10669results about How to "The test result is accurate" patented technology

The invention provides a test system and a test method. The testing system comprises a test fixture, a test device and a differential tunable matching network, wherein the test fixture is provided with a bearing structure for loading a chip to be tested and a test port electrically connected to the chip to be tested; the test device comprises a radio frequency signal source, a receiving unit and a processing and display unit; the radio frequency signal source is provided with at least one radio frequency test port; the receiving unit is used for at least receiving a reflected signal and a transmitted signal which are generated after a radio frequency signal passes through the chip to be tested; the processing and display unit is used for processing the received radio frequency signal and displaying the processed signal; and the differential tunable matching network is provided with an input port and a differential output port and is used for tuning the impedance of a load end including the chip to be tested to make the impedance of the load end matched with the internal resistance of the test device and providing the test device to measure the characteristic of the chip to be detected in the test fixture. Compared with the prior art, the invention has the advantages that: the differential tunable matching network is provided for realizing impedance matching, the test system and the test method are easy and convenient to operate, and a more accurate test result can be acquired.

A sampling hub directs a medical device towards a target area. The hub may have some of: a hub body; a lumen passing between openings at the front end and the rear end, the lumen allowing for passage of an elongate element through the entire lumen; the bottom of the hub body may be flat; the top of hub body preferably is sloped downwardly; the lumen is preferably sloped downwardly to enable guidance of the elongate body towards the target area; and an area surrounding the opening of the lumen at the rear end configured to receive a support for the elongate element, the support for the elongate element having a diameter in the support larger than a diameter of the elongate element.

The invention discloses an automatic assembly production line of buzzers, which comprises a feeding mechanism, a glue coating mechanism, a buzzer piece placing mechanism, a straight contact pin placing mechanism, a first thermoplastic pipe placing mechanism, an inclined contact pin placing mechanism, a second thermoplastic pipe placing mechanism, a thermoplastic pipe heat sealing mechanism, a contact pin welding mechanism, a dispensing mechanism, a curing mechanism and a detecting and sorting mechanism, which are sequentially arranged on a work table; the glue coating mechanism comprises an automatic shell locating mechanism located behind a glue applicator, and the automatic shell locating mechanism comprises a motor, a rotating jig, an optical fiber sensor, a motor base, a supporting plate and a sensor bracket; the optical fiber sensor is a reflective optical fiber sensor and is arranged to be aligned to the shell; and the optical fiber sensor is installed on the upper part of the sensor bracket, and the lower part of the optical fiber sensor is fixed to the side plate of the supporting plate. The automatic assembly production line disclosed by the invention has the advantages of smart design and simple structure, realizes high level automation, replaces the manual operation, reduces the cost of manpower and physical resources and improves the production efficiency of the assembly line.

The disclosed detector comprises: a driver, a magnetic-leakage probe, a magnetic-leakage signal process device with a rotary coder, a power, an ultrasonic probe, and a ultrasonic signal processor with a roller carried a milometer all connected by gimbals in turn. This invention integrates both magnetic-leakage and ultrasound, realizes precise positioning to defect in pipeline, and can detect the defect and hidden danger all round.

The invention discloses a CNN-deep-learning-based bridge-crack detecting and positioning method, comprising: first, using the window sliding algorithm to cut a bridge image into smaller bridge crack surface element images and bridge crack background element images; and at the same time, based on the CNN-based DBCC classification model, identifying the bridge crack background element images and the bridge crack surface element images; then, in combination with the window sliding algorithm, performing bridge crack detecting and positioning on the entire bridge crack image; and finally, speeding up the algorithm through the search strategy of combining the image pyramid and ROI. Compared with the traditional crack detecting and positioning method, not only the bridge crack detecting and positioning method of the invention achieves a better detection effect and a stronger generalization ability, but also the method is performed directly based on color images, an impossible situation for the traditional crack detecting and positioning method.

The invention discloses a vehicle anti-collision early warning system and method based on vehicle-road cooperation. The early warning system comprises a vehicle device, a roadside device, a control module, a communication module and a roadside prompting device; the vehicle device and the roadside device are subjected to data exchange through the communication module, the various collected data are converged to the control module through the established data channel to perform collision risk assessment, and early warning information or control instructions formed after risk assessment information are issued to a vehicle terminal or the roadside prompting device to prompt the vehicle to take corresponding measures to avoid vehicle collision. According to the invention, the accurate collision risk value of the vehicle can be obtained by means of a vehicle-road cooperation technology and a collision early warning model, the vehicle device can remind the vehicle to take corresponding anti-collision measures through voice and images after receiving early warning information, and the roadside prompting device performs collision risk prompting through lamplight or display device.

The present invention relates to the automatic test method and the system of mobile phone software. The method mainly includes five steps; firstly, the keystroke operation of a mobile phone is simulated by a program-controlled switching switch; secondly, communication between a base station and the mobile phone is simulated by a comprehensive mobile phone tester; thirdly, the images of the display screen of the mobile phone are real-timely collected by a camera; fourthly, according to a test task, an industrial control computer controls the unified operation of the program-controlled switching switch and the comprehensive mobile phone tester, collects information coming from the serial port of the mobile phone and the camera-collected real-time images of the display screen of the mobile phone and compares the collected real-time images with corresponding preset template images; fifthly, according to the information coming from the serial port of the mobile phone and the comparison result of the images, the industrial control computer judges the operation state of the mobile phone software. The present invention can accurately simulate the process in which a person operates a mobile phone, so the test result is more accurate. Moreover, the present invention can increase the test efficiency and ensure the comprehensive traversal of test cases.

The invention provides a test paper reading method and a test paper reading device, which can read dry chemical test paper strips, colloidal gold immunochromatograohic assay test paper strips/cards and rapid pesticide residue test cards, are easy to operate, need no extra detection instrument and equipment, can automatically judge and read the detection result by only acquiring corresponding developing pictures through electronic equipment such as computers or mobile phones, have reliable testing accuracy and are particularly suitable for personal and household wide application. The method comprises the following steps: A. acquiring images; B. processing the acquired images; C. performing negative and positive discrimination; and D. performing concentration conversion on a sample which is discriminated to be positive in the step C through a concentration-gray scale relation to obtain a concentration value of the to-be-tested paper card/strip. The device comprises a shell and a built-in standard gray scale strip, wherein the shell is provided with a standard gray scale strip display window and is also provided with a first card slot, a second card slot and a third card slot for arranging the colloidal gold card, the rapid pesticide residue test card and the dry chemical test paper respectively.

The invention provides a multi-direction ship target detection and identification method in a high-resolution remote sensing image. The method is characterized by designing and realizing a multi-direction ship target detection and identification network structure under a complex scene and in a large-scale environment; automatically exploring shallow-layer and deep-layer multidimensional features and the like of a ship target based on a convolutional neural network; and realizing quick and accurate detection and recognition of multi-directional, and different scales and kinds of ship targets inthe high-resolution remote sensing image under a small sample environment. Compared with a conventional target detection method, the method is faster in detection speed and more accurate in detectionresult.

The invention discloses a printing image defect detection method, which comprises the following steps: carrying out real-time image model learning in a gray scale region and a gradient region by aiming at specific images on a large image; comparing the large image to be detected to the a gray scale region model and a gradient region model established during learning; realizing small-dimension strong-contrast defect detection through Blob cluster analysis; when no small-dimension strong-contrast defect is detected, dividing the large image into sub regions, and respectively calculating image integrated features; adopting a variable threshold method for carrying out threshold division on each sub region; carrying out Blob cluster analysis on divided images; and realizing the large-area weak-contrast defect detection. Compared with the prior art, the invention does not rely on a reference template, is not sensitive on the real-time imaging brightness change, can overcome the defects of missing detection, error detection and poor self adaptation of the template by using a reference template comparison detection method, and can simultaneously solve the problems of eliminating tiny wrinkles and blackspots in printing and papermaking industries.

The invention provides an intrusion detection system (IDS) and a method based on IPv6 network environment. The system comprises a protocol set and rule base module, a data packet capture module, an IPV6 protocol analysis module, a protocol analysis and state tracking module, a rule analysis and packet detection module and a warning and logging module. The invention well solves the new problem of transplant of the IDS, brought about by the new IPv6 standards and characteristics, and improves the capture ability of the data packet, the detection means of the IDS and the safety detection abilityof the IDS.

The invention relates to the technical field of biology, and specifically provides a detection kit for a detection kit for antigens of a novel coronavirus (SARS-CoV-2). According to the detection kitprovided by the invention, the antigens of the SARS-CoV-2 are detected by virtue of a colloidal gold double antibody sandwich method, and two monoclonal antibodies and colloidal gold are mixed for labeling, so that a detection result of the antigens of the SARS-CoV-2 is accurate and high in sensitivity, and meanwhile, the detection rate can be remarkably increased. According to the detection kit,a blank in immunological detection of the SARS-CoV-2 is filled up, and field detection can be realized without a detection instrument, so that the time and the labor are saved, and operation is flexible.

The invention discloses a frequency spectrum cognitive method, cognitive radio user equipment and the structure of a central node in a cognitive radio system. In the frequency spectrum cognitive method, at least one cognitive radio user in the cognitive radio system detects signals of a main user in a selected channel, and sends the detection result to the central node of the cognitive radio system, wherein the detection result is the parameter correlative with the average signal-to-noise ratio of the channel; and the central node combines the detection results from all the cognitive radio users detecting the same channel, makes the conclusive judgment according to the result of the combination to obtain the judgment result on whether the channel is occupied by the main user in a main usersystem, and can further return the result to all the cognitive radio users. Besides, the invention also discloses a method and a device for energy detection.

The invention discloses a deep learning saliency detection method based on the global a priori and local context. The method includes the steps of firstly, performing superpixel segmentation for a color image and a depth image, obtaining a global a priori feature map of each superpixel based on middle-level features such as compactness, uniqueness and background of each superpixel, and further obtaining a global a priori saliency map through a deep learning model; then, combining the global a priori saliency map and the local context information in the color image and the depth image, and obtaining an initial saliency map through the deep learning model; and finally, optimizing the initial saliency map based on spatial consistency and appearance similarity to obtain a final saliency map. The method of the invention can be used for solving the problem that a traditional saliency detection method cannot effectively detect a salient object in a complex background image and also for solving the problem that a conventional saliency detection method based on deep learning leads to false detection due to the presence of noise in the extracted high-level features.

The invention discloses a machine vision-based glass surface detect detection apparatus and method. The detection apparatus comprises a detection table and a detection system, the detection table comprises a workbench used for clamping glass to be detected, a pillar supported on the workbench, an installing plate above the pillar, and a movement mechanism and a CCD camera which are arranged on the workbench; the detection system comprises an image acquisition module, a movement control module and a host computer; the image acquisition module comprises an image acquisition card and the CDD camera; and the movement control module comprises a movement control card. The above machine vision-based detection scheme carries out vision detection analysis on the defect area of the surface of glass in order to realize high-precision quality detection, so high requirements of the surface detection precision in the glass production are well met.

The invention discloses an automatic extractor hood speed regulating control method based on image analysis and an automatic extractor hood speed regulating control system based on mage analysis. The control method specifically comprises the following steps: (1), by virtue of an image acquisition unit, collecting an oil fume image of the upper part of a gas stove at a fixed frequency f; (2), by virtue of an image processing unit, extracting edge information by taking frame difference image of the collected oil fume image and an oil fume-free background image as a signal source; (3), by virtue of a main controller, performing quantitative analysis by taking the edge information transmitted by the image processing unit as an image feature value, thereby obtaining a frequency signal required by a frequency conversion fan; and (4), by virtue of the frequency conversion fan, regulating the rotation speed according to the received frequency signal sent by the main controller. By virtue of an image analysis means, the concentration of oil fume generated by the gas stove is detected in real time, the rotation speed of the fan is regulated and closed-loop automatic control is realized.

A remote sensing image target detection method based on a deep neural network is provided. The method comprises: obtaining a training sample and carrying out a scaling preprocessing operation on the training sample; carrying out multiple types of labeling operations on a training sample image containing a remote sensing target and a remote sensing background in the preprocessed training sample; based on the maximum number of iterations, carrying out pre-training and fine-tuning operations on a selected deep convolutional neural network model to obtain a fine-tuned deep convolutional neural network model; processing a full-connected layer of the fine-tuned deep convolutional neural network model to obtain a fine-tuned deep full convolutional network model; and detecting the remote-sensing image target based on the fine-tuned deep convolutional neural network model and the fine-tuned deep full convolutional network model. The method has the advantages of a high detection speed and high detection accuracy, and can be widely used in the fields such as target detection, target tracking, intelligent navigation, urban planning and the like.

The invention provides a storage battery residual capacity and health state rapid detection method and device. The method comprises the following steps of: enabling a storage battery to carry out instant larger current discharging through a controllable discharge circuit, monitoring the discharging current in the discharging circuit in the process by a current sampling circuit, synchronously monitoring the end voltage of the storage battery through a voltage sampling circuit, and utilizing a direct current discharge method to measure the internal resistance of the storage battery, wherein the discharge circuit and the voltage sampling circuit are connected in parallel with two wiring columns of the storage battery, so that the internal resistance of the storage battery is measured according to a Kelvin four-wire system measuring method, and the maximum discharge current, the load voltage and the internal resistance data of the storage battery are obtained; and according to an associated relation model, calculating SOC and SOH of the storage battery. By adopting the method provided by the invention, the residual capacity and the health state of the storage battery can be accurately detected on line.

Development tools and a methodology for efficient development of distributed web services. A tool tracks changes in packages used to create images deployed for testing. Rather than build a complete image for each change, a current image may be created by substituting changed packages in a previously created image. Another tool allocates components of an image to a number of servers specified by a user of the tool. Such a tool simplifies integration testing of the web service by allowing a developer to initially test a web service on a single server or a small number of servers and then easily scale-up the test environment. The servers may be physical servers or may be virtual servers. Interface rules for packages that constitute the software for the web service are defined to reduce the likelihood of integration problems as the environment is scaled up.

An automated sorting system provides the ability to receive specimens for any number of diagnostic test procedures and to selectively transfer specimens to designated ones of a plurality of specimen processors based upon criteria of the laboratory facility such as the particular laboratory to perform the requisite diagnostic test, timing aspects like a lab's hours of operation or delivery schedule, type of specimen (e.g. tissue, blood, serum, and the like) or other factor that may affect specimen throughput efficiency. Automated accessioning comprises the determination of physical attributes of specimens using a specimen processor while reading data provided with a specimen as it is provided to the specimen processor (such data provided by the carrier and/or the vial by codes, ID tags, and the like), recording the determined information in a database of a control system, and comparing the determined information with information from a client diagnostic test order from a same or different database for connecting the specimen and an associated electronic record. Preferably also, the accessioning includes a labeling of the specimen after the connection with an electronic record for associating the specimen and record through the specimen diagnostic test procedure and reporting back to the client.