Liquid level meter based on image and millimeter wave

Abstract

The application discloses a liquid level meter based on images and millimeter waves, which comprises a millimeter wave liquid level detection module, an image acquisition module, a signal processing system module and a power supply system unit. The method measures the distance to the reflecting surface in real time through the millimeter wave liquid level detection module; the signal processing system module judges whether the measurement data is mutated; if not, the liquid level is directly calculated and output; if yes, the image acquisition module is started, the dot matrix structured light projector projects regular dot matrix light to the water surface, and the camera synchronously acquires images; the signal processing system module processes the images, calculates the height difference of the floating object relative to the real water surface by analyzing the deformation of the dot matrix light; and finally, the millimeter wave distance data and the image height difference data are fused, the corrected real liquid level height is calculated and output. The application solves the interference problem of millimeter wave measurement caused by water surface floating objects, waves and the like, realizes high-precision and high-anti-interference liquid level detection, and has the advantages of low power consumption and automatic operation.

Description

Technical Field

[0001] This invention relates to the field of hydrological monitoring technology, and in particular to a level gauge based on image and millimeter wave. Background Technology

[0002] Currently, non-contact millimeter-wave radar technology is mainly used for liquid level detection in open water areas both domestically and internationally. This technology has become the mainstream solution in the field of water conservancy monitoring due to its advantages such as no mechanical wear, insensitivity to water quality, convenient installation, and low maintenance costs. Its core principle is as follows: the millimeter-wave radar module emits high-frequency millimeter-wave signals vertically towards the water surface. The signals are reflected upon encountering the water surface, and the radar receiver captures the reflected echo. By measuring the signal's flight time, the straight-line distance between the radar probe and the water surface is calculated. Combined with the fixed installation height of the equipment, the current liquid level is obtained.

[0003] However, existing non-contact millimeter-wave radar level gauges still have the following drawbacks: 1. Floating object interference causes measurement distortion: When there are floating foreign objects such as branches, plastic bags, aquatic plants, garbage, foam, and duckweed on the water surface, the signal emitted by the millimeter-wave radar will be directly reflected from the surface of the foreign objects rather than the actual water surface, resulting in a smaller measurement distance, a higher, abrupt, and distorted liquid level height, and failing to reflect the true water level.

[0004] 2. Interference-free identification and automatic correction mechanism: Existing single millimeter-wave radar equipment can only collect distance data and cannot distinguish between "real water surface" and "floating foreign objects". When interference occurs, the equipment continuously outputs erroneous data, which seriously affects the accuracy of hydrological monitoring, water conservancy scheduling and flood control early warning.

[0005] 3. Wave interference exacerbates measurement errors: Waves on the surface of natural rivers and canals can cause irregularities in the radar reflector, further amplifying measurement errors. A single sensor cannot compensate for these errors.

[0006] 4. Limited functionality and lack of visual verification methods: Traditional radar level gauges lack image acquisition capabilities, making it impossible for maintenance personnel to remotely view the actual state of the water surface, which makes troubleshooting and data verification difficult.

[0007] In real-world scenarios such as smart water conservancy, urban flood monitoring, farmland irrigation, and industrial wastewater treatment, floating debris on the water surface is a common occurrence. The measurement accuracy of a single millimeter-wave radar level gauge cannot meet national standards, leading to monitoring data failure and scheduling decision errors. Therefore, there is an urgent need for a fusion detection solution that is anti-interference, high-precision, and automatically corrects. Summary of the Invention

[0008] To improve the accuracy of hydrological level monitoring, this invention provides a level gauge based on image and millimeter wave.

[0009] The present invention provides a liquid level gauge based on image and millimeter wave, which adopts the following technical solution: A liquid level gauge based on image and millimeter wave, comprising: The millimeter-wave liquid level detection module is used to transmit millimeter-wave signals to the water surface and receive the echoes in order to measure the distance from the radar probe to the reflecting surface. An image acquisition module is communicatively connected to the millimeter-wave liquid level detection module and is used to acquire water surface images containing dot matrix structured light when there is interference on the water surface. The image acquisition module includes a high-definition image acquisition camera and a dot matrix structured light projector that works in conjunction with the high-definition image acquisition camera. The signal processing system module is communicatively connected to the millimeter-wave liquid level detection module and the image acquisition module, respectively, and is used for: Receive and process the distance data measured by the millimeter-wave liquid level detection module; Determine whether the distance data has undergone a sudden change, and if a sudden change is determined, activate the image acquisition module; The system receives and processes images acquired by the image acquisition module to extract dot matrix light features and calculate the height difference between floating objects on the water surface and the actual water surface. By combining the distance data and the height difference, the corrected true liquid level height is calculated. The power supply system unit is used to supply power to the millimeter-wave liquid level detection module, the image acquisition module, and the signal processing system module.

[0010] As a preferred embodiment of the present invention, it further includes a millimeter-wave flow velocity detection module that is communicatively connected to the millimeter-wave liquid level detection module and the signal processing system module, for measuring water surface flow velocity based on the Doppler effect.

[0011] As a preferred embodiment of the present invention, the signal processing system module is further configured to, when the image acquisition module is started, control the dot matrix structured light projector to project dot matrix light onto the water surface and control the high-definition image acquisition camera to acquire images synchronously; and control the dot matrix structured light projector to turn off after the image acquisition is completed.

[0012] As a preferred embodiment of the present invention, the logic of the signal processing system module to determine that a sudden change has occurred in the distance data is as follows: calculate the absolute value of the difference between the current distance measurement value and the historical stable distance value; if the absolute value is greater than a preset change threshold, it is determined that a change has occurred.

[0013] As a preferred embodiment of the present invention, the signal processing system module calculates the true liquid level height in the following manner: by subtracting the height difference of floating objects on the water surface calculated by the image acquisition module from the distance measured by the millimeter-wave liquid level detection module, the distance from the radar probe to the true water surface is obtained, and then the true liquid level height is calculated based on the fixed installation height of the equipment.

[0014] As a preferred embodiment of the present invention, when calculating the height difference, the signal processing system module obtains the pixel offset by comparing the pixel coordinates of the dot matrix light points in the current image with the standard light point pixel coordinates stored during system calibration, and converts the pixel offset into the physical height difference according to the pre-calibrated mapping coefficient.

[0015] As a preferred embodiment of the present invention, the power supply system unit includes a solar power supply module and / or an AC power supply module.

[0016] This invention also discloses an image- and millimeter-wave-based liquid level detection method, using any one of the liquid level gauges described above, comprising the following steps: The distance data from the radar probe to the reflector surface is continuously collected through the millimeter-wave liquid level detection module; Determine if the currently collected distance data has undergone a sudden change; If no sudden change occurs, the liquid level height is calculated and output based on the current distance data and the equipment installation height; If a sudden change occurs, the image acquisition module is activated, which projects dot matrix light onto the water surface through its dot matrix structured light projector and acquires water surface images containing the dot matrix light through a high-definition image acquisition camera. The image is processed to extract the dot matrix light features, and the height difference between the floating objects on the water surface and the real water surface is calculated based on these features. By combining the distance data and the height difference, the corrected true liquid level height is calculated and output.

[0017] As a preferred embodiment of the present invention, in the determination step, the current distance data is compared with the dynamically updated historical stable distance value to determine whether a sudden change has occurred.

[0018] As a preferred embodiment of the present invention, the step of calculating the height difference includes: extracting the actual pixel coordinates of the dot matrix light spots in the image, matching them with the standard pixel coordinates obtained during system calibration, calculating the average pixel offset, and then using pre-calibrated coefficients to convert the average pixel offset into a physical height difference.

[0019] In summary, the present invention has at least one of the following beneficial technical effects: 1. This invention, through the coordinated operation of an image acquisition module (camera + dot matrix structured light projector) and a millimeter-wave module (flow velocity + liquid level), completely eliminates the interference of floating objects, aquatic plants, foam, and waves on millimeter-wave radar, ensuring the accuracy and reliability of measurement results and overcoming the core defects of existing single millimeter-wave radars. Furthermore, compared to the errors of traditional single millimeter-wave radars, by fusing detection errors, the accuracy is improved by more than 50 times, meeting the high-precision requirements of national-level hydrological monitoring and precision irrigation of farmland. 2. This invention, led by a signal processing system module, enables automatic identification of millimeter-wave data mutations, automatic activation of the image acquisition module, and automatic completion of correction calculations throughout the entire process, requiring no manual operation. It is suitable for unattended monitoring scenarios and reduces operation and maintenance costs. 3. The dot matrix structured light projector of the image acquisition module of the present invention is activated only when there is a sudden change in millimeter-wave data and is normally turned off. With the low power management of the power supply system unit, the average power consumption of the device can be reduced. The solar power supply mode can realize long-term operation in the field. Attached Figure Description

[0020] Figure 1 This is a schematic diagram of the liquid level gauge structure based on image and millimeter wave according to an embodiment of the present invention.

[0021] Figure 2 This is a schematic diagram of the liquid level gauge measurement using images and millimeter waves according to the present invention.

[0022] Figure 3 This is a flowchart of the measurement method of the liquid level gauge based on images and millimeter waves according to the present invention. Detailed Implementation

[0023] The following is in conjunction with the appendix Figure 1-3 The present invention will be described in further detail below.

[0024] This invention discloses an image-based and millimeter-wave-based liquid level gauge and method, aiming to solve the technical problem of measurement distortion caused by existing single millimeter-wave radar liquid level gauges in open water due to interference from floating objects, foam, waves, etc. This invention achieves interference-resistant and high-precision liquid level detection by integrating millimeter-wave radar ranging with dot-matrix structured light machine vision technology.

[0025] Reference Figure 1 and Figure 2 The image- and millimeter-wave-based level gauge of this invention adopts an integrated design, and its hardware system mainly consists of the following five core modules: Millimeter-wave flow velocity detection module 1: Based on the Doppler effect principle, it is used for real-time non-contact measurement of water surface flow velocity. Its velocity measurement range is, for example, 0.01 m / s to 10 m / s, with an accuracy of ±0.01 m / s. This module and the millimeter-wave liquid level detection module can be integrated on the same chip or board, communicating with the main control system via interfaces such as UART or RS485.

[0026] Millimeter-wave liquid level detection module 2: This is the core ranging unit. It vertically transmits high-frequency (e.g., 60GHz or 77GHz) millimeter-wave signals towards the water surface and receives the echoes. By measuring the signal's time of flight, it calculates the straight-line distance from the radar probe to the reflecting surface (water surface or floating object). Its ranging range is, for example, 0.5m to 30m, with an accuracy of ±1mm. This module operates continuously, providing real-time distance data.

[0027] Image acquisition module 3: This is a key correction unit of the present invention, used to activate upon detection of interference to acquire visual information about the water surface. This module integrates two cooperating sub-components: High-definition image acquisition camera: used to capture images of water surface and light field, with resolutions such as 1080P or 4K, and supports wide-angle and infrared night vision functions to adapt to different lighting environments.

[0028] Dot matrix structured light projector: As a supporting component of the camera, it is used to project regular infrared dot matrix light (such as circular, square, or grid dot matrix) onto the water surface when needed, providing optical feature markers for subsequent 3D reconstruction. This projector is only triggered by the main control system under specific conditions to reduce power consumption.

[0029] Signal Processing System Module 4: As the "brain" of the entire device, it is typically implemented using an ARM Cortex-A series embedded processor, an STM32 series high-end microcontroller, or an FPGA chip. This module is responsible for system control, data processing, and algorithm execution, specifically including: controlling the start and stop of each module, receiving and processing millimeter-wave and image data, performing data mutation judgment, image preprocessing and feature extraction, 3D height reconstruction, data fusion calculation, final liquid level calculation, data storage, and communication.

[0030] Power Supply System Unit 5: Provides a stable power supply for all the above modules. This unit is designed to be compatible with both solar and mains power supply modes, and has a built-in power management chip to achieve overvoltage / overcurrent protection and low power consumption management, adapting to the long-term operation requirements of unattended outdoor scenarios.

[0031] The aforementioned modules are integrated into a single, IP68-rated housing. The millimeter-wave probe, camera, and structured light projector are coaxially mounted at the bottom of the housing, ensuring overlapping measurement fields of view. The device is mounted on bridges, railings, or poles via a top flange or clamp bracket, and is vertically aligned with the water surface.

[0032] Reference Figure 3 The liquid level gauge based on image and millimeter wave of this invention, when performing liquid level detection, is controlled and executed by the signal processing system module, specifically including the following steps: Step S1: System Initialization and Calibration: After the device is powered on, a hardware self-test and parameter configuration are performed first. Key calibrations include: (1) Measuring and recording the fixed installation height H_install (vertical distance from the probe to the river datum plane); (2) Calibrating the image acquisition module: Place a standard flat plate above a calm, undisturbed water surface, start the dot matrix structured light projector and camera, acquire standard dot matrix images, establish a standard coordinate database of light spots, and calculate the calibration coefficient K between the pixel offset and the actual physical height difference. This coefficient will be used to convert the pixel changes in the image into the actual height difference later.

[0033] Step S2: Millimeter-wave real-time ranging and data preprocessing: The millimeter-wave liquid level detection module continuously transmits signals to the water surface and receives echoes, calculating the single distance D_single using the time-of-flight method. To suppress random noise, the signal processing system module performs a moving average filter on N consecutive measurement results (e.g., N=10) to obtain the stable distance value D_avg at the current moment. Simultaneously, the millimeter-wave flow velocity detection module synchronously measures the water surface flow velocity.

[0034] Step S3: Liquid Level Data Abrupt Change Judgment (Interference Identification): The signal processing system module compares the current filtered distance D_avg with a dynamically updated historical stable distance value D_history, and calculates the absolute value of the difference ΔD. A pre-set abrupt change threshold ΔD_th (e.g., 0.02m-0.05m). If ΔD ≤ ΔD_th, it is determined that there is no significant interference on the water surface, and the process jumps to step S8, directly calculating the liquid level based on D_avg. If ΔD > ΔD_th, it is determined that there may be interference such as floating objects on the water surface, triggering the image correction process and executing step S4. Afterwards, the current D_avg is updated to the new D_history to adapt to the natural and slow changes in water level.

[0035] Step S4: Start the image acquisition module for image acquisition: When interference is detected, the signal processing system module issues a command to start the image acquisition module. Specifically: First, the dot matrix structured light projector is started to project an infrared dot matrix light field onto the water surface; then, the high-definition camera is started simultaneously to continuously acquire multiple frames (e.g., 3-5 frames) of water surface images containing the deformed light field; after acquisition is completed, the dot matrix structured light projector is immediately turned off to save power. The system selects the clearest frame from the acquired images for subsequent processing.

[0036] Step S5: Image preprocessing: The signal processing system module preprocesses the selected image to improve the analysis accuracy, including: converting the color image to grayscale; removing noise and reflections using algorithms such as Gaussian filtering and median filtering; performing lens distortion correction; and cropping the region of interest (ROI) that contains only the dot matrix light field, excluding irrelevant background.

[0037] Step S6: Structured light feature extraction and 3D height reconstruction.

[0038] This step is the core of image correction. The signal processing system module extracts the dot matrix light spot features from the preprocessed image, calculates the light spot offset, and then reconstructs the three-dimensional height of the floating foreign object, providing a key basis for millimeter-wave data correction. The specific sub-steps are as follows: Step 6.1: Extraction of the center of the dot matrix light spot The preprocessed grayscale image is binarized, and an appropriate threshold is set to separate the dot matrix light spots from the background, so that the light spots appear white and the background appears black, which is convenient for extraction. By combining centroid algorithm and edge detection algorithm, the actual pixel coordinates (X_i, Y_i) of each dot matrix light point are accurately extracted, and blurry and overlapping light points are eliminated to ensure that the extracted light point coordinates are accurate and reliable. The extracted actual light spot coordinates (X_i, Y_i) are matched one-to-one with the standard coordinates in the established standard light field database.

[0039] Step 6.2: Calculation of Matrix Offset For each successfully matched light spot, calculate the pixel offset ΔPixel_i of the individual light spot, using the formula:

[0040] Where: (X_i, Y_i) are the actual light spot pixel coordinates, (X0_i, Y0_i) are the standard light spot pixel coordinates, and ΔPixel_i is the pixel offset of a single light spot (unit: pixels); Calculate the average pixel offset of all valid light spots (successfully matched, with no significant error). ΔPixel_avg, formula:

[0041] Where: n is the number of effective light spots (if the number of effective light spots is insufficient, the image is re-acquired), and ΔPixel_avg is the average pixel offset, which is used for subsequent calculation of the height of the foreign object.

[0042] Step 6.3: Calculation of the relative height of the foreign object The signal processing system module calls the calibrated coefficient K to convert the average pixel offset ΔPixel_avg into the protrusion height H_object of the floating foreign object relative to the real water surface, using the formula:

[0043] Where H_object: the height of the foreign object above the actual water surface, in millimeters (mm) (which can be converted to meters (m); K: calibration coefficient (mm / pixel).

[0044] After the calculation is completed, the H_object data is stored in the signal processing system module for subsequent data fusion and correction.

[0045] Step S7: Millimeter Wave and Image Data Fusion Correction: The signal processing system module fuses the millimeter wave data with the visual calculation results. The distance measured by the millimeter wave, D_radar (i.e., D_avg), is the distance from the probe to the surface of the floating object. Subtracting the visually calculated height of the floating object, H_object, from this distance yields the distance from the probe to the actual water surface, D_real (D_real = D_radar - H_object). Finally, based on the equipment installation height, H_install, the actual liquid level height, H_real, is calculated, i.e., H_real = H_install - D_real. Smoothing processes such as Kalman filtering can be applied to H_real to output a more stable liquid level value.

[0046] Step S8: Data Output and System Loop: The signal processing system module uploads the final calculated liquid level height (direct calculation result when there is no interference, and fusion correction result when there is interference) and flow velocity data to the remote monitoring platform via built-in 4G, NB-IoT, and other communication units, and stores them in the local memory. The device then returns to step S2 to continue the next monitoring loop. Under normal interference-free conditions, the image acquisition module (especially the high-power dot matrix light projector) is turned off, and the system operates only with the millimeter-wave module at low power, greatly reducing overall energy consumption.

[0047] To illustrate the present invention in more detail, the following two non-limiting embodiments are provided: Example 1: Urban River Monitoring The device is installed on the urban riverbank railing at a height of H_install=5m and powered by mains electricity. Under normal, interference-free conditions, it continuously measures the distance using millimeter waves, calculates the liquid level, and uploads the data. When a garbage bag floats on the water, the millimeter wave distance measurement value D_avg suddenly changes from 3.20m to 3.15m, with the difference ΔD=0.05m exceeding the threshold (0.03m). The system automatically triggers the image acquisition and processing flow, calculating the height of the garbage bag protrusion H_object=0.01m. After data fusion correction, the actual liquid level H_real=5-(3.15-0.01)=1.86m, instead of the incorrectly displayed 1.85m. After the interference is eliminated, the system automatically reverts to pure millimeter wave monitoring mode.

[0048] Example 2: Monitoring of farmland irrigation ditches The equipment is installed beside an irrigation canal in farmland, powered by solar energy, at a height of H_install=3m. When aquatic plants grow on the canal surface, the millimeter-wave measurement value changes abruptly. The image correction process calculates the aquatic plant height H_object=0.02m and performs fusion correction. This solution improves the liquid level measurement error from the centimeter level of traditional radar to the millimeter level, meeting the water control requirements of precision irrigation. Its low-power design ensures continuous and stable operation under solar power.

[0049] The above are all preferred embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Therefore, all equivalent changes made in accordance with the structure, shape and principle of the present invention should be covered within the scope of protection of the present invention.

Claims

1. A liquid level gauge based on image and millimeter wave, characterized in that, include: The millimeter-wave liquid level detection module is used to transmit millimeter-wave signals to the water surface and receive the echoes in order to measure the distance from the radar probe to the reflecting surface. An image acquisition module is communicatively connected to the millimeter-wave liquid level detection module and is used to acquire water surface images containing dot matrix structured light when there is interference on the water surface. The image acquisition module includes a high-definition image acquisition camera and a dot matrix structured light projector that works in conjunction with the high-definition image acquisition camera. The signal processing system module is communicatively connected to the millimeter-wave liquid level detection module and the image acquisition module, respectively, and is used for: Receive and process the distance data measured by the millimeter-wave liquid level detection module; Determine whether the distance data has undergone a sudden change, and if a sudden change is determined, activate the image acquisition module; The system receives and processes images acquired by the image acquisition module to extract dot matrix light features and calculate the height difference between floating objects on the water surface and the actual water surface. By combining the distance data and the height difference, the corrected true liquid level height is calculated. The power supply system unit is used to supply power to the millimeter-wave liquid level detection module, the image acquisition module, and the signal processing system module.

2. The image- and millimeter-wave-based level gauge according to claim 1, characterized in that: It also includes a millimeter-wave flow velocity detection module that is communicatively connected to the millimeter-wave liquid level detection module and the signal processing system module, for measuring water surface flow velocity based on the Doppler effect.

3. The image- and millimeter-wave-based level gauge according to claim 1, characterized in that: The signal processing system module is also used to control the dot matrix structured light projector to project dot matrix light onto the water surface when the image acquisition module is started, and to control the high-definition image acquisition camera to acquire images synchronously; and to control the dot matrix structured light projector to turn off after the image acquisition is completed.

4. The image- and millimeter-wave-based level gauge according to claim 1, characterized in that: The logic of the signal processing system module to determine if a change in distance data has occurred is as follows: calculate the absolute value of the difference between the current distance measurement value and the historical stable distance value. If the absolute value is greater than the preset change threshold, it is determined that a change has occurred.

5. A liquid level gauge based on image and millimeter wave as described in claim 1, characterized in that, The signal processing system module calculates the true liquid level height by subtracting the height difference of floating objects on the water surface calculated by the image acquisition module from the distance measured by the millimeter-wave liquid level detection module, thus obtaining the distance from the radar probe to the true water surface, and then calculating the true liquid level height based on the fixed installation height of the equipment.

6. The image- and millimeter-wave-based level gauge according to claim 1, characterized in that, When calculating the height difference, the signal processing system module compares the pixel coordinates of the dot matrix light points in the current image with the standard light point pixel coordinates stored during system calibration to obtain the pixel offset, and converts the pixel offset into the physical height difference according to the pre-calibrated mapping coefficient.

7. A liquid level gauge based on image and millimeter wave as described in claim 1, characterized in that, The power supply system unit includes a solar power supply module and / or an AC power supply module.

8. A liquid level detection method based on image and millimeter wave, applied to a liquid level gauge as described in any one of claims 1-7, characterized in that, Includes the following steps: The distance data from the radar probe to the reflector surface is continuously collected through the millimeter-wave liquid level detection module; Determine if the currently collected distance data has undergone a sudden change; If no sudden change occurs, the liquid level height is calculated and output based on the current distance data and the equipment installation height; If a sudden change occurs, the image acquisition module is activated, which projects dot matrix light onto the water surface through its dot matrix structured light projector and acquires water surface images containing the dot matrix light through a high-definition image acquisition camera. The image is processed to extract the dot matrix light features, and the height difference between the floating objects on the water surface and the real water surface is calculated based on these features. By combining the distance data and the height difference, the corrected true liquid level height is calculated and output.

9. The liquid level detection method based on image and millimeter wave as described in claim 8, characterized in that, In the judgment step, the current distance data is compared with the dynamically updated historical stable distance values ​​to determine whether a sudden change has occurred.

10. The liquid level detection method based on image and millimeter wave as described in claim 8, characterized in that, The steps for calculating the height difference include: extracting the actual pixel coordinates of the dot matrix light spots in the image, matching them with the standard pixel coordinates obtained during system calibration, calculating the average pixel offset, and then using pre-calibrated coefficients to convert the average pixel offset into a physical height difference.

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