Sound wave multiple reflection sediment concentration measuring method based on FPGA (Field Programmable Gate Array)

Abstract

The invention discloses an FPGA-based sound wave multiple reflection sediment concentration measurement method. The method comprises the following steps: constructing an ultrasonic underwater measurement system capable of realizing ultrasonic multiple reflection and driving the ultrasonic underwater measurement system to work; an ultrasonic transducer is driven by the FPGA to emit ultrasonic waves; echo signals of the ultrasonic waves passing through the turbid liquid are collected, subjected to analog-to-digital conversion and then transmitted to the FPGA; digital filtering and peak detection are carried out on the echo data based on the FPGA; according to a peak value detection result, an ultrasonic attenuation coefficient is calculated based on the FPGA in combination with numerical integration; for a plurality of turbid liquid bodies of the same type with known sediment concentrations, the second step to the fifth step are executed respectively, ultrasonic attenuation coefficients under different concentrations are obtained, and then fitting is conducted on the ultrasonic attenuation coefficients and the concentrations to obtain a regression equation of the attenuation coefficients and the sediment concentrations; and executing the second step to the sixth step to obtain an ultrasonic attenuation coefficient aiming at a to-be-detected turbid liquid body, and substituting the ultrasonic attenuation coefficient into the regression equation to obtain the sediment concentration of the to-be-detected turbid liquid body. According to the method, the defects of the traditional method in real-time performance and precision are overcome, and the real-time performance and accuracy of sediment concentration measurement are remarkably improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of sediment measurement, and particularly relates to a method for measuring sediment concentration based on multiple reflections of acoustic waves by FPGA. Background Technique

[0002] Rivers are important sources of water resources and core components of ecosystems. Changes in sediment concentration not only reflect water quality conditions but are also closely related to environmental problems such as soil erosion and water pollution. Excessive sediment concentration may lead to river channel siltation, rising water levels, and increased flood risks, thereby threatening the aquatic ecosystem, river channel stability, and water resource management. In the fields of water conservancy projects and soil and water conservation, accurate measurement of sediment concentration can provide a scientific basis for reservoir operation, siltation treatment, and optimization of land use. Therefore, adopting a scientific and reasonable method to accurately monitor river sediment concentration is of great significance for environmental protection, water resource management, and maintenance of ecological balance.

[0003] Common methods include the weighing method, optical method, and acoustic method. Although the traditional weighing method has high accuracy, it is complex in operation and low in efficiency, making it difficult to meet the requirements of dynamic monitoring. The optical method has a fast response speed but is easily affected by water turbidity and chromaticity, increasing the complexity of error compensation and limiting its application range. In contrast, the acoustic method is not affected by chromaticity and turbidity. Among them, the area ratio method measures the ultrasonic reflection echo and is not affected by particle scattering, so it is widely used in sediment concentration measurement. However, the traditional area ratio method uses rectangular integration, resulting in low measurement accuracy. The traditional acoustic area ratio method is difficult to accurately reflect the continuous attenuation of the echo signal in the case of large signal changes or strong noise interference, and the measurement accuracy is low, especially significant in the measurement of high-concentration or coarse-grained sediment. Summary of the Invention

[0004] The purpose of the present invention is to provide a method for measuring sediment concentration based on multiple reflections of acoustic waves, which solves the problem of low measurement accuracy caused by insufficient fitting accuracy of the signal non-linear attenuation of the traditional acoustic area ratio method.

[0005] The technical solution for achieving the purpose of the present invention is: A method for measuring sediment concentration based on multiple reflections of acoustic waves by FPGA, the method includes:

[0006] Step 1, build an ultrasonic underwater measurement system capable of realizing multiple reflections of ultrasonic waves, including an ultrasonic transducer;

[0007] Step 2, generate an excitation signal through DDS modulation and drive in the FPGA, and convert and output it through a digital-to-analog converter to drive the ultrasonic transducer to emit ultrasonic waves;

[0008] Step 3: Collect the echo signal of the ultrasonic wave passing through the suspension liquid, convert the analog echo signal into a digital signal, and then transmit it to the FPGA;

[0009] Step 4: Perform digital filtering and peak detection on the echo data based on the FPGA;

[0010] Step 5: According to the peak detection result, calculate the ultrasonic attenuation coefficient based on the FPGA combined with numerical integration;

[0011] Step 6: For multiple suspensions of the same type with known sediment concentrations, respectively execute Steps 2 to 5 to obtain the ultrasonic attenuation coefficients at different concentrations, and then fit the ultrasonic attenuation coefficients and concentrations to obtain the regression equation of the attenuation coefficient and sediment concentration;

[0012] Step 7: For the suspension to be measured, execute Steps 2 to 6 to obtain the ultrasonic attenuation coefficient, and substitute the ultrasonic attenuation coefficient into the regression equation of the attenuation coefficient and sediment concentration to obtain the sediment concentration of the suspension to be measured.

[0013] Further, in Step 1, the ultrasonic underwater measurement system includes: the ultrasonic transducer, the reflection wall, and a distance control track arranged between the ultrasonic transducer and the reflection wall;

[0014] The ultrasonic transducer is used to emit ultrasonic waves to the suspension liquid and receive the scattered signals;

[0015] The reflection wall is used to reflect the ultrasonic wave signal to generate an echo signal;

[0016] The distance control track is used to adjust and control the distance between the ultrasonic transducer and the reflection wall.

[0017] Further, the ultrasonic underwater measurement system further includes: a fixing rod for fixing the ultrasonic underwater measurement system in the suspension.

[0018] Further, in Step 3, the echo signal is transmitted to the FIFO buffer area of the FPGA.

[0019] Further, in Step 4, a Chebyshev type-I bandpass FIR filter is implemented by the FPGA to perform FIR digital filtering on the echo data, specifically including:

[0020] Use a shift register to implement a delay line. When a new input signal arrives, the delay line pushes the current signal in, and at the same time, the historical data moves backward in sequence to form a sliding window;

[0021] Adopt a parallel pipelined multiplication and accumulation technique. Each input signal is multiplied by the corresponding filter coefficient, all multiplications are performed simultaneously, and all products are accumulated through an adder tree to generate the filtered output value.

[0022] Further, in step 4, peak detection is performed by an FPGA, including extracting the peaks of each echo. Specifically: The peak is detected by using a comparison register combined with a pipeline structure. The process includes:

[0023] Step 4-1: Set the minimum threshold A for the echo peak amplitude, initialize the initial value of the echo sequence number i to 1, and initialize a pesks array and a Pesks array. There is an initial value in the pesks array;

[0024] Step 4-2: Initially detect the peak of the i-th echo and store the peak in the pesks array;

[0025] Step 4-3: Perform a quadratic interpolation operation on the peaks in the pesks array except the initial value. Then, based on the adjacent sampling points before and after the peak, fit out the peak position and amplitude, and eliminate false peaks according to the amplitude change of the adjacent sampling points;

[0026] Step 4-4: Repeat step 4-3 until there is one peak remaining for the i-th echo;

[0027] Step 4-5: In the pesks array, determine whether the peak corresponding to the i-th echo is less than the previous value. If so, it indicates that the peak corresponding to the current i-th echo is a valid peak, and then step 4-6 is executed; otherwise, it indicates that the peak corresponding to the current i-th echo is an invalid peak, the peak is eliminated, and step 4-2 is returned for execution;

[0028] Step 4-6: Store the valid peak and its echo sequence number in the Pesks array;

[0029] Step 4-7: Determine whether the valid peak is less than the minimum threshold A. If so, output the valid peak and the corresponding echo sequence number. Otherwise, increment the echo sequence number i by 1, and then execute step 4-8;

[0030] Step 4-8: Determine whether the echo sequence number i is greater than the total number of echoes. If it is greater, end the peak detection process. Otherwise, return to execute step 4-2.

[0031] Further, in step 5, according to the peak detection result, based on the FPGA combined with numerical integration, calculate the ultrasonic attenuation coefficient, specifically including:

[0032] Step 5-1: Construct an echo sequence number - echo signal amplitude sequence diagram;

[0033] Step 5-2: Consider the interval between the first echo and the last echo as the integration interval, and take the distance between these two echoes as the length of the integration interval;

[0034] Step 5-3, adaptively divide the integral interval;

[0035] Step 5-4, randomly calculate the areas of any two echoes, and calculate the ratio of the two areas; the area is the area of the triangular region formed between the amplitude of the echo and the first position where the echo decays to zero;

[0036] Step 5-5, convert the area ratio to a floating-point number;

[0037] Step 5-6, calculate the attenuation coefficient α according to the area ratio in Step 5-5:

[0038]

[0039] where A 1 and A 2 are the areas of the two echoes respectively, and L is the distance between the ultrasonic transducer and the reflection wall;

[0040] Step 5-7, determine whether the accuracy of the attenuation coefficient α meets the preset condition. If it meets, convert the attenuation coefficient α to a fixed-point format and output, and then end the process. Otherwise, return to execute Step 5-4.

[0041] Further, the adaptive division of the integral interval in Step 5-3 specifically includes:

[0042] Step 5-3-1, assume the total number of echoes is N + 1, and equally divide the integral interval into N intervals, that is, the two endpoints of each interval correspond to two adjacent echoes;

[0043] Step 5-3-2, for each interval, calculate the absolute value of the change rate R i of the peaks of the two corresponding echoes, and the peak value is obtained from Step 4; then determine whether the absolute value of the change rate R i is greater than the preset change rate threshold R. If it is greater, execute Step 5-3-3;

[0044] Step 5-3-3, divide the interval into two equal parts through the intermediate endpoint value, and then return to execute Step 5-3-2;

[0045] Step 5-3-4, repeatedly execute from Step 5-3-2 to Step 5-3-3 until the absolute value of the change rate corresponding to all intervals is less than the preset change rate threshold R.

[0046] Further, the intermediate endpoint value in Step 5-3-3 is obtained by quadratic interpolation fitting according to the left and right endpoint values.

[0047] Further, the calculation of the area of the echo in Step 5-4 specifically includes:

[0048] Determine whether the total number of intervals in the triangle region corresponding to the echo is odd or even;

[0049] If it is even, use the composite Simpson's method to perform integral approximation calculation on two adjacent intervals to obtain the area;

[0050] If it is odd, use the composite Simpson's method to perform integral approximation calculation on the previous even number of intervals in sequence, and use the trapezoidal method to approximate the calculation for the remaining one interval.

[0051] Compared with the prior art, the remarkable advantages of the present invention are as follows:

[0052] (1) An improved acoustic method is adopted for sediment concentration measurement, overcoming the deficiencies of traditional methods in real-time performance and accuracy, and significantly improving the real-time performance and accuracy of sediment concentration measurement. This research is of great significance for environmental monitoring, river regulation, and in-depth exploration of sediment transport laws, and can provide a solid scientific basis for water resource management, ecological protection, and engineering planning.

[0053] (2) Based on the ultrasonic attenuation theory, the present invention measures the amplitude of the echo signal through multiple reflections, accurately capturing the attenuation characteristics of ultrasonic waves when propagating in the sediment solution. Compared with traditional single-transmission measurement, it can more accurately reflect the energy attenuation law of ultrasonic signals as the propagation distance increases, and is applicable to high-precision monitoring of sediment concentration in different concentration ranges.

[0054] (3) An innovative adaptive interval segmentation method is proposed, which dynamically adjusts the segmentation strategy according to the change rate of data. This method can flexibly handle the changes in complex waveforms in echo data. It finely divides the processing intervals according to the local change characteristics of the echo signal, performs more accurate analysis and processing on the severely changing regions, and at the same time avoids excessive calculation in the stable regions, thereby effectively improving the accuracy and efficiency of echo signal processing and being able to automatically adapt to the distribution and changes of different data.

[0055] (4) An innovative peak detection method is proposed, which can significantly improve the accuracy of echo signal processing by combining multiple steps such as preliminary detection, quadratic interpolation, pseudo-peak elimination, validity judgment, and threshold screening. This method quickly screens potential peaks through preliminary detection and accurately calculates the specific position and amplitude of the peaks using quadratic interpolation, effectively avoiding positioning errors caused by the sampling point interval. During the processing, pseudo-peak elimination can filter out invalid peaks caused by noise or minor fluctuations through rapid detection of amplitude changes, ensuring the reliability of the finally output peak data. Through validity judgment and threshold screening, invalid peaks with too low amplitudes are further eliminated, ensuring the rationality and accuracy of the detection results. Moreover, this multi-step peak detection method can accurately adapt to the waveform changes of complex echo signals, improve the calculation efficiency while ensuring high precision, has good real-time performance and strong anti-interference ability, and is applicable to signal detection tasks in various complex environments.

[0056] (5) To improve the measurement accuracy, this invention adopts a numerical integration scheme that combines the composite Simpson method and the trapezoidal method, and selects an adaptive integral interval segmentation method to improve the integral calculation accuracy. It can better reflect the subtle fluctuations of the signal, reduce the influence of external factors such as temperature fluctuations, power supply instability, and electromagnetic interference, and enhance the robustness and stability of the method.

[0057] (6) When implementing complex mathematical operations such as multiplication, division, logarithm, and integration in FPGA, this invention uses floating-point format operations. Compared with traditional fixed-point number calculations, floating-point operations have a higher dynamic range and accuracy, can effectively prevent numerical overflow and rounding errors, and improve the stability and accuracy in high-precision operation scenarios.

[0058] (7) With the help of optimized algorithm design and pipeline parallel processing technology, a higher calculation speed is achieved in FPGA, giving full play to the potential of hardware resources, meeting the real-time and accuracy requirements of signal processing, and further improving the overall performance and stability of the method.

[0059] The present invention will be further described in detail below with reference to the accompanying drawings. Description of the Drawings

[0060] Figure 1 It is a principle block diagram of the acoustic wave multiple reflection sediment concentration measurement method based on FPGA.

[0061] Figure 2 It is a schematic diagram of the ultrasonic underwater measurement system.

[0062] Figure 3 It is a flowchart of FIR digital filter implementation.

[0063] Figure 4 It is a flowchart of echo peak detection.

[0064] Figure 5 It is a flowchart for calculating the ultrasonic attenuation coefficient. Specific implementation manners

[0065] In order to make the objectives, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0066] It should be noted that if there are directional indications (such as up, down, left, right, front, back...) involved in the embodiments of the present invention, the directional indications are only used to explain the relative positional relationship and movement conditions between components in a specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indications will also change accordingly.

[0067] In addition, if there are descriptions involving "first", "second", etc. in the embodiments of the present invention, the descriptions of "first", "second", etc. are only for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include at least one of such features. In addition, the technical solutions between various embodiments can be combined with each other, but it must be based on the fact that those of ordinary skill in the art can implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be considered that such a combination of technical solutions does not exist and is not within the protection scope required by the present invention.

[0068] In one embodiment, a method for measuring sediment concentration based on multiple reflections of sound waves by FPGA is provided, including the following steps:

[0069] Step 1, build an ultrasonic underwater measurement system capable of realizing multiple reflections of ultrasonic waves, including an ultrasonic transducer;

[0070] Step 2, generate an excitation signal through DDS modulation driving in the FPGA, convert and output it through a digital-to-analog converter, and drive the ultrasonic transducer to emit ultrasonic waves;

[0071] Step 3, collect the echo signal of the ultrasonic wave passing through the suspension liquid, convert the analog echo signal into a digital signal, and then transmit it to the FPGA;

[0072] Step 4, perform digital filtering and peak detection on the echo data based on the FPGA;

[0073] Step 5, calculate the ultrasonic attenuation coefficient based on the peak detection result by combining numerical integration with the FPGA;

[0074] Step 6: For multiple homogeneous suspension liquids with known sediment concentrations, perform Steps 2 to 5 respectively to obtain the ultrasonic attenuation coefficients at different concentrations, and then fit the ultrasonic attenuation coefficients and concentrations to obtain the regression equation of the attenuation coefficient and sediment concentration.

[0075] Step 7: For the suspension liquid to be measured, perform Steps 2 to 6 to obtain the ultrasonic attenuation coefficient, and substitute the ultrasonic attenuation coefficient into the regression equation of the attenuation coefficient and sediment concentration to obtain the sediment concentration of the suspension liquid to be measured.

[0076] Further, in one embodiment, in combination with Figure 2 , in Step 1, the ultrasonic underwater measurement system includes: the ultrasonic transducer 3, the reflection wall 4, and a distance adjustment track 5 arranged between the ultrasonic transducer 3 and the reflection wall 4;

[0077] The ultrasonic transducer 3 is used to emit ultrasonic waves to the suspension liquid and receive the scattered signals;

[0078] The reflection wall 4 is used to reflect the ultrasonic wave signal to generate an echo signal;

[0079] The distance adjustment track 5 is used to adjust and control the distance between the ultrasonic transducer 3 and the reflection wall 4.

[0080] Here, after the ultrasonic wave propagates through the water body and undergoes scattering and attenuation with the sediment particles, the generated echo signal is amplified and filtered by the ultrasonic acquisition circuit, and then converted into a digital signal by the analog-to-digital converter and transmitted to the FPGA for processing.

[0081] Further, the ultrasonic underwater measurement system further includes: a fixed rod 2, which is used to fix the ultrasonic underwater measurement system in the suspension.

[0082] Further, in one embodiment, in Step 3, the echo signal is transmitted to the FIFO buffer area of the FPGA.

[0083] Further, in one embodiment, in Step 4, a Chebyshev type-I bandpass FIR filter is implemented by the FPGA to perform FIR digital filtering on the echo data. Driven by the system clock, the Chebyshev type-I bandpass FIR filter filters out the noise of the echo data and extracts the effective signal. In combination with Figure 3 , it specifically includes:

[0084] Use a shift register to implement a delay line. When a new input signal arrives, the delay line pushes the current signal in, and at the same time, the historical data moves backward in turn to form a sliding window;

[0085] By adopting the parallel pipelined multiplication and accumulation technology, each input signal is multiplied by the corresponding filter coefficient. All multiplications are carried out simultaneously, and the accumulation operation of all products is completed through an adder tree, thereby generating the filtered output value.

[0086] Further, in one embodiment, in step 4, peak detection is performed by an FPGA, including extracting the peaks of each echo. Specifically: The peak is detected by using a comparison register combined with a pipeline structure. Combining Figure 4 , the process includes:

[0087] Step 4-1: Set the minimum threshold A of the echo peak amplitude, initialize the initial value of the echo sequence number i to 1, and initialize a pesks array and a Pesks array. There is an initial value (this initial value is set by oneself) in the pesks array;

[0088] Step 4-2: Initially detect the peak of the i-th echo and store the peak in the pesks array;

[0089] Step 4-3: Perform quadratic interpolation on the peaks in the pesks array except the initial value. Then, based on the adjacent sampling points before and after the peak, fit out the peak position and amplitude, and eliminate the false peaks according to the amplitude change of the adjacent sampling points;

[0090] Step 4-4: Repeat step 4-3 until there is one peak left in the i-th echo;

[0091] Step 4-5: In the pesks array, judge whether the peak corresponding to the i-th echo is less than the previous value. If so, it indicates that the peak corresponding to the current i-th echo is a valid peak, and then step 4-6 is executed; otherwise, it indicates that the peak corresponding to the current i-th echo is an invalid peak, and this peak is eliminated, and then return to execute step 4-2;

[0092] Step 4-6: Store the valid peak and its echo sequence number in the Pesks array;

[0093] Step 4-7: Judge whether the valid peak is less than the minimum threshold A. If so, output the valid peak and the corresponding echo sequence number. Otherwise, increment the echo sequence number i by 1, and then execute step 4-8;

[0094] Step 4-8: Judge whether the echo sequence number i is greater than the total number of echoes T. If it is greater, end the peak detection process. Otherwise, return to execute step 4-2.

[0095] Adopting the solution of this embodiment, through multiple steps such as preliminary detection, quadratic interpolation, pseudo-peak elimination, validity judgment, and threshold screening, the accuracy of echo signal processing can be significantly improved. This method quickly screens potential peaks through preliminary detection and accurately calculates the specific position and amplitude of the peaks using quadratic interpolation, effectively avoiding the positioning error caused by the sampling point interval. During the processing, pseudo-peak elimination can filter out invalid peaks caused by noise or minor fluctuations through rapid detection of amplitude changes, ensuring the reliability of the final output peak data. Through validity judgment and threshold screening, invalid peaks with too low amplitudes are further eliminated, ensuring the rationality and accuracy of the detection results. Moreover, this multi-step peak detection method can accurately adapt to the waveform changes of complex echo signals, improve the calculation efficiency while ensuring high precision, has good real-time performance and strong anti-interference ability, and is applicable to signal detection tasks in various complex environments.

[0096] Further, in one embodiment, in combination with Figure 5 , according to the peak detection result in step 5, based on FPGA and combined with numerical integration, calculating the ultrasonic attenuation coefficient specifically includes:

[0097] Step 5-1, constructing a graph of echo sequence number - echo signal amplitude sequence;

[0098] Step 5-2, regarding the interval between the first echo and the last echo as the integration interval, and taking the distance between these two echoes as the length of the integration interval;

[0099] Step 5-3, adaptively dividing the integration interval;

[0100] Step 5-4, randomly calculating the areas of any two echoes and calculating the ratio of the two areas; the area is the area of the triangular region formed between the amplitude of the echo and the first position where the echo decays to zero;

[0101] Step 5-5, converting the area ratio into a floating-point number;

[0102] Step 5-6, calculating the attenuation coefficient α according to the area ratio in step 5-5:

[0103]

[0104] In the formula, A 1 , A 2 are the areas of the two echoes respectively, and L is the distance between the ultrasonic transducer and the reflecting wall;

[0105] Step 5-7, judging whether the accuracy of the attenuation coefficient α meets the preset condition. If it meets, convert the attenuation coefficient α into a fixed-point format and output, and then end the process. Otherwise, return to execute step 5-4.

[0106] Here, a floating-point IP core is used to automatically scale the data bit width to ensure the measurement accuracy.

[0107] Preferably, in some embodiments, the adaptive segmentation of the integration interval described in step 5-3 specifically includes:

[0108] Step 5-3-1: Assume the total number of echoes is N + 1, and divide the integration interval (not limited to equal division) into N intervals, that is, the two endpoints of each interval correspond to two adjacent echoes;

[0109] Step 5-3-2: For each interval, calculate the absolute value of the change rate R of the peaks of the two corresponding echoes i , where the peak value is obtained from step 4; then judge whether the absolute value of the change rate R i is greater than the preset change rate threshold R. If it is greater, execute step 5-3-3;

[0110] Step 5-3-3: Divide the interval into two equal parts (or k sub-intervals, k = R i / R (at least two)) through the intermediate endpoint value, and then return to execute step 5-3-2;

[0111] Step 5-3-4: Repeat steps 5-3-2 to 5-3-3 until the absolute value of the change rate corresponding to all intervals is less than the preset change rate threshold R.

[0112] Preferably, in one of the embodiments, the intermediate endpoint value in step 5-3-3 is obtained by fitting using quadratic interpolation according to the left and right endpoint values.

[0113] Using the adaptive segmentation method of this embodiment, the segmentation strategy is dynamically adjusted according to the change rate of the data. This method can flexibly handle the changes in complex waveforms in the echo data. It finely divides the processing interval according to the local change characteristics of the echo signal, performs more accurate analysis and processing on the severely changing areas, and at the same time avoids excessive calculation in the stable areas, thereby effectively improving the accuracy and efficiency of echo signal processing and being able to automatically adapt to the distribution and changes of different data.

[0114] Preferably, in one of the embodiments, the calculation of the area of the echo in step 5-4 specifically includes:

[0115] Judge whether the total number of intervals in the triangular region corresponding to the echo is odd or even;

[0116] If it is even, use the composite Simpson's method to perform integral approximation calculation on two adjacent intervals to obtain the area, and the calculation result of the attenuation coefficient is:

[0117]

[0118] If it is odd, the composite Simpson's method is used to approximate the integral for the previous even number of intervals in sequence, and the trapezoidal method is used to approximate the remaining one interval. Then the calculation result of the attenuation coefficient is:

[0119]

[0120] In the formula, i is the serial number of the effective peak finally output, that is, the serial number of the interval endpoint, and n is the total number of effective peaks finally output; V pi is the i-th effective peak, and V pn is the n-th effective peak.

[0121] Here, the above embodiment adopts a numerical integration scheme combining the composite Simpson's method and the trapezoidal method, and selects an adaptive integral interval segmentation method, which improves the integral calculation accuracy. It can better reflect the subtle fluctuations of the signal, reduce the influence of external factors such as temperature fluctuations, power supply instability, and electromagnetic interference, and enhance the robustness and stability of the method.

[0122] In one embodiment, an FPGA-based acoustic wave multiple reflection sediment concentration measurement system is provided. The system includes the following modules executed in sequence:

[0123] The first module is used to drive the ultrasonic underwater measurement system that can achieve multiple reflections of ultrasonic waves to work;

[0124] The second module is used to generate an excitation signal through DDS modulation driving in the FPGA, and convert and output it through a digital-to-analog converter to drive the ultrasonic transducer to emit ultrasonic waves;

[0125] The third module is used to collect the echo signal of the ultrasonic wave passing through the suspension liquid, convert the analog echo signal into a digital signal, and then transmit it to the FPGA;

[0126] The fourth module is used to perform digital filtering and peak detection on the echo data based on the FPGA;

[0127] The fifth module is used to calculate the ultrasonic attenuation coefficient based on the FPGA in combination with numerical integration according to the peak detection result;

[0128] The sixth module is used to respectively execute the second module to the fifth module for multiple suspensions of the same type with known sediment concentrations to obtain the ultrasonic attenuation coefficients at different concentrations, and then fit the ultrasonic attenuation coefficients and concentrations to obtain the regression equation of the attenuation coefficient and the sediment concentration;

[0129] The seventh module is used to execute the second module to the sixth module for the suspension liquid to be measured to obtain the ultrasonic attenuation coefficient, and substitute the ultrasonic attenuation coefficient into the regression equation of the attenuation coefficient and the sediment concentration to obtain the sediment concentration of the suspension liquid to be measured.

[0130] For the specific limitations of the FPGA-based acoustic wave multiple reflection sediment concentration measurement system, reference can be made to the limitations of the FPGA-based acoustic wave multiple reflection sediment concentration measurement method in the above text, which will not be elaborated here. Each module in the above FPGA-based acoustic wave multiple reflection sediment concentration measurement system can be implemented in whole or in part by software, hardware, and their combination. Each of the above modules can be embedded in the processor of the computer device in hardware form or independent of it, or stored in the memory of the computer device in software form, so as to facilitate the processor to call and execute the operations corresponding to each of the above modules.

[0131] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the following is implemented:

[0132] Step 1, drive the ultrasonic underwater measurement system capable of realizing multiple reflections of ultrasonic waves to work;

[0133] Step 2, generate an excitation signal through DDS modulation drive in the FPGA, and convert and output it through a digital-to-analog converter to drive the ultrasonic transducer to emit ultrasonic waves;

[0134] Step 3, collect the echo signal of the ultrasonic wave passing through the suspension liquid, convert the analog echo signal into a digital signal, and then transmit it to the FPGA;

[0135] Step 4, perform digital filtering and peak detection on the echo data based on the FPGA;

[0136] Step 5, based on the peak detection result, calculate the ultrasonic attenuation coefficient by combining numerical integration based on the FPGA;

[0137] Step 6, for multiple suspensions of the same type with known sediment concentrations, respectively execute Steps 2 to 5 to obtain the ultrasonic attenuation coefficients at different concentrations, and then fit the ultrasonic attenuation coefficients and concentrations to obtain the regression equation of the attenuation coefficient and sediment concentration;

[0138] Step 7, for the suspension to be measured, execute Steps 2 to 6 to obtain the ultrasonic attenuation coefficient, and substitute the ultrasonic attenuation coefficient into the regression equation of the attenuation coefficient and sediment concentration to obtain the sediment concentration of the suspension to be measured.

[0139] For the specific limitations of each step, reference can be made to the limitations of the FPGA-based acoustic wave multiple reflection sediment concentration measurement method in the above text, which will not be elaborated here.

[0140] In one of the embodiments, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following is implemented:

[0141] Step 1, operate an ultrasonic underwater measurement system capable of multiple reflections of ultrasonic waves;

[0142] Step 2, generate an excitation signal through DDS modulation driving within the FPGA, convert it through a digital-to-analog converter and output it to drive the ultrasonic transducer to emit ultrasonic waves;

[0143] Step 3, collect the echo signal of the ultrasonic wave passing through the suspension liquid, convert the analog echo signal into a digital signal, and then transmit it to the FPGA;

[0144] Step 4, perform digital filtering and peak detection on the echo data based on the FPGA;

[0145] Step 5, calculate the ultrasonic attenuation coefficient based on the peak detection result by combining numerical integration with the FPGA;

[0146] Step 6, for multiple suspensions of the same type with known sediment concentrations, respectively execute Steps 2 to 5 to obtain the ultrasonic attenuation coefficients at different concentrations, and then fit the ultrasonic attenuation coefficients and concentrations to obtain the regression equation of the attenuation coefficient and sediment concentration;

[0147] Step 7, for the suspension to be measured, execute Steps 2 to 6 to obtain the ultrasonic attenuation coefficient, substitute this ultrasonic attenuation coefficient into the regression equation of the attenuation coefficient and sediment concentration to obtain the sediment concentration of the suspension to be measured.

[0148] For the specific limitations of each step, reference can be made to the limitations of the method for measuring sediment concentration based on multiple reflections of sound waves by FPGA in the above text, which will not be elaborated here.

[0149] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments. What is described in the above embodiments and the specification only illustrates the principles of the present invention. Without departing from the spirit and scope of the present invention, any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for measuring sediment concentration by multiple reflections of sound waves based on FPGA, characterized in that: The method comprises: Step 1, building an ultrasonic underwater measurement system capable of realizing multiple reflections of ultrasonic waves and driving it to work, wherein the ultrasonic underwater measurement system includes an ultrasonic transducer; Step 2, generate an excitation signal through the DDS modulation drive in the FPGA, and convert the output through the digital-to-analog converter to drive the ultrasonic transducer to emit ultrasonic waves; Step 3, collecting the echo signal of the ultrasonic wave passing through the suspended liquid, converting the analog echo signal into a digital signal, and then transmitting it to the FPGA; Step 4, digital filtering and peak detection of echo data based on FPGA; Step 5, according to the peak detection result, the ultrasonic attenuation coefficient is calculated based on FPGA combined with numerical integration; Step 6, for multiple suspended liquids of the same type with known sediment concentrations, respectively perform steps 2 to 5 to obtain ultrasonic attenuation coefficients at different concentrations, and then fit the ultrasonic attenuation coefficient and concentration to obtain a regression equation of the attenuation coefficient and the sediment concentration; Step 7: for the suspended liquid to be measured, execute steps 2 to 6 to obtain the ultrasonic attenuation coefficient, substitute the ultrasonic attenuation coefficient into the regression equation of the attenuation coefficient and the sediment concentration to obtain the sediment concentration of the suspended liquid to be measured.

2. The FPGA-based method for measuring sediment concentration by multiple reflections of sound waves according to claim 1, characterized in that: The ultrasonic underwater measurement system in step 1 comprises: the ultrasonic transducer (3), a reflecting wall (4), and a distance control track (5) arranged between the ultrasonic transducer (3) and the reflecting wall (4); The ultrasonic transducer (3) is used to transmit ultrasonic waves to the suspended liquid and receive scattered signals; The reflecting wall (4) is used to reflect the ultrasonic signal to generate an echo signal; The distance control track (5) is used to adjust and control the distance between the ultrasonic transducer (3) and the reflection wall (4).

3. The FPGA-based sound wave multiple reflection sediment concentration measurement method according to claim 2 is characterized in that: The ultrasonic underwater measurement system further comprises: a fixing rod (2) for fixing the ultrasonic underwater measurement system in the suspension.

4. The FPGA-based method for measuring sediment concentration by multiple reflections of sound waves according to claim 1, characterized in that: In step 3, the echo signal is transmitted to the FIFO buffer area of ​​the FPGA.

5. The FPGA-based method for measuring sediment concentration by multiple reflections of sound waves according to claim 1, characterized in that: In step 4, a Chebyshev type I bandpass FIR filter is implemented through FPGA to perform FIR digital filtering on the echo data, specifically including: Use shift registers to implement delay lines. When a new input signal arrives, the delay line pushes the current signal in, and the historical data moves backwards in sequence to form a sliding window. Using parallel pulsating multiplication and accumulation technology, each input signal is multiplied by the corresponding filter coefficient, all multiplications are performed simultaneously, and the accumulation operation of all products is completed through the addition tree to generate the filtered output value.

6. The FPGA-based method for measuring sediment concentration by multiple reflections of sound waves according to claim 1, characterized in that: In step 4, peak value detection is performed by FPGA, including extracting the peak value of each echo. Specifically, the peak value is detected by using a comparison register combined with a pipeline structure. The process includes: Step 4-1, set the minimum threshold value A of the echo peak amplitude, initialize the initial value of the echo sequence number i to 1, and initialize a pesks array and a Pesks array, wherein an initial value is set in the pesks array; Step 4-2, preliminarily detect the peak value of the i-th echo and store the peak value in the pesks array; Step 4-3, performing a secondary interpolation operation on the peak values ​​in the pesks array except the initial value, then fitting the peak position and amplitude based on the adjacent sampling points before and after the peak, and removing the pseudo peak value according to the amplitude change of the adjacent sampling points; Step 4-4, repeat step 4-3 until there is one peak remaining in the i-th echo; Step 4-5, in the pesks array, determine whether the peak value corresponding to the i-th echo is less than the previous value. If so, it indicates that the peak value corresponding to the current i-th echo is a valid peak value, and then execute step 4-6; otherwise, it indicates that the peak value corresponding to the current i-th echo is an invalid peak value, and the peak value is removed, and return to execute step 4-2; Step 4-6, store the valid peak value and its echo number into the Pesks array; Step 4-7, determining whether the effective peak value is less than the minimum threshold value A, if so, outputting the effective peak value and the corresponding echo number, otherwise increasing the echo number i by 1, and then executing step 4-8; Step 4-8, determine whether the echo number i is greater than the total number of echoes, if so, end the peak detection process, otherwise return to step 4-2.

7. The FPGA-based method for measuring sediment concentration by multiple reflections of sound waves according to claim 1 or 2, characterized in that: According to the peak detection result, the ultrasonic attenuation coefficient is calculated based on FPGA combined with numerical integration, which specifically includes: Step 5-1, constructing an echo number-echo signal amplitude sequence diagram; Step 5-2, regarding the interval between the first echo and the last echo as an integration interval, and regarding the distance between the two echoes as the length of the integration interval; Step 5-3, adaptively dividing the integration interval; Step 5-4, randomly calculating the areas of any two echoes, and calculating the ratio of the two areas; the area is the area of ​​a triangular region formed between the amplitude of the echo and the first position where the echo decays to zero; Step 5-5, converting the area ratio into a floating point number; Step 5-6, calculate the attenuation coefficient α based on the area ratio in step 5-5: In the formula, A1 and A2 are the areas of the two echoes respectively, and L is the distance between the ultrasonic transducer and the reflecting wall; Step 5-7, determining whether the accuracy of the attenuation coefficient α meets the preset conditions, if so, converting the attenuation coefficient α into a fixed-point format and outputting it, then terminating the process, otherwise returning to execute step 5-4.

8. The FPGA-based method for measuring sediment concentration by multiple reflections of sound waves according to claim 7, characterized in that: The step 5-3 of adaptively dividing the integral interval specifically includes: Step 5-3-1, assuming the total number of echoes is N+1, divide the integration interval into N intervals, that is, the two endpoints of each interval correspond to two adjacent echoes; Step 5-3-2: For each interval, calculate the absolute value R of the change rate of the peak values ​​of the two corresponding echoes. i , the peak value is obtained by step 4; then determine the absolute value of the rate of change R i Is it greater than the preset change rate threshold R? If so, execute step 5-3-3; Step 5-3-3, divide the interval into two by the middle endpoint value, and then return to execute step 5-3-2; Step 5-3-4, repeat steps 5-3-2 to 5-3-3 until the absolute values ​​of the change rates corresponding to all intervals are less than the preset change rate threshold R.

9. The FPGA-based method for measuring sediment concentration by multiple reflections of sound waves according to claim 8, characterized in that: The intermediate endpoint value described in step 5-3-3 is obtained by fitting the left and right endpoint values ​​using quadratic interpolation.

10. The method for measuring sediment concentration by multiple reflections of sound waves based on FPGA according to claim 8, characterized in that: The area of ​​the echo is calculated in step 5-4, specifically including: Determine whether the total number of intervals in the triangular area corresponding to the echo is an odd number or an even number; If it is an even number, the area is calculated by using the complex Simpson method for two adjacent intervals through integral approximation. If it is an odd number, the complex Simpson method is used to perform integral approximation calculations on the first even intervals in sequence, and the trapezoidal method is used to approximate the remaining interval.

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