Molten aluminum slag particle concentration mapping and automatic sampling system

Abstract

The invention provides a molten aluminum slag particle concentration mapping and automatic sampling system which comprises an ultrasonic transmitting and receiving array used for transmitting ultrasonic waves to molten aluminum and receiving echo signals; the signal processor is connected with the ultrasonic transmitting and receiving array and used for processing the echo signals and generating a molten aluminum slag particle concentration mapping graph; the mechanical execution unit is connected with the signal processor and is used for automatically adjusting a sampling position and completing sampling operation according to the concentration mapping graph; wherein the signal processor comprises a wavelet denoising module which is used for carrying out denoising processing on an echo signal; the scattering ratio calculation module is used for calculating the ratio of the slag particle scattering signal intensity to the incident signal intensity; the concentration calibration module is used for calibrating a concentration calculation coefficient according to the standard sample; and the back projection algorithm module is used for reconstructing a two-dimensional slag particle concentration distribution diagram, generating a real-time slag concentration mapping diagram through acoustic signal processing, and automatically adjusting the sampling position according to the real-time slag concentration mapping diagram, so that the sampling precision and representativeness are remarkably improved.

Description

Technical Field

[0001] This invention relates to an aluminum slag particle concentration mapping and automatic sampling system. Background Technology

[0002] This invention relates to the field of acoustic sensing and control system technology, and in particular to an aluminum molten slag particle concentration mapping and automatic sampling system based on ultrasonic signal processing, which is mainly used for real-time monitoring and accurate sampling of slag particle concentration in aluminum molten smelting process.

[0003] In aluminum smelting processes, existing technologies primarily rely on manual visual inspection or fixed-point sampling to detect the slag particle content in molten aluminum. These methods have significant limitations: manual visual inspection is heavily influenced by the operator's subjective experience and cannot provide quantitative analysis; fixed-point sampling suffers from poor sample representativeness due to the uneven distribution of slag particles in the molten aluminum, resulting in concentration variations of up to ±25%. More advanced detection technologies, such as X-rays or optical imaging systems, while enabling non-contact detection, suffer from severe signal attenuation and blurred images due to the high temperature and strong reflectivity of molten aluminum. The root cause of these technical deficiencies lies in the lack of real-time, precise means of sensing the distribution of slag particles within the molten aluminum and the inability to establish a dynamic feedback mechanism between slag concentration and sampling location.

[0004] Therefore, an aluminum slag particle concentration mapping and automatic sampling system is needed to solve the problems of large sampling error and poor representativeness in the existing technology, especially the sampling randomness caused by the inability to obtain the spatial distribution information of slag particles in real time. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of the prior art and provide an aluminum slag particle concentration mapping and automatic sampling system. This system generates a real-time slag concentration mapping map through acoustic signal processing and automatically adjusts the sampling position accordingly, thereby significantly improving sampling accuracy and representativeness. This objective is achieved as follows:

[0006] This invention proposes an aluminum slag particle concentration mapping and automatic sampling system, comprising: an ultrasonic transmitting and receiving array for transmitting ultrasonic waves to the aluminum slag and receiving echo signals; a signal processor connected to the ultrasonic transmitting and receiving array for processing the echo signals and generating an aluminum slag particle concentration mapping map; and a mechanical execution unit connected to the signal processor for automatically adjusting the sampling position and completing the sampling operation according to the concentration mapping map.

[0007] The signal processor includes: a wavelet denoising module for denoising the echo signal; a scattering ratio calculation module for calculating the ratio of the intensity of the scattered signal from the slag particles to the intensity of the incident signal; a concentration calibration module for calibrating the concentration and calculating the coefficient based on a standard sample; and a back projection algorithm module for reconstructing a two-dimensional slag particle concentration distribution map.

[0008] Furthermore, the ultrasonic transmitting and receiving array includes 16 piezoelectric transducers arranged in a ring array, each piezoelectric transducer having a built-in temperature compensation module.

[0009] Furthermore, the signal processor also includes: an ADC module with a sampling rate of 100 MS / s and a resolution of 14 bits; and a memory for signal buffering; wherein the signal processor performs an ultrasound scan in a cycle of less than 1 second.

[0010] Furthermore, the mechanical execution unit includes: a three-axis robotic arm; a sampling probe, the probe tip of which is made of silicon nitride ceramic material; and a force feedback sensor for controlling the sampling force accuracy.

[0011] Furthermore, the signal processor calculates the slag particle concentration using the following formula: Where C is the slag particle concentration and K is the system calibration coefficient. The intensity of the scattered signal. denoted as the incident signal intensity, and f as the ultrasonic frequency.

[0012] Furthermore, the back-projection algorithm module reconstructs the concentration distribution using the following formula: ,in, This is a weighting factor used to represent the directivity of the sound beam and the degree of propagation attenuation. These are concentration measurements in polar coordinates.

[0013] Furthermore, the hotspot region identification of the mechanical actuator determines the sampling location using the following priority scoring function: , among which, among which, Let A be the regional average concentration and A be the regional area.

[0014] Furthermore, the wavelet denoising module performs a 3-level decomposition based on the db4 wavelet basis and then applies adaptive thresholding, as shown in the following formula: ,in, For the standard deviation estimate of the noise in the j-th layer, The number of coefficients.

[0015] Furthermore, the sampling operation includes: the sampling probe of the mechanical actuator is vertically inserted into the molten aluminum to a depth of 15 mm at a speed of 10 mm / s, held for 10-15 seconds, and then withdrawn at a speed of 5 mm / s.

[0016] Compared with the prior art, the beneficial effects of the present invention are as follows: In terms of concentration detection accuracy, by generating a concentration mapping map of aluminum slag particles through an improved signal processor, the error of the traditional method of ±25% is reduced to within ±5%, and the repeatability error of the measurement of standard samples is only ±3.2%. With the help of a high-precision robotic arm, the sampling position is automatically adjusted according to the concentration mapping map to ensure that the sampling point is always located in the region of highest concentration. Actual tests show that this method improves the representativeness of the sampling by 82.7%. Attached Figure Description

[0017] Figure 1 This is a schematic diagram of a system for mapping and automatically sampling the concentration of aluminum slag particles. Detailed Implementation

[0018] To enhance understanding of the present invention, the present invention will be further described in detail below with reference to embodiments and accompanying drawings. These embodiments are only used to explain the present invention and do not constitute a limitation on the scope of protection of the present invention.

[0019] Please refer to Figure 1 This invention proposes an aluminum slag particle concentration mapping and automatic sampling system, comprising: an ultrasonic transmitting and receiving array for transmitting ultrasonic waves to the aluminum slag and receiving echo signals; a signal processor connected to the ultrasonic transmitting and receiving array for processing the echo signals and generating an aluminum slag particle concentration mapping map; and a mechanical execution unit connected to the signal processor for automatically adjusting the sampling position according to the concentration mapping map and completing the sampling operation.

[0020] The signal processor includes: a wavelet denoising module for denoising the echo signal; a scattering ratio calculation module for calculating the ratio of the intensity of the scattered signal from the slag particles to the intensity of the incident signal; a concentration calibration module for calibrating the concentration and calculating the coefficient based on a standard sample; and a back projection algorithm module for reconstructing a two-dimensional slag particle concentration distribution map.

[0021] In a preferred embodiment, the ultrasonic transmitting and receiving array includes 16 piezoelectric transducers arranged in a ring array, each with a built-in temperature compensation module. This array actively transmits ultrasonic waves and receives echo signals to achieve non-contact detection of slag particle distribution within molten aluminum. Its multi-transducer design can acquire multi-angle acoustic information, providing a data basis for subsequent concentration mapping. The piezoelectric transducers can be implemented using various piezoelectric materials, and the array arrangement can be a ring array, a linear array, or other geometric configurations to adapt to aluminum molten container shapes. Based on the propagation characteristics of ultrasonic waves in molten aluminum, scattered echoes are generated when encountering slag particles. The echo signal intensity has a quantitative relationship with the slag particle concentration. Through the coordinated operation of multiple transducers, sound beam focusing and scanning can be achieved, improving detection sensitivity and spatial resolution.

[0022] Specifically, the ultrasonic transmitting and receiving array consists of 16 piezoelectric transducers arranged in a ring, with an included angle of 22.5° between the centers of adjacent transducers. Each piezoelectric transducer is made of PZT-8 material, has a diameter of 15mm, and an adjustable operating frequency of 1-5MHz. The array is surrounded by an aluminum nitride ceramic protective cover, 3mm thick, capable of withstanding temperatures up to 1000℃. The ultrasonic transmitting and receiving array has a built-in array controller, and beamforming is achieved through an FPGA. Electron focusing is achieved by adjusting the phase difference Δφ between the transmissions of each transducer, as shown in the following formula: , among which, among which Let be the distance from the i-th transducer to the focal point. For reference distance, c = 4500 m / s is the speed of sound in molten aluminum.

[0023] In a preferred embodiment, the signal processor further includes: an ADC module with a sampling rate of 100 MS / s and a resolution of 14 bits; and a memory for signal buffering. The signal processor performs ultrasonic scanning in cycles of less than 1 second. By establishing a mathematical model of acoustic signal characteristics and slag particle concentration, the signal processing technology is used to extract the characteristic parameters of the scattered signal, thereby retrieving the spatial distribution of slag particles and determining the concentration mapping map.

[0024] In a preferred embodiment, the mechanical execution unit includes: a three-axis robotic arm; a sampling probe, the probe tip of which is made of silicon nitride ceramic material; and a force feedback sensor for controlling the sampling force accuracy. Based on the spatial distribution characteristics of the concentration map, the sampling mechanism is precisely controlled to reach the target position and complete the sampling operation through path planning and motion control algorithms.

[0025] Specifically, the sampling probe is made of silicon nitride ceramic, with a diameter of 8mm, a length of 300mm, an internal sampling chamber volume of 1.5mL, and a 200μm aluminum oxide heat insulation layer on the surface.

[0026] In a preferred embodiment, the signal processor calculates the slag particle concentration using the following formula: Where C is the slag particle concentration and K is the system calibration coefficient. The intensity of the scattered signal. Let be the incident signal intensity, and f be the ultrasonic frequency. The back-projection algorithm module reconstructs the concentration distribution using the following formula: ,in, This is a weighting factor used to represent the directivity of the sound beam and the degree of propagation attenuation. This module displays concentration measurements in polar coordinates, transforming discrete measurement data into a continuous concentration distribution image to visually represent the spatial distribution of slag particles. Based on the principle of acoustic projection, it uses mathematical transformations to invert the two-dimensional concentration distribution from multi-angle measurement data. The hotspot area identification of the mechanical actuator determines the sampling location using the following priority scoring function: , among which, among which, Let A be the average concentration of the region and A be the area of ​​the region. The wavelet denoising module performs a 3-level decomposition based on the db4 wavelet basis and then performs adaptive thresholding, as shown in the following formula: ,in, For the standard deviation estimate of the noise in the j-th layer, The number of coefficients is used to suppress various noise interferences in the molten aluminum environment, improve signal quality, and provide a clean signal source for subsequent processing. This module utilizes the multi-resolution analysis characteristics of wavelet transform to decompose the signal into different scale spaces and perform noise suppression at each scale.

[0027] In a preferred embodiment, the sampling operation includes: the sampling probe of the mechanical actuator is vertically inserted into the molten aluminum to a depth of 15 mm at a speed of 10 mm / s, held for 10-15 seconds, and then withdrawn at a speed of 5 mm / s.

[0028] This embodiment generates a real-time slag concentration mapping map through acoustic signal processing and automatically adjusts the sampling position accordingly. In terms of concentration detection accuracy, the improved signal processor generates an aluminum slag particle concentration mapping map, reducing the error of the traditional method from ±25% to within ±5%. The repeatability error of the measurement of standard samples is only ±3.2%. With the help of a high-precision robotic arm, the sampling position is automatically adjusted according to the concentration mapping map to ensure that the sampling point is always located in the area with the highest concentration. The actual test shows that this method improves the representativeness of the sample by 82.7%.

[0029] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A system for mapping and automatically sampling the particle concentration of molten aluminum slag, characterized in that, include: An ultrasonic transmitting and receiving array is used to transmit ultrasonic waves to molten aluminum and receive echo signals; a signal processor is connected to the ultrasonic transmitting and receiving array and is used to process the echo signals and generate a concentration mapping map of aluminum slag particles; a mechanical execution unit is connected to the signal processor and is used to automatically adjust the sampling position and complete the sampling operation according to the concentration mapping map. The signal processor includes: a wavelet denoising module for denoising the echo signal; a scattering ratio calculation module for calculating the ratio of the intensity of the scattered signal from the slag particles to the intensity of the incident signal; a concentration calibration module for calibrating the concentration and calculating the coefficient based on a standard sample; and a back projection algorithm module for reconstructing a two-dimensional slag particle concentration distribution map.

2. The aluminum slag particle concentration mapping and automatic sampling system according to claim 1, characterized in that, The ultrasonic transmitting and receiving array includes 16 piezoelectric transducers arranged in a ring array, and each piezoelectric transducer has a built-in temperature compensation module.

3. The aluminum slag particle concentration mapping and automatic sampling system according to claim 1, characterized in that, The signal processor further includes: an ADC module with a sampling rate of 100 MS / s and a resolution of 14 bits; and a memory for signal buffering; wherein the signal processor performs an ultrasound scan in a cycle of less than 1 second.

4. The aluminum slag particle concentration mapping and automatic sampling system according to claim 1, characterized in that, The mechanical execution unit includes: a three-axis robotic arm; a sampling probe with a probe tip made of silicon nitride ceramic material; and a force feedback sensor for controlling the sampling force accuracy.

5. The aluminum slag particle concentration mapping and automatic sampling system according to claim 1, characterized in that, The signal processor calculates the slag particle concentration using the following formula: Where C is the slag particle concentration and K is the system calibration coefficient. The intensity of the scattered signal. denoted as the incident signal intensity, and f as the ultrasonic frequency.

6. The aluminum slag particle concentration mapping and automatic sampling system according to claim 1, characterized in that, The back-projection algorithm module reconstructs the concentration distribution using the following formula: ,in, This is a weighting factor used to represent the directivity of the sound beam and the degree of propagation attenuation. These are concentration measurements in polar coordinates.

7. The aluminum molten slag particle concentration mapping and automatic sampling system according to claim 1, characterized in that, The hotspot region identification of the mechanical actuator determines the sampling location using the following priority scoring function: , Among them, among them, Let A be the regional average concentration and A be the regional area.

8. The aluminum slag particle concentration mapping and automatic sampling system according to claim 1, characterized in that, The wavelet denoising module performs a 3-level decomposition based on the db4 wavelet basis and then performs adaptive thresholding, as shown in the following formula: ,in, For the standard deviation estimate of the noise in the j-th layer, The number of coefficients.

9. The aluminum slag particle concentration mapping and automatic sampling system according to claim 1, characterized in that, The sampling operation includes: the sampling probe of the mechanical actuator is vertically inserted into the molten aluminum to a depth of 15mm at a speed of 10mm / s, held for 10-15 seconds, and then withdrawn at a speed of 5mm / s.

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