252results about How to "Reduce detection efficiency" patented technology

The invention provides a large-aperture ultra-smooth surface defect detection device and method. The device mainly comprises a laser device, a laser beam expanding system, a high-reflectivity mirror, a polarizer, a polarization splitting prism, a 1/4 wave plate, a rotary prism, a telecentric field lens, a high-angle-scattering light detector, a low-angle-scattering light detector, a line triggering detector, a reflection light detector, a precise display platform and a computer. Detection efficiency of a large-aperture optical element can be remarkably improved, and the situation that detection results are severely influenced by vibration, axial jumping and the like, caused by high-speed rotation, of the large-aperture optical element is avoided. Surface defects can be classified, and it can be recognized whether the detected defects are pits, scratches, protruding dust, fibers and the like.

There are provided an X-ray detector which can realize a larger area without lowering resolution and reducing X-ray detective efficiency when obtaining a matrix construction having a large number of X-ray detecting elements by tiling and a system using the same. An X-ray detector 104 has a construction in which a plurality of photo-electric modules 111 having a plurality of X-ray detecting elements 110 located in a two-dimensional manner are pasted onto a distribution module 113. The X-ray detecting element 110 has scintillators 112, transparent means 121 and photo-electric means 114. These are optically connected to each other. On the edge of the transparent means 121 on one of the photo-electric modules 111 mounted on the distribution module to be adjacent to each other is formed a cutaway part 120 so that the area of an output surface 211 outputting a light to the photo-electric means 114 is smaller than that of an incident surface 210 upon which a light is incident from the scintillators 112. A space caused by the cutaway part 120 is located wiring between the photo-electric module 111 and the distribution module 113 or wiring between the photo-electric modules 111 adjacent to each other.

The present application discloses a method for detection of insertion deletion mutation based on second generation sequencing, a device and a storage medium. The method comprises the following steps:comparing a sample to be tested with a file of a reference genome to extract a set of candidate mutation sites with mutation allele frequency being greater than or equal to a threshold; filtering to remove sites in a short tandem repeat region; making detail statistics of comparison information of the mutation sites and comparison information surrounding the mutation sites, wherein the comparisoninformation includes InDel site and reference base support number, comparison quality, coverage depth, surrounding non-reference base and other insertion deletion mutations, surrounding read quality;and filtering to remove sites that do not reach the set threshold according to statistical information to obtain mutation results. The method does not require partial assembly, and filters second-generation sequencing data in advance to quickly eliminate most of false positive results caused by the comparison, reduces detection running time and computing resources, improves detection efficiency, has strong sensitivity and specificity, and can quickly and accurately detect InDel mutations.

An object of the invention is to realize a method and an apparatus for processing and observing a minute sample which can observe a section of a wafer in horizontal to vertical directions with high resolution, high accuracy and high throughput without splitting any wafer which is a sample. In an apparatus of the invention, there are included a focused ion beam optical system and an electron optical system in one vacuum container, and a minute sample containing a desired area of the sample is separated by forming processing with a charged particle beam, and there are included a manipulator for extracting the separated minute sample, and a manipulator controller for driving the manipulator independently of a wafer sample stage.

The invention relates to a SAR image iron tower target detection method based on deep learning. The method comprises the following steps of randomly extracting a plurality of SAR images from a SAR data set, segmenting and obtaining sample slices, setting sample labels for each sample slice and constructing a training sample set; processing each sample slice in the training sample set to generate aplurality of different artificial sample slices, and adding the training sample set after labeling the sample slices to expand the training sample set; constructing an SSD model; inputting the expanded training sample set into the constructed SSD model, and using the gradient descent method to train the SSD model; cutting the data to be measured into a plurality of slices which are the same sizeas the sample slices, and inputting the trained SSD model to obtain the target detection results of the data to be measured. The method of the invention has the advantages of strong robustness, fast running speed, high detection performance and easy migration, and can be used for detection under complex scenes without high contrast between the target and the background.

The invention discloses a digital imaging acquisition system for aggregate grading detection. The system consists of an aggregate sampling device, an image acquiring device, an optical processing optimizer and communication and storage equipment, wherein the aggregate sampling device comprises a material dividing plate, a distance adjusting rod and an angle adjusting rod; the image acquiring device comprises an infrared laser, a linear array camera and an image acquiring card; the optical processing optimizer comprises a filter device and a diffuse coating layer; and the communication and storage equipment comprises a data line and a computer. A digital imaging acquisition method for aggregate grading detection comprises the following steps of: setting the aggregate sampling device; setting the image acquiring device; setting the communication and storage equipment; acquiring an image of a sampled aggregate; and transmitting and storing the image. An aggregate stream is sampled and acquired by arranging the material dividing plate, so the problem that the image of a falling stream of the aggregate must be completely acquired is solved and the defects of poor quality of the acquired image, difficult separation of particles and a large amount of processing data are overcome.

The fast detection method and instrument for microbe content in food has two parallel sample detecting systems adopted, including one for food sample detection and the other for detecting contrast. These two systems are in the same environment conditions and heated with the same heating element, the CO2 these two systems generate is detected separately in two identical CO2 detecting devices, and the detected data are analyzed and processed to obtain the detection result. The present invention has short detection period, simple structure, low cost and other advantages, and is suitable for fast site detection.

An ion detector for detecting positive ions and negative ions, includes a housing provided with an ion entrance to make the positive ions and the negative ions enter, a conversion dynode which is disposed in the housing and to which a negative potential is applied, a scintillator which is disposed in the housing and has an electron incident surface which is opposed to the conversion dynode and into which secondary electrons emitted from the conversion dynode are made incident, a conductive layer which is formed on the electron incident surface and to which a positive potential is applied, and a photodetector which detects light emitted by the scintillator in response to incidence of the secondary electrons.

The invention discloses a urinalysis device for an intelligent toilet. A fixing assembly comprises a mounting bottom plate, a sliding plate and a mounting top plate, wherein the mounting bottom plateis fixedly connected with the toilet, and the sliding plate is mounted on the mounting bottom plate; one end of the sliding plate faces a toilet bowl; the mounting top plate is mounted above the sliding plate, and a void space for mounting a telescopic mechanism is reserved between the sliding plate and the mounting top plate; a paper feeding mechanism is mounted on the mounting top plate; a testpaper slot is glidingly formed in the sliding plate; a detection mechanism is mounted on the mounting top plate; a paper discharging mechanism comprises a flushing pipe and a flushing device; a dryingmechanism comprises an air guide pipe and an air blowing device, one end of the air guide pipe is communicated with the test paper slot, and the other end of the air guide pipe is communicated with the air blowing device. The problems of user discomfort and poor user experience which are easily caused by the fact that a urinalysis device for a toilet in the prior art is complex in structure and larger in size and occupies more space, urine pollution is easily produced to affect detection results and detection efficiency is low as a result of manual replacement of the urine detection test paper are solved.

The invention relates to a truck side guard rail mounting size measurement system and a method based on a machine vision technology, so as to solve problems that as the truck guard rail is detected manually in the prior art, random errors such as a reading error and an environment error exist, the measurement result is influenced, and the measurement efficiency is low. The system comprises a ranging module, a graph acquisition module and a graph processing module, wherein the graph acquisition module comprises a camera unit, the ranging module is connected with the camera unit, the graph processing module comprises an image information processing unit, and the camera unit is connected with the image information processing unit. The system acquires two-dimensional image information of the side surface of the truck via the image acquisition module, the image is analyzed and processed via the image processing module, and mounting size information of the truck side guard rail is obtained. The system and the method of the invention have the advantages that a truck side guard device does not need to be touched, the mounting size of the truck side guard device can be quickly and effectively measured, and the detection efficiency is higher.

The invention provides a rice flooding-tolerant gene Sub1 co-dominant molecular marker and application. The molecular marker comprises an SNP marker and an InDel marker which are separately located onrice No. 9 chromosome genes Sub1A and Sub1C, wherein the polymorphic site of the SNP marker on the gene Sub1A is G/C; and the polymorphic site of the InDel marker on the gene Sub1C is 5'-GCCGTCG-3'/5'-CA-3'. For the molecular marker, specific amplification primers are designed, and Sub1 genotype detection is carried out through PCR amplification. The provided molecular marker and an amplificationprimer thereof for Sub1 can be used for identifying the genotype of rice Sub1, a flooding-tolerant rice resource is bred, the rice flooding-tolerant gene Sub1 co-dominant molecular marker has the advantages of high identification accuracy, simplicity in operation, low cost and the like, the breeding period of the flooding-tolerant rice can be shortened, and the breeding cost is reduced.

The invention relates to a general module system for on-site detection of an air-conditioner refrigeration system, belonging to the technical field of detection technology. The system comprises a general test host, a temperature test submodule, a pressure test submodule, a flow test submodule and an electric quantity test submodule as well as a signal transmitting detecting module and upper computer software which are specially used for detecting other relative parameters. The invention is suitable for performance detection, fault diagnosis, and scientific research of an air-conditioner refrigeration system on the spot in industry application. During the on-site test process, different special detection module systems can be chosen to form a suitable test system according to the test requirement. The invention can flexibly build the test system aiming at different application locale, thereby having convenient use, effectively reducing the test cost, enhancing the commonality of the test system and greatly enhancing the expandability and the secondary development performance of the test system.

The invention discloses a packet-level dynamic mail attachment virus detection method and relates to website security technical field. The method includes that: the received packet is judged if containing attachment information; the encoding mode of the attachment information is checked; the packet is judged if the packet is the end part of the mail; the packet is processed according to the relationship of decoded attachment information length and the preset threshold. The packet-level dynamic mail attachment virus detection method can improve the internal memory utilization rate and the virus detection efficiency.

The invention provides a static railway track assembly overall dimension and damage optical detection system which comprises linear hard light sources, annular hard light sources, high-speed cameras for optical detection, an image processing card, a computer, data and power source cables, walking type machine frameworks and mileage sensors installed on wheels of the walking type machine frameworks. A track assembly comprises steel rails, steel rail fastener combinations, sleepers, sleeper plates and railway ballasts. Each high-speed camera for optical detection and the corresponding linear hard light source which are installed on the corresponding walking type machine framework and located on the same side of the same corresponding steel rail and are higher than the rail surface form a steel rail and steel rail fastener combination contour section dimension optical detecting set. By means of the technology, the functions of detecting the steel rail overall dimension, the steel rail top face corrugated abrasion and rail bottom slopes and the functions of detecting steel rail fastener gland nut loosening, failures and missing are achieved.

The invention relates to detection equipment for intelligent manufacturing. Through the detection equipment, the problems that existing equipment is low in detection precision and influences product quality, the detection efficiency of bottle cap airtightness is low, and operation is tedious are effectively solved. According to the technical scheme, an airtight rotating trough is fixed above a supporting plate, an airtight lifting shaft is rotationally connected into the airtight rotating trough, a space lifting cylindrical cam is arranged on the airtight lifting shaft in a coaxial rotation mode, airtight detection rods are rotationally arranged on the space lifting cylindrical cam, a lifting guide rod is arranged in a sliding groove of the space lifting cylindrical cam, a claw-type feeding disc is arranged below the space lifting cylindrical cam and is coaxially arranged on the airtight lifting shaft in a sleeving mode, and the space lifting cylindrical cam is connected with the claw-type feeding disc through a spring; According to the detection equipment, unqualified products can be screened and gathered respectively, subsequent recovery is facilitated, all bottle caps on an assembly line can be detected and screened, the detection efficiency is high, and the detection equipment has high practicability and universality.

The invention discloses an infrared thermal image nondestructive testing method based on a convolutional neural network, and belongs to the field of image recognition. The problem that nondestructivetesting of an existing convolutional neural network cannot be applied to infrared imaging is solved. An infrared thermal image nondestructive testing method based on a convolutional neural network comprises the following steps: arranging an infrared image data acquisition scene, and acquiring an infrared image with defects of a to-be-tested object; performing enhancement and noise reduction processing on the acquired defective infrared image of the to-be-detected object to complete a preprocessing process; carrying out data set augmentation and construction by utilizing the preprocessed defective infrared image of the to-be-detected object; fusing the models of the VGG16 network and the DenseNet169 network, and training, testing and identifying the fused model by using the data set; and identifying and detecting defects in the defective infrared image of the to-be-detected object by using the fused network model. The identification precision of the detection method provided by the invention reaches 98.5%.

The invention discloses a measurement method for a permanganate index. The method comprises the following steps: (1) adding a to-be-measured water sample into a colorimetric tube provided with a plug, adding (1+10) sulfuric acid for acidification, adding a potassium permanganate solution, and shaking uniformly; (2) digesting the water sample in the step (1) under a certain condition and quickly cooling to a room temperature; (3) adding an excessive ammonium ferrous sulfate solution into a digestion solution in the step (2), and shaking uniformly; (4) adding a proper amount of a sulfosalicylic acid aqueous solution into a reaction solution in the step (3) for producing a color development reaction; (5) performing absorbance testing on the water sample in the step (4) by taking de-ionized water as a reference at the wavelength of 510 nm, and calculating the permanganate index of the water sample by a formula IMn=-8.5*(A-A0), wherein in the formula, IMn is the permanganate index of the water sample, A is the absorbance of the water sample, and A0 is the absorbance of a blank solution. The measurement method is quick and accurate in detection, suitable for batch measurement and simple to operate, and can be widely applied to laboratory detection and outdoor emergency detection.

The invention relates to a method for calculating the contents of three effective components in a curcuma longa product through a relative correction factor, and belongs to the technical field of drug quality determination. The method comprises: (1) preparing a reference substance stock solution; (2) preparing a reference substance solution; (3) preparing a sample solution; (4) determining through high performance liquid chromatography; (5) determining the relative correction factor value; (6) calculating the curcumin content; and (7) calculating the demethoxycurcumin content and the bisdemethoxycurcumin content. According to the present invention, the relative correction factor is used to detect the contents of the three effective components in the curcuma longa product, such that the demethoxycurcumin reference substance preparation and the bisdemethoxycurcumin reference substance preparation in each experiment are eliminated, the detection cost is reduced, and the detection efficiency is improved; the relative correction factor f is verified under different detection equipment, different chromatographic columns, different detection wavelengths, different column temperatures, different flow rates and different flow relative ratios; and the method has characteristics of rapidness, efficiency, high precision, low cost and the like, and is the feasible and effective detection method.

The invention relates to an active mobile vehicle bottom dangerous goods detection device based on a deep learning algorithm. The system comprises an information acquisition device and an industrial personal computer. The information acquisition device is in wireless communication with the industrial personal computer. The information acquisition device comprises an industrial camera, a light supplementing lamp, a radiation sensor, a gas sensor and a wireless transmission module. The information acquisition device further comprises a mobile platform, the mobile platform comprises a motion controller, an infrared wireless module and a remote controller, and the mobile platform is controlled by the remote controller to traverse the vehicle bottom through a U-shaped route. The controller is connected with a remote controller through an infrared wireless module. An industrial camera is installed on the upper surface of a machine body of the mobile platform. Light supplementing lamps are symmetrically arranged on the machine body on the front side and the rear side of the industrial camera, and a deep learning algorithm is loaded in the industrial personal computer. The device is an active mobile detection device, that is, after parking, the mobile detection device is actively operated to enter the vehicle bottom for detection, dangerous target detection can be better achieved, andthe detection precision is high.

The invention discloses a time synchronism method in an Ethernet ring network, comprising the following steps that: a health detection message which is used for detecting the integrity of the ring network is transmitted on the Ethernet ring network; a time synchronism message which carries over synchronizing time information is transmitted on the Ethernet ring network, and the synchronizing time information can be then informed to various transmission nodes on the Ethernet ring network. Moreover, the invention also discloses another time synchronism method in the Ethernet ring network, an Ethernet ring network system and a main node in the Ethernet ring network. By adoption the technical proposal of the invention, time synchronism in the ring network can be realized without the necessity for utilization of the health detection message, thereby reduction of the CPU efficiency of the transmission nodes and reduction of the detection efficiency of the integrity of the ring network are avoided.

The invention relates to a circular orbit robot for nondestructive testing of a large workpiece. According to the technical scheme, for the large workpiece complex in appearance and large in testing workload, a circular orbit capable of moving up and down is arranged on the periphery of the workpiece, and the industrial robot walks on the orbit and can arrive at different positions; a portable nondestructive testing device is installed on a mechanical arm, each small part is tested in a movable mode, and the nondestructive testing of the large workpiece is completed; meanwhile, the device is connected with a control center, receives the position information transmitted by the control center and returns nondestructive testing results of the corresponding positions back. By means of the method, the limitation on the workpiece and the requirement for labor of a traditional nondestructive testing device are broken through, the nondestructive testing of the large workpiece can be achieved with low cost, and the circular orbit robot is especially suitable for the nondestructive testing of large workpieces many in batch, large in quantity and small in single batch quantity.