample into the calculation model respectively: Calculate whether the 10 groups of data and the thickness of the standard sample meet the above calculation model;

[0025] Step S36: Determine the best theoretical position with the smallest difference between the left and right sides of the calculation model as the actual installation position;

[0026] Step S37: Record the coordinate information of the actual installation position relative to the reference point on the outer wall of the kiln for reference during subsequent maintenance and reinstallation.

[0027] As a further description of the technical solution of the present invention, the specific process of step S5 includes:

[0028] Step S51: The data processing module performs amplification and filtering preprocessing on the received radar wave signals.

[0029] Step S52: Obtain the propagation speed of the radar wave in the bottom material of the pool and the time difference between the transmitted signal and the received reflected signal.

[0030] Step S53: Substitute the obtained parameters into the thickness calculation model to obtain the bottom thickness d of the pool, where ∈ is the temperature compensation coefficient, which changes with temperature.

[0031] As a further description of the technical solution of the present invention, the acquisition process of the temperature compensation coefficient includes:

[0032] Intercept a known-thickness refractory brick sample of the same batch as the kiln, drill holes on the surface of the sample and embed thermocouples.

[0033] In a high-temperature experimental furnace, raise the temperature from room temperature to 1600°C at a rate of 20°C / min, and synchronously collect the time difference Δt between the transmitted signal and the received reflected signal at intervals of 50°C.

[0034] Then, through the thickness calculation model obtain the temperature compensation coefficients at different temperatures.

[0035] As a further description of the technical solution of the present invention, the specific process of step S6 includes:

[0036] The data processing module transmits the calculated bottom thickness value of the pool to the display and storage module, which is displayed in an intuitive graphical or digital form. At the same time, the data processing module also stores the measurement data in the local database for subsequent query, analysis, and comparison, providing data support for the maintenance and management of the kiln.

[0037] As a further description of the technical solution of the present invention, the display and storage module also has a human-computer interaction function to perform operations such as zooming, panning, and switching the display mode on the displayed content, so as to view the bottom thickness information of the area of interest in more detail.

[0038] A radar-based glass kiln bottom thickness measurement system, the system includes:

[0039] A data acquisition module for real-time acquisition of measurement parameter information;

[0040] The data analysis module analyzes the measured parameter information and obtains the bottom thickness of the pool;

[0041] The data processing module processes the collected parameters and analysis results and sends them to the display and storage module;

[0042] The display and storage module is used to intuitively display the bottom thickness value of the pool and the corresponding parameters.

[0043] Advantages of the present invention:

[0044] The present invention proposes a method for measuring the bottom thickness of a glass furnace pool based on radar. First, according to the different materials of the furnace bottom, the propagation speed of radar waves in the furnace bottom materials is corrected. Then, according to the structure of the glass furnace, the most suitable radar installation position is calibrated to ensure the accuracy of the measurement results. Then, according to the different temperatures of the furnace, the radar wave compensation coefficient is obtained. Finally, the bottom thickness is calculated by combining the propagation speed correction coefficient, the radar wave compensation coefficient and the collected radar wave parameters, and is intuitively displayed through the display and storage module. It can achieve fast and accurate measurement under the operating state of the furnace, and has significant economic benefits and practical value.

[0045] Of course, it is not necessary for any product implementing the present invention to simultaneously achieve all the above-mentioned advantages.

[0046] BRIEF DESCRIPTION OF THE DRAWINGS To more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for describing the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0047] Figure 1 It is a partial process schematic diagram of the method for measuring the bottom thickness of a glass furnace pool based on radar of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0048] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts belong to the scope of protection of the present invention.

[0049] Please refer to Figure 1 As shown, a method for measuring the bottom thickness of a glass furnace pool based on radar is disclosed. The method includes the following steps:

[0050] Step S1. Construct a thickness measurement system, which consists of a radar transmitting device, a radar receiving device, a data processing module, and a display and storage module;

[0051] Step S2. Calibrate the measurement system using a standard sample with a known thickness to obtain the propagation speed correction coefficient of the radar wave in the bottom material of the furnace;

[0052] Step S3. Set up the radar-based measurement system, install the radar transmitting device and the radar receiving device at appropriate positions on the corresponding outer wall of the bottom of the furnace, and calibrate the installation position of the radar transmitting device;

[0053] Step S4. When the glass furnace is operating normally, start the radar transmitting device and transmit high-frequency radar wave signals to the bottom of the furnace according to the set parameters;

[0054] Step S5. Analyze the parameter characteristics of the reflected signal, combine the propagation speed of the radar wave in the bottom material of the furnace, and use a specific algorithm to calculate the thickness values at different positions of the bottom of the furnace;

[0055] Step S6. The data processing module transmits the calculated thickness values of the bottom of the furnace to the display and storage module, which are displayed in an intuitive graphical or numerical form.

[0056] Through the above technical solution, the present invention proposes a method for measuring the thickness of the bottom of a glass furnace based on radar. First, according to the different materials of the bottom of the furnace, the propagation speed of the radar wave in the bottom material of the furnace is corrected. Then, according to the structure of the glass furnace, the most suitable radar installation position is calibrated to ensure the accuracy of the measurement results. Then, according to the different temperatures of the furnace, the radar wave compensation coefficient is obtained. Finally, the thickness of the bottom of the furnace is calculated by combining the propagation speed correction coefficient, the radar wave compensation coefficient, and the collected radar wave parameters, and is intuitively displayed through the display and storage module. It can achieve rapid and accurate measurement under the operating state of the furnace, and has significant economic benefits and practical value.

[0057] The specific process of step S2 includes:

[0058] Step S21. Construct a calibration mathematical model: where v is the propagation speed of the radar wave in the object to be measured, Δt is the time difference between the transmitted signal and the received reflected signal, and k is the propagation speed correction coefficient;

[0059] Step S22. Select a standard sample with a known thickness as the calibration target;

[0060] Step S23. Assemble the calibration target and set the transmission frequency and pulse width parameters of the radar wave;

[0061] Step S24: Activate the radar transmitting device and collect the time difference between the transmitted signal and the received reflected signal.

[0062] Step S25: Obtain the propagation speed of the radar wave in the calibration target, and substitute it into the calibration mathematical model to obtain the propagation speed correction coefficient.

[0063] Through the above technical solution, this embodiment provides a method for obtaining the propagation speed correction coefficient. Select a standard sample with a known thickness as the calibration target, collect the time difference between the transmitted signal and the received reflected signal, obtain the propagation speed of the radar wave in the calibration target, and substitute it into the calibration mathematical model to obtain the propagation speed correction coefficient, so as to improve the measurement accuracy.

[0064] The specific process of step S3 includes:

[0065] Step S31: Divide the bottom of the kiln into multiple regular measurement areas according to the geometric shape and size of the bottom of the kiln.

[0066] Step S32: Place standard samples with known thicknesses in different measurement areas at the bottom of the kiln.

[0067] Step S33: Based on the propagation characteristics of the radar wave and the measurement accuracy requirements, select 10 optimal theoretical positions to install the radar transmitting device.

[0068] Step S34: Activate the radar transmitting device and collect the parameters at 10 optimal theoretical positions respectively.

[0069] Step S35: Substitute the 10 groups of collected data and the thickness of the standard sample into the calculation model respectively: Calculate whether the 10 groups of data and the thickness of the standard sample meet the above calculation model.

[0070] Step S36: Determine the optimal theoretical position with the smallest difference between the left and right sides of the calculation model as the actual installation position.

[0071] Step S37: Record the coordinate information of the actual installation position relative to the reference point on the outer wall of the kiln for reference during subsequent maintenance and reinstallation.

[0072] Through the above technical solution, this embodiment provides a method for calibrating the installation position of the radar device. According to the geometric shape and size of the bottom of the kiln, divide the bottom of the kiln into multiple regular measurement areas, place standard samples with known thicknesses in different measurement areas at the bottom of the kiln, select 10 optimal theoretical positions to install the radar transmitting device, substitute the 10 groups of collected data and the thickness of the standard sample into the calculation model respectively, calculate whether the 10 groups of data and the thickness of the standard sample meet the above calculation model, and determine the optimal theoretical position with the smallest difference between the left and right sides of the calculation model as the actual installation position.

[0073] The specific process of step S5 includes:

[0074] Step S51: The data processing module performs amplification and filtering preprocessing on the received radar wave signals.

[0075] Step S52: Obtain the propagation speed of the radar wave in the bottom material of the pool and the time difference between the transmitted signal and the received reflected signal.

[0076] Step S53: Substitute the obtained parameters into the thickness calculation model to obtain the bottom thickness d of the pool, where ∈ is the temperature compensation coefficient, which varies with temperature.

[0077] The process of obtaining the temperature compensation coefficient includes:

[0078] Intercept a refractory brick sample with a known thickness from the same batch as the kiln, drill holes on the surface of the sample and embed thermocouples.

[0079] In a high-temperature experimental furnace, raise the temperature from room temperature to 1600°C at a rate of 20°C / min, and synchronously collect the time difference Δt between the transmitted signal and the received reflected signal at every 50°C interval.

[0080] Then, through the thickness calculation model obtain the temperature compensation coefficients at different temperatures.

[0081] Through the above technical solution, this embodiment provides a thickness calculation method, compensates the thickness according to the working temperature of the kiln during measurement, intercepts a refractory brick sample with a known thickness from the same batch as the kiln, drills holes on the surface of the sample and embeds thermocouples, raises the temperature from room temperature to 1600°C at a rate of 20°C / min in a high-temperature experimental furnace, synchronously collects the time difference Δt between the transmitted signal and the received reflected signal at every 50°C interval, obtains the temperature compensation coefficients at different temperatures through the thickness calculation model, and then obtains the bottom thickness of the pool according to the actual measured parameters in combination with the temperature compensation coefficient and the speed correction coefficient.

[0082] The specific process of step S6 includes:

[0083] The data processing module transmits the calculated bottom thickness value of the pool to the display and storage module, which is displayed in an intuitive graphical or digital form. At the same time, the data processing module also stores the measurement data in the local database for subsequent query, analysis and comparison, providing data support for the maintenance and management of the kiln.

[0084] The display and storage module also has a human-computer interaction function, and can perform operations such as zooming, panning, and switching the display mode on the displayed content, so as to view the bottom thickness information of the area of interest in more detail.

[0085] A radar-based measuring system for the bottom thickness of a glass furnace, the system comprising:

[0086] A data acquisition module for real-time acquisition of measured parameter information;

[0087] A data analysis module for analyzing the measured parameter information and obtaining the bottom thickness;

[0088] A data processing module for processing the acquired parameters and analysis results and sending them to the display and storage module;

[0089] A display and storage module for visually displaying the bottom thickness value and the corresponding parameters.

[0090] The above content is only an example and illustration of the concept of the present invention. Those skilled in the art of the present technology may make various modifications or supplements to the described specific embodiments or use similar ways to replace them, as long as they do not deviate from the concept of the invention or exceed the scope defined by this claim book, they shall fall within the protection scope of the present invention.

Claims

1. A method for measuring the thickness of the bottom of a glass furnace based on radar, characterized in that, The method includes the following steps: Step S1: Construct a thickness measurement system, which consists of a radar transmitting device, a radar receiving device, a data processing module, and a display and storage module; Step S2: Calibrate the measurement system using a standard sample with a known thickness to obtain the propagation speed correction coefficient of radar waves in the bottom material of the kiln; Step S3: Set up the radar-based measurement system, install the radar transmitting device and the radar receiving device at appropriate positions on the corresponding outer wall of the kiln bottom, and calibrate the installation position of the radar transmitting device; Step S4: When the glass kiln is operating normally, start the radar transmitting device and transmit high-frequency radar wave signals to the bottom according to the set parameters; Step S5: Analyze the parameter characteristics of the reflected signal, combine with the propagation speed of radar waves in the bottom material, and calculate the thickness values at different positions of the bottom using a specific algorithm; Step S6: The data processing module transmits the calculated bottom thickness values to the display and storage module, which are displayed in an intuitive graphical or digital form.

2. The method for measuring the bottom thickness of a glass furnace based on radar according to claim 1, characterized in that, The specific process of step S2 includes: Step S21, constructing a calibration mathematical model: Wherein, v is the propagation speed of the radar wave in the target to be measured, Δt is the time difference between the transmitted signal and the received reflected signal, and k is the propagation speed correction coefficient; Step S22: Select a standard sample with a known thickness as the calibration target; Step S23: Assemble the calibration target and set the transmission frequency and pulse width parameters of the radar wave; Step S24: Start the radar transmitting device and collect the time difference between the transmitted signal and the received reflected signal; Step S25: Obtain the propagation speed of radar waves in the calibration target and substitute it into the calibration mathematical model to obtain the propagation speed correction coefficient.

3. The method for measuring the bottom thickness of a glass furnace based on radar according to claim 1, characterized in that, The specific process of step S3 includes: Step S31: Divide the bottom of the kiln into multiple regular measurement areas according to the geometric shape and size of the kiln bottom; Step S32: Place standard samples with known thicknesses in different measurement areas of the bottom; Step S33: Based on the propagation characteristics of radar waves and the measurement accuracy requirements, select 10 optimal theoretical positions to install the radar transmitting device; Step S34: Start the radar transmitting device and collect the parameters at 10 optimal theoretical positions respectively; Step S35: Substitute the 10 sets of collected data and the thickness of the standard sample into the calculation model respectively: Calculate whether the 10 sets of data and the thickness of the standard sample satisfy the above calculation model; Step S36: Determine the optimal theoretical position with the smallest difference between the left and right sides of the calculation model as the actual installation position; Step S37: Record the coordinate information of the actual installation position relative to the reference point on the outer wall of the kiln for reference during subsequent maintenance and reinstallation.

4. A method for measuring the thickness of the bottom of a glass furnace based on radar according to claim 1, characterized in that, The specific process of step S5 includes: Step S51: The data processing module performs preprocessing such as amplification and filtering on the received radar wave signals; Step S52: Obtain the propagation speed of radar waves in the bottom material and the time difference between the transmitted signal and the received reflected signal; Step S53: Substitute the obtained parameters into the thickness calculation model Obtain the bottom thickness d, where ∈ is the temperature compensation coefficient, which varies with temperature.

5. The method for measuring the bottom thickness of a glass furnace based on radar according to claim 4, characterized in that, The process of obtaining the temperature compensation coefficient includes: Intercept a refractory brick sample with a known thickness from the same batch as the kiln, drill holes on the sample surface and embed thermocouples; In a high-temperature furnace, heat from room temperature to 1600 °C at a rate of 20 °C / min, and synchronously collect the time difference Δt between the transmitted signal and the received reflected signal at intervals of 50 °C; Then, through the thickness calculation model obtain the temperature compensation coefficients at different temperatures.

6. A method for measuring the bottom thickness of a glass furnace based on radar according to claim 1, characterized in that, The specific process of step S6 includes: The data processing module transmits the calculated bottom thickness value to the display and storage module, which is presented in an intuitive graphical or numerical form. Meanwhile, the data processing module also stores the measurement data in the local database for subsequent query, analysis, and comparison, providing data support for the maintenance and management of the kiln.

7. The method for measuring the bottom thickness of a glass furnace based on radar according to claim 6, characterized in that, The display and storage module also has a human-computer interaction function to perform operations such as zooming, panning, and switching the display mode on the displayed content, so as to view the bottom thickness information of the area of interest in more detail.

8. A radar-based glass furnace bottom thickness measurement system, applicable to the radar-based glass furnace bottom thickness measurement method described in any one of claims 1-7, characterized in that, The system includes: A data acquisition module for real-time acquisition of the measured parameter information; A data analysis module for analyzing the measured parameter information and obtaining the bottom thickness; A data processing module for processing the acquired parameters and analysis results and sending them to the display and storage module; A display and storage module for intuitively displaying the bottom thickness value and the corresponding parameters.

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