Intelligent ultrasonic-assisted ToF water level monitoring device and method

Abstract

The invention provides an intelligent ultrasonic-assisted ToF water level monitoring device and method, and relates to the technical field of water level monitoring. Respectively carrying out power supply and support connection, and simultaneously carrying out auxiliary biological deposition removal treatment; signal emission distance measurement is carried out through a ToF sensor; performing data communication acquisition on the water level distance measurement monitoring signal flow according to a preset acquisition period; and calling the water level ranging data algorithm model library, performing matched data processing on the water level ranging periodic signal flow set, performing variation trend analysis, and generating a target water level monitoring report. The technical problem that in the prior art, due to the fact that a traditional water level sensor is prone to being affected by riverway weeds and the like, misinformation is caused, and the accuracy of water level monitoring data is low can be solved, by integrating the ToF sensor and the ultrasonic module, misinformation caused by the riverway weeds and other objects is reduced, and the accuracy of the water level monitoring data is improved. And the accuracy of water level monitoring data is improved.

Description

Technical Field

[0001] The present application relates to the technical field of water level monitoring, and in particular to an intelligent ultrasound-assisted ToF water level monitoring device and method. Background Art

[0002] When typhoons and rainy seasons come, the risk of river overflow and riverbank breach increases significantly due to the surge in water volume. In this case, accurate and timely water level monitoring is essential for early warning of potential risks and providing effective information for riverbank maintenance and personnel transfer. However, there are some problems with existing water level monitoring technologies. Traditional water level sensors, such as millimeter wave sensors, are easily affected by objects such as weeds in river environments, resulting in false alarms. In addition, biological sediments may adhere to sensors or floats / floats, affecting measurement accuracy.

[0003] In summary, there is a technical problem in the prior art that traditional water level monitoring equipment, such as millimeter wave water level sensors, are easily affected by objects such as weeds in the river environment, resulting in false alarms and low accuracy of water level monitoring data. Summary of the invention

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

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

[0006] In the first aspect, the present application provides an intelligent ultrasonic-assisted ToF water level monitoring device, wherein the intelligent ultrasonic-assisted ToF water level monitoring device includes: an equipment construction unit, 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 float or a float, a wireless communication module, a data processor and a corresponding supporting connection device; an equipment processing unit, used to power and support the water level monitoring device through the power management module and the corresponding supporting connection device, and at the same time drive the ultrasonic module to assist the water level monitoring device in removing biological deposits; a signal transmitting unit, used to use the float or the float as a target The ToF sensor is used to transmit signals to the target water surface for ranging, and collect water level ranging monitoring signal streams; a data acquisition unit is used to perform data communication acquisition on the water level ranging monitoring signal streams through the wireless communication module based on the data processor according to a preset acquisition cycle, and obtain a water level ranging period signal stream set; a trend analysis unit is used to call the water level ranging data algorithm model library through the data processor, match the water level ranging period signal stream set based on the water level ranging data algorithm model library, respectively, to process the data, obtain a target period water level information set, and perform change trend analysis based on the target period water level information set, and generate a target water level monitoring report.

[0007] In the second aspect, the present application also provides an intelligent ultrasonic-assisted ToF water level monitoring method, wherein the intelligent ultrasonic-assisted ToF water level monitoring method includes: building a water level monitoring device, wherein the water level monitoring device includes a ToF sensor, an ultrasonic module, a power management module, a float or a float, 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 and connecting devices, and the ultrasonic module is driven to assist the water level monitoring device in removing biological deposits; the float or the float is used as a matching target, through The ToF sensor transmits signals to measure the distance to the target water surface, and collects and acquires a water level ranging monitoring signal stream; based on the data processor, data communication and collection are performed on the water level ranging monitoring signal stream through the wireless communication module according to a preset collection period, to obtain a water level ranging period signal stream set; the data processor calls the water level ranging data algorithm model library, and based on the water level ranging data algorithm model library, matching data processing is performed on the water level ranging period signal stream set to obtain a target period water level information set, and a change trend analysis is performed based on the target period water level information set to generate a target water level monitoring report.

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

[0009] The equipment construction unit is used to build a water level monitoring device, and 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 a corresponding supporting connection device; the equipment processing unit is used to respectively power and support the water level monitoring device through the power management module and the corresponding supporting connection device, and at the same time drive the ultrasonic module to perform auxiliary biological deposit removal treatment on the water level monitoring device; the signal transmission unit is used to use the floating plate or the floating ball as a matching target, and transmit a signal to the target water surface through the ToF sensor Distance, collect and obtain the water level ranging monitoring signal stream; the data acquisition unit is used to perform data communication acquisition on the water level ranging monitoring signal stream through the wireless communication module based on the data processor according to the preset acquisition cycle, and obtain the water level ranging period signal stream set; the trend analysis unit is used to call the water level ranging data algorithm model library through the data processor, and perform matching data processing on the water level ranging period signal stream set based on the water level ranging data algorithm model library, obtain the target period water level information set, and perform change trend analysis based on the target period water level information set to generate a target water level monitoring report. In other words, by building a water level monitoring device that integrates 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 acquisition and analysis, and improve the accuracy of water level monitoring data in complex environments.

[0010] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented according to the contents of the specification, and in order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are specifically cited below. It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present application, nor is it intended to limit the scope of the present application. Other features of the present application will become easy to understand 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 drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only exemplary, and for ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0012] Figure 1 This is a schematic diagram of the structure of the intelligent ultrasound-assisted ToF water level monitoring device of this application;

[0013] Figure 2This is a flow chart of the intelligent ultrasound-assisted ToF water level monitoring method of this application.

[0014] Description of the accompanying drawings: equipment construction unit 11, equipment processing unit 12, signal transmission unit 13, data collection unit 14, trend analysis unit 15. DETAILED DESCRIPTION

[0015] This application provides an intelligent ultrasound-assisted ToF water level monitoring device and method to solve the technical problem in the prior art that the traditional water level sensor is easily affected by weeds and other objects in the river environment, resulting in false alarms and low accuracy of water level monitoring data. By building a water level monitoring device that integrates 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 data processor improve the efficiency and automation of data collection and analysis, thereby improving the accuracy of water level monitoring data in complex environments.

[0016] Below, 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 part of the embodiments of the present application, rather than all of the embodiments of the present application. It should be understood that the present application is not limited to the example embodiments described herein. Based on the embodiments of the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present application. It should also be noted that, for the convenience of description, only the parts related to the present application are shown in the accompanying drawings, rather than all of them.

[0017] For example, please refer to the attached Figure 1 The present application provides an intelligent ultrasonic assisted ToF water level monitoring device, wherein 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, and the intelligent ultrasonic assisted ToF water level monitoring device includes:

[0018] The equipment construction unit 11 is 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.

[0019] Specifically, a comprehensive water level monitoring device is built, which integrates a variety of technical modules, including ToF sensors, ultrasonic modules, power management modules, floating plates or floating balls, wireless communication modules, data processors and corresponding supporting and connecting devices. Among them, the ToF sensor is the core measurement component of the equipment, which is used to emit light signals (such as infrared light) and measure the time from the emission to the return of the signal, so as to accurately calculate the water level. The ToF sensor is insensitive 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, measures the distance by sending and receiving ultrasonic pulses, and is also used to assist in removing biological deposits and keep the sensor clean, thereby ensuring measurement accuracy. The existence of the ultrasonic module is to remove possible blockages in the anti-biological net, and destroy the activity of the organisms through short-term high-energy ultrasonic vibrations and water cavitation effects. At the same time, some attached organisms or other dirt are 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 a stable power supply for the entire device. The floating plate or buoy is provided as a matching target of the ToF sensor to overcome the inability of the optical sensor to directly monitor the water surface. The floating plate or buoy helps stabilize the sensor and maintain its proper 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 cycle, it receives data through the wireless communication module and calls the water level ranging data algorithm model library for data processing. The target data of the ToF sensor is collected periodically, and the current average water level is determined by combining the algorithm of historical data. The supporting connection device is used to fix and support the device to ensure that it maintains the correct position and stability in the water. It includes brackets and pipes, as well as components such as vents and biological nets. The vents ensure the pressure balance inside the device, and the biological net is used to prevent biological attachment and protect the sensor.

[0021] When the water level monitoring equipment is working normally, it is fixed to the riverside by brackets and pipes, in which the pipes and brackets play a protective role. Install the bracket at the monitoring point, fix the pipe on the bracket, and fix other components. Set vents on the pipe to facilitate signal transmission of the sensor and communication module. 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 equipment. 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 gap between the sensor end and the pipe, which is not in close contact to avoid ultrasonic imaging sensors. The sensor end is easy to disassemble and provides a possible quick cleaning channel. Install the ultrasonic module near the ToF sensor and connect it to the outer wall of the pipe with bolts and stainless steel cranks to clean the sensor. Connect the power management module to the components of the device to ensure power supply. Place a floating plate 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 building water level monitoring equipment, we ensure efficient and accurate water level monitoring in various environments. It is particularly suitable for application scenarios that require high-precision and reliable monitoring, such as water resource management, flood warning and reservoir operation.

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

[0023] Specifically, the power management module may include batteries, solar panels or other power supply devices, as well as related circuits and control systems, responsible for providing stable power for the entire water level monitoring equipment, such as ToF sensors, ultrasonic modules, wireless communication modules, data processors, etc. The supporting connection device includes brackets and pipes, as well as components such as vents and biological nets. The vents ensure the pressure balance inside the equipment, and the biological net is used to prevent biological attachment and protect the sensor. The bracket is installed at the monitoring point to ensure that it is 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 biological deposits that may be attached to prevent the equipment pipeline from being blocked. At the same time, it will automatically start the resonance point scan before and after work to ensure that the system resonates normally and can achieve the expected effect. The ultrasonic module is not only used to assist in measurement, but also to remove biological deposits. By high-frequency vibration, biological deposits such as algae, shellfish or other aquatic organisms attached to the surface of the device are removed, which helps to keep the sensor clean and ensure measurement accuracy. The power management module ensures that the device can obtain a stable power supply under various conditions. The supporting connection device ensures the stability and correct position of the device in the water. Ultrasonic module-assisted biodeposits removal processing reduces maintenance requirements and improves device reliability and measurement accuracy.

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

[0025] Specifically, the floating plate or buoy, as the matching target of the ToF sensor, provides a stable and easily identifiable reflective surface, so that the ToF sensor can accurately measure the distance between it and the water surface. Since the floating plate or buoy floats on the water surface, the distance between the floating plate or buoy and the ToF sensor represents the current water level. The ToF sensor emits a light signal (such as infrared light) to the floating plate or buoy, and measures the time from the emission to the return of the signal, which can accurately calculate the distance between the sensor and the floating plate or buoy. Usually, the floating plate or buoy needs to be placed on the water surface to ensure that its position is stable and will not move significantly due to water flow or wind. The ToF sensor is installed on a bracket or pipe at a certain height from the water surface to ensure that there is no obstruction in its line of sight and it is aligned with the center of the floating plate or buoy to ensure the accuracy of signal transmission and reception. By using a floating plate or buoy as a target and combining the precise measurement capabilities of the ToF sensor, the water level monitoring equipment can provide efficient and accurate water level monitoring in various environments.

[0026] The data acquisition unit 14 is used to perform 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 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 collection cycle, it receives data through the wireless communication module and calls the water level ranging data algorithm model library for data processing. According to the monitoring requirements and environmental conditions, determine the frequency of data collection, such as every minute, every hour or every day. Set the collection cycle in the data processor to ensure that it can automatically collect data at the preset time interval. The data processor triggers the ToF sensor to measure the water level according to the preset collection cycle. The ToF sensor transmits a signal and receives the signal reflected from the floating plate or the floating ball to calculate the water level distance. The water level distance data measured each time is recorded in the data processor, packaged in a certain format, and sent to the monitoring center or cloud server through the wireless communication module. The received water level ranging data is stored in the monitoring center or cloud server, and the data in the same collection cycle is sorted into a set to form a water level ranging period signal flow set. Ensure that the water level monitoring equipment effectively collects and transmits water level data through the wireless communication module according to the preset collection cycle, so as to form a water level ranging period signal flow set on the monitoring center or cloud server.

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

[0029] Specifically, the influencing factors of the water level monitoring scenario are analyzed to determine the combined parameters of various factors that affect the accuracy of water level data processing. The data processing algorithm is matched to the water level ranging factor parameter table to obtain the adapted data processing algorithm set for various factor parameters. A complete water level ranging data algorithm model library is obtained through integrated configuration, which includes a complete set of algorithms from data filtering to data processing. The data processor processes the water level ranging period signal stream set according to the model in the water level ranging data algorithm model library, including filtering, feature extraction, prediction and other operations, to extract and optimize water level data. Through data processing, a set containing target period water level information is obtained, which contains processed water level data and reflects the water level changes and status within a specific time period. The target period water level information set is analyzed for change trends, comparing data at different time points, identifying patterns or trends of water level changes, such as rise, fall, stability, etc. Any abnormal changes, such as sudden rise or fall, are detected in trend analysis. Based on the trend analysis and abnormal monitoring results, a water level monitoring report is generated, which contains detailed information on water level changes, such as water level trend charts, abnormal event records, water level accuracy analysis, confidence assessment, etc. By using trained models for data processing, the accuracy of data processing is improved, and the data processing effect is optimized, accurate and reliable water level monitoring reports are generated to provide decision support for water resources management, flood warning and environmental protection.

[0030] Furthermore, the trend analysis unit 15 in the intelligent ultrasound-assisted ToF water level monitoring device is also used for:

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

[0032] Specifically, the water level ranging factor parameter table includes the combined parameters of various factors that affect the accuracy of water level data processing, such as water temperature, water surface fluctuations, water quality, reflections of surrounding objects, atmospheric conditions, etc. The noise characteristics of the water level ranging factor parameter table are analyzed to identify and quantify various noises that affect the accuracy of water level measurement data, including the type of noise (such as random noise, periodic noise, etc.) and characteristics. According to the noise characteristics, a suitable filtering algorithm is selected 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 and improve the accuracy and reliability of the data. The selected filtering algorithm is configured as a parameterized list to form a multi-factor data filtering algorithm list, including the adaptive filtering algorithm of the various factor parameters in the water level ranging factor parameter table. Based on the multi-factor data filtering algorithm list, a data filtering algorithm suitable for the current measurement environment and conditions is selected and configured to remove or reduce the noise in the data in the early stage of the data processing process and improve the accuracy and reliability of the data.

[0033] Select and configure data processing algorithms 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, a model list containing multiple data processing algorithms is obtained. 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 a water level data processing node. 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 process. Through the integrated configuration, a complete water level ranging data algorithm model library is obtained, which includes a complete set of algorithms from data filtering to data processing, which is used to optimize and improve the accuracy and reliability of water level measurement data. The water level ranging data algorithm model library is stored 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, a complete and optimized data processing process is formed, and the filtering algorithm and processing algorithm suitable for the current environment and conditions are selected and configured to reduce 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 most appropriate processing method to be selected according to different environments and conditions, enhancing the adaptability and flexibility of the system.

[0034] Furthermore, the intelligent ultrasound-assisted ToF water level monitoring device further includes a parameter table acquisition unit, which is used to:

[0035] The water level monitoring scenario information is analyzed for influencing factors to obtain water level monitoring influencing factor information, wherein the water level monitoring influencing factor information includes weather conditions, hydrogeological conditions and water quality conditions; based on the water level monitoring influencing factor information, the water level monitoring scenario information is classified and filled to obtain a water level monitoring scenario factor parameter set; the ToF sensor database is classified and integrated through 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.

[0036] Specifically, the water level monitoring scene information is analyzed to identify and resolve various factors that affect water level monitoring, including weather conditions (such as temperature, humidity, wind speed, precipitation, etc.), hydrogeological conditions (such as groundwater level, soil type, river flow, topography, etc.) and water quality conditions (such as pH value, dissolved oxygen, suspended solids, etc.). The water level monitoring scene information includes the geographical location, environmental conditions, water body characteristics, etc. of the monitoring site. The specific weather conditions, hydrogeological conditions and water quality parameters are classified into the corresponding monitoring scenes, and a set of specific weather conditions, hydrogeological conditions and water quality parameters in each water level monitoring scene is obtained through classification and filling.

[0037] Various sensors (such as temperature sensors, humidity sensors, water quality analysis sensors, etc.) are used to measure various factors that affect the performance of ToF sensors, including ambient temperature, humidity, water quality, etc. The measured influencing factor data are classified and integrated into the ToF sensor database, that is, different types of influencing factor data are associated with the corresponding ToF sensor models and performance parameters. The specific model, performance parameters (such as measurement range, accuracy, resolution, etc.) and calibration information of the ToF sensor are recorded to form sensor performance factor parameter information. The water level monitoring scenario factor parameter set and the sensor performance factor parameter information are combined using the orthogonal arrangement method 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 impact on the results. Through parameter orthogonal arrangement, a water level ranging factor parameter containing multiple different combinations is obtained, which includes various combinations of factors that may affect water level ranging under different scenarios and sensor conditions. By considering various influencing factors, the accuracy and reliability of water level monitoring are improved, and according to the sensor performance factor parameter information, different environments and conditions are adapted to improve the performance of the overall monitoring system. Water level monitoring equipment can more comprehensively consider various influencing factors of the monitoring scene, thereby improving the accuracy and reliability of water level monitoring.

[0038] Furthermore, the intelligent ultrasound-assisted ToF water level monitoring device further includes an algorithm model acquisition unit, which is used to:

[0039] Mining and acquiring water level measurement historical data sets, classifying and marking the water level measurement historical data sets according to the water level measurement factor parameter table, and obtaining a water level measurement cluster data set; constructing a water level data processing algorithm list, performing data characteristic analysis and processing algorithm matching on the water level measurement cluster data set based on the water level data processing algorithm list, and determining a cluster data matching algorithm set; training water level processing models on the water level measurement cluster data set based on the cluster data matching algorithm set, and obtaining a water level measurement factor data processing model library; identifying and integrating the water level measurement factor data processing model library based on the water level measurement factor parameter table, and obtaining the multi-factor data processing algorithm model list.

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

[0041] The algorithm in the cluster data matching algorithm set is used to train the water level ranging clustering data set, and the data set is used to adjust the parameters of the algorithm so that it can better adapt to the characteristics and laws of the data. Through model training, a library containing multiple water level processing models is obtained. 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, each model in the water level ranging factor data processing model library is identified, that is, each model is assigned one or more identifiers related to its applicable factor parameters to facilitate subsequent water level data processing. Through identifier integration, a list of adapted data processing algorithms including various factor parameters in the water level ranging factor parameter table is obtained. Through classification labeling and model training, the accuracy of data processing is improved, the processing effect of data is optimized, and the model library and algorithm model list obtained through training are used to accurately process and analyze water level data, thereby improving the accuracy and efficiency of water level monitoring.

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

[0043] According to the water level ranging factor parameter table, the water level ranging periodic signal stream set is classified and labeled respectively to obtain a water level periodic signal factor parameter set; the water level periodic signal factor parameter set is used 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 turn 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 respectively to obtain the target periodic water level information set.

[0044] Specifically, each data stream in the water level ranging period signal stream set (a set of water level ranging data collected within a specific time period) is classified and identified according to the water level ranging factor parameter table (including various factor combination parameters that affect the accuracy of water level data processing), and the data streams with the same water level ranging factor parameters are classified into one category to form a water level period signal factor parameter set. The water level period signal factor parameter set is used as a water level factor calibration parameter set for subsequent model matching and data processing. The calibration parameters are parameters used to calibrate and optimize the measurement system to ensure the accuracy and reliability of the 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. The water level factor calibration parameter set is matched with the model in the water level ranging data algorithm model library to find the processing model that best suits each factor parameter to form a ranging data processing algorithm model set.

[0045] Using the models in the ranging data processing algorithm model set, each signal stream in the water level ranging period signal stream set is processed separately, including filtering, feature extraction, prediction, etc., to extract and optimize water level data. Through data processing, a target period water level information set is obtained, which includes processed water level data and reflects the water level changes and status within a specific time period. Through classification identification and model matching, the accuracy of data processing is improved and the data processing effect is optimized. The water level monitoring equipment can select and apply the most appropriate processing model according to different data characteristics and requirements, thereby improving the accuracy and reliability of water level monitoring data.

[0046] Furthermore, the intelligent ultrasound-assisted ToF water level monitoring device also includes a result correction unit, which is used to:

[0047] The working status of the ToF sensor is monitored by the data processor to obtain the sensor working status data stream; the sensor working status data stream is detected for abnormality according to the sensor working threshold to obtain abnormal sensor working data information; abnormal factors are classified and the degree of influence is analyzed based on the abnormal sensor working data information to obtain the water level accuracy influencing factor; the target period water level information set is evaluated for confidence and the result is corrected based on the water level accuracy influencing factor.

[0048] Specifically, the data processor monitors the working status of the ToF sensor in real time through various sensors and monitoring systems, obtains the working status data of the ToF sensor, including water level ranging data, signal strength, sampling frequency, communication status, etc., and forms a sensor working status data stream. According to the sensor performance and design standards, set normal working thresholds for the working parameters of the sensor, such as signal strength threshold, sampling frequency range, etc., to determine whether the sensor working status is normal. Compare the sensor working status data stream with the preset sensor working threshold, identify and record abnormal data exceeding the threshold, and form abnormal sensor working data information. Classify the abnormal sensor working data information, including sensor failures (such as window contamination, electronic component failure), environmental factors (such as water surface fluctuations, atmospheric refraction) or operational errors. Analyze the classified abnormal factors, evaluate the degree of influence of each abnormal factor on the water level measurement accuracy, and obtain the water level accuracy influencing factor by calculating the error size, analyzing the data fluctuation situation, or comparing the measurement results under normal and abnormal conditions.

[0049] According to the water level accuracy influencing factors, a confidence assessment is performed on each data point in the target period water level information set, and the reliability of the water level information is scored according to the influencing factors, thereby reflecting the credibility of the measurement results. According to the results of the confidence assessment, the water level information is corrected for accuracy, including adjusting the measured value, adding an error range, or using a more reliable data source. Through confidence assessment and result correction, the accuracy of water level information is improved and measurement errors are reduced. The data processor periodically determines whether the ToF sensor is working abnormally, such as window contamination (abnormal distance, too close), and provides information to the staff for cleaning. Real-time monitoring of the working status of the sensor helps to adapt to different environments and conditions and improve the performance of the overall monitoring system.

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

[0051] When the ToF sensor is in a window contamination state, the pollution situation of the abnormal sensor working data information is analyzed to obtain sensor window contamination characteristic parameters; based on the sensor window contamination characteristic parameters, the working parameters of the ultrasonic module are optimized and analyzed to determine ultrasonic working control parameter information; based on the ultrasonic working control parameter information, the control effect of the ultrasonic module is verified to obtain a deposition removal control effect, and the ultrasonic working control parameter information is feedback optimized through the deposition removal control effect.

[0052] Specifically, when the ToF sensor has a window contamination state, that is, the front window of the ToF sensor (that is, the interface between the sensor and the external environment) is covered or blocked by dirt, sediment, biological attachments or other obstacles, the sensor cannot accurately measure or receive the reflected signal. Abnormal sensor working data information refers to a collection of abnormal sensor working data obtained through abnormal identification detection, including abnormal voltage, current, signal strength, etc. The window contamination situation is analyzed according to the abnormal sensor working data information, including analyzing data changes, comparing measurement results under normal and polluted conditions, etc., to determine the degree of contamination. Through the analysis of the pollution situation, the sensor window pollution characteristic parameters are obtained, including pollution type (such as biological attachment, sediment, etc.), pollution area and pollution degree.

[0053] According to the characteristic parameters of the sensor window contamination, the working parameters of the ultrasonic module are optimized and analyzed, and the optimal ultrasonic vibration frequency, duration, energy intensity and other parameters are selected according to the type, area and degree of contamination. Through the optimization analysis of the working parameters, a set of optimal ultrasonic working control parameters are determined to control the ultrasonic module to remove the contamination on the sensor window with the best effect. Use the ultrasonic working 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 deposit removal, and check the cleanliness of the sensor window. According to the control effect of deposit removal, the ultrasonic working control parameter information is feedback optimized, and the parameters are adjusted according to the actual cleaning effect to improve the cleaning efficiency and effect. Automatically identify and handle the contamination problem of the sensor window to ensure that the ToF sensor can restore its normal working state through effective cleaning of the ultrasonic module when the window is contaminated, thereby ensuring the accuracy and reliability of water level monitoring.

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

[0055] The equipment construction unit is used to build a water level monitoring device, and 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 a corresponding supporting connection device; the equipment processing unit is used to respectively power and support the water level monitoring device through the power management module and the corresponding supporting connection device, and at the same time drive the ultrasonic module to perform auxiliary biological deposit removal treatment on the water level monitoring device; the signal transmission unit is used to use the floating plate or the floating ball as a matching target, and transmit a signal to the target water surface through the ToF sensor Distance, collect and obtain the water level ranging monitoring signal stream; the data acquisition unit is used to perform data communication acquisition on the water level ranging monitoring signal stream through the wireless communication module based on the data processor according to the preset acquisition cycle, and obtain the water level ranging period signal stream set; the trend analysis unit is used to call the water level ranging data algorithm model library through the data processor, and perform matching data processing on the water level ranging period signal stream set based on the water level ranging data algorithm model library, obtain the target period water level information set, and perform change trend analysis based on the target period water level information set to generate a target water level monitoring report. In other words, by building a water level monitoring device that integrates 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 acquisition 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 ultrasound-assisted ToF water level monitoring device in the aforementioned embodiment 1, the present application also provides an intelligent ultrasound-assisted ToF water level monitoring method, please refer to the attached Figure 2 , the intelligent ultrasound-assisted ToF water level monitoring method comprises:

[0057] A water level monitoring device is constructed, wherein the water level monitoring device comprises 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 and connecting devices, and the ultrasonic module is driven to perform auxiliary biological sediment 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 target water surface, and a water level ranging monitoring signal stream is collected; based on the data processor, data communication and collection of the water level ranging monitoring signal stream are performed through the wireless communication module according to a preset collection 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 period signal stream set based on the water level ranging data algorithm model library to obtain a target period water level information set, and a change trend analysis is performed according to the target period water level information set to generate a target water level monitoring report.

[0058] Further, calling the water level ranging data algorithm model library through the data processor includes:

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

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

[0061] The water level monitoring scenario information is analyzed for influencing factors to obtain water level monitoring influencing factor information, wherein the water level monitoring influencing factor information includes weather conditions, hydrogeological conditions and water quality conditions; based on the water level monitoring influencing factor information, the water level monitoring scenario information is classified and filled to obtain a water level monitoring scenario factor parameter set; the ToF sensor database is classified and integrated through 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.

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

[0063] Mining and acquiring water level measurement historical data sets, classifying and marking the water level measurement historical data sets according to the water level measurement factor parameter table, and obtaining a water level measurement cluster data set; constructing a water level data processing algorithm list, performing data characteristic analysis and processing algorithm matching on the water level measurement cluster data set based on the water level data processing algorithm list, and determining a cluster data matching algorithm set; training water level processing models on the water level measurement cluster data set based on the cluster data matching algorithm set, and obtaining a water level measurement factor data processing model library; identifying and integrating the water level measurement factor data processing model library based on the water level measurement factor parameter table, and obtaining the multi-factor data processing algorithm model list.

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

[0065] According to the water level ranging factor parameter table, the water level ranging periodic signal stream set is classified and labeled respectively to obtain a water level periodic signal factor parameter set; the water level periodic signal factor parameter set is used 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 turn 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 respectively to obtain the target periodic water level information set.

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

[0067] The working status of the ToF sensor is monitored by the data processor to obtain the sensor working status data stream; the sensor working status data stream is detected for abnormality according to the sensor working threshold to obtain abnormal sensor working data information; abnormal factors are classified and the degree of influence is analyzed based on the abnormal sensor working data information to obtain the water level accuracy influencing factor; the target period water level information set is evaluated for confidence and the result is corrected based on the water level accuracy influencing factor.

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

[0069] When the ToF sensor is in a window contamination state, the pollution situation of the abnormal sensor working data information is analyzed to obtain sensor window contamination characteristic parameters; based on the sensor window contamination characteristic parameters, the working parameters of the ultrasonic module are optimized and analyzed to determine ultrasonic working control parameter information; based on the ultrasonic working control parameter information, the control effect of the ultrasonic module is verified to obtain a deposition removal control effect, and the ultrasonic working control parameter information is feedback optimized through the deposition removal control effect.

[0070] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. Figure 1 The intelligent ultrasonic-assisted ToF water level monitoring device and specific examples in Example 1 are also applicable to the intelligent ultrasonic-assisted ToF water level monitoring method of this embodiment. Through the above 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, so for the sake of brevity 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 system description.

[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 apparent to those skilled in the art, and the general principles defined herein may 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 the embodiments shown herein, but will conform to 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 belong to the scope of the present application and its equivalent technology, the present application is also intended to include these modifications and variations.

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 is used to call the water level ranging data algorithm model library through the data processor, perform matching data processing on the water level ranging periodic signal stream set based on the water level ranging data algorithm model library, obtain a target periodic water level information set, and perform change trend analysis based on the target periodic water level information set to generate a target water level monitoring report.

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: 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.

3. The intelligent ultrasound-assisted ToF water level monitoring device according to claim 2, 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.

4. The intelligent ultrasound-assisted ToF water level monitoring device according to claim 2, 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.

5. The intelligent ultrasound-assisted ToF water level monitoring device according to claim 2, 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.

6. 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.

7. The intelligent ultrasound-assisted ToF water level monitoring device according to claim 6, 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.

8. 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 7, 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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