35 results about "Sonar sensor" patented technology

The invention relates to an unmanned aerial vehicle towed body positioning attitude measurement method based on binocular vision positioning, and relates to the technical field of computer processing, and the method comprises the following steps: S01, constructing a measurement system which comprises an unmanned aerial vehicle and a towed body connected with the unmanned aerial vehicle through a cable; the unmanned aerial vehicle carries a GNSS module, an IMU module and a binocular camera, and the upper surface of the towed body is provided with a coding pattern and carries a sonar sensor; s02, establishing a towed body coordinate system by taking the acoustic center of the sonar sensor as an original point, obtaining three-dimensional coordinates of feature points on the towed body in the towed body coordinate system, and generating a three-dimensional space model operation simulation model of the towed body; and S03, the binocular camera is calibrated. According to the invention, the problem of underwater topographic survey of a near-shore high-flow-velocity turbid water area is solved, and high-efficiency, low-cost and high-precision surveying and mapping operation is realized.

A maritime drone as uncrewed surface vessel is provided. The maritime drone has a control and a monohull. The control is configured such that a movement and / or an operation of the maritime drone is autonomously controlled by the control. The monohull has a casing which encloses an interior volume of the maritime drone. The maritime drone comprises at least one sonar sensor which is coupled to the control and is configured for detecting underwater objects. The at least one sonar sensor is arranged within the maritime drone. The maritime drone has furthermore compact dimensions, namely a maximum length of 200 cm, a maximum width of 60 cm, a maximum height of 60 cm and a maximum weight that the maritime drone can be transported by a single person. The maritime drone comprises a self-righting functionality, which is based at least on a shape of the monohull and a weight distribution of the maritime drone.

The application discloses a kind of autonomous operation methods of deep-sea mining car, and mining car is equipped with sonar sensor, camera sensor and control unit.Through sonar, three-dimensional point cloud information of seabed operation area is obtained, and synchronous positioning and map construction are carried out in combination with vehicle pose, to form global point cloud map;Based on the map, cubic surface fitting is carried out on seabed topography, to generate continuous three-dimensional curved surface model;Through camera, seabed image is collected and sulfide target is identified, in combination with camera calibration parameter, vehicle real-time pose and curved surface model, two-dimensional target information is mapped to global coordinate system, to obtain target three-dimensional space position;Construct the grid map containing sulfide target distribution and operation state mark, generate target-oriented mining operation path, and control mining car to execute mining operation;After operation is completed, detection and identification are carried out again using sonar and camera, and operation completion state is updated.The application improves target positioning accuracy, path planning efficiency and autonomous operation ability in deep-sea mining.

The application relates to the technical field of image processing, and discloses a fish school target tracking and swimming speed calculation method based on a sonar image, which comprises the following steps: acquiring a sonar video set and a parameter set collected by a sonar sensor array, performing isochronous interval frame processing to obtain a first video frame set, performing screening and denoising to obtain a second video frame set, determining position data and fish school type data of a target fish school based on the second video frame set, the parameter set, a pre-trained identification model, performing identification frame marking on each video frame image in the second video frame set, extracting target data of the identification frame, and calculating the swimming speed of the target fish school. Through implementation of the application, from comprehensive and accurate data collection to high-quality image processing, accurate target identification and tracking are realized, and the problems that related technologies are not perfect, target loss or misjudgment is prone to occurring when multiple targets are tracked, and the demand for accurate measurement of fish school speed cannot be met are solved.

The invention provides an adaptive space calibration method and device, an underwater robot and electronic equipment, and the method comprises the steps: carrying out the multi-view image collection of a first feature of a target object through a visual sensor, obtaining a first feature image set, carrying out the point cloud extraction of a first feature image in the first feature image set, and generating a first point cloud; performing image acquisition on a second feature of the target object through a sonar sensor to obtain a second feature image set, and performing point cloud extraction on a second feature image in the second feature image set to generate a second point cloud; and performing dynamic matching on the first point cloud and the second point cloud according to the visibility of the water area so as to realize adaptive space calibration of the camera vision sensor and the sonar sensor. Through a three-dimensional reconstruction method, space coordinate calibration of a visual sensor and a sonar sensor is adaptively completed, and correct fusion of point cloud data of at least two sets of different sensors is guaranteed in multiple imaging modes.

This invention relates to a biomimetic brain-like synchronous localization and environmental perception method for underwater robots. The invention addresses the problems of poor visual odometry, insufficient robustness, and low accuracy in loop closure detection in existing underwater robot navigation systems. The robot first acquires environmental feature information through sonar sensors and its own motion information through navigation sensors. A local scene template is obtained by processing the sonar data using an acoustic-visual processing method. The sensor data undergoes pre-integration processing, and the processed data is used as input to a convolutional neural network to output motion displacement, thus forming the robot's perception of its own position. Finally, an empirical map integrates the above information, and loop closure detection updates the empirical map, reducing drift during robot movement and completing the construction of the empirical map. This invention belongs to the fields of bionics and motion navigation technology.

The invention belongs to the technical field of voltage type pre-amplifiers. The invention provides a fully differential rail-to-rail voltage type preamplifier for a sonar sensor. According to the embodiment of the invention, the two rail-to-rail input stages and the shared four-input dual-output node output stage are integrated, so that a unique signal processing structure is formed. By means of the flexibility of multiple input nodes, differential signal amplification and additional input common-mode control nodes can be achieved in the preamplifier, and therefore output common-mode level can be accurately adjusted, and the good active common-mode rejection capacity is achieved. Under the condition that the linearity is ensured, the input and output range of the circuit is remarkably widened, the common-mode rejection capability of the circuit is effectively improved, and a high-performance solution is provided for the multichannel sonar array.

A ground assembly for wireless charging of electric vehicles according to an embodiment of the present invention includes: a transmitting coil; a power supply unit capable of supplying power to the transmitting coil; a detection sensor unit capable of detecting foreign matter in an external matter detection area surrounding the transmitting coil; and a control unit for detecting foreign matter using the detection sensor unit, measuring the distance to the detected foreign matter, determining the presence of foreign matter in the foreign matter detection area based on the measured distance, and controlling the power supplied to the transmitting coil based on the determination result. The detection sensor unit includes at least one of a sonar sensor, a lidar, and a camera device. The foreign matter detection area can be within a predetermined distance from the edge of the transmitting coil in a direction parallel to the ground surface, and can be within a predetermined distance from the upper part of the transmitting coil in a direction perpendicular to the ground surface.

The invention discloses a full-simulation class volume accumulation and calculation integrated chip and a cross-medium multi-mode detection method thereof, and belongs to the field of computer vision. The optical sensor array is used for capturing an optical image signal and directly outputting a voltage signal through an analog circuit; the sonar sensor array is used for receiving acoustic signals and converting the acoustic signals into corresponding electric signals; and the shared and reusable convolution-like hybrid storage calculation unit is used for executing weight storage and analog calculation. The invention aims to solve the problems of high delay, high resource consumption and analog-to-digital conversion bottleneck in cross-media detection.

The utility model discloses a sonar temperature sensor and an electric kettle realizing water level measurement based on sonar technology, the sonar temperature sensor is integrated with a sonar sensor and a temperature sensor, the sonar temperature sensor comprises a T-shaped sensor housing, a sonar transduction sheet and a temperature measurement circuit board, and the sonar transduction sheet and the temperature measurement circuit board are both arranged in the sensor housing; wherein the sonar transduction sheet is glued at the upper part in the sensor shell by using epoxy resin glue, and the temperature measurement circuit board is arranged on the inner wall of the sensor shell, so that the temperature measurement circuit board is respectively connected with the sensor shell and then is encapsulated by epoxy resin; the sensor shell is made of 304 stainless steel, and the sensor shell is directly used for signal receiving and transmitting of the sonar sensor and the temperature sensor so that the water level height and the water temperature can be conveniently detected. According to the utility model, the sonar temperature sensor is integrated, the installation is convenient, and the water level measurement accuracy can be improved through the sonar sensor.

The invention discloses a pier scour prediction method and system based on a single-beam sonar and water tank experiment, and the method comprises the steps: carrying out the quantitative evaluation of a pier position in a navigable river channel, and selecting a pier with the highest comprehensive scour risk as a monitoring object; acquiring field flow field parameters; setting a pier model and a riverbed scene in the water tank, and carrying out a water tank scouring experiment; detecting the section of a scouring pit on the upstream side of the pier after the water tank scouring experiment, and obtaining a curve shape from the pit bottom to an edge transition area; extracting water tank scouring experiment data, and constructing a training data set; training a pre-established pier scouring curve prediction model by adopting the training data set; and acquiring field real-time data and inputting the field real-time data into the trained pier scour curve prediction model to obtain a pier scour prediction curve. According to the method, a small number of sonar sensors are installed on actual piers to monitor the depth of the scouring pit, and calculation and prediction of the section curve of the scouring pit of the multiple piers of the actual bridge are achieved in combination with a prediction model trained through a water tank model experiment and a data driving method.

Techniques are described for calibrating a coordinate frame of a remote sensing sensor of a perception system of a machine with respect to a coordinate frame of the machine. An application of a mobile device, such as a smartphone, a tablet computing device, or a laptop, or a web service detects a visual fiducial tag and a feature of the machine in an image by using an optical sensor of a digital camera system. The fiducial tag detection provides the coordinate transformation between the mobile device and a housing of the remote sensing sensor, e.g., radar sensor, lidar sensor, sonar sensor, or camera. Detecting a feature of the machine, e.g., a traction component such as a wheel or track, a brake light, a headlight, a turn signal, or a logo, provided constraints for the transformation between the device and machine.

The utility model discloses an unmanned diving device. The unmanned diving device comprises a frame body; one end of the mounting assembly is fixedly connected with one end of the frame body; the sealing assembly is arranged at the other end of the frame body, a controller is arranged in the sealing assembly, and the controller is used for controlling movement of the unmanned diving device; the sampling assembly is arranged at the end, away from the frame body, of the sealing assembly, and the sampling assembly is electrically connected with the controller; and the sonar sensor is arranged on one side of the sealing assembly, and the sonar sensor is electrically connected with the controller. The unmanned diving device is small in size, simple in structure, high in working efficiency, convenient to transport and high in control precision.

The invention relates to the field of energy storage battery assembly, and discloses a battery box screw installation abnormity detection system based on an artificial intelligence large model, and the system comprises the steps: collecting echo signals of a battery box screw and a hole wall through a sonar sensor, and comprehensively judging the fastening state of the screw and whether a workpiece has a dark damage through a multi-mode fusion algorithm; performing joint modeling and semantic reasoning on the sonar signal features and the visual image features by using an artificial intelligence large model, and automatically generating specific reasons causing abnormity; based on the corresponding relationship between the abnormal reason and the repair knowledge graph, retrieving repair process parameters and operation steps related to the type of the dark injury or the fastening defect; the abnormal position is directly marked on the surface of the battery box through high-precision laser; and collecting process data and feedback information after repair execution of the operator, and outputting an updated anomaly detection and repair guidance result in combination with a historical repair result and a detection record. The method has the advantage of improving the detection accuracy.

The utility model discloses depth measuring equipment for river channel construction, which comprises a base, the upper surface of the base is fixedly connected with an angle adjusting seat, the inner wall of the angle adjusting seat is hinged with a primary support frame, and the front surface of the angle adjusting seat is fixedly connected with a motor. According to the device, the laser distance measuring sensor is matched with the sonar sensor, the laser distance measuring sensor in a shallow water area quickly obtains accurate data by means of the high precision advantage, the sonar sensor in a deep water area effectively works, the limitation of a single sensor in different water areas is avoided, and the accuracy of measurement data of the whole water area is ensured; meanwhile, the first-stage supporting frame with the adjustable angle can flexibly adjust the measurement angle according to the actual conditions of different measurement sites, and the device adapts to diversified measurement environments; the electric hydraulic telescopic rod can adjust the measurement length according to the estimated river channel depth, the measurement requirements of river channels with different depths are met, and the application range of the device is greatly expanded.

The embodiment of the invention provides a visual control method and device for an underwater unmanned underwater vehicle, and a medium, and the method comprises the steps: responding to a first operation for a BIM model, and generating siltation blocking position information; controlling the unmanned underwater vehicle to travel to a first area along a first path according to the deposition and blockage position information and the underwater position information of the unmanned underwater vehicle; detecting real-time position information of the unmanned underwater vehicle in the first area through a sonar sensor with a preset layout; according to the real-time position information and first video information and first sonar map information acquired by the unmanned underwater vehicle in real time, the unmanned underwater vehicle is controlled to travel to a siltation area indicated by the siltation blocking position information along a second path; and controlling the unmanned underwater vehicle to clean deposits in the deposition area. Through visual display and control of the BIM model terminal, the cleaning error of the unmanned underwater vehicle can be timely handled and timely processed, so that the cleaning effect is improved.

A maritime drone (10) as uncrewed surface vessel is provided. The maritime drone (10) has a control (28) and a monohull (12). The control (28) is configured such that a movement and / or an operation of the maritime drone (10) is autonomously controlled by the control (28). The monohull (12) has a casing (14) which encloses an interior volume (16) of the maritime drone (10). The maritime drone (10) comprises at least one sonar sensor (48) which is coupled to the control (28) and is configured for detecting underwater objects. The at least one sonar sensor (48) is arranged within the maritime drone (10). The maritime drone (10) has furthermore compact dimensions, namely a maximum length of 200 cm, a maximum width of 60 cm, a maximum height of 60 cm and a maximum weight that the maritime drone (10) can be transported by a single person. The maritime drone (10) comprises a self-righting functionality, which is based at least on a shape of the monohull (12) and a weight distribution of the maritime drone (10).

To prevent consumption of battery power due to a hands-free sensor falsely detecting an object around a parked vehicle, which causes the vehicle to start CAN communication, when the object is present around the vehicle while parked.SOLUTION: Provided is a sensor erroneous detection prevention system including a hands-free sensor that detects objects, a sonar sensor that detects the distance between a vehicle and objects around the vehicle, a first control unit that acquires information detected by the hands-free sensor and the sonar sensor, and a plurality of control units that control devices to be controlled, the first control unit being capable of sending signals to the plurality of control units based on detection by the hands-free sensor, monitoring the state of a shift lever and an ignition that are provided in a vehicle, and, if the distance between the vehicle and objects around the vehicle when the shift lever is shifted to park is within a predetermined distance, after the ignition is turned off, entering a mode in which signals based on detection by the hands-free sensor are not sent.SELECTED DRAWING: Figure 3

The invention relates to the technical field of drainage well measurement, in particular to an intelligent rod for measuring the water depth, the mud depth, the well depth and the position of a drainage well, a telescopic rod, an RTU, an underwater rod and a mud-entering rod are connected through threads, a user can conveniently select rods according to different well depths, different water depths and different mud depths, a laser sensor and a radar sensor are installed in the RTU, and the intelligent rod can be used for measuring the water depth, the mud depth, the well depth and the position of the drainage well. The laser sensor emits upwards to measure the distance to the wellhead, and the radar sensor emits downwards to measure the distance to the water surface. A sonar sensor and a static pressure sensor are installed in the water depth sensor, the water depth sensor automatically slides down to a mud-water separation surface along the underwater rod during measurement, the sonar sensor emits upwards to measure the water depth, and when the water depth is extremely shallow and the sonar sensor is difficult to measure, the water depth is measured through the static pressure sensor. The distance between the laser sensor and the bottom of the mud entering rod and the distance between the radar sensor and the bottom of the mud entering rod are fixed, the water depth, the mud depth and the well depth can be calculated according to laser, radar and sonar measurement values, and accurate well positioning can be achieved through RTK.

A contact object detection apparatus includes an on-road static object detector, a sonar sensor, a position estimator, a corrector, and a contact object determination unit. The on-road static object detector detects an on-road static object from an image of an environment behind a vehicle to calculate a position of the object. When the object is no longer detectable, the position estimator estimates a current position of the object based on the last position detected by the on-road static object detector, traveling speed data, and steering angle data, to calculate an angle between a center axis of the sonar sensor and the estimated current position. The corrector corrects a decrease in a sensor output value of the sonar sensor based on the calculated angle. The contact object determination unit determines whether the object has a possibility of contact with the vehicle, based on the corrected sensor output value.

The application discloses a kind of underwater target tracking methods based on multivariate skew laplace distribution modeling, the motion state data of underwater target is collected using the mode of sonar sensor, and the target position measurement information is obtained by the mode of coordinate system conversion;Underwater target motion model is established, the state space equation of underwater target is determined, the mathematical characteristics of underwater noise are analyzed, and the measurement model of target under non-gaussian noise is established;Based on multivariate skew laplace distribution, the non-gaussian noise is modeled, the mixed parameters, shape parameters and scale matrix of noise are solved under the variational bayesian framework, the target state and noise covariance matrix are iteratively updated, and the target motion state is iteratively updated using Kalman filtering estimation, after the iteration number, the estimated value of underwater target position and speed and the estimated value of covariance matrix are output.The application has better robustness and estimation accuracy, and does not need to select the degree of freedom parameter, and can be better applied to the tracking of target.

The invention relates to the field of underground equipment, and discloses an underground equipment cooperative control method and system based on deep learning, and the method comprises the steps: obtaining seabed depth data collected by a sonar sensor and texture feature data collected by a visual sensor, and obtaining a seabed feature data set; constructing a seabed three-dimensional coordinate point cloud according to the seabed feature data set and generating a three-dimensional terrain surface model; analyzing geometric mutation features in the three-dimensional terrain surface model; calculating a path node optimization sequence based on the three-dimensional coordinates and the geometric boundary information of the impassable obstacles and the current coordinate positions of the devices; in the process that the equipment generates a motion trail according to the path node optimization sequence and executes collaborative operation, the position coordinates and the operation completion percentage are obtained in real time; and adjusting the operation priority of each device based on the real-time position coordinates and the operation completion percentage.

This application discloses a method, equipment, and medium for monitoring and early warning of scour of offshore wind turbine foundations, relating to the field of marine monitoring technology. The method includes: controlling a gimbal to rotate a sonar sensor along a preset trajectory; controlling the sonar sensor to emit ultrasonic waves and receive raw echo signals at a preset angle; using an elastic wave vibration signal as a reference signal to adaptively cancel interference in the raw echo signal; calculating the distance between the sonar sensor and the scanning point on the seabed based on the clean echo signal; compensating the original azimuth and pitch angles for wave motion based on the instantaneous attitude angle; converting the distance, compensated azimuth, and compensated pitch angles into Cartesian coordinates to obtain the current elevation of the scanning point; comparing the waveform similarity between the clean echo signal of the scanning point and the reference echo signal to calculate the waveform distortion coefficient. This application achieves over-threshold perception of microstructural changes in the early stages of scour through the above method, significantly advancing the early warning response time.

The invention relates to the technical field of underwater robots, in particular to an autonomous obstacle avoidance control system and method for an underwater robot. The system comprises a sensor assembly, a controller assembly and an actuator assembly, the sensor assembly is used for acquiring surrounding environment information of the robot, the controller assembly is used for processing sensor data signals and formulating an obstacle avoidance strategy, and the actuator assembly is used for adjusting motion parameters of the robot to achieve obstacle avoidance. The method of the system comprises the steps of acquiring sensor data, formulating an obstacle avoidance strategy, adjusting motion parameters, executing the obstacle avoidance strategy, realizing autonomous obstacle avoidance and the like. The system can avoid obstacles based on various sensors such as a sonar sensor, a camera sensor, a pressure sensor and a positioning system, can also adopt artificial intelligence technologies such as deep learning and reinforcement learning to improve the accuracy and efficiency of obstacle avoidance, and can also perform data exchange and cooperation with other robots through an internal communication system of the robot. And the overall obstacle avoidance effect is improved. The system and the method can be widely applied to the fields of underwater scientific research, seabed exploration, underwater operation and the like, and the autonomy and the application value of the underwater robot are improved.

The invention provides a small gas-liquid dual-purpose high-precision sound velocity measurement device and method. The device comprises a tubular cavity with two closed ends, a receiving and transmitting integrated sonar sensor, a high-reflectivity reflecting plate and an environment module, the tubular cavity is made of a rigid material, the length is fixed, the error and the surface roughness of the inner wall are within a preset threshold range, no complex separation structure exists in the tubular cavity, and the tubular cavity is suitable for sound velocity measurement of gas and liquid media; the transmitting-receiving integrated sonar module is fixed at one end of the tubular cavity, the high-reflectivity reflecting plates are arranged in the middle and at the other end of the tubular cavity, and the transmitting-receiving integrated sonar module, the high-reflectivity reflecting plates and the tubular cavity cooperate to achieve transmitting, reflecting and receiving of sound waves; the environment module is integrated with a temperature sensor, a pressure sensor and a data transmission interface, and is used for collecting environment parameters in the tubular cavity in real time and transmitting the environment parameters to external processing equipment; the universality and the operation efficiency are greatly improved; the measurement reliability is improved; the size of the equipment is compressed through the integrated design of the assembly, miniaturization is achieved, and the applicability of space-limited scenes is improved.

The utility model discloses a sonar pipeline detection device, including work box, probing dolly and sonar sensor, work box is used for the probing dolly accommodation and convenient access work, the probing dolly includes first cavity and second cavity, the first cavity and second cavity are mutually independent, and the sonar sensor is arranged in the first cavity. The second cavity is located at the front end of the detection trolley, the sonar sensor is installed in the second cavity, a cover plate assembly is arranged on the side, close to the second cavity, of the detection trolley, and the cover plate assembly is used for overturning, adjusting and protecting the sonar sensor in the second cavity. The protection capability of the equipment in deep water and complex pipelines is enhanced; the operation process is simplified, and the operation convenience is improved; the modular cavity layout and the detachable structure optimize the maintenance efficiency, reduce the failure rate, prolong the service life, significantly improve the adaptability and reliability of the detection device, and have certain use value and popularization value.

A driving assistance device (10) having a processor (12) that executes a process of detecting objects around a vehicle (1), wherein the processor is configured to execute following processes: obtaining first detection values outputted from a plurality of sonar sensors provided in the vehicle, second detection values indicating the state of the shift range, and third detection values corresponding to the steering angle of the steering device, controlling a notification device (20) that operates in conjunction with the first detection values and adjusting notification contents to be output, calculating the relative distance between the vehicle and the objects existing around the vehicle based on the first detection values, determining the traveling direction of the vehicle based on the second detected values, calculating priorities according to the sonar sensors individually based on the traveling direction and the steering angle, adjusting the notification contents according to level of the priorities.

The application discloses a UAV towed body positioning and pose measurement method based on binocular vision positioning, and relates to the technical field of computer processing.The method comprises the following steps: S01, a measurement system is constructed, the measurement system comprises a UAV and a towed body connected with the UAV through a cable; the UAV is provided with a GNSS module, an IMU module and a binocular camera; the upper surface of the towed body is provided with a coded pattern and is provided with a sonar sensor; S02, a towed body coordinate system is established with the acoustic center of the sonar sensor as the origin, three-dimensional coordinates of feature points on the towed body in the towed body coordinate system are obtained, and a three-dimensional space model of the towed body is generated to run a simulation model; and S03, the binocular camera is calibrated.The application solves the underwater topographic survey problem in the near-shore high-flow-speed turbid water area, and realizes efficient, low-cost and high-precision surveying and mapping operation.

The invention relates to the technical field of bridge pier scouring state monitoring, and discloses a pre-embedded sonar bridge pier scouring state monitoring system and method, a sensor unit is pre-embedded in a bridge pier foundation, and the sensor unit comprises a sonar sensor, a lateral acoustic window and acoustic coupling liquid. The lateral acoustic window is exposed and automatically activates monitoring only when scour develops to a basic key area, and intelligent conversion from'whole process recording 'to'key early warning' is achieved. An electric pulse self-cleaning assembly is integrated, so that biological attachment on the acoustic window can be effectively removed through pulses generated by electrodes, and long-term reliability is ensured. All the units are coordinated through the control module. According to the invention, the direct, accurate, long-acting and maintenance-free automatic monitoring of the scouring of the pier foundation is realized, and the safety guarantee level of the bridge is obviously improved.

The application discloses a kind of underwater robot image enhancement methods and systems based on sonar structure constraint generation confrontation, belong to underwater robot environment perception and multimodal information fusion technical field.The method is through underwater camera equipment and sonar sensor synchronous acquisition original underwater image data and sonar point cloud data, and pretreatment is carried out to sonar point cloud;Space guide map is constructed, and the structural boundary information and distance distribution information of different regions in scene are represented;Original underwater image and space guide map are input into generator, enhanced image is generated, and enhanced image is discriminated by discriminator, and finally enhanced underwater image is output after training;The application introduces the spatial structure information of sonar point cloud into the generation confrontation image enhancement process, so that the enhanced result can better maintain the target boundary and scene structure while improving brightness, contrast and color performance, and reduce the over-enhancement and false color problems prone to occur in traditional image enhancement methods.