Ultrasonic algae removal device, control method thereof, electronic device and storage medium

Abstract

The embodiment of the application provides an ultrasonic algae removal device, a control method thereof, an electronic device and a storage medium, and belongs to the technical field of environmental governance. According to the present application, the target water area model is obtained, the path planning is performed according to the obstacle distribution position and the algae distribution position to obtain an algae removal path, the control instruction is determined according to the algae removal path, and the control instruction is issued to the motion component, so that the ultrasonic algae removal device moves according to the algae removal path. Through automatic path planning and control, the algae removal efficiency is improved. Further, the water quality sensor is used to collect water quality data in the movement process of the ultrasonic algae removal device in real time, the algae concentration degree of the current area is determined according to the water quality data, and the working strength of the ultrasonic wave component is adjusted according to the algae concentration degree. The working strength of the ultrasonic wave component is adaptively adjusted, and the environmental adaptability and algae removal effect of the algae removal process are improved.

Description

Technical Field

[0001] This application relates to the field of environmental governance technology, and in particular to an ultrasonic algae removal device and its control method, electronic equipment and storage medium. Background Technology

[0002] Currently, cyanobacterial blooms pose a serious negative impact on the health of aquatic ecosystems and water resources. A cyanobacterial bloom is a phenomenon caused by the excessive proliferation of cyanobacterial cells, typically occurring in eutrophic water bodies. The overgrowth of these cells leads to the accumulation of cyanobacterial toxins in the water, threatening drinking water, aquaculture, and ecosystems. Related technologies for cyanobacterial control include chemical treatment and biological control. Chemical methods use chemicals such as copper sulfate and ammonium sulfate to control cyanobacterial growth. While these chemicals can destroy the cellular structure of cyanobacteria, they can also adversely affect the aquatic ecosystem and require extensive maintenance and monitoring to ensure safe use. Furthermore, the effects of this method are often short-lived, as cyanobacteria may re-emerge within a short period. Biological control methods utilize natural organisms to control cyanobacterial growth, including using herbivores (such as fish that feed on algae) or other organisms to consume the algae. However, this method usually requires complex ecosystem management and time to establish a balance, and its algae removal effect is limited. To reduce the impact on the ecosystem and improve algae removal efficiency, ultrasonic mechanical equipment can also be used for algae removal. By emitting ultrasonic waves towards the cyanobacteria, the ultrasonic energy destroys the cellular structure of the algae, resulting in less impact on the ecological environment and a longer-lasting algae removal effect. However, current ultrasonic algae removal equipment requires operators to control the equipment to reach the observed blue-green algae area and then activate the ultrasonic function to remove the algae. This method requires professional operators and the equipment operates in a fixed manner, resulting in low algae removal efficiency and poor environmental adaptability. Summary of the Invention

[0003] The main objective of this application is to provide an ultrasonic algae removal device and its control method, electronic equipment and storage medium, which aim to improve algae removal efficiency and environmental adaptability.

[0004] To achieve the above objectives, one aspect of this application proposes a control method for an ultrasonic algae removal device. The ultrasonic algae removal device includes an ultrasonic component, a motion component, and a sensing component. The sensing component includes a water quality sensor. The control method for the ultrasonic algae removal device includes the following steps:

[0005] Obtain a target water area model, wherein the target water area model includes the distribution locations of obstacles and algae;

[0006] Based on the distribution locations of the obstacles and the algae, a path for algae removal is planned.

[0007] The control command is determined according to the algae removal path, and the control command is sent to the motion component so that the ultrasonic algae removal device moves according to the algae removal path.

[0008] The water quality sensor collects water quality data in real time during the operation of the ultrasonic algae removal device.

[0009] The algae density in the current area is determined based on the water quality data, and the working intensity of the ultrasonic component is adjusted according to the algae density.

[0010] In some embodiments, the sensing components include a sonar sensor and a position sensor, and the target water area model includes the following steps:

[0011] The location coordinates of the ultrasonic algae removal device are determined by the position sensor, and sonar images are acquired by the sonar sensor.

[0012] The identification results were obtained by identifying obstacles and algae regions in sonar images at different coordinates.

[0013] A three-dimensional model of the target water area is constructed based on the recognition results of multiple sonar images.

[0014] In some embodiments, the step of planning a path based on the distribution locations of the obstacles and the algae to obtain an algae removal path includes the following steps:

[0015] Multiple target locations were determined based on the distribution location of the algae;

[0016] Based on the distances between multiple target locations and the current location, the multiple target locations are arranged in ascending order of distance;

[0017] Initialize the starting position to the current position and the ending position to the first target position;

[0018] Determine the segmented path from the starting point to the ending point based on the location of the obstacles;

[0019] Update the starting position to the first target position, update the ending position to the second target position, and repeat the step of determining the segmented path from the starting position to the ending position based on the distribution of obstacles, and so on, until the segmented path with the ending position as the last target position is obtained;

[0020] Combining multiple segmented paths yields an algae removal path.

[0021] In some embodiments, the step of planning the path based on the distribution locations of the obstacles and the distribution locations of the algae to obtain the algae removal path further includes the following steps:

[0022] The target water area model is divided into multiple grid nodes;

[0023] Determining the segmented path from the starting point to the ending point based on the distribution of obstacles includes the following steps:

[0024] The actual cost is determined based on the distance from the current grid node to the starting point, and the predicted cost is determined based on the distance from the current grid node to the ending point.

[0025] The estimated cost from the current grid node to its neighboring grid nodes is determined based on the location of the obstacles, the actual cost, and the predicted cost, and the next grid node to be searched is determined based on the estimated cost.

[0026] The segmented path is determined based on multiple searched grid nodes.

[0027] In some embodiments, the water quality data includes water temperature, water pH, and dissolved oxygen content. Determining the algae density in the current area based on the water quality data includes the following steps:

[0028] The water temperature, the water pH, and the dissolved oxygen content are input into the density prediction model to obtain the algae density in the current area.

[0029] The density prediction model is constructed through the following steps;

[0030] Obtain sample data, which includes water temperature, water pH and dissolved oxygen content collected in areas with different algae density.

[0031] A density prediction model is constructed based on the sample data.

[0032] In some embodiments, determining multiple target locations based on the algae distribution location includes the following steps:

[0033] Obtain the direction of water flow;

[0034] Determine the downstream area based on the water flow direction and current location;

[0035] Multiple target locations were determined based on the distribution of algae in the downstream region.

[0036] To achieve the above objectives, another aspect of this application provides an ultrasonic algae removal device, including an ultrasonic component, a motion component, a sensing component, and a processing control component. The sensing component includes a water quality sensor, and the processing control component is used for:

[0037] Obtain a target water area model, wherein the target water area model includes the distribution locations of obstacles and algae;

[0038] Based on the distribution locations of the obstacles and the algae, a path for algae removal is planned.

[0039] The control command is determined according to the algae removal path, and the control command is sent to the motion component so that the ultrasonic algae removal device moves according to the algae removal path.

[0040] The water quality sensor collects water quality data in real time during the operation of the ultrasonic algae removal device.

[0041] The algae density in the current area is determined based on the water quality data, and the working intensity of the ultrasonic component is adjusted according to the algae density.

[0042] In some embodiments, the processing control assembly is disposed within the housing, and the motion assembly includes four horizontal thrusters and four vertical thrusters, each horizontal thruster and each vertical thruster being connected to the processing control assembly. The four vertical thrusters are distributed in pairs on both sides of the housing, and the four horizontal thrusters are distributed in pairs on both sides of the housing.

[0043] To achieve the above objectives, another aspect of the present application provides an electronic device, which includes a memory, a processor, a program stored in the memory and executable on the processor, and a data bus for enabling communication between the processor and the memory. When the program is executed by the processor, it implements the control method of the ultrasonic algae removal device described in the above embodiments.

[0044] To achieve the above objectives, another aspect of the embodiments of this application proposes a storage medium, which is a computer-readable storage medium for computer-readable storage. The storage medium stores one or more programs, which can be executed by one or more processors to implement the control method of the ultrasonic algae removal device described in the above embodiments.

[0045] The ultrasonic algae removal device, its control method, electronic equipment, and storage medium proposed in this application acquire a target water area model, plan the path to obtain an algae removal path based on the distribution of obstacles and algae, determine control commands based on the algae removal path, and send control commands to the moving components to make the ultrasonic algae removal device move according to the algae removal path. The algae removal efficiency is improved through automatic path planning and control. Furthermore, water quality data during the movement of the ultrasonic algae removal device is collected in real time by a water quality sensor. The algae density in the current area is determined based on the water quality data, and the working intensity of the ultrasonic components is adjusted according to the algae density to achieve adaptive adjustment of the working intensity of the ultrasonic components, thereby improving the environmental adaptability and algae removal effect of the algae removal process. Attached Figure Description

[0046] Figure 1 This is a flowchart of the method of the ultrasonic algae removal device provided in the embodiments of this application;

[0047] Figure 2 This is a schematic diagram of the component connection structure of the ultrasonic algae removal device provided in the embodiments of this application;

[0048] Figure 3 This is a schematic diagram of the overall ultrasonic algae removal device provided in the embodiments of this application;

[0049] Figure 4 This is a schematic diagram of the hardware structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0050] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0051] It should be noted that although functional modules are divided in the system diagram and the logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than the module division in the system or the order in the flowchart. The terms "first," "second," etc., in the specification, claims, and the aforementioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence.

[0052] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0053] The ultrasonic algae removal device, its control method, electronic equipment, and storage medium provided in this application are specifically described through the following embodiments. First, the control method of the ultrasonic algae removal device in this application embodiment is described.

[0054] The control method provided in this application can be applied to a terminal, a server, or software running on either a terminal or a server. In some embodiments, the terminal can be a smartphone, tablet, laptop, desktop computer, etc.; the server can be configured as an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms; the software can be an application that implements the control method, but is not limited to the above forms. The terminal or server that implements the control method for the ultrasonic algae removal device can serve as the host computer for the ultrasonic algae removal device, generating relevant control instructions according to the control method of this application embodiment to control the various components of the ultrasonic algae removal device.

[0055] Figure 1 This is an optional flowchart of the control method for the ultrasonic algae removal device provided in the embodiments of this application. Figure 1 The method may include, but is not limited to, steps S101 to S105.

[0056] Step S101: Obtain the target water area model, wherein the target water area model includes the distribution locations of obstacles and algae.

[0057] Step S102: Path planning is performed based on the distribution locations of obstacles and algae to obtain the algae removal path;

[0058] Step S103: Determine the control command according to the algae removal path and send the control command to the motion component so that the ultrasonic algae removal device moves according to the algae removal path;

[0059] Step S104: Real-time water quality data during the operation of the ultrasonic algae removal device is collected using a water quality sensor.

[0060] Step S105: Determine the algae density in the current area based on water quality data, and adjust the working intensity of the ultrasonic component according to the algae density.

[0061] In some embodiments, the ultrasonic algae removal device mainly includes a motion component, a sensing component, and an ultrasonic component. The shell of the ultrasonic algae removal device adopts a flat, streamlined design and smooth wall surface to reduce resistance during movement. The motion component includes horizontal and vertical thrusters, enabling flexible movement of the ultrasonic algae removal device in all directions. The sensing component includes a sonar sensor, a position sensor (depth sensor and GPS positioning), a camera, and a water quality sensor. The sonar sensor is mainly used to detect water areas over a long distance to construct a water area model. The position sensor is mainly used to obtain the actual three-dimensional spatial coordinates of the ultrasonic algae removal device for positioning and motion control. The camera is mainly used to acquire image data to determine the algae situation in the water. The water quality sensor is mainly used to collect water quality data such as water temperature, pH, and dissolved oxygen content to achieve water quality monitoring and analyze the algae density in the area based on the water quality data. The ultrasonic component mainly includes an ultrasonic transmitter and an ultrasonic transducer. The ultrasonic transmitter generates a signal and amplifies it, then the ultrasonic transducer emits ultrasonic waves of a specific frequency to destroy algal cells such as cyanobacteria.

[0062] In some embodiments of step S101, the target water area model is a computer model that is identical to the actual environment, represented by computer data, obtained by detecting and identifying various objects in the water area using detection devices. The detection devices can be acoustic or optical devices, such as radar, sonar, or cameras. The target water area model can be pre-constructed using any type of detection device, or it can be obtained using an ultrasonic algae removal device. This application embodiment illustrates the construction process of the target water area model using the detection function of an ultrasonic algae removal device.

[0063] In some embodiments, the step of obtaining the target water area model in step S101 may include, but is not limited to, the following steps:

[0064] Step S201: Determine the current location coordinates of the ultrasonic algae removal device using a position sensor, and acquire sonar images using a sonar sensor;

[0065] Step S202: Identify obstacles and algae regions in sonar images at different coordinates to obtain identification results;

[0066] Step S203: Construct a three-dimensional target water area model based on the recognition results of multiple sonar images.

[0067] In this embodiment, the current location coordinates of the ultrasonic algae removal device are determined by a position sensor, and sonar images are acquired by a sonar sensor, thus obtaining sonar images corresponding to different coordinate positions. These sonar images contain the position and shape information of objects in the water. The sonar images are processed to detect and segment obstacles and algae in the water area, and the processing results are integrated from multiple processing results at different coordinate positions to obtain a virtual model of the target water area. It is understood that obstacles can be objects such as rocks, debris, and plants that affect the movement of the device.

[0068] In some embodiments of step S102, a path planning algorithm can be used, with the algae distribution location as the motion target, to plan a path that can bypass obstacle locations, thus obtaining an algae removal path. The path planning algorithm can be the A* algorithm, D* algorithm, artificial potential field method, etc., and this application embodiment does not impose specific limitations. Considering the special characteristics of the underwater environment and the need to adapt to the dynamically changing environment, this embodiment can use the A* algorithm (A* algorithm) path planning algorithm, which is more adaptable and can more effectively remove cyanobacteria. Furthermore, through the path planning algorithm, an S-shaped path is generated in the water area to optimally avoid obstacles and achieve efficient removal of cyanobacteria. The S-shaped path helps avoid obstacles and optimize path length, ensuring that the underwater vehicle can navigate efficiently and safely during the cyanobacteria removal process.

[0069] For example, the target water area model is divided into grid nodes, each grid node representing a small area of ​​water, and the A* algorithm is used to search on the grid map.

[0070] The A* algorithm selects the next node to explore by evaluating the cost function of each neighboring node. The cost function comprehensively considers the actual cost from the starting point to the current node (the distance already traveled) and the estimated cost from the current node to the target node (the heuristic function), thus finding the shortest path while maintaining search efficiency. Furthermore, to plan S-shaped paths, special path generation strategies can be introduced based on the A* algorithm. For example, the weights of the heuristic function can be adjusted to make the path more meandering, thus forming an S-shaped path. In addition, dynamic perception of underwater obstacles can be introduced during the search, allowing for timely path adjustments to avoid obstacles.

[0071] In some embodiments, step S102, which involves path planning based on the locations of obstacles and algae to obtain an algae removal path, may include, but is not limited to, the following steps:

[0072] Step S301: Determine multiple target locations based on the distribution location of algae;

[0073] Step S302: Arrange the multiple target locations in ascending order of distance based on the distance between the multiple target locations and the current location;

[0074] Step S303: Initialize the starting position to the current position and initialize the ending position to the first target position;

[0075] Step S304: Determine the segmented path from the starting point to the ending point based on the location of the obstacles;

[0076] Step S305: Update the starting position to the first target position and the ending position to the second target position. Repeat step S304 and so on until a segmented path with the ending position as the last target position is obtained.

[0077] Step S306: Combine multiple segmented paths to obtain an algae removal path.

[0078] In this embodiment, since algae may be distributed in multiple locations within the water body, multiple target locations (i.e., algae locations) can be determined based on the algae distribution location in the target water area model. Then, segmented path planning is performed based on these multiple target locations to obtain a complete algae removal path. During segmented path planning, the nearest target location is first used as the endpoint to calculate the shortest, unobstructed path from the current location to the nearest target location. Then, the same path planning process is performed again, starting from the nearest target location and ending at the second closest target location. This process is repeated, combining multiple segmented paths to obtain the algae removal path. Motion control is then performed based on this path, enabling the ultrasonic algae removal device to reach areas with regulated algae and improve removal efficiency. Furthermore, during motion control based on the algae removal path, local path optimization can be performed based on real-time dynamic information. For example, dynamic obstacles can be identified using image information captured by the binocular camera on the ultrasonic algae removal device, and the local path can be optimized based on the location of these obstacles to avoid them. In another example, since the location of algae distribution obtained by sonar detection and analysis may be inaccurate, algae-producing areas may be missed, or other plant growth areas may be mistakenly identified as algae-producing areas. Therefore, it is possible to determine whether a new algae-producing area has been identified based on real-time image information within a certain space. If so, the current local path is optimized, and the device is controlled to move towards the new algae-producing area before returning to the global algae removal path. Alternatively, it is possible to determine whether there is algae growth at the target location based on real-time image information within a certain space. If not, the segmented path is replanned with the next target location as the endpoint, so that the ultrasonic algae removal device bypasses the non-algae-growing target area and directly reaches the next target location, thereby improving algae removal efficiency.

[0079] In some embodiments, step S301, which involves determining multiple target locations based on the distribution location of algae, may include, but is not limited to, the following steps:

[0080] Step S401: Obtain the water flow direction;

[0081] Step S402: Determine the downstream area based on the water flow direction and current location;

[0082] Step S403: Determine multiple target locations based on the distribution of algae in the downstream area.

[0083] In this embodiment, the downstream area at the current position can be determined according to the current water flow direction, and a path can be planned for the algae in the downstream area so that the ultrasonic algae removal device moves downstream along the algae removal path, thus achieving stable navigation.

[0084] In some embodiments, step S304, which involves determining the segmented path from the starting point to the ending point based on the location of obstacles, may include, but is not limited to, the following steps:

[0085] Step S501: Determine the actual cost based on the distance from the current grid node to the starting point, and determine the predicted cost based on the distance from the current grid node to the ending point.

[0086] Step S502: Determine the estimated cost from the current grid node to the adjacent grid node based on the obstacle distribution location, actual cost, and predicted cost, and determine the next grid node to search based on the estimated cost.

[0087] Step S503: Determine the segmented path based on the multiple searched grid nodes.

[0088] In this embodiment, the A* algorithm can be used for segmented path planning. The next node to be explored is selected by evaluating the cost function of each adjacent grid node. In addition to considering the impact of obstacles on node selection, the cost function also considers the actual cost (distance already traveled) from the starting position to the current node and the predicted cost (heuristic function) from the current node to the destination position, so as to find the shortest path while ensuring search efficiency.

[0089] In step S103 of some embodiments, real-time control commands are generated based on the algae removal path, and these commands are sent to the motion component, causing the motion component to control the ultrasonic algae removal device to move to a designated position and depth according to the algae removal path. During the movement of the ultrasonic algae removal device, the algae removal path can be optimized by combining real-time image data. The optimization process has been described in the above embodiments and will not be repeated here.

[0090] In step S104 of some embodiments, the water quality sensor may include a temperature sensor, an oxygen content sensor, and a pH value testing instrument, thereby collecting water quality data such as water temperature, water pH, and dissolved oxygen content.

[0091] In step S105 of some embodiments, water temperature, water pH, and dissolved oxygen content are correlated with algae (such as cyanobacteria). For example, 1 mg of algae releases 1.98 mg of oxygen through photosynthesis. The amount of algae produced can be approximately estimated based on the amount of dissolved oxygen generated. As the algae content in the water increases, the dissolved oxygen content will increase, and the pH value will also increase. However, once the dissolved oxygen increases to a certain level, it will escape from the water into the atmosphere. At the same time, as the pH in the water becomes higher and higher, the concentration of photosynthetic raw material HCO3- decreases sharply, which will limit the growth and reproduction of algae. Therefore, the instantaneous dissolved oxygen content in the water will not exceed three times the saturated dissolved oxygen. Based on the relationship between water quality data and the density of algae growth, a mapping model can be constructed. The current algae density can then be determined according to the mapping model. For areas with higher algae density, the working intensity of the ultrasonic component can be increased to efficiently remove cyanobacteria while reducing the impact on other organisms. It is understood that increasing the working intensity of the ultrasonic component can be achieved by increasing the working time or increasing the working power.

[0092] In some embodiments, step S105, which involves determining the algae density of the current area based on water quality data, may include, but is not limited to, the following steps:

[0093] Step S601: Input the water temperature, water pH and dissolved oxygen content into the density prediction model to obtain the current algae density in the area;

[0094] The density prediction model is constructed through the following steps;

[0095] Obtain sample data, including water temperature, pH, and dissolved oxygen content collected in areas with different algae density.

[0096] A density prediction model is constructed based on sample data.

[0097] In this embodiment, the density prediction model can be a density prediction model, support vector machine, logistic regression model, or decision tree model, etc., and this application embodiment does not impose specific limitations.

[0098] Please refer to Figure 2 This application also provides an ultrasonic algae removal device, including an ultrasonic component, a motion component, a sensing component, and a processing control component. The sensing component includes a water quality sensor, and the processing control component is used for:

[0099] Obtain a target water area model, which includes the locations of obstacles and algae.

[0100] Based on the location of obstacles and the location of algae, a path for algae removal is planned.

[0101] The control command is determined according to the algae removal path, and the control command is sent to the moving components so that the ultrasonic algae removal device moves according to the algae removal path.

[0102] Water quality data during the operation of the ultrasonic algae removal device is collected in real time using a water quality sensor.

[0103] The current algae density in the area is determined based on water quality data, and the working intensity of the ultrasonic components is adjusted accordingly.

[0104] It is understood that the content of the control method embodiments of the ultrasonic algae removal device described above is applicable to the processing control component embodiments of this device. The specific functions implemented by the processing control component embodiments of this device are the same as those of the control method embodiments of the ultrasonic algae removal device described above, and the beneficial effects achieved are also the same as those achieved by the control method embodiments of the ultrasonic algae removal device described above. The description of the ultrasonic algae removal device involved in the above embodiments is applicable to the device of this embodiment, and the ultrasonic algae removal device will not be described again here.

[0105] In some embodiments, refer to Figure 3 The processing and control components of the ultrasonic algae removal device can be housed within the casing 104. The casing features a streamlined design, with four horizontal thrusters 101 and four vertical thrusters 102 installed on both sides. The four horizontal thrusters 101 and four vertical thrusters 102 are connected to the processing and control components. The four horizontal thrusters 101 are arranged in pairs, positioned at the four corners of the overall horizontal center of the ultrasonic algae removal device, providing horizontal thrust parallel to the plane of the main casing. The two horizontal thrusters in each pair are symmetrically arranged about the casing's line of symmetry, forming a 45° angle with the axis. The processing and control components can individually control each horizontal thruster, thereby achieving the device's steering behavior. Additionally, the four vertical thrusters are symmetrically arranged about the casing's line of symmetry, providing vertical thrust perpendicular to the casing's plane. Depending on the propeller speed, they enable the device to perform functions such as buoyancy, descent, and levitation. This device can perform underwater navigation without changing its pitch and roll angles when moving forward, backward, left, or right. A binocular camera 203 is also installed on the housing to capture images and transmit them to the processing and control components for processing. Ultrasonic transmitters 301 and ultrasonic transducers 302 are installed on the smooth walls 103 on both sides of the device to perform ultrasonic algae removal.

[0106] In some embodiments, the overall shape of the ultrasonic algae removal device is designed based on the streamlined body structure of a dolphin. The shell is made of a carbon fiber and resin composite material. The lightweight nature of the carbon fiber and the waterproof properties of the resin ensure that the device possesses both high strength and effective resistance to water pressure in underwater environments, enabling stable operation at different water depths. The shell surface is coated with a material made of epoxy resin and a curing agent in a specific ratio to fill the tiny pores on the carbon fiber surface, enhancing the overall sealing and waterproofing. The ultrasonic algae removal device is flexible and can remove algae in any location in the water, achieving thorough algae removal without dead angles and reducing the regeneration of blue-green algae.

[0107] This application also provides an electronic device, which includes: a memory, a processor, a program stored in the memory and executable on the processor, and a data bus for communication between the processor and the memory. When the program is executed by the processor, it implements the control method of the ultrasonic algae removal device described above. This electronic device can be any smart terminal, including tablet computers, in-vehicle computers, etc.

[0108] Please see Figure 4 , Figure 4 The hardware structure of an electronic device according to another embodiment is illustrated. The electronic device includes:

[0109] The processor 901 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this application.

[0110] The memory 902 can be implemented as a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 902 can store the operating system and other application programs. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 902 and is called and executed by the processor 901 using the control method of the embodiments of this application.

[0111] The input / output interface 903 is used to implement information input and output;

[0112] The communication interface 904 is used to enable communication and interaction between this device and other devices. Communication can be achieved through wired means (such as USB, Ethernet cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.).

[0113] Bus 905 transmits information between various components of the device (e.g., processor 901, memory 902, input / output interface 903, and communication interface 904);

[0114] The processor 901, memory 902, input / output interface 903, and communication interface 904 are connected to each other within the device via bus 905.

[0115] This application also provides a storage medium, which is a computer-readable storage medium for computer-readable storage. The storage medium stores one or more programs, which can be executed by one or more processors to implement the above-described control method.

[0116] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. Furthermore, memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory may optionally include memory remotely located relative to the processor, and these remote memories can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0117] The embodiments described in this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided by the embodiments of this application. As those skilled in the art will know, with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of this application are also applicable to similar technical problems.

[0118] Those skilled in the art will understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of this application, and may include more or fewer steps than shown, or combine certain steps, or different steps.

[0119] The system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0120] Those skilled in the art will understand that all or some of the steps in the methods disclosed above, as well as the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, or suitable combinations thereof.

[0121] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0122] It should be understood that in this application, "at least one (item)" means one or more, and "more than" means two or more. "And / or" is used to describe the relationship between related objects, indicating that three relationships can exist. For example, "A and / or B" can represent three cases: only A exists, only B exists, and both A and B exist simultaneously, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one (item) of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one (item) of a, b, or c can represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0123] In the embodiments provided in this application, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative; for instance, the division of the units described above is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between systems or units may be electrical, mechanical, or other forms.

[0124] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0125] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0126] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes multiple instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing programs, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0127] The preferred embodiments of the present application have been described above with reference to the accompanying drawings, but this does not limit the scope of the claims of the present application. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and substance of the embodiments of the present application shall be within the scope of the claims of the present application.

Claims

1. A control method for an ultrasonic algae removal device, characterized in that, The ultrasonic algae removal device includes an ultrasonic component, a motion component, and a sensing component. The sensing component includes a water quality sensor, a camera, a sonar sensor, and a position sensor. The control method of the ultrasonic algae removal device includes the following steps: Obtain a target water area model, wherein the target water area model includes the distribution locations of obstacles and algae; Based on the distribution locations of the obstacles and the algae, a path for algae removal is planned. The control command is determined according to the algae removal path, and the control command is sent to the motion component so that the ultrasonic algae removal device moves according to the algae removal path. The water quality sensor collects water quality data in real time during the operation of the ultrasonic algae removal device. The algae density in the current area is determined based on the water quality data, and the working intensity of the ultrasonic component is adjusted according to the algae density. The process of obtaining the target water area model includes the following steps: The location coordinates of the ultrasonic algae removal device are determined by the position sensor, and sonar images are acquired by the sonar sensor. Obstacles and algae regions in sonar images at different coordinates are detected and segmented to obtain recognition results; A three-dimensional model of the target water area is constructed based on the recognition results of multiple sonar images; The control method for the ultrasonic algae removal device also includes the following steps: The system uses real-time image information captured by the camera within a certain space to determine whether a new algae area has been identified. If so, it optimizes the current local path, controls the movement towards the new algae area, and then returns to the algae removal path.

2. The control method according to claim 1, characterized in that, The process of planning a path based on the distribution locations of obstacles and algae to obtain an algae removal path includes the following steps: Multiple target locations were determined based on the distribution location of the algae; Based on the distances between multiple target locations and the current location, the multiple target locations are arranged in ascending order of distance; Initialize the starting position to the current position and the ending position to the first target position; Determine the segmented path from the starting point to the ending point based on the location of the obstacles; Update the starting position to the first target position, update the ending position to the second target position, and repeat the step of determining the segmented path from the starting position to the ending position based on the distribution of obstacles, and so on, until the segmented path with the ending position as the last target position is obtained; Combining multiple segmented paths yields an algae removal path.

3. The control method according to claim 2, characterized in that, The process of planning the path based on the distribution locations of the obstacles and the algae to obtain the algae removal path also includes the following steps: The target water area model is divided into multiple grid nodes; Determining the segmented path from the starting point to the ending point based on the distribution of obstacles includes the following steps: The actual cost is determined based on the distance from the current grid node to the starting point, and the predicted cost is determined based on the distance from the current grid node to the ending point. The estimated cost from the current grid node to its neighboring grid nodes is determined based on the location of the obstacles, the actual cost, and the predicted cost, and the next grid node to be searched is determined based on the estimated cost. The segmented path is determined based on multiple searched grid nodes.

4. The control method according to claim 1, characterized in that, The water quality data includes water temperature, pH, and dissolved oxygen content. Determining the algae density in the current area based on the water quality data includes the following steps: The water temperature, the water pH, and the dissolved oxygen content are input into the density prediction model to obtain the algae density in the current area. The density prediction model is constructed through the following steps; Obtain sample data, which includes water temperature, water pH and dissolved oxygen content collected in areas with different algae density. A density prediction model is constructed based on the sample data.

5. The control method according to claim 2, characterized in that, The process of determining multiple target locations based on the distribution location of the algae includes the following steps: Obtain the direction of water flow; Determine the downstream area based on the water flow direction and current location; Multiple target locations were determined based on the distribution of algae in the downstream region.

6. An ultrasonic algae removal device, characterized in that, It includes an ultrasonic component, a motion component, a sensing component, and a processing and control component. The sensing component includes a water quality sensor, a camera, a sonar sensor, and a position sensor. The processing and control component is used for: Obtain a target water area model, wherein the target water area model includes the distribution locations of obstacles and algae; Based on the distribution locations of the obstacles and the algae, a path for algae removal is planned. The control command is determined according to the algae removal path and sent to the motion component so that the ultrasonic algae removal device moves according to the algae removal path; the image information in a certain space collected in real time by the camera is used to determine whether a new algae area is identified. If so, the current local path is optimized, the device is controlled to move towards the new algae area, and then returns to the algae removal path. The water quality sensor collects water quality data in real time during the operation of the ultrasonic algae removal device. The algae density in the current area is determined based on the water quality data, and the working intensity of the ultrasonic component is adjusted according to the algae density. The target water area model includes the following steps: The location coordinates of the ultrasonic algae removal device are determined by the position sensor, and sonar images are acquired by the sonar sensor. Obstacles and algae regions in sonar images at different coordinates are detected and segmented to obtain recognition results; A three-dimensional model of the target water area is constructed based on the recognition results of multiple sonar images.

7. The ultrasonic algae removal device according to claim 6, characterized in that, The processing control component is disposed inside the housing. The motion component includes four horizontal thrusters and four vertical thrusters. Each horizontal thruster and each vertical thruster is connected to the processing control component. The four vertical thrusters are distributed in pairs on both sides of the housing, and the four horizontal thrusters are distributed in pairs on both sides of the housing.

8. An electronic device, characterized in that, The electronic device includes a memory, a processor, a program stored in the memory and executable on the processor, and a data bus for establishing communication between the processor and the memory. When the program is executed by the processor, it implements the steps of the control method for the ultrasonic algae removal device as described in any one of claims 1 to 5.

9. A storage medium, said storage medium being a computer-readable storage medium for computer-readable storage, characterized in that, The storage medium stores one or more programs, which can be executed by one or more processors to implement the steps of the control method for the ultrasonic algae removal device according to any one of claims 1 to 5.

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