Intelligent Ultrasonic-Assisted ToF Water Level Monitoring Device and Method

Abstract

The present application provides an intelligent ultrasonic-assisted ToF water level monitoring device and method, which relates to the technical field of water level monitoring, and includes: building a water level monitoring device; respectively performing power supply and support connection, and at the same time performing auxiliary biological deposition removal treatment; transmitting signals for ranging through a ToF sensor; according to a preset acquisition period, performing data communication acquisition on the water level ranging monitoring signal stream; invoking a water level ranging data algorithm model library, respectively performing matching data processing on the water level ranging periodic signal stream set, and performing change trend analysis to generate a target water level monitoring report. Through the present application, the technical problem in the prior art that due to the fact that traditional water level sensors are easily affected by river weeds, etc., resulting in false alarms and low accuracy of water level monitoring data can be solved. By integrating a ToF sensor and an ultrasonic module, false alarms caused by objects such as river weeds are reduced, and the accuracy of water level monitoring data is improved.

Description

Technical Field

[0001] This application relates to the technical field of water level monitoring, and particularly to an intelligent ultrasonic-assisted ToF water level monitoring device and method. Background Art

[0002] When typhoons and rainy seasons arrive, due to the sharp increase in water volume, the risks of river overflow and levee breach are significantly increased. In such cases, accurate and timely water level monitoring is crucial for early warning of potential risks and providing effective information for levee maintenance and personnel evacuation. However, there are some problems with existing water level monitoring technologies. Traditional water level sensors, such as millimeter-wave sensors, are vulnerable to the influence of objects such as weeds in the river environment, resulting in false alarms. In addition, biological deposits may adhere to the sensors or floating boards / balls, affecting the measurement accuracy.

[0003] In summary, in the prior art, there is a technical problem that due to traditional water level monitoring devices, such as millimeter-wave water level sensors, being easily affected by objects such as weeds in the river environment, false reports are caused, resulting in low accuracy of water level monitoring data. Summary of the Invention

[0004] The purpose of this application is to provide an intelligent ultrasonic-assisted ToF water level monitoring device and method to solve the technical problem in the prior art that due to traditional water level sensors being easily affected by objects such as weeds in the river environment, false reports are caused, resulting in low accuracy of water level monitoring data.

[0005] In view of the above problems, this application provides an intelligent ultrasonic-assisted ToF water level monitoring device and method.

[0006] In a first aspect, the present application provides an intelligent ultrasonic-assisted ToF water level monitoring device. Among them, the intelligent ultrasonic-assisted ToF water level monitoring device includes: a device construction unit for constructing a water level monitoring device, where the water level monitoring device includes a ToF sensor, an ultrasonic module, a power management module, a floating board or a floating ball, a wireless communication module, a data processor, and corresponding support and connection devices; a device processing unit for supplying power and providing support and connection to the water level monitoring device respectively through the power management module and the corresponding support and connection devices, and at the same time driving the ultrasonic module to perform auxiliary biological deposition removal processing on the water level monitoring device; a signal transmitting unit for using the floating board or the floating ball as a cooperation target, and transmitting signals and measuring distances to the target water surface through the ToF sensor to collect and obtain a water level distance measurement monitoring signal stream; a data acquisition unit for performing data communication acquisition on the water level distance measurement monitoring signal stream through the wireless communication module based on the data processor according to a preset acquisition period to obtain a set of water level distance measurement period signal streams; a trend analysis unit for calling a water level distance measurement data algorithm model library through the data processor, performing matching data processing on the set of water level distance measurement period signal streams respectively based on the water level distance measurement data algorithm model library to obtain a set of target period water level information, and performing a change trend analysis according to the set of target period water level information to generate a target water level monitoring report.

[0007] In a second aspect, the present application further provides an intelligent ultrasonic-assisted ToF water level monitoring method. Among them, the intelligent ultrasonic-assisted ToF water level monitoring method includes: constructing a water level monitoring device, where the water level monitoring device includes a ToF sensor, an ultrasonic module, a power management module, a floating board or a floating ball, a wireless communication module, a data processor, and corresponding support and connection devices; supplying power and providing support and connection to the water level monitoring device respectively through the power management module and the corresponding support and connection devices, and at the same time driving the ultrasonic module to perform auxiliary biological deposition removal processing on the water level monitoring device; using the floating board or the floating ball as a cooperation target, and transmitting signals and measuring distances to the target water surface through the ToF sensor to collect and obtain a water level distance measurement monitoring signal stream; performing data communication acquisition on the water level distance measurement monitoring signal stream through the wireless communication module based on the data processor according to a preset acquisition period to obtain a set of water level distance measurement period signal streams; calling a water level distance measurement data algorithm model library through the data processor, performing matching data processing on the set of water level distance measurement period signal streams respectively based on the water level distance measurement data algorithm model library to obtain a set of target period water level information, and performing a change trend analysis according to the set of target period water level information to generate a target water level monitoring report.

[0008] One or more technical solutions provided in the present application have at least the following technical effects or advantages:

[0009] A device construction unit is used to construct a water level monitoring device. The water level monitoring device includes a ToF sensor, an ultrasonic module, a power management module, a floating board or a floating ball, a wireless communication module, a data processor, and corresponding support and connection devices. A device processing unit is used to supply power and support and connect the water level monitoring device through the power management module and the corresponding support and connection devices, and at the same time drive the ultrasonic module to perform auxiliary biological sediment removal processing on the water level monitoring device. A signal transmitting unit is used to use the floating board or the floating ball as a cooperation target, and transmit signals and measure distances to the target water surface through the ToF sensor to collect and obtain a water level distance measurement monitoring signal stream. A data collection unit is used to perform data communication collection on the water level distance measurement monitoring signal stream based on the data processor according to a preset collection period through the wireless communication module to obtain a set of water level distance measurement periodic signal streams. A trend analysis unit is used to call a water level distance measurement data algorithm model library through the data processor, perform matching data processing on the set of water level distance measurement periodic signal streams based on the water level distance measurement data algorithm model library respectively to obtain a set of target periodic water level information, and perform a change trend analysis according to the set of target periodic water level information to generate a target water level monitoring report. That is to say, by constructing a water level monitoring device integrating a ToF sensor and an ultrasonic module, false alarms caused by objects such as river weeds are reduced. The ultrasonic module assists in removing biological sediments. The wireless communication module and the data processor improve the efficiency and automation of data collection and analysis, and improve the accuracy of water level monitoring data in a complex environment.

[0010] The above description is only an overview of the technical solution of the present application. In order to be able to understand the technical means of the present application more clearly, it can be implemented according to the content of the specification. And in order to make the above and other purposes, features and advantages of the present application more obvious and understandable, the following specifically gives the specific implementation manners of the present application. It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present application, nor is it used to limit the scope of the present application. Other features of the present application will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] In order to more clearly illustrate the technical solutions in the present application or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings described below are only exemplary, and for those of ordinary skill in the art, other drawings can be obtained according to the provided drawings without creative efforts.

[0012] Figure 1 It is a structural schematic diagram of the intelligent ultrasonic-assisted ToF water level monitoring device of the present application;

[0013] Figure 2This is a schematic flowchart of the intelligent ultrasonic-assisted ToF water level monitoring method of the present application.

[0014] Explanation of reference numerals: Device construction unit 11, device processing unit 12, signal transmission unit 13, data acquisition unit 14, trend analysis unit 15. Detailed implementation manners

[0015] By providing an intelligent ultrasonic-assisted ToF water level monitoring device and method, the present application solves the technical problem in the prior art that due to the traditional water level sensor being easily affected by objects such as weeds in the river environment, false alarms occur, resulting in low accuracy of water level monitoring data. By building a water level monitoring device integrating a ToF sensor and an ultrasonic module, false alarms caused by river weeds and other objects are reduced. The ultrasonic module assists in removing biological sediments, and the wireless communication module and data processor improve the efficiency and automation of data acquisition and analysis, and improve the accuracy of water level monitoring data in complex environments.

[0016] Next, the technical solutions in the present application will be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. It should be understood that the present application is not limited by the example embodiments described here. Based on the embodiments of the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the scope of protection of the present application. In addition, it should be noted that for the convenience of description, only the parts related to the present application are shown in the drawings, rather than all of them.

[0017] Embodiment 1. Please refer to the attached Figure 1 drawings. The present application provides an intelligent ultrasonic-assisted ToF water level monitoring device. Among them, the intelligent ultrasonic-assisted ToF water level monitoring device is used to implement the steps of the intelligent ultrasonic-assisted ToF water level monitoring method. The intelligent ultrasonic-assisted ToF water level monitoring device includes:

[0018] A device construction unit 11, which is used to build a water level monitoring device. The water level monitoring device includes a ToF sensor, an ultrasonic module, a power management module, a floating board or a floating ball, a wireless communication module, a data processor, and corresponding support and connection devices.

[0019] Specifically, a comprehensive water level monitoring device is built, integrating multiple technical modules, including a ToF sensor, an ultrasonic module, a power management module, a floating board or a floating ball, a wireless communication module, a data processor, and corresponding support and connection devices. Among them, the ToF sensor is the core measurement component of the device, which is used to emit optical signals (such as infrared light) and measure the time from signal emission to return, so as to accurately calculate the water level. The ToF sensor is not sensitive to environmental changes and can provide more stable and accurate measurement results under various conditions. The ToF sensor has the advantages of anti-light interference, long-distance ranging, and high ranging accuracy. The ultrasonic module assists the ToF sensor in measurement. It measures the distance by sending and receiving ultrasonic pulses and is also used to assist in removing biological deposits to keep the sensor clean, thus ensuring measurement accuracy. The ultrasonic module exists to remove possible blockages in the anti-biological net. Through short-term high-energy ultrasonic vibration and the cavitation effect of water, the activity of organisms is destroyed. At the same time, part of the attached organisms or other dirt is removed in the form of vibration to prevent the water inlet from being blocked and affecting measurement and monitoring.

[0020] The power management module is responsible for providing stable power for the entire device. The floating board or floating ball, as a cooperation target for the ToF sensor, is provided to overcome the inability of the optical sensor to directly monitor the water surface. The floating board or floating ball helps to stabilize the sensor and keep it in an appropriate position on the water surface. The wireless communication module allows the device to wirelessly transmit the collected data to the data processing center. The data processor is the brain of the device, responsible for processing and analyzing the collected data. According to the preset collection period, it receives data through the wireless communication module and invokes the water level ranging data algorithm model library for data processing. It periodically collects the target data of the ToF sensor and judges the current average water level through an algorithm that combines historical data. The support and connection devices are used to fix and support the device to ensure its correct position and stability in the water. Specifically, they include components such as brackets, pipes, ventilation holes, and biological nets. The ventilation holes ensure the internal pressure balance of the device, and the biological net is used to prevent biological attachment and protect the sensor.

[0021] When the water level monitoring device is working properly, it is fixed by brackets and pipes beside the river. Among them, the pipes and brackets play a protective role. Install the brackets at the monitoring points, fix the pipes on the brackets, and fix other components. Set ventilation holes on the pipes to facilitate the signal transmission of the sensors and communication modules. At the same time, install a biological net at the appropriate position of the pipe to prevent organisms from entering the pipe and interfering with the device. Install the ToF sensor at the appropriate position of the pipe to ensure that it can be vertically aligned with the water surface. There is a vibration isolation structure and a gap between the sensor end and the pipe, and they are not in close contact to avoid ultrasonic imaging sensors. The sensor end is convenient to disassemble, providing a possible rapid cleaning channel. Install the ultrasonic module near the ToF sensor and connect it to the outer wall of the pipe through bolts and stainless steel cranks to facilitate the cleaning of the sensor. Connect the power management module to each component of the device to ensure power supply. Place a floating board or a floating ball on the water surface as a reference target for the ToF sensor to measure the distance. Install the wireless communication module on the device and ensure that its signal transmission path is unobstructed. Install the data processor inside the device and connect all sensors and communication modules. By setting up the water level monitoring device, it is ensured that efficient and accurate water level monitoring can be provided in various environments, especially suitable for application scenarios that require high-precision and reliable monitoring, such as water resource management, flood warning, and reservoir operation.

[0022] The device processing unit 12 is used to supply power and support connection to the water level monitoring device respectively through the power management module and the corresponding support connection device, and at the same time drive the ultrasonic module to perform auxiliary biological deposit removal processing on the water level monitoring device.

[0023] Specifically, the power management module may include a battery, a solar panel or other power supply devices, as well as related circuits and control systems, which are responsible for providing stable power for the entire water level monitoring device, such as the ToF sensor, the ultrasonic module, the wireless communication module, the data processor, etc. The support connection device includes brackets, pipes, and components such as ventilation holes and biological nets. The ventilation holes ensure the internal pressure balance of the device, and the biological net is used to prevent biological attachment and protect the sensors. Install the brackets at the monitoring points to ensure that they are stable and horizontal and can support the weight of the entire device. The processor periodically drives the ultrasonic module to work for a short time to process the possible attached biological deposits, prevent the device pipes from being blocked, and automatically start the resonance point scanning before and after work to ensure the normal resonance of the system and achieve the expected effect. The ultrasonic module is not only used for auxiliary measurement but also for removing biological deposits. Through high-frequency vibration, the biological deposits attached to the device surface, such as algae, shellfish or other aquatic organisms, are removed, which helps to keep the sensors clean and thus ensures the measurement accuracy. The power management module ensures that the device can obtain stable power supply under various conditions. The support connection device ensures the stability and correct position of the device in the water. The auxiliary biological deposit removal processing of the ultrasonic module reduces the maintenance requirements and improves the reliability and measurement accuracy of the device.

[0024] A signal transmitting unit 13 is configured to use the floating board or floating ball as a cooperation target, and perform signal transmission ranging on the target water surface through the ToF sensor to collect and obtain a water level ranging monitoring signal stream.

[0025] Specifically, the floating board or floating ball serves as a cooperation target for the ToF sensor, providing a stable and easily recognizable reflection surface, enabling the ToF sensor to accurately measure the distance between it and the water surface. Since the floating board or floating ball floats on the water surface, the distance between the floating board or floating ball and the ToF sensor represents the current water level height. The ToF sensor emits an optical signal (such as infrared light) to the floating board or floating ball and measures the time from signal emission to return, and can accurately calculate the distance between the sensor and the floating board or floating ball. Generally, the floating board or floating ball needs to be placed on the water surface to ensure its stable position and not move significantly due to water flow or wind. The ToF sensor is installed on a bracket or pipeline at a certain height above the water surface to ensure no obstruction within its line of sight and is aligned with the center of the floating board or floating ball to ensure the accuracy of signal emission and reception. By using the floating board or floating ball as a target and combining the precise measurement ability of the ToF sensor, the water level monitoring device can provide efficient and accurate water level monitoring in various environments.

[0026] A data acquisition unit 14 is configured to perform data communication acquisition on the water level ranging monitoring signal stream based on the data processor according to a preset acquisition period through the wireless communication module to obtain a water level ranging period signal stream set.

[0027] Specifically, the data processor is the brain of the device, responsible for processing and analyzing the collected data. According to the preset acquisition period, it receives data through the wireless communication module and invokes the water level ranging data algorithm model library for data processing. Determine the data acquisition frequency according to monitoring requirements and environmental conditions, such as every minute, every hour, or every day. Set the acquisition period in the data processor to ensure that it can automatically perform data acquisition at a preset time interval. The data processor triggers the ToF sensor to perform water level ranging at regular intervals according to the preset acquisition period. The ToF sensor emits a signal and receives the signal reflected from the floating board or floating ball, and calculates the water level distance. Record the water level distance data measured each time in the data processor, pack it in a certain format, and send it to the monitoring center or cloud server through the wireless communication module. Store the received water level ranging data on the monitoring center or cloud server, and organize the data within the same acquisition period into a set to form a water level ranging period signal stream set. Ensure that the water level monitoring device effectively acquires and transmits water level data through the wireless communication module according to the preset acquisition period, so as to form a water level ranging period signal stream set on the monitoring center or cloud server.

[0028] A trend analysis unit 15 is configured to call a water level ranging data algorithm model library through the data processor, perform matching data processing on the water level ranging period signal flow set based on the water level ranging data algorithm model library, obtain a target period water level information set, and perform a change trend analysis based on the target period water level information set to generate a target water level monitoring report.

[0029] Specifically, analyze the influencing factors of the water level monitoring scenario to determine various factor combination parameters that affect the accuracy of water level data processing. Match the data processing algorithms with the water level ranging factor parameter table to obtain an adaptation data processing algorithm set for various factor parameters. Integrate and configure to obtain a complete water level ranging data algorithm model library, which contains a complete algorithm set from data filtering to data processing. The data processor processes the water level ranging period signal flow set according to the models in the water level ranging data algorithm model library, including operations such as filtering, feature extraction, and prediction, to extract and optimize the water level data. Through data processing, a set containing target period water level information is obtained, which includes the processed water level data and reflects the water level changes and states within a specific time period. Perform a change trend analysis on the target period water level information set, compare the data at different time points, identify the patterns or trends of water level changes, such as rising, falling, stable, etc. Detect any abnormal changes in the trend analysis, such as sudden rises or drops. Generate a water level monitoring report based on the change trend analysis and abnormal monitoring results, which includes detailed information on water level changes, such as water level change trend charts, abnormal event records, water level accuracy analysis, confidence level assessment, etc. By using the trained models for data processing, improve the accuracy of data processing, optimize the data processing effect, and thus generate accurate and reliable water level monitoring reports to provide decision-making support for water resource management, flood warning, environmental protection, etc.

[0030] Furthermore, the trend analysis unit 15 in the intelligent ultrasonic-assisted ToF water level monitoring device is further configured to:

[0031] Obtain a water level ranging factor parameter table, perform noise characteristic analysis and filter algorithm configuration in sequence based on the water level ranging factor parameter table to obtain a multi-factor data filtering algorithm list; obtain data filtering preprocessing nodes according to the multi-factor data filtering algorithm list; perform data processing algorithm matching based on the water level ranging factor parameter table to obtain a multi-factor data processing algorithm model list, and train a water level data processing node based on the multi-factor data processing algorithm model list; sequentially integrate and configure the data filtering preprocessing nodes and the water level data processing nodes to obtain the water level ranging data algorithm model library, and store the water level ranging data algorithm model library in the data processor.

[0032] Specifically, the water level ranging factor parameter table includes various factor combination parameters that affect the accuracy of water level data processing, such as water temperature, water surface fluctuations, water quality, reflections from surrounding objects, atmospheric conditions, etc. Conduct a noise characteristic analysis on the water level ranging factor parameter table to identify and quantify various noises that affect the accuracy of water level measurement data, including the types of noises (such as random noise, periodic noise, etc.) and characteristics. According to the noise characteristics, select a suitable filtering algorithm for each factor, such as low-pass filtering, high-pass filtering, band-pass filtering, Kalman filtering, etc. The filtering algorithm is used to remove or reduce the noise in the data, improving the accuracy and reliability of the data. Configure the selected filtering algorithm as a parameterized list to form a multi-factor data filtering algorithm list, including the adaptive filtering algorithms for various factor parameters in the water level ranging factor parameter table. Based on the multi-factor data filtering algorithm list, select and configure a data filtering algorithm suitable for the current measurement environment and conditions to remove or reduce the noise in the data at the initial stage of the data processing flow, improving the accuracy and reliability of the data.

[0033] Select and configure a data processing algorithm suitable for the current measurement environment and conditions for the water level ranging factor parameter table, such as linear regression, neural network, support vector machine, etc. Through algorithm matching, obtain a model list containing multiple data processing algorithms. Each algorithm model is optimized and configured according to specific factor parameters and data processing requirements. Prepare a training data set, including the input water level ranging data and the corresponding target output. Use the training data set to train each model in the multi-factor data processing algorithm model list to obtain water level data processing nodes. Integrate and configure the data filtering preprocessing node and the water level data processing node in a certain order to form a complete data processing flow. Through the integration and configuration, obtain a complete water level ranging data algorithm model library, including a complete set of algorithms from data filtering to data processing, for optimizing and improving the accuracy and reliability of water level measurement data. Store the water level ranging data algorithm model library in the data processor so that the data processor can access and call these algorithm models to process and optimize the collected water level measurement data. By integrating and configuring the data filtering preprocessing node and the water level data processing node, form a complete and optimized data processing flow, select and configure filtering algorithms and processing algorithms suitable for the current environment and conditions, reduce the errors in the data, and improve the accuracy and reliability of the data. The multi-factor data filtering algorithm list and the data processing algorithm model list allow the selection of the most suitable processing method according to different environments and conditions, enhancing the adaptability and flexibility of the system.

[0034] Furthermore, the intelligent ultrasonic-assisted ToF water level monitoring device further includes a parameter table acquisition unit for:

[0035] Analyze the influencing factors of the water level monitoring scenario information to obtain the water level monitoring influencing factor information, where the water level monitoring influencing factor information includes weather conditions, hydrogeological conditions, and water quality status; classify and fill the water level monitoring scenario information based on the water level monitoring influencing factor information to obtain a set of water level monitoring scenario factor parameters; classify and integrate the ToF sensor database by measuring the influencing factors with sensors to obtain the sensor performance factor parameter information; perform parameter orthogonal arrangement based on the set of water level monitoring scenario factor parameters and the sensor performance factor parameter information to obtain the water level ranging factor parameter table.

[0036] Specifically, analyze the water level monitoring scenario information, identify and analyze various factors affecting water level monitoring, including weather conditions (such as temperature, humidity, wind speed, precipitation, etc.), hydrogeological conditions (such as groundwater level, soil type, river flow direction, topography, etc.), and water quality status (such as pH value, dissolved oxygen, suspended solids, etc.). The water level monitoring scenario information includes the geographical location, environmental conditions, water body characteristics, etc. of the monitoring location. Classify the specific weather condition, hydrogeological condition, and water quality status parameters into the corresponding monitoring scenarios, and through classification and filling, obtain a set that includes the specific weather condition, hydrogeological condition, and water quality status parameters in each water level monitoring scenario.

[0037] Use various sensors (such as temperature sensors, humidity sensors, water quality analysis sensors, etc.) to measure various factors affecting the performance of the ToF sensor, including environmental temperature, humidity, water quality status, etc. Classify and integrate the measured influencing factor data into the ToF sensor database, that is, associate different types of influencing factor data with the corresponding ToF sensor models and performance parameters. Record the specific models, performance parameters (such as measurement range, accuracy, resolution, etc.) of the ToF sensor and calibration information to form the sensor performance factor parameter information. Adopt the method of orthogonal arrangement to combine the set of water level monitoring scenario factor parameters and the sensor performance factor parameter information to ensure that all possible factor combinations are considered. Parameter orthogonal arrangement is a multi-factor experimental design method used to arrange and combine multiple factors to determine their influence on the results. Through parameter orthogonal arrangement, obtain a set of water level ranging factor parameters containing various different combinations, including various factor combinations that may affect water level ranging under different scenarios and sensor conditions. By considering various influencing factors, improve the accuracy and reliability of water level monitoring, and adapt to different environments and conditions according to the sensor performance factor parameter information to improve the performance of the overall monitoring system. The water level monitoring device can more comprehensively consider various influencing factors of the monitoring scenario, thereby improving the accuracy and reliability of water level monitoring.

[0038] Furthermore, the intelligent ultrasonic-assisted ToF water level monitoring device further includes an algorithm model acquisition unit for:

[0039] Mine and obtain the historical water level ranging data set, classify and label the historical water level ranging data set according to the water level ranging factor parameter table to obtain a water level ranging clustering data set; construct a water level data processing algorithm list, perform data characteristic analysis and processing algorithm matching based on the water level data processing algorithm list and the water level ranging clustering data set respectively, and determine a clustering data matching algorithm set; based on the clustering data matching algorithm set, train a water level processing model for the water level ranging clustering data set respectively to obtain a water level ranging factor data processing model library; based on the water level ranging factor parameter table, perform identification integration on the water level ranging factor data processing model library to obtain the multi-factor data processing algorithm model list.

[0040] Specifically, collect and obtain past water level ranging data, including water level data measured at different times and under different conditions. Use the water level ranging factor parameter table as a classification standard to classify and label the historical data set, and group the data with the same water level ranging factor parameters into one category to form a water level ranging clustering data set. According to the requirements of data processing, select appropriate algorithms, such as deep neural network (DNN), recurrent neural network (RNN), clustering analysis algorithm, etc. Combine these algorithms into a list, namely the water level data processing algorithm list. Perform data characteristic analysis on the water level ranging clustering data set, including analyzing characteristics such as the distribution, range, and change trend of the data. According to the data characteristics, match a suitable processing algorithm for each clustering data set to form a clustering data matching algorithm set.

[0041] Use the algorithms in the clustering data matching algorithm set to train a model for the water level ranging clustering data set, and use the data set to adjust the parameters of the algorithm so that it can better adapt to the characteristics and laws of the data. Through model training, obtain a library containing multiple water level processing models. These models are trained based on different processing algorithms, and each model is optimized for specific data characteristics and processing requirements. According to the water level ranging factor parameter table, identify each model in the water level ranging factor data processing model library, that is, assign one or more identifiers related to the factor parameters it applies to for each model, so as to facilitate subsequent water level data processing. Through identification integration, obtain an adapted data processing algorithm list including various factor parameters in the water level ranging factor parameter table. Through classification and labeling and model training, improve the accuracy of data processing, optimize the data processing effect, and accurately process and analyze water level data through the trained model library and algorithm model list, improving the accuracy and efficiency of water level monitoring.

[0042] Furthermore, the trend analysis unit 15 in the intelligent ultrasonic-assisted ToF water level monitoring device is further used for:

[0043] Classify and identify the water level ranging period signal flow sets respectively according to the water level ranging factor parameter table to obtain the water level period signal factor parameter set; use the water level period signal factor parameter set as the water level factor calibration parameter set; based on the water level factor calibration parameter set, perform processing model matching with the water level ranging data algorithm model library in sequence to obtain the ranging data processing algorithm model set; based on the ranging data processing algorithm model set, perform water level data processing on the water level ranging period signal flow sets respectively to obtain the target period water level information set.

[0044] Specifically, according to the water level ranging factor parameter table (including various factor combination parameters affecting the accuracy of water level data processing), classify and identify each data flow in the water level ranging period signal flow set (a set containing water level ranging data collected within a specific time period). Group the data flows with the same water level ranging factor parameters into one category to form the water level period signal factor parameter set. Use the water level period signal factor parameter set as the water level factor calibration parameter set for subsequent model matching and data processing. Calibration parameters are parameters used to calibrate and optimize the measurement system to ensure the accuracy and reliability of measurement results. The water level period signal factor parameter set is used to calibrate and optimize the water level monitoring system to improve the accuracy and reliability of water level measurement. Match the water level factor calibration parameter set with the models in the water level ranging data algorithm model library to find the most suitable processing model for each factor parameter, forming a ranging data processing algorithm model set.

[0045] Use the models in the ranging data processing algorithm model set to process each signal flow in the water level ranging period signal flow set respectively, including filtering, feature extraction, prediction, etc., to extract and optimize the water level data. Through data processing, obtain a target period water level information set, which contains the processed water level data and reflects the water level changes and status within a specific time period. By classification identification and model matching, improve the accuracy of data processing and optimize the data processing effect. The water level monitoring device can select and apply the most suitable processing model according to different data characteristics and requirements, thereby improving the accuracy and reliability of water level monitoring data.

[0046] Furthermore, the intelligent ultrasonic-assisted ToF water level monitoring device further includes a result correction unit for:

[0047] The data processor monitors the working state of the ToF sensor to obtain the data stream of the sensor working state; performs anomaly recognition detection on the data stream of the sensor working state according to the sensor working threshold to obtain the information of abnormal sensor working data; classifies the abnormal factors and analyzes the degree of influence based on the information of abnormal sensor working data to obtain the water level accuracy influence factors; performs confidence evaluation and result correction on the target cycle water level information set based on the water level accuracy influence factors.

[0048] Specifically, the data processor monitors the working state of the ToF sensor in real time through various sensors and monitoring systems to obtain the working state data of the ToF sensor, including water level ranging data, signal strength, sampling frequency, communication status, etc., forming a data stream of the sensor working state. According to the sensor performance and design standards, normal working thresholds are set for the working parameters of the sensor, such as signal strength threshold, sampling frequency range, etc., to judge whether the working state of the sensor is normal. The data stream of the sensor working state is compared with the preset sensor working threshold, and the abnormal data exceeding the threshold is identified and recorded to form the information of abnormal sensor working data. The information of abnormal sensor working data is classified, including faults of the sensor itself (such as window contamination, electronic component faults), environmental factors (such as water surface fluctuation, atmospheric refraction), or operation errors, etc. The classified abnormal factors are analyzed to evaluate the degree of influence of each abnormal factor on the water level measurement accuracy. By calculating the error size, analyzing the data fluctuation situation, or comparing the measurement results under normal and abnormal conditions, the water level accuracy influence factors are obtained.

[0049] According to the water level accuracy influence factors, confidence evaluation is performed on each data point in the target cycle water level information set, and the reliability of the water level information is scored according to the influence factors, so as to reflect the credibility of the measurement result. According to the result of the confidence evaluation, accuracy correction is performed on the water level information, including adjusting the measurement value, adding the error range, or using a more reliable data source. Through confidence evaluation and result correction, the accuracy of the water level information is improved and the measurement error is reduced. The data processor periodically judges whether the ToF sensor works abnormally, such as window contamination (abnormal distance, too close), and provides information to the staff for cleaning. Real-time monitoring of the working state of the sensor helps to adapt to different environments and conditions and improve the performance of the overall monitoring system.

[0050] Furthermore, the intelligent ultrasonic-assisted ToF water level monitoring device further includes a parameter optimization unit for:

[0051] When the ToF sensor is in a window contamination state, analyze the contamination situation of the abnormal sensor operating data information to obtain the sensor window contamination characteristic parameters; based on the sensor window contamination characteristic parameters, perform an optimization analysis of the operating parameters of the ultrasonic module to determine the ultrasonic operating control parameter information; based on the ultrasonic operating control parameter information, verify the control effect of the ultrasonic module to obtain the deposition removal control effect, and feedback-optimize the ultrasonic operating control parameter information through the deposition removal control effect.

[0052] Specifically, when the ToF sensor is in a window contamination state, that is, the front window of the ToF sensor (i.e., the interface between the sensor and the external environment) is covered or blocked by dirt, sediment, biological attachments, or other obstacles, resulting in the sensor being unable to accurately measure or receive the reflected signal. The abnormal sensor operating data information refers to the set of abnormal sensor operating data obtained through abnormal identification detection, including abnormal voltage, current, signal strength, etc. Analyze the window contamination situation based on the abnormal sensor operating data information, including analyzing data changes, comparing measurement results under normal and contaminated conditions, etc., to determine the degree of contamination. Through the contamination situation analysis, obtain the sensor window contamination characteristic parameters, including the contamination type (such as biological attachment, sediment, etc.), contamination area, and contamination degree, etc.

[0053] According to the sensor window contamination characteristic parameters, perform an optimization analysis of the operating parameters of the ultrasonic module, and select the best ultrasonic vibration frequency, duration, energy intensity, etc. parameters according to the type, area, and degree of contamination. Through the optimization analysis of the operating parameters, determine a set of optimal ultrasonic operating control parameters for controlling the ultrasonic module to remove the contamination on the sensor window with the best effect. Use the ultrasonic operating control parameter information to control the ultrasonic module to remove the contamination on the sensor window. Verify the control effect, evaluate the control effect of the deposition removal, and check the cleanliness of the sensor window. According to the deposition removal control effect, perform feedback optimization on the ultrasonic operating control parameter information, adjust the parameters according to the actual cleaning effect, and improve the cleaning efficiency and effect. Automatically identify and handle the contamination problem of the sensor window to ensure that when the ToF sensor is contaminated on the window, through the effective cleaning of the ultrasonic module, its normal working state is restored, thereby ensuring the accuracy and reliability of the water level monitoring.

[0054] In summary, the intelligent ultrasonic-assisted ToF water level monitoring device provided by this application has the following technical effects:

[0055] A device construction unit is used to construct a water level monitoring device. The water level monitoring device includes a ToF sensor, an ultrasonic module, a power management module, a floating board or a floating ball, a wireless communication module, a data processor, and corresponding support and connection devices. A device processing unit is used to supply power and support and connect the water level monitoring device through the power management module and the corresponding support and connection devices respectively, and at the same time drive the ultrasonic module to perform auxiliary biological sediment removal processing on the water level monitoring device. A signal transmitting unit is used to use the floating board or the floating ball as a cooperation target, and transmit signals and measure distances to the target water surface through the ToF sensor to collect and obtain a water level distance measurement monitoring signal stream. A data collection unit is used to perform data communication collection on the water level distance measurement monitoring signal stream through the wireless communication module based on the data processor according to a preset collection period to obtain a set of water level distance measurement periodic signal streams. A trend analysis unit is used to call a water level distance measurement data algorithm model library through the data processor, perform matching data processing on the set of water level distance measurement periodic signal streams respectively based on the water level distance measurement data algorithm model library to obtain a set of target periodic water level information, and perform a change trend analysis according to the set of target periodic water level information to generate a target water level monitoring report. That is to say, by constructing a water level monitoring device integrating a ToF sensor and an ultrasonic module, false alarms caused by objects such as river weeds are reduced. The ultrasonic module assists in removing biological sediments, and the wireless communication module and the data processor improve the efficiency and automation of data collection and analysis, and improve the accuracy of water level monitoring data in complex environments.

[0056] Embodiment 2. Based on the same inventive concept as the intelligent ultrasonic-assisted ToF water level monitoring device in the foregoing Embodiment 1, the present application also provides an intelligent ultrasonic-assisted ToF water level monitoring method. Please refer to the appendix Figure 2 , and the intelligent ultrasonic-assisted ToF water level monitoring method includes:

[0057] Build a water level monitoring device, where the water level monitoring device includes a ToF sensor, an ultrasonic module, a power management module, a floating board or a floating ball, a wireless communication module, a data processor, and corresponding support and connection devices; the power management module and the corresponding support and connection devices are used to supply power and support and connect the water level monitoring device respectively, and at the same time drive the ultrasonic module to perform auxiliary biological deposition removal processing on the water level monitoring device; use the floating board or the floating ball as a cooperation target, emit signals and measure distances to the target water surface through the ToF sensor, and collect and obtain a water level distance measurement monitoring signal stream; based on the data processor according to a preset acquisition period, perform data communication acquisition on the water level distance measurement monitoring signal stream through the wireless communication module to obtain a water level distance measurement period signal stream set; call a water level distance measurement data algorithm model library through the data processor, perform matching data processing on the water level distance measurement period signal stream set respectively based on the water level distance measurement data algorithm model library to obtain a target period water level information set, and perform a change trend analysis according to the target period water level information set to generate a target water level monitoring report.

[0058] Further, the calling of the water level distance measurement data algorithm model library by the data processor includes:

[0059] Obtain a water level distance measurement factor parameter table, perform noise characteristic analysis and filter algorithm configuration in sequence based on the water level distance measurement factor parameter table to obtain a multi-factor data filter algorithm list; obtain a data filter preprocessing node according to the multi-factor data filter algorithm list; perform data processing algorithm matching based on the water level distance measurement factor parameter table to obtain a multi-factor data processing algorithm model list, and train based on the multi-factor data processing algorithm model list to obtain a water level data processing node; sequentially integrate and configure the data filter preprocessing node and the water level data processing node to obtain the water level distance measurement data algorithm model library, and store the water level distance measurement data algorithm model library in the data processor.

[0060] Further, the obtaining of the water level distance measurement factor parameter table includes:

[0061] Analyze the influencing factors of the water level monitoring scenario information to obtain water level monitoring influencing factor information, where the water level monitoring influencing factor information includes weather conditions, hydrogeological conditions, and water quality conditions; classify and fill the water level monitoring scenario information based on the water level monitoring influencing factor information to obtain a water level monitoring scenario factor parameter set; classify and integrate the ToF sensor database by measuring the influencing factors with sensors to obtain sensor performance factor parameter information; perform parameter orthogonal arrangement based on the water level monitoring scenario factor parameter set and the sensor performance factor parameter information to obtain the water level distance measurement factor parameter table.

[0062] Further, the obtaining of the multi-factor data processing algorithm model list includes:

[0063] Mining and obtaining the historical water level ranging data set, classifying and labeling the historical water level ranging data set according to the water level ranging factor parameter table to obtain the water level ranging clustering data set; constructing a water level data processing algorithm list, respectively performing data characteristic analysis and processing algorithm matching based on the water level data processing algorithm list and the water level ranging clustering data set to determine the clustering data matching algorithm set; based on the clustering data matching algorithm set, respectively training the water level processing model for the water level ranging clustering data set to obtain the water level ranging factor data processing model library; based on the water level ranging factor parameter table, performing identification integration on the water level ranging factor data processing model library to obtain the multi-factor data processing algorithm model list.

[0064] Further, the obtaining of the target cycle water level information set includes:

[0065] Classifying and identifying the water level ranging cycle signal flow set according to the water level ranging factor parameter table to obtain the water level cycle signal factor parameter set; using the water level cycle signal factor parameter set as the water level factor calibration parameter set; sequentially performing processing model matching between the water level factor calibration parameter set and the water level ranging data algorithm model library to obtain the ranging data processing algorithm model set; based on the ranging data processing algorithm model set, respectively performing water level data processing on the water level ranging cycle signal flow set to obtain the target cycle water level information set.

[0066] Further, the result correction of the target cycle water level information set includes:

[0067] Monitoring the working state of the ToF sensor through the data processor to obtain the sensor working state data stream; performing abnormal identification and detection on the sensor working state data stream according to the sensor working threshold to obtain the abnormal sensor working data information; performing abnormal factor classification and influence degree analysis based on the abnormal sensor working data information to obtain the water level accuracy influence factor; performing confidence evaluation and result correction on the target cycle water level information set based on the water level accuracy influence factor.

[0068] Further, the feedback optimization of the ultrasonic working control parameter information includes:

[0069] When the ToF sensor is in a window pollution state, analyze the pollution condition of the abnormal sensor working data information to obtain the sensor window pollution characteristic parameters; perform an optimization analysis of the working parameters of the ultrasonic module based on the sensor window pollution characteristic parameters to determine the ultrasonic working control parameter information; verify the control effect of the ultrasonic module based on the ultrasonic working control parameter information to obtain the deposition removal control effect, and feedback and optimize the ultrasonic working control parameter information through the deposition removal control effect.

[0070] The various embodiments in this specification are described in a progressive manner, and the key point of each embodiment is to illustrate the differences from other embodiments. The foregoing Figure 1 The intelligent ultrasonic-assisted ToF water level monitoring device and specific examples in the first embodiment are equally applicable to the intelligent ultrasonic-assisted ToF water level monitoring method in this embodiment. Through the foregoing detailed description of the intelligent ultrasonic-assisted ToF water level monitoring device, those skilled in the art can clearly know the intelligent ultrasonic-assisted ToF water level monitoring method in this embodiment. Therefore, for the sake of simplicity of the specification, it will not be described in detail here. For the method disclosed in the embodiment, since it corresponds to the system disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the description of the system part.

[0071] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be obvious to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to these embodiments shown herein, but will be accorded the widest scope consistent with the principles and novel features disclosed herein.

[0072] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalent technologies, the present application is also intended to include these changes and modifications.

Claims

1. Intelligent ultrasonic-assisted ToF water level monitoring device, characterized in that: include: An equipment construction unit, used to construct a water level monitoring device, wherein the water level monitoring device includes a ToF sensor, an ultrasonic module, a power management module, a floating plate or a floating ball, a wireless communication module, a data processor, and corresponding supporting and connecting devices; An equipment processing unit, used to respectively power and support the water level monitoring equipment through the power management module and the corresponding support connection device, and drive the ultrasonic module to perform auxiliary biological deposit removal processing on the water level monitoring equipment; A signal transmitting unit, used to use the floating plate or floating ball as a matching target, transmit signals to measure the distance of the target water surface through the ToF sensor, and collect and obtain a water level ranging monitoring signal stream; A data acquisition unit, configured to acquire a water level ranging period signal stream set by performing data communication acquisition on the water level ranging monitoring signal stream through the wireless communication module based on the data processor according to a preset acquisition cycle; A trend analysis unit, configured to call the water level ranging data algorithm model library through the data processor, perform matching data processing on the water level ranging period signal stream set based on the water level ranging data algorithm model library, obtain a target period water level information set, perform change trend analysis based on the target period water level information set, and generate a target water level monitoring report; The trend analysis unit is also used for: Obtain a water level ranging factor parameter table, perform noise characteristic analysis and filter algorithm configuration in sequence based on the water level ranging factor parameter table, and obtain a multi-factor data filter algorithm list; According to the multi-factor data filtering algorithm list, obtaining a data filtering preprocessing node; Perform data processing algorithm matching based on the water level ranging factor parameter table to obtain a multi-factor data processing algorithm model list, and obtain a water level data processing node based on training based on the multi-factor data processing algorithm model list; The data filtering preprocessing node and the water level data processing node are sequentially integrated and configured to obtain the water level ranging data algorithm model library, and the water level ranging data algorithm model library is stored in the data processor.

2. The intelligent ultrasound-assisted ToF water level monitoring device according to claim 1, characterized in that: The trend analysis unit is also used for: Analyze the influencing factors of the water level monitoring scene information to obtain the influencing factor information of the water level monitoring, wherein the influencing factor information of the water level monitoring includes weather conditions, hydrogeological conditions and water quality conditions; Classify and fill the water level monitoring scenario information based on the water level monitoring influencing factor information to obtain a water level monitoring scenario factor parameter set; The ToF sensor database is classified and integrated by sensor measurement influencing factors to obtain sensor performance factor parameter information; Based on the water level monitoring scenario factor parameter set and the sensor performance factor parameter information, parameters are orthogonally arranged to obtain the water level ranging factor parameter table.

3. The intelligent ultrasound-assisted ToF water level monitoring device according to claim 1, characterized in that: The trend analysis unit is also used for: Mining and acquiring a water level ranging historical data set, classifying and marking the water level ranging historical data set according to the water level ranging factor parameter table, and obtaining a water level ranging cluster data set; Constructing a water level data processing algorithm list, performing data characteristic analysis and processing algorithm matching based on the water level data processing algorithm list and the water level ranging clustering data set, and determining a clustering data matching algorithm set; Based on the cluster data matching algorithm set, water level processing model training is performed on the water level ranging cluster data set to obtain a water level ranging factor data processing model library; The water level ranging factor data processing model library is identified and integrated based on the water level ranging factor parameter table to obtain the multi-factor data processing algorithm model list.

4. The intelligent ultrasound-assisted ToF water level monitoring device according to claim 1, characterized in that: The trend analysis unit is also used for: Classify and identify the water level ranging periodic signal stream set according to the water level ranging factor parameter table to obtain a water level periodic signal factor parameter set; Using the water level periodic signal factor parameter set as a water level factor calibration parameter set; Based on the water level factor calibration parameter set, processing models are matched with the water level ranging data algorithm model library in sequence to obtain a ranging data processing algorithm model set; Based on the ranging data processing algorithm model set, water level data processing is performed on the water level ranging periodic signal stream set to obtain the target periodic water level information set.

5. The intelligent ultrasound-assisted ToF water level monitoring device according to claim 1, characterized in that: The trend analysis unit is also used for: Monitor the working status of the ToF sensor by the data processor to obtain a sensor working status data stream; Performing abnormality identification and detection on the sensor working state data stream according to the sensor working threshold value to obtain abnormal sensor working data information; Based on the abnormal sensor working data information, abnormal factors are classified and the influence degree is analyzed to obtain the water level accuracy influence factor; Based on the water level accuracy influencing factor, confidence evaluation and result correction are performed on the target period water level information set.

6. The intelligent ultrasound-assisted ToF water level monitoring device according to claim 5, characterized in that: The trend analysis unit is also used for: When the ToF sensor has a window pollution state, the pollution situation is analyzed for the abnormal sensor working data information to obtain sensor window pollution characteristic parameters; Performing an optimization analysis on the working parameters of the ultrasonic module based on the sensor window contamination characteristic parameters to determine ultrasonic working control parameter information; The control effect of the ultrasonic module is verified based on the ultrasonic work control parameter information to obtain a deposit removal control effect, and the ultrasonic work control parameter information is feedback optimized through the deposit removal control effect.

7. Intelligent ultrasound-assisted ToF water level monitoring method, characterized in that: The intelligent ultrasound-assisted ToF water level monitoring method is performed by the intelligent ultrasound-assisted ToF water level monitoring device according to any one of claims 1 to 6, and comprises: Build a water level monitoring device, which includes a ToF sensor, an ultrasonic module, a power management module, a floating plate or a floating ball, a wireless communication module, a data processor and corresponding supporting and connecting devices; The water level monitoring device is powered and supported by the power management module and the corresponding supporting connection device, and the ultrasonic module is driven to perform auxiliary biological deposit removal treatment on the water level monitoring device; The floating plate or the floating ball is used as a matching target, and the ToF sensor is used to transmit and measure the distance of the target water surface, and a water level ranging monitoring signal stream is collected and obtained; Based on the data processor, data communication acquisition is performed on the water level ranging monitoring signal stream through the wireless communication module according to a preset acquisition cycle to obtain a water level ranging period signal stream set; The water level ranging data algorithm model library is called by the data processor, and matching data processing is performed on the water level ranging data algorithm model library respectively to obtain a target periodic water level information set, and a change trend analysis is performed based on the target periodic water level information set to generate a target water level monitoring report.

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