A multi-sensor based online detection system and method for suspended sediment concentration

Abstract

This invention discloses an online suspended sediment concentration detection system and method based on multiple sensors, relating to the field of hydrological monitoring technology. The online suspended sediment concentration detection system based on multiple sensors includes a sensing unit, an edge processing unit, a cloud analysis unit, and an application interaction unit connected in sequence. The sensing unit includes an optical detection module, a dielectric detection module, and an impedance detection module. The edge processing unit includes an STM32 microcontroller and a 4G dial-up internet module. The STM32 microcontroller is used to preprocess and encapsulate the data detected by the sensing unit. The 4G dial-up internet module is used to encrypt and transmit the encapsulated detection data to the cloud analysis unit. The cloud analysis unit is used to output a predicted sediment concentration value based on the encapsulated detection data. The application interaction unit provides a visualization interface for the predicted sediment concentration value. This invention meets the high-precision measurement requirements in different hydrological scenarios.

Description

Technical Field

[0001] This invention relates to an online detection system and method for suspended sediment concentration based on multiple sensors, belonging to the field of hydrological monitoring technology. Background Technology

[0002] Real-time and accurate monitoring of suspended sediment concentration (SSC) plays an irreplaceable and crucial role in river ecological management, reservoir operation regulation, and the construction of flood control and disaster relief systems. Based on different measurement principles, sediment concentration measurement methods can be divided into direct and indirect methods. Direct measurement methods include the drying method and the specific gravity method; indirect methods include photometry, infrared spectroscopy, capacitance spectroscopy, vibration spectroscopy, ultrasonic spectroscopy, laser spectroscopy, and gamma-ray spectroscopy. Direct measurement methods use simple equipment and are faster and more direct. However, at high sediment concentrations, the data from the measuring cylinder is difficult to read accurately, and the requirements for drying temperature and heating time make the entire measurement process time-consuming and laborious, affecting the accuracy of the measurement results to some extent. Photometric and infrared methods can measure extremely low sediment content. Due to the large variation in sediment content in runoff during slope erosion, the capacitance is greatly affected by temperature. The output voltage across the capacitor increases nonlinearly with increasing temperature and soil salinity. In addition, the runoff velocity also affects the applicability of the capacitance method. The results of the vibration method for measuring sediment content are unstable, with severe zero-point drift. Furthermore, the measuring instrument is large, and the runoff depth in slope erosion is shallow, making it impossible for the vibration device to work properly. Therefore, such instruments are not suitable for measuring runoff sediment content, but only for measuring sediment content in rivers.

[0003] Current technological systems have significant shortcomings: measurement methods relying on single sensors are susceptible to environmental interference and lack multi-physical quantity collaborative calibration mechanisms, making it difficult to simultaneously meet the wide-range measurement requirements for both low and high concentrations. In data transmission, traditional monitoring systems often rely on wired transmission or inefficient wireless communication technologies, resulting in significant data transmission delays and hindering real-time decision-making. At the data processing level, traditional regression models are insufficiently adaptable to the nonlinear dynamic changes in SSC (Self-Containing Sensor Computational Sensor), while basic machine learning models struggle to effectively capture the spatiotemporal correlation characteristics between sensor data. Summary of the Invention

[0004] The purpose of this invention is to provide an online detection system and method for suspended sediment concentration based on multiple sensors. By incorporating an edge-cloud collaborative computing architecture, enhancing environmental anti-interference capabilities through multimodal data fusion, achieving real-time data preprocessing through edge computing, and dynamically adjusting sensor weight configuration using intelligent algorithms, the system can meet the high-precision measurement requirements of different hydrological scenarios.

[0005] To achieve the above objectives, the present invention is implemented using the following technical solution.

[0006] On the one hand, the present invention provides an online detection system for suspended sediment content based on multiple sensors, comprising a sensing unit, an edge processing unit, a cloud analysis unit and an application interaction unit connected in sequence; The sensing unit includes an optical detection module, a dielectric detection module, and an impedance detection module; the optical detection module is used to measure the optical reflection intensity of the water body; the dielectric detection module is used to measure the change in the dielectric constant of the water body; and the impedance detection module is used to measure the complex impedance spectrum data of the water body. The edge processing unit includes an STM32 microcontroller and a 4G dial-up internet access module; The STM32 microcontroller is used to preprocess and format the data detected by the sensing unit. The 4G dial-up internet module is used to encrypt and transmit the packaged detection data to the cloud analysis unit. The cloud-based analysis unit is used to output a predicted sand content value based on the packaged detection data. The application interaction unit is used to provide a visualization interface for the predicted sediment content.

[0007] Optionally, the optical detection module employs a fiber optic diffuse reflection sensor.

[0008] Optionally, the dielectric detection module uses an FDC2214 chip as a capacitance sensor, with an excitation frequency configured to 1.5-2.0MHz; a temperature sensor is provided at the point where the FDC2214 chip is attached to the capacitor electrode.

[0009] Optionally, the impedance detection module uses an AD5933 chip as an impedance sensor, with a sweep frequency range of 10-100kHz and an excitation voltage of 100-200mVpp.

[0010] Secondly, the present invention provides an online detection method for suspended sediment content based on multiple sensors, comprising: The raw data is obtained by collecting optical and electrical parameters of the water body through the sensing unit; The STM32 microcontroller performs filtering and encapsulation processing on the raw data to obtain the encapsulated data. The 4G dial-up internet module encrypts the encapsulated data using an encryption protocol and uploads it to the cloud analysis unit. The cloud-based analysis unit outputs a predicted sand content value based on the packaged detection data. The application's interactive unit displays the predicted sediment concentration in real time.

[0011] Optionally, the process of preprocessing and format encapsulating the data detected by the sensing unit is as follows: The data measured by the fiber optic diffuse reflection sensor are subjected to moving average filtering, the data measured by the capacitance sensor are subjected to first-order Kalman filtering, and the data measured by the impedance sensor are subjected to complex Kalman filtering. The filtered data from the fiber optic diffuse reflection sensor, the capacitance sensor, and the impedance sensor are then encapsulated in JSON format.

[0012] Optionally, the encrypted transmission uses the MQTT protocol (Message Queuing Telemetry Transport).

[0013] Optionally, the cloud analysis unit deploys a PSO-LSTM fusion model (a hybrid prediction model combining particle swarm optimization algorithm and long short-term memory neural network), inputting the encapsulated data from the capacitance sensor and the impedance sensor into the PSO-LSTM fusion model to output the predicted sand content.

[0014] Optionally, the PSO-LSTM fusion model also includes a dynamic compensation mechanism: when the temperature sensor on the capacitive sensor detects a temperature change, it triggers the impedance sensor to recalibrate; when the change in fiber reflection intensity detected by the fiber diffuse reflection sensor exceeds a threshold, it automatically increases the sampling frequency of the capacitive sensor.

[0015] Thirdly, the present invention provides a computer-readable storage medium having a computer program / instructions stored thereon, which, when executed by a processor, implements the steps of the online detection method for suspended sediment content based on multiple sensors as described in any of the second aspects.

[0016] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: 1. This invention utilizes an edge-cloud collaborative computing architecture to enhance environmental anti-interference capabilities through multimodal data fusion, achieves real-time data preprocessing through edge computing, and dynamically adjusts sensor weight configuration using intelligent algorithms, thereby meeting the high-precision measurement requirements of different hydrological scenarios.

[0017] 2. The application interaction unit of this invention provides a human-computer interaction interface, supporting real-time data display, historical record management, and system configuration functions. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of the online suspended sediment content detection system based on multiple sensors according to the present invention; Figure 2 This is a logic structure diagram of the STM32 microcontroller of the present invention; Figure 3 This is a flowchart illustrating the design process of the application interaction unit display interface of the present invention. Detailed Implementation

[0019] The technical solution of the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the embodiments of the present invention and the specific features in the embodiments are detailed descriptions of the technical solution of the present invention, rather than limitations thereof. In the absence of conflict, the embodiments of the present invention and the technical features in the embodiments can be combined with each other. Example 1:

[0020] This embodiment introduces an online detection system for suspended sediment concentration based on multiple sensors, such as... Figure 1 As shown, it includes a sensing unit, an edge processing unit, a cloud analysis unit, and an application interaction unit connected in sequence; The sensing unit includes an optical detection module, a dielectric detection module, and an impedance detection module; the optical detection module is used to measure the optical reflection intensity of the water body; the dielectric detection module is used to measure the change in the dielectric constant of the water body; and the impedance detection module is used to measure the complex impedance spectrum data of the water body. The edge processing unit includes an STM32 microcontroller and a 4G dial-up internet access module; The STM32 microcontroller is used to preprocess and format the data detected by the sensing unit. The 4G dial-up internet module is used to encrypt and transmit the packaged detection data to the cloud analysis unit. The cloud-based analysis unit is used to output a predicted sand content value based on the packaged detection data. The application interaction unit is used to provide a visualization interface for the predicted sediment content.

[0021] In this embodiment, the optical detection module is equipped with a Φ200μm multimode fiber optic probe (model FS-N18N), installed inside a 304 stainless steel protective cover. The probe is 2cm above the water surface, using a 650nm wavelength light source and a sampling frequency of 10Hz. The dielectric detection module uses an FDC2214 capacitance sensor, set with an excitation frequency of 1.8MHz, an electrode spacing of 10mm, and an epoxy resin anti-corrosion layer covering the surface. The impedance detection module uses an AD5933 chip, set with a sweep frequency range of 20-80kHz, a sampling density of 128 points / cycle, and an excitation voltage of 200mVpp. For environmental compensation, a DS18B20 temperature sensor is integrated on the back of the capacitance electrode, with a sampling interval of 1 second. Example 2:

[0022] Based on the same inventive concept as Embodiment 1, this embodiment introduces an online detection method for suspended sediment concentration based on multiple sensors, including: The raw data is obtained by collecting optical and electrical parameters of the water body through the sensing unit; The STM32 microcontroller performs filtering and encapsulation processing on the raw data to obtain the encapsulated data. The 4G dial-up internet module encrypts the encapsulated data using an encryption protocol and uploads it to the cloud analysis unit. The cloud-based analysis unit outputs a predicted sand content value based on the packaged detection data. The application's interactive unit displays the predicted sediment concentration in real time.

[0023] like Figure 2 As shown, the STM32 microcontroller synchronously acquires capacitance and impedance data via the SPI interface and reads the fiber optic voltage signal through the ADC channel. During data processing, a first-order Kalman filter is applied to the acquired capacitance data, a frequency-division complex Kalman filter is used for the impedance data (real and imaginary parts are processed independently), and the optical data is noise-reduced using a moving average filter. The processed data is encapsulated in JSON format and transmitted to the 4G dial-up internet module via the UART interface. The 4G dial-up internet module accesses the mobile network via PPP dial-up, uses the MQTT protocol for data transmission, and enables TLS 1.3 encryption to ensure communication security.

[0024] The cloud-based analysis unit deploys a PSO-LSTM fusion model, inputting encapsulated data from capacitance sensors and impedance sensors into the model to output a predicted sediment content. The network structure consists of three LSTM layers (128 / 64 / 32 units) and a regularization layer with a 0.2 dropout rate. Model training employs a particle swarm optimization algorithm, with 50 particles iterating 200 times, aiming to minimize the validation set MAE. The search space covers the learning rate [0.001, 0.01] and the time step [10, 30].

[0025] The PSO-LSTM fusion model also includes a dynamic compensation mechanism: the impedance data is converted into magnitude and phase angle, and the impedance sensor reference value is updated when the temperature change exceeds the threshold three times in a row; the optical reflection intensity is logarithmically transformed, and when the fiber reflection intensity change rate exceeds 5% / s, the capacitance sampling rate is temporarily increased to 50Hz and lasts for 10 seconds.

[0026] like Figure 3 As shown, the application interaction unit provides a real-time monitoring interface, displaying the sediment concentration prediction curve at a 1Hz refresh rate. It supports overlay analysis of raw data from multiple sensors and allows for chart zooming via gestures or buttons. The data management module uses SQLite to store historical data for the past 30 days and supports exporting in CSV / Excel formats. The system log module records the device's operating status, providing a basis for troubleshooting. Example 3:

[0027] Based on the same inventive concept as other embodiments, this embodiment introduces a computer-readable storage medium storing a computer program / instructions thereon, which, when executed by a processor, implements the steps of the online detection method for suspended sediment concentration based on multiple sensors as described in any of Embodiment 2.

[0028] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0029] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0030] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0031] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0032] The embodiments of the present invention have been described above with reference to the accompanying drawings. However, the present invention is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of the present invention without departing from the spirit and scope of the claims. All of these forms are within the protection scope of the present invention.

Claims

1. A multi-sensor based online detection system for suspended sediment concentration, characterized in that, It includes a sensing unit, an edge processing unit, a cloud analysis unit, and an application interaction unit connected in sequence; The sensing unit includes an optical detection module, a dielectric detection module, and an impedance detection module; the optical detection module is used to measure the optical reflection intensity of the water body; the dielectric detection module is used to measure the change in the dielectric constant of the water body; and the impedance detection module is used to measure the complex impedance spectrum data of the water body. The edge processing unit includes an STM32 microcontroller and a 4G dial-up internet access module; The STM32 microcontroller is used to preprocess and format the data detected by the sensing unit. The 4G dial-up internet module is used to encrypt and transmit the packaged detection data to the cloud analysis unit. The cloud-based analysis unit is used to output a predicted sand content value based on the packaged detection data. The application interaction unit is used to provide a visualization interface for the predicted sediment content.

2. The multi-sensor based online detection system for sediment concentration of suspended sediment according to claim 1, wherein, The optical detection module uses a fiber optic diffuse reflection sensor. 3.The multi-sensor based online detection system for suspended sediment concentration according to claim 1, wherein, The dielectric detection module uses an FDC2214 chip as a capacitance sensor, with an excitation frequency configured to be 1.5-2.0MHz; a temperature sensor is provided at the point where the FDC2214 chip is attached to the capacitor electrode.

4. The multi-sensor based online detection system for sediment concentration of suspended sediment according to claim 1, wherein, The impedance detection module uses an AD5933 chip as an impedance sensor, with a sweep frequency range of 10-100kHz and an excitation voltage of 100-200mVpp.

5. A multi-sensor based online detection method of sediment concentration of suspended sediment, characterized in that, include: The raw data is obtained by collecting optical and electrical parameters of the water body through the sensing unit; The STM32 microcontroller performs filtering and encapsulation processing on the raw data to obtain the encapsulated data. The 4G dial-up internet module encrypts the encapsulated data using an encryption protocol and uploads it to the cloud analysis unit. The cloud-based analysis unit outputs a predicted sand content value based on the packaged detection data. The application's interactive unit displays the predicted sediment concentration in real time.

6. The method according to claim 5, wherein, The process of preprocessing and format encapsulating the data detected by the sensing unit is as follows: The data measured by the fiber optic diffuse reflection sensor are subjected to moving average filtering, the data measured by the capacitance sensor are subjected to first-order Kalman filtering, and the data of the impedance sensor are subjected to complex Kalman filtering. The filtered data from the fiber optic diffuse reflection sensor, the capacitance sensor, and the impedance sensor are encapsulated in JSON format.

7. The method according to claim 5, wherein, The encrypted transmission uses the MQTT protocol. 8.The method according to claim 5, wherein, The cloud-based analysis unit deploys a PSO-LSTM fusion model, which inputs the encapsulated data from the capacitance sensor and the impedance sensor into the PSO-LSTM fusion model and outputs the predicted value of sand content. 9.The method according to claim 8, wherein, The PSO-LSTM fusion model also includes a dynamic compensation mechanism: when the temperature sensor on the capacitive sensor detects a temperature change, it triggers the impedance sensor to recalibrate; when the change in fiber reflection intensity detected by the fiber diffuse reflection sensor exceeds a threshold, it automatically increases the sampling frequency of the capacitive sensor.

10. A computer readable storage medium having stored thereon computer programs / instructions, characterized in that, When the computer program / instructions are executed by the processor, they implement the steps of the online detection method for suspended sediment concentration based on multiple sensors as described in any one of claims 5 to 9.

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