543results about How to "Distinctive features" patented technology

The invention provides a mobile robot path planning method with combination of a depth automatic encoder and a Q-learning algorithm. The method comprises a depth automatic encoder part, a BP neural network part and a reinforced learning part. The depth automatic encoder part mainly adopts the depth automatic encoder to process images of an environment in which a robot is positioned so that the characteristics of the image data are acquired, and a foundation is laid for subsequent environment cognition. The BP neural network part is mainly for realizing fitting of reward values and the image characteristic data so that combination of the depth automatic encoder and the reinforced learning can be realized. According to the Q-learning algorithm, knowledge is obtained in an action-evaluation environment via interactive learning with the environment, and an action scheme is improved to be suitable for the environment to achieve the desired purpose. The robot interacts with the environment to realize autonomous learning, and finally a feasible path from a start point to a terminal point can be found. System image processing capacity can be enhanced, and environment cognition can be realized via combination of the depth automatic encoder and the BP neural network.

A hubless caster assembly includes a caster body and at least one wheel, the wheel comprising a toroidal member having a bearing race, and a complementary bearing race supported by the caster body. Bearing elements in the races support the wheel in free rotation. The caster body may comprise a ring body having an axial opening, whereby the caster assembly has a large central aperture extending entirely therethrough. A centering ring may be secured in the axial opening with the complementary bearing race formed therein. A hub cap with visual treatment may be secured over the central aperture.

The invention relates to a single-end fault ranging method based on initial reversed-polarity directional traveling wave detection, which can effectively realize single-end traveling wave fault ranging and has high reliability and high accuracy. The method comprises the following steps: (1) when a traveling wave fault ranging device is started, testing the arriving time t1 of the line modular component of the initial traveling wave of a fault, and extracting traveling wave signals in the time interval [0, 2L / v], wherein L indicates the length of the line, and v indicates the wave speed of theline module component; (2) testing the initial reversed-polarity directional traveling wave in the time interval, calculating the difference of the arriving time of the line modular component of the initial reversed-polarity directional traveling wave and the arriving time of the line modular component of the initial traveling wave of the fault, determining whether the fault is a nearby fault or a remote fault with reference to Curve Chart 3, and accordingly determining the section with the fault point; (3) judging the properties of the second arriving wave head through the determined fault section; and (4) determining final ranging results through the initial traveling wave and the wave head of the second traveling wave of the fault.

The present ivnention relates to a high-strength ultrafine fibre imitation leather. It is made up by using sea-island ultrafine fibre base cloth through processes of impregnating with polyurethane, extracting treatment and after-finishing. The described base cloth is a double-layer or more than double-layer composite base cloth formed from sea-island composite fibre woven fabric and non-woven fabric which are combined together by means of needling process or cohesive process, then said invention makes the composite base cloth undergo the processes of impregnating with polyurethane, hardening, extracting 'sea' component in the solvent capable of removing 'sea' component from sea-island fibre to obtain semifinished product, widening forming, mellowing, dyeing, grinding or sticking film so as to obtain the invented product.

The invention discloses a method for detecting winding deformation faults of a power transformer. The method includes that different vibration characteristics of the transformer in a normal state and a fault state are combined according to running characteristics of the transformer, vibration signals are monitored by a vibration sensor mounted on the surface of the transformer, frequency spectrums of the vibration signals are analyzed, and the transformer is judged to have winding deformation faults if the ratio of 50Hz energy sum and 150Hz energy sum to (50+150Hz) energy sum to (100+200Hz) energy sum which are actually measured is obvious increased as compared with that of the transformer in the normal state and an actually measured 100Hz energy value is hardly changed or even reduced as compared with that of the transformer in the normal state. The invention further discloses a system for detecting the winding deformation faults of the power transformer. The method and the system have the advantages of obvious fault characteristics and good repeatability, and are universal for power transformers of the same type, engineering implementation is simple, and diagnosis is intuitive.

The invention discloses a brain tumor image automatic segmentation method based on a convolution neural network, which comprises the following steps: acquiring a multimodal MRI image of the brain tumor and carrying out image preprocessing to obtain an original image set; constructing the frame of brain tumor segmentation based on multimodal MRI images; the frame comprises a module 1 and a module 2. The module 1 comprises a parallel deep deconvolution neural network based on a 3d convolution neural network, a residual unit and a transposed convolution; the module 2 includes adding a hopping structure on the basis of the deep deconvolution neural network structure in the module 1; after several iterative training, the ideal weights are obtained and the segmentation images of brain tumors areoutput. Image segmentation results are tested and evaluated. The invention effectively solves the problem of low accuracy of brain tumor segmentation image segmentation. It can improve the recognition of tumors and make the image preprocessing more convenient. Using the loss function based on d coefficients in the segmentation module can effectively solve the problem of class imbalance.

A Chinese medicine in the form of particles for treating cervical spondylopathy, especially the nerve root type one, is prepared from 7 Chinese-medicinal materials including notoginseng, Chuan-xiong rhizome, white peony root, clematis root, etc. through pretreating, crushing, solvent extraction, purifying, concentrating, drying and granulating.

The invention discloses a lower-limb flat ground walking gait recognition method based on a GA-BP neural network. The method comprises the following steps: performing denoising smoothing and time domain feature parameters extraction to the acquired lower-limb continuous flat ground waking four-way surface electromyogram signals to obtain a feature value sample set; then optimizing the BP neural network with the GA to obtain a group of complete initial weight values and threshold values with the minimum BP neural network deviation; randomly dividing the extracted feature values into a training sample group and a test sample group, and using the training samples to train the GA optimized BP neural network; at last, inputting the test sample in the trained BP neural network classifier to perform recognition and classification. By virtue of the lower-limb flat ground walking gait recognition method, the time domain features of the electromyogram signals are easy to extract and obvious and has good expression capability.

The invention provides a community discovery method. The community discovery method includes the steps that community division is conducted on a plurality of nodes in a network based on modularity maximization, and community boundary nodes obtained in the last step are adjusted based on community property entropy minimality. The community discovery method further includes the steps that if the community division obtained after adjustment meets an end condition, the community division will be used as final community division; otherwise, the communities obtained after adjustment will be used as nodes, community division will be conducted on the nodes again, and the community boundary nodes need to be readjusted. According to the community discovery method, the structure of the network and the attributive characters of the nodes are taken into account at the same time, and the degree of accuracy of community discovery is improved. In addition, the community discovery method is close to be linear in time complexity and suitable for large-scale on-line social network data.

The invention belongs to the communication technique area related to the method for automatic recognizing the general used digital signal modulation modes without need of prior knowledge. First, the noise is separated out through the A1 parameter. Then the CW signal is recognized. The signal is preprocessed so as to separate the analog signal or unknown signal with no constant envelope. The Cp in the normalized parameter of instantaneous frequency distinguishes the frequency-modulated signal and the phase-modulated signal. The frequency-modulated signal are sorted by the peak number Nf in the normalized parameter. The phase-modulated signals are sorted through the square spectrum and fourth power spectrum. The emulation of BPSK, QPSK, OQPSK, pi / 4QPSK, MAK, FSK, FM, CW indicates that the recognition rate reaches 95%.

The invention provides a method and device for extracting a text from an image. The method comprises the following steps: carrying out grey level nonlinear dynamic compression on an original image to obtain an enhanced image; extracting textural characteristics and edge characteristics of the enhanced image; constructing the textural characteristics and the edge characteristics into homogeneous characteristics, and mapping the enhanced image to a homogeneous space according to the homogeneous characteristics to obtain a characteristic image; extracting a text area from the characteristic image by a text area detector; and extracting and identifying characters from the text area of the enhanced image. According to the invention, the accuracy and robustness in text detection can be effectively improved.

A hubless caster assembly includes a caster body and at least one wheel, the wheel comprising a toroidal member having a bearing race, and a complementary bearing race supported by the caster body. Bearing elements in the races support the wheel in free rotation. The caster body may comprise a ring body having an axial opening, whereby the caster assembly has a large central aperture extending entirely therethrough. A centering ring may be secured in the axial opening with the complementary bearing race formed therein. A hub cap with visual treatment may be secured over the central aperture.

The invention discloses hotpot condiment and a preparation method. The method comprises the following steps: heating A grade rapeseed oil to 185-195 DEG C, adding dry red pepper powder, and stir-frying for 4 min at 175-185 DEG C; adding Pixian bean paste and fermented soya beans, and stir-frying for 3 min at 95-105 DEG C; adding ginger granules and garlic granules, and stir-frying for 4 min at 90-100 DEG C; adding pickled ginger and ciba pepper, and stir-frying for 2 min at 75-85 DEG C; adding compound spices and white granulated sugar, and stir-frying for 1 min at 80-90 DEG C; adding green pepper powder and red pepper powder, and stir-frying for 1.5 min at 75-85 DEG C; adding edible salt and monosodium glutamate, and stir-frying for 1 min at 80-90 DEG C; adding white spirit, millet wine, disodium 5'-ribonucleotide, yeast extract, edible essence, scallop powder, capsanthin and fermented glutinous rice, stir-frying for 1 min at 75-85 DEG C, and uniformly stirring the components. The hotpot is red in oil color, clear in soup color, spicy, fragrant, free of greasy feeling after eating for a long time and is led up to meaningful afterthoughts, thereby being well praised by consumers.

The invention discloses a satellite communication signal modulation identification method based on high-order cumulants and spectrum characteristics. The method includes the following steps of carrying out signal band-pass filtering, estimating carrier frequency, estimating the symbol rate, obtaining high-order cumulant parameters, identifying APSK or 16QAM signals, obtaining the number of spectral peaks of a quadratic spectrum, identifying BPSK or MSK signals, obtaining a quadruplicate spectrum, obtaining the number of spectral peaks of the quadruplicate spectrum, identifying pi / 4DQPSK signals, obtaining the number of spectral peaks of the quadratic spectrum of a base band, and identifying 6PSK, 8PSK, OQPSK, QPSK signals. According to the satellite communication signal modulation identification method, total blindness identification of a satellite communication signal modulation mode can be achieved, and the method is simple, easy to carry out and high in accuracy.

The present invention relates to an organic optoelectronic device and to a display device including same. The organic optoelectronic device includes a positive electrode, a negative electrode, and one or more organic thin film layers formed between the positive electrode and the negative electrode. The organic thin film layer has a light-emitting layer, a hole transport layer, a hole injection layer, an electron transport layer, an electron injection layer, or a combination thereof. Also, said organic thin film layer has a light-emitting layer and a plurality of hole transport layers. One of the plurality of hole transport layers adjacent to the light-emitting layer contains a compound which is represented by a combination of chemical formula 1, chemical formula 2 or chemical formula 3, and chemical formula 4. One of the hole transport layers not adjacent to the light-emitting layer contains a compound represented by chemical formula B-1.

The invention discloses a locating method and device of electronic equipment, the electronic equipment and an electronic locating system. The method comprises the steps: calculating out a prospected pose position of target electronic equipment at a second moment according to pose position information of the target electronic equipment at a first moment and state increment of target electronic equipment at the second moment relative to the first moment, wherein the first moment is ahead of the second moment; obtaining first detection data by detecting a beacon, wherein the first detection data carry relative position information of the beacon and the target electronic equipment; screening out the first detection data which can meet a first preset condition to obtain first target detection data; correcting a beacon map and the prospected pose position of the target electronic equipment at the second moment according to the first target detection data; utilizing the corrected pose position as the pose position of the target electronic equipment at the second moment. The method disclosed by the invention solves the technical problem that electronic equipment location accuracy is low in the prior art.

The invention discloses a filter and trunk edge based finger vein recognition method and system and overcomes instability of minimum feature points and improves redundancy of noise. The method includes performing pretreatment on an image and acquiring an image subjected to pretreatment; performing feature extraction on the image subjected to pretreatment and acquiring trunk edge feature points of the image subjected to pretreatment; comparing the trunk edge feature points of the image subjected to pretreatment with point set of a standard template, judging matching of two images as success if the matching result of the two point set is smaller than a preset threshold value and judging matching of the two images as failure if the matching result of the two point set is not smaller than a preset threshold value. According to the invention, through pretreatment, feature extraction and matching of the image in sequence, finger vein recognition accuracy can be improved effectively.

The invention discloses a lithium ion storage battery temperature combinational circuit model including an energy balancing circuit and a voltage responsive circuit. The energy balancing circuit predicts the continuous operation time and charged state SOC of a battery, and the voltage responsive circuit stimulates the transient response of the battery, and elements of the circuit are variables and change continuously according to the change of the environment temperature and SOC. The parameter identification method of the lithium ion storage battery temperature combinational circuit model includes four steps of charged state and battery open-circuit voltage relation identification, battery capability and temperature relation identification, self-discharge resistance identification, and internal resistance and polarized parameter identification. The lithium ion storage battery temperature combinational circuit model and the parameter identification method thereof make the stimulation approximate to the real response of the storage battery at different temperatures and give guidance to battery state estimation, and have the advantages of distinct characteristic, visual construction, clear physical meaning, convenient parameter identification, and easy application in engineering.

The invention discloses a current adaptive protecting method which belongs to the technical field of an electric power system. The current adaptive protecting method comprises the following steps: utilizing a fault network equivalence simplifying method and a fault steady state component theory to obtain a relation between a node voltage and a fault steady state injection current before failure happens; utilizing a network system parameter matrix to construct the linear mapping relation between the fault steady state injection current and a fault steady state branch current; and utilizing a fault steady state current of a related branch to form novel current adaptive protection. According to the invention, the network system parameter matrix is used for eliminating the effect of a distributed power supply on the fault steady state current of each branch, thereby avoiding a protective relaying false operation caused by the accessing of the distributed power supply. A setting algorithm is simpler and more practical. A main protection scope is 72.88%-72.94% of the full length of a circuit. A protection scope of spare protection which extends to a subordinate circuit is less than the protection scope of main protection; therefore the demand of protection matching is met.

The invention discloses a fluorescence excitation real-time imaging system and method. The system comprises an optical signal acquisition module, a light source module, a system support module, a synchronous triggering module and a computer module, wherein the optical signal acquisition module is used for acquiring optical signals in an imaging area; the light source module is used for providing light source irradiation for the image area; the system support module is used for supporting equipment used in the system; the synchronous triggering module is used for synchronously triggering a CCD (Charge Coupled Device) camera and an optical filter rotating disk; and the computer module is used for performing necessary parameter setting on the system and processing and displaying image data. According to the method and the system, optical fluorescent images and white light images of an object in an imaging visual field can be acquired continuously and dynamically, and fluorescent images and white light images are fused and displayed by using the computer module, so that the problem that a single CCD camera displays continuous and dynamic fused images of the fluorescent images and the white light images is solved effectively. The system is reasonable and practical in structure, can be widely applied to the research of optical molecular image experiments and the research and development of medicines, and has a wide development prospect.

The invention discloses a making method of convenience seasoning mix for boiled fish with Sichuan pickles and chili. Raw materials include: by weight, 2-3 parts of meat tenderizer, 3-4 parts of monosodium glutamate, 1-1.5 parts of pepper, 0.5-1 part of white granulated sugar, 3-5 parts of Chinese red pepper, 1-2 parts of salt, 10-20 parts of rapeseed soil, 0.1-0.15 part of potassium sorbate, 20-25 parts of chopped red chili, 200-300 parts of pickled vegetable, 3-4 parts of ginger, 1-2 parts of garlic, and 2-15 parts of upturned chili. The making method includes: setting a pot, adding rapeseed oil into the pot, heating the oil to 40% maturity, adding Chinese red pepper, ginger slices and garlic and frying until fragrance occurs, pouring and stir-frying the picked vegetable till the picked vegetable is seasoned, adding 200 parts of water, boiling the water, sequentially adding the meat tenderizer, the monosodium glutamate, the pepper, the white granulated sugar, the salt, the potassium sorbate, the chopped red chili and the upturned chili, and mixing these well and packaging into a small pack. The convenience seasoning mix for boiled fish with Sichuan pickles and chili is featured, has complete ingredients, is convenient to use and can be used by adding boiling water and fresh fish. The boiled fish with Sichuan pickles and chili made with the convenience seasoning mix is sour, spicy, delicious, appetizing and spleen-invigorating, the fish is tender, and the soup is sour with fragrance, delicious and agreeably spicy.

The invention relates to a power transformer load tap changer switching contact slap fault diagnosis method and device. The diagnosis method includes that: firstly, real-time monitoring is carried outon tap changer switching action process, in the monitored signal, the latter half of time domain signal major energy is selected, so as to avoid the energy maximum point in time domain signal; secondly, time-frequency transformation analysis is carried out; thirdly, spectral line of the signal, which is higher in amplitude at the range of 800-1000Hz in frequency domain, is determined through analysis; fourthly, comparing is carried out, if the spectral line is obviously amplified compared with the normal condition of the tap changer, the tap changer is in the switching contact slap fault. Theinvention has the advantages that: the found fault characteristic value can accurately reflect tap changer switching contact slap fault, characteristic is obvious, repeatability is good, and the method has universality on tap changers of the same type; the load tap changer contact slap fault diagnosis technology is simple in engineering realization, and a sensor is convenient in installation; anda microcomputer is adopted for detection, processing and diagnosis, performance is reliable, realization is convenient, and diagnosis conclusion is visual.

The invention provides a traffic monitoring image-based automatic detection system for a safety belt non-fastening behavior of a driver. The system comprises a module for extracting a to-be-detected region of the safety belt and a module for judging whether the driver fastens the safety belt or not; the module for extracting the to-be-detected region of the safety belt comprises a license plate detection sub-module, a driver region extraction sub-module, an image enhancement sub-module, a human face detection sub-module and a safety belt detection region extraction sub-module; the module for judging whether the driver fastens the safety belt or not adopts a straight line detection-based safety belt judgment method; and the straight line detection-based safety belt judgment method is used for detecting an edge straight line section of the safety belt by using a Canny edge detection algorithm and a progressive probabilistic Hough transform straight line detection algorithm. The safety belt non-fastening behavior of the driver can be accurately and quickly detected and recorded, so that the disadvantages of high labor cost of manual identification, easy fatigue, easy negligence and the like are effectively overcome, and the safety belt non-fastening driving behavior of the driver is effectively inhibited.

The invention discloses a service robot visual picture privacy protection method based on a generative adversarial network. The method is characterized in that, the privacy identification and protection comprises the functions of data preprocessing, privacy identification, picture conversion and the like. The method comprises the following steps: firstly, performing data preprocessing on data acquired by a visual data acquisition end, then judging whether the input preprocessed data has privacy or not by a privacy recognition module, if so, performing picture conversion, converting the pictureinto picture data which does not involve privacy, and storing the picture data, wherein the training data growth and feature learning are used for updating a training data set, and based on the training data set, a feature model is obtained through an improved Cycle-GAN algorithm and used for picture conversion. According to the method, the picture data does not involve the private content from the source, and the method has the characteristics of short training time and strong generalization ability of private picture conversion.

The invention relates to a traditional Chinese medicine clinical digital evaluation system.The system includes five first-grade indexes including a clinical treatment effect index, a preponderant disease index, a traditional Chinese medicine diagnosis and treatment method index, a work attitude index and a workload index.The ability of a doctor can be graded and analyzed through the big data analysis technology on the basis of the traditional Chinese medicine clinical digital evaluation system.Evaluation is conducted layer upon layer from sub-index evaluation to comprehensive evaluation, internal evaluation and external evaluation are organically combined, and clinical treatment effects, preponderant disease categories, traditional Chinese medicine diagnosis and treatment methods and work efficiency and work attitude of doctors are comprehensively analyzed.By means of the big data processing technology, the indexes are subjected to detailed weight calculation to obtain a data conclusion with bases, and accordingly work ability and level of traditional Chinese medicine doctors are scientifically evaluated.

The invention discloses a fluorescence molecule probe which belongs to the technical field of chemical analysis and detection, and particularly relates to a zinc and copper molecule probe, a method for preparing the probe and the application of the probe in heavy metal ion identification and detection. As a 1-(7-acetamide-1, 8-naphthyridine)-2-(6-acetamide-pyridine)-vinyl compound, the zinc and copper ion fluorescence probe can be applied in ion detection and heavy metal ion detection for biological tissues, and has the advantages of rapidity, accuracy, convenience, good specificity and better prospect of application.

The invention discloses an inspection robot image processing system and method with a self-adaptive polarizer adjusting function. The inspection robot image processing system comprises an inspection robot body, an image acquisition mechanism, a polarizer and an automatic polarizer rotating and driving device, wherein the image acquisition mechanism is arranged at the front end of the inspection robot body and is used for acquiring video and image data in a transformer substation, the polarizer is arranged at the front end of the image acquisition mechanism, and the polarizer is fixed on the automatic polarizer rotating and driving device, so that an optical axis of a camera vertically passes through the center of the polarizer, and the polarizer rotates by taking the optical axis of the visible light camera as the center axis. The inspection robot image processing system and method have the advantages that the problem that a certain instrument index is mistakenly identified due to glare, light reflection and shadow interference is solved, so that an inspection robot can observe operating status details of electrical equipment, the aim that all the equipment of the substation are covered and observed by the inspection robot is realized, and safe operation of all the equipment of the substation is guaranteed.

The invention relates to a transformer excitation inrush current recognize method based on wave-shape sine theory, wherein it uses the sine function character of normal operation, short circuit, and external circuit short; the excitation inrush current contains non-periodical component, and the distant angle has no sine character; via comparing the sine degrees, it can judge inrush current and short circuit. The invention defines and calculates out the wave-length non-sine degree sigmaS (t); comparing the wave-length non-sine degree and non-sine preset value sigmaSZd, to judge the inrush current and short circuit current; when the transformer is idle and closes gate, there is inrush current, sigmaS (t) is higher than preset value sigmaSZd; opening judging condition, closing protecting; when the transformer has short circuits, sigmaS (t) is lower than sigmaSZd, it will open protection. The invention has accurate judge and phase-divert brake, with significant effect on CT saturation.

The invention requests to protect an electroencephalogram signal identification method based on a spatiotemporal feature weighted convolutional neural network. The method comprises the following steps: firstly, de-noising a motor imagery electroencephalogram signal by using discrete wavelet transform; designing a spatial-temporal feature weighted convolutional neural network to perform feature extraction on the processed electroencephalogram signal, wherein the convolution operation of the first layer is carried out on the time scale of the motor imagery electroencephalogram signal, and the convolution operation of the second layer is carried out on the channel scale, so that the extracted features include the space-time characteristics of the motor imagery electroencephalogram signal; because the importance degrees of the extracted features are different, a feature weighting module is added into the network, so that the important features are highlighted, and the unimportant featuresare weakened. Characteristics extracted by the model can reflect the characteristics of various motor imagery electroencephalogram signals more effectively, and the recognition accuracy of the motor imagery electroencephalogram signals can be improved.

The invention relates to a squarylium type chemical sensor for colorimetric identification of a copper ion and a preparation method thereof, belonging to the field of chemical analysis and testing. The squarylium type chemical sensor is provided with a symmetric 2, 3, 3-trimethyl-indole squarylium compound and is prepared by the following steps of: mixing a 2, 3, 3-trimethyl-indole ring compound and squaric acid with a molar ratio of 2:1, adding mixture into a three-necked flask, adding mixed solvent of toluene and n-butanol with a volume ratio of 1:1, performing heating, mixing and back-flowing for 2-24 hours, and separating water produced in reaction with a water separator; stopping heating, cooling to the room temperature, depressurizing and evaporating to remove part of the solvent, and filtering to obtain green solid; and repeatedly washing the obtained green solid with ethyl acetate, drying at 60 DEG C, and recrystallizing with ethanol solvent to obtain pure green crystals. When the squarylium compound is applied in identification of the copper ions, the color can change in addition to changes in the absorption spectrum, the characteristics are obvious, and detection of the copper ions can be facilitated.