31results about How to "Automatic and accurate detection" patented technology

A wheel identifying apparatus according to the present invention includes a plurality of transceivers, a triggering device, a receiver, and a wheel identifier. Each of the transceivers is located on one of a plurality of wheels of a vehicle and works to receive a trigger signal and transmit a response signal in response to receipt of the trigger signal. The triggering device is located on a body of the vehicle at different distances from the transceivers and works to transmit the trigger signal. The receiver works to receive the response signals transmitted by the transceivers. The wheel identifier is operatively connected to the receiver and works to identify, for each of the response signals received by the receiver, the wheel on which the transceiver having transmitted the response signal is located using the fact that strengths of the trigger signal at the transceivers are different from each other.

The embodiment of the invention discloses a dangerous road condition reminding method and device, a vehicle-mounted terminal, a server and a medium. The method applied to a vehicle-mounted terminal comprises: identifying a surrounding road image of a vehicle by using an image recognition technology to obtain obstacle information; determining whether any dangerous road condition exists around the vehicle by combining obstacle information and vehicle driving data collected in real time; if so, generating a dangerous road condition reminding message according to the obstacle information and the dangerous road condition location information and uploading the message to a server; and determining at least one prompting object by the server based on the dangerous road condition reminding messageand issuing the dangerous road condition reminding message to all reminded objects to carry out dangerous road condition reminding. Therefore, the obstacle information on the road can be obtained timely, the existence of the dangerous road condition can be detected automatically and accurately, and the dangerous road condition reminding message is uploaded to the server and the server warns the vehicle timely, so that the probability of traffic accidents and congestion occurrence is reduced.

The invention discloses a cloud layer detection and classification method based on multi-cloud-layer features, and the method comprises the steps: calculating the color, texture and shape feature quantities of a cloud picture, and building a cloud picture feature space; carrying out cloud layer pixel and sky pixel division on the shot current cloud picture by utilizing the optimal normalized red-blue ratio threshold value, and searching an optimal segmentation threshold value position on the normalized red-blue ratio histogram by adopting a minimum cross entropy method; and performing KNN classification on the currently photographed cloud picture according to the cloud picture feature space to obtain the type of the cloud layer to be shielded from the sun. According to the method, the cloud layer can be automatically and accurately detected based on the RGB characteristics of the cloud picture, the cloud layer characteristics are comprehensively extracted, and efficient and accurate judgment of the cloud layer type is achieved.

An image processing chip test method comprising: controlling a power supply circuit to provide a first operating voltage to an image processing chip comprising a storage device; and when reading written first image data from the storage device, the test device receives a first error detection code corresponding to the first image data and determines whether the first error detection code means an error occurs. If an error occurs, record the first operating voltage as an erroneous operating voltage, and if the error does not occur, provide a second operating voltage to the image processing chip. Also, when the written second image data is read from the storage device, the test device receives a second error detection code corresponding to the second image data and determines whether the second error detection code means an error occurs.

The embodiment of the invention discloses a vehicle parameter detection method and system and a storage medium. The method comprises the following steps of determining position coordinates of radar data in a target coordinate system according to the radar data of at least two laser radars for scanning a vehicle in a driving process, wherein the at least two laser radars are arranged in a staggered manner along two sides of a vehicle driving road, extracting a wheel point cloud according to the position coordinates of the radar data in the target coordinate system, and determining current vehicle parameters of the vehicle according to the position coordinates of the wheel point cloud in the target coordinate system. According to the technical scheme, automatic and accurate vehicle parameter detection can be achieved, the detection cost is reduced, the detection efficiency is improved, and a new thought is provided for vehicle parameter detection.

The invention discloses defect detection equipment and a production line, and belongs to the technical field of honeycomb ceramic carriers. An acquisition detection unit of the defect detection equipment comprises a central objective table, a first detection module and a rotation detection module. The first detection module is arranged over the central objective table, faces the central objective table and is used for detecting the position information of the outer contour of a to-be-detected workpiece, and a second detection module is configured to perform surrounding detection around the to-be-detected workpiece along with the XY plane moving mechanism. Meanwhile, the detection device rotates and always faces the side face of the workpiece to be detected, so that the side face of the honeycomb ceramic carrier is automatically and accurately detected, the labor intensity of workers is reduced, and batch production of the honeycomb ceramic carrier is facilitated.

The invention relates to the technical field of optical fiber signal detection, and concretely relates to strong magnetic field transmission performance detection equipment for optical fibers. The equipment comprises: a rack; a stretching driving mechanism horizontally arranged on the rack; two sets of optical fiber clamping mechanisms arranged at the two output ends of the stretching driving mechanism respectively; two sets of end push-out mechanisms respectively arranged on two output ends of the stretching driving mechanism, and located between the output end of the stretching driving mechanism and the optical fiber clamping mechanisms; an electric signal connection mechanism; a magnetic field generating device; and two sets of magnetic field displacement driving mechanisms arranged on the two sides of the stretching driving mechanism correspondingly. The strong magnetic field transmission performance detection equipment for the optical fibers can stretch the installed optical fibers automatically, and the relationship between the magnetic field and the optical fiber signal transmission performance under different conditions can be comprehensively reflected.

The invention discloses a self-compensation adjusting mechanism and method for new energy battery module welding, the self-compensation adjusting mechanism comprises a workbench and a welding gun mechanism with one side provided with a measuring seat, and the workbench is slidably connected with a supporting plate used for supporting the welding gun mechanism in the connecting line direction of the two sides of the welding gun mechanism; one side of the measuring seat is provided with a through groove for fixedly placing three sides of a to-be-measured battery and the end of one side of the to-be-measured battery, the other side of the measuring seat is fixedly connected with one side of the supporting plate, the other side of the welding gun mechanism is provided with an elastic reset mechanism for buffering or resetting the supporting plate, and the elastic reset mechanism is installed at the upper end of the workbench. The workbench is provided with an adjusting driving assembly for pushing the other side end of the battery to be detected to translate towards the direction of the elastic reset mechanism, and the rear end of the welding gun mechanism is provided with a clamping assembly for preventing the supporting plate from sliding; the function of automatically and accurately detecting the width difference value of the battery to be welded and the function of automatically adjusting the position of the welding gun according to the width difference value are integrated, and the welding gun mechanism has the advantages of being high in positioning accuracy, simple in structure and low in cost.

The invention relates to the technical field of batteries, in particular to a pole piece turnover detection method and device, detection equipment and a storage medium, and the pole piece turnover detection method of a battery cell pole group comprises the following steps: collecting an actual pole piece image of the battery cell pole group; inputting the actual pole piece image into a pre-trained pole piece turnover prediction model to obtain a plurality of initial prediction frames in the actual pole piece image, and determining a final prediction frame corresponding to each pole piece of the battery cell pole group according to the non-maximum suppression score of each initial prediction frame; and calculating the confidence value of the final prediction frame corresponding to each pole piece, identifying the category of the final prediction frame corresponding to each pole piece, and detecting a folded pole piece in the battery cell pole group when the confidence value is greater than or equal to a preset threshold value and the category is a folded category. The method can automatically and accurately detect the folded pole piece in the battery cell pole group, improves the detection efficiency, reduces the detection cost, and improves the overall quality of a product.

The embodiment of the invention provides a tire pressure detection method and a computer storage medium. The method comprises the following steps: performing feature extraction operation on a to-be-detected wheel tire image to obtain tire feature data of the wheel tire image; preliminarily judging the tire pressure of the wheel tire in the wheel tire image based on first characteristic data included in the tire characteristic data to obtain a preliminary judgment result of the tire pressure of the wheel tire; if it is determined that the tire pressure of the wheel tire is normal based on the preliminary judgment result, predicting the tire pressure of the wheel tire in the wheel tire image based on second feature data included in the tire feature data to obtain a prediction result of the tire pressure of the wheel tire; and on the basis of the prediction result of the tire pressure of the wheel tire, re-determining the tire pressure of the wheel tire in the wheel tire image to obtain a re-determination result of the tire pressure of the wheel tire. According to the embodiment, the tire pressure can be automatically detected, so the possibility of accidents in the low-speed and high-speed driving process of the vehicle is reduced.

The invention discloses a railway engineering detection method and system based on an unmanned aerial vehicle inspection video. The method comprises the following steps: performing frame-by-frame detection on the inspection video based on a target detection algorithm, and obtaining a plurality of target detection frames comprising target structures; tracking each target detection frame based on a target tracking algorithm and acquiring a target trajectory of each target structure; according to the frame data of each trajectory frame in each target trajectory, determining an estimated coordinate of each target structure; determining the positioning information of each target structure appearing in the inspection video according to each estimation coordinate and the design data of each target structure in the railway line design drawing; wherein the inspection video is a video obtained after the unmanned aerial vehicle shoots the whole or part of the predetermined railway line, and the frame data comprises the position data of the unmanned aerial vehicle and the attitude data of the camera, so that the target structure on the railway line can be automatically and accurately detected from the inspection video of the unmanned aerial vehicle, and the efficiency of railway construction inspection is improved.

The invention belongs to the field of mask detection, and relates to a mask ear strap detection system. The mask ear strap detection system comprises a shell, a third rotating shaft is arranged at the upper end of the shell, a horizontal position control device is arranged on the third rotating shaft, the horizontal position control device is used for controlling the position of an equipment working mechanism in the horizontal direction, a first sliding block cavity is formed in the shell, roller cavities are formed in the shell, a vertical position control device is arranged in the first sliding block cavity and the roller cavities, and the vertical position control device is used for changing the position of the working mechanism in the vertical direction. After masks are produced and manufactured, the mounting firmness degree of mask ear straps is automatically detected, the masks can be automatically discharged to a corresponding follow-up treatment device according to the detection result of qualified or unqualified ear straps, the detection result of the mounting firmness degree of the mask ear straps is accurate, and the masks cannot be damaged.