8610results about How to "Accurate judgment" patented technology

A gas-sparing vehicle is achieved by a control system for a hybrid vehicle equipped at least with: a hybrid engine which includes at least a first rotary electric unit for deciding the rpm of the engine and a second rotary electric unit for deciding the driving force of the vehicle and which has power converting means connected to the output shaft of the engine; and electricity storing means. In one embodiment, a hybrid controller 16 controls the drive of a first rotary electric unit 2000 according to a startup torque command value which is decided based on the rpm of an engine at the time of engine startup and which decreases as the rpm increases; it also determines that the complete explosion in an engine 1 has occurred when the startup torque command value falls below a predetermined complete explosion judgment value.

A vehicle environment monitoring device identifies objects from an image taken by an infrared camera. Object extraction from images is performed in accordance with the state of the environment as determined by measurements extracted from the images as follows: N1 binarized objects are extracted from a single frame. Height of a grayscale objects corresponding to one of the binarized objects are calculated. If a ratio of the number of binarized objects C, where the absolute value of the height difference is less than the predetermined value ΔH, to the total number N1 of binarized objects, is greater than a predetermined value X1, the image frame is determined to be rainfall-affected. If the ratio is less than the predetermined value X1, the image frame is determined to be a normal frame. A warning is provided if it is determined that the object is a pedestrian and if a collision is likely.

The invention relates to an external skeleton robot, in particular to a human-simulated external skeleton robot assisting the lower limbs. The human-simulated external skeleton robot assisting the lower limbs aims to solve the problems that an existing external skeleton robot is low in coupling degree of motion space and poor in wearing comfort, reliability and adaptation, and power needed by a motor is large. The human-simulated external skeleton robot assisting the lower limbs comprises an upper body back part, a left leg and a right leg. The left leg and the right leg respectively comprise a hip drive system, a knee drive system and a foot wearing system. A rear side connection board of the waist is in rotating connection with a load installation board. Each hip joint supporting board is provided with a first motor and a first reducer, wherein the first motor is provided with an encoder, and the output end of the first motor provided with the encoder is connected with the input end of the first reducer. Each hip joint connecting board can rotate in the vertical plane. Each thigh stretching board is in detachable connection with the corresponding hip joint connecting board. The output end of a main drive mechanism is connected with each crus connecting board. The lower surfaces of elastic boards are bonded with the upper surfaces of the rubber soles of the feet. The human-simulated external skeleton robot assisting the lower limbs can assist in walking.

When the three-dimensional direction the head faces is detected by three axes, that is, a yaw angle that is an angle turning around an erect axis erected on the horizontal surface of the head, and a pitch angle and a roll angle that are angles formed by the above erect axis and two axes perpendicular thereto, a gyro sensor 11 which detects the yaw angle from the integral value of the acceleration, a tilt sensor 12 which detects the inclination of a plane that intersects the direction of the erect axis at right angles, and calculation element 14 which calculates the pitch angle and the roll angle from the output of a tilt sensor are provided, so that the direction that the head faces can be detected with a simple detecting structure including the two sensors, in a head mounted display or the like.

A swing analyzing apparatus includes at least an angular velocity sensor, an impact detection section, an angular velocity information calculation section, and an impact state judgment section. The impact detection section detects the timing of impact in a swing of a sporting good. The angular velocity information calculation section calculates at least one of the amount of change in angular velocity with respect to a predetermined axis in a predetermined period after the impact timing and the greatest value of the angular velocity based on data outputted form the angular velocity sensor. The impact state judgment section judges the state of impact based on the result calculated by the angular velocity information calculation section.

The invention relates to a movement human abnormal behavior identification method based on template matching, which mainly comprises the steps of: video image acquisition and behavior characteristic extraction. The movement human abnormal behavior identification method is a mode identification technology based on statistical learning of samples. The movement of a human is analyzed and comprehended by using a computer vision technology, the behavior identification is directly carried out based on geometric calculation of a movement region and recording and alarming are carried out; the Gaussian filtering denoising and the neighborhood denoising are combined for realizing the denoising, thereby improving the independent analysis property and the intelligent monitoring capacity of an intelligent monitoring system, achieving higher identification accuracy for abnormal behaviors, effectively removing the complex background and the noise of a vision acquired image, and improving the efficiency and the robustness of the detection algorithm. The invention has simple modeling, simple algorithm and accurate detection, can be widely applied to occasions of banks, museums and the like, and is also helpful to improve the safety monitoring level of public occasions.

The invention provides a method for detecting lane lines based on grayscale estimation and cascade Hough transform, belonging to the technical field of image processing, and relating to image segmentation, image line geometrical characteristics detection and intelligent vehicle navigation simultaneously, which is mainly applicable to an auxiliary safety drive system. The method comprises the following steps: carrying out grayscale estimation on sensitive areas of an original image I of the collected vehicle road conditions ahead; dividing the sensitive areas into a vehicle shadow region, a roadway non-mark region and a roadway mark region (including the area of the car body of the vehicles ahead); adopting a mathematical morphology method to obtain a boundary image from the roadway mark region in the areas divided by the grayscale estimation; then carrying out Hough transform on the obtained boundary image of the roadway mark region to extract line image characteristics therein; and finally realizing the detection of the lane lines by searching end points of roadway mark boundary. Compared with the congeneric method, the method in the invention has stronger stability and wider application occasions and the like.

A subject judgment program is capable of reducing the calculation load on a computer functioning as a device for judging the subject in a subject image. In a controller of a digital still camera, when a CPU running the subject judgment program (stored in a flash memory) obtains image data from an A/D converter via a first interface circuit, the CPU generates two-dimensional distribution data of product-moment correlation coefficients for each of model image data stored in the flash memory by successively calculating the product-moment correlation coefficient between the model image data and each part of the obtained image data, identifies a piece of model image data corresponding to two-dimensional distribution data having the highest maximum value, and thereby identifies subject information which has been associated with the identified model image data.

The invention discloses a multi-round automatic chat and conversation method and system based on deep learning. The method comprises the following steps that: on the basis of the current input processing result of a user, using a deep learning model to mine the current input intention of the user; according to the current input intention of the user, the chat theme of a previous round of conversation and the current input processing result of the user, using the deep learning model to judge whether the current input intention of the user is consistent with the chat theme of the previous round of conversation, updating entity information according to a judgment result, then, obtaining response contents according to the current input intention of the user from a preset response database, and sending the response contents to the user. The method has the beneficial effects that the contents and the context scene information of the current round of conversation and the previous round of conversation can be simultaneously considered when a chatting robot carries out continuous multi-round conversations with the user, more accurate contents can be responded to the user, and answering quality is improved.

Frequency of judgment of welding of relays is increased to increase likelihood of early detection of welding. It is determined that a battery 22 is not being recharged or discharged when a vehicle speed V of an electric vehicle is approximately 0 and a brake pedal 54 is pressed, and a switching element of an inverter 24 is controlled to be switched to discharge electric charges which are stored in a capacitor 44. After discharging, relays 30, 32 are turned off, and voltages RV1, RV2 between the terminals of the relays 30, 32 are detected by voltmeters 40, 42 to judge whether either of the voltages RV1, RV2 has a threshold value RVref (approximate value 0) or less. When it is so determined, it is judged that the relays 30, 32 are welded, and an LED 70 is illuminated.

A vehicle surroundings monitoring apparatus recognizes a pedestrian from existence of a leg, in the case in which a width in real space of a binarized object is suitable as a pedestrian's leg, the binarized object has longwise shape, the lower end position of the binarized object exists in the lower part (lower half) of a gray scale object region, and a serial luminance transition exists in the binarized object. The vehicle surroundings monitoring apparatus also recognizes a pedestrian from existence of an umbrella held up by the pedestrian, in the case in which an umbrella region with a low temperature exists above the binarized object, the width of the umbrella region is suitable as a pedestrian's umbrella, and, the spatial correlation between the centroid position of the umbrella region and the centroid position of the binarized object is suitable as a spatial relationship between a pedestrian and his/her umbrella.

A collision avoidance ECU estimates a traveling locus based on an estimated curve radius of an own vehicle in a basic traveling locus estimating unit, and in a changed traveling locus estimating unit, obtains separation distances between an own vehicle and white lines based on the relative positional relationship between an own vehicle and the white lines, and estimates, as a changed traveling locus, a route along the white lines with the obtained separation distances maintained. In a collision judging unit, when auto-steering control and departure warning control are not performed, collision judgment is performed based on the basic traveling locus estimated in the basic traveling locus estimating unit, and when the auto-steering control and departure warning control are performed, the traveling locus is changed to the changed traveling locus estimated in the changed traveling locus estimating unit and collision judgment is performed.

The invention relates to a online testing process for shorted fault of asynchronous motor's stator winding, which is belong to Detecting Technology. It was designed to solve the detecting problem of stator winding. The project is that it figures out the voltage and current of negative sequence and positive sequence of the stator winding by collecting three-phase stator voltage, instantaneous-current signal. Then using of normal motor sample reference document estimated the filter value of the stator negative sequence, figured out the stator negative sequence current fault component. And then base on the threshold of the stator negative sequence current fault component educe failure exponent. Finally according to the index judge whether to exist short circuit failure or not. This invention also gave corresponding detection device. Not only can high sensitivity, high reliability and on-line measurement asynchronous motor stator windings at the beginning of the early short circuit fault, but also can judge short circuit phase. This can effectively ensure the asynchronous motor operating safely.

The invention discloses a vehicle information detecting and recognizing system under the multilane condition. The vehicle information detecting and recognizing system comprises a computer system and a portal frame stretching over lanes, wherein a laser scanner and a high-definition license plate recognition device are arranged on the portal frame, a first dot matrix type wheel shaft sensor, a shaft weight sensor and a second dot matrix type wheel shaft sensor are sequentially arranged on the lane under the portal frame, and the laser scanner, the high-definition license plate recognition device, the first dot matrix type wheel shaft sensor, the shaft weight sensor and the second dot matrix type wheel shaft sensor are respectively connected with the computer system. The vehicle information detecting and recognizing system has the advantages that the two-dimension cross section size and the running position of a vehicle are detected through the laser scanner, and the vehicle three-dimension reconstitution and the vehicle separation are realized; the license plate information and the human face information are precisely collected through the license plate recognition device; the vehicle information such as the shaft distance, the shaft length, the shaft number, the shaft type, the wheel distance, the wheel width and the wheel number are measured according to signals output after a vehicle tyre presses the wheel shaft sensor; and the shaft weight and the total weight are measured through the shaft weight sensor.

The related network abnormal detection method based Bayes statistical model comprises: 1. grasping TCP/IP flow data package by bypass interception way; 2. decomposing attributes to form a data matrix; 3. mining data to build normal training matrix, known-abnormal training matrix, and unknown-abnormal training matrix; 4. continual grasping the TCP/IP package to detect them with Bayes evaluator; and 5. alarming the abnormal condition and filling into the known-abnormal training matrix by self-learning way; or else, back to step 4. This invention overcomes defects in prior art.

The present invention provides a method capable of detecting single or multiple fetal chromosomal aneuploidies in a maternal sample comprising fetal and maternal nucleic acids, and verifying that the correct determination has been made. The method is applicable to determining copy number variations (CNV) of any sequence of interest in samples comprising mixtures of genomic nucleic acids derived from two different genomes, and which are known or are suspected to differ in the amount of one or more sequence of interest. The method is applicable at least to the practice of noninvasive prenatal diagnostics, and to the diagnosis and monitoring of conditions associated with a difference in sequence representation in healthy versus diseased individuals.

The invention discloses a wavelet transformation and deep learning-based rolling bearing weak fault diagnosis method. The method comprises the following steps: a rolling bearing vibration signal is obtained, and the acquired vibration signal is subjected to continuous wavelet transformation to obtain a time-frequency diagram; autocorrelation operation is performed on wavelet coefficients corresponding to each frequency on the time-frequency diagram to filter out noise interference and extract periodic fault components; the Hilbert transformation is used to perform envelope demodulation to obtain a fault characteristic frequency; a processed time-frequency diagram is input as a feature diagram, and categories of early faults are determined by training a deep learning classification model. Theoretical and experimental results show that fault categories can be determined accurately at an early stage when weak fault of a rolling bearing occur based on an improved wavelet time-frequency diagram used as the classification model for input training, right determination results can be given when the method is applied to different bearings, high training speed can be realized, and high actual application value can be achieved.

An analyzer (A) includes a current measurer (42) for measuring the current flowing between paired electrodes (22a), (22b) when a sample is introduced to the reagent layer (23) of a sensor (2) and voltage is applied across the electrodes, while also including a processor (3) for analyzing the sample based on the current after a predetermined reference time point. The analyzer (A) further includes a fail determiner (44) which monitors the change of the current before and after the reference time point and determines that the sensor (2) is improper when the current change does not correspond to a predetermined current change.