612results about How to "Implement features" patented technology

The invention discloses a wide-field ultra-high-resolution imaging system comprising a narrow-field long-focal-length optical imaging sub-system array, an image processing device with an image splicing function and a system control device with a system control function. According to the invention, the formed image has an ultra-high resolution. Within the selected design index, the purpose of obtaining narrow-field close-up images while obtaining the wide-field wide-angle images is fulfilled by field selection.

Disclosed is a teaching auxiliary device, a system and a method, wherein the device is a data storage module for storing the teaching course or / and the courseware and outputting the stored teaching course or / and the courseware to the teaching output module under the control of the CPU; a teaching output module for outputting the teaching course or / and the courseware in the given ways under the control of the CPU; a teaching mutual information input module for inputting the teaching information in the teaching process to realize the alternation in the teaching process. The method is that, the teaching auxiliary device provides the teaching course or / and the courseware to different types of terminals, receives the teaching mutual information input by different terminals; the different terminal obtains the teaching course or / and the courseware from the teaching auxiliary device, inputs the teaching mutual information to the teaching auxiliary device. The invention provides the teaching service on the basis of satisfying the self teaching characteristics.

The invention provides a motor rolling bearing fault diagnosis method and a diagnosis system thereof. The motor rolling bearing fault diagnosis method comprises the steps that a three-dimensional coordinate system in radial direction X, forward direction Y and vertical direction Z is used; a three-way acceleration sensor is arranged near a motor rolling bearing to acquire a three-way vibration signal; a rotational speed sensor and an ammeter are arranged to acquire the rotational speed pulse signal of the rolling bearing and measure the current signal of a motor stator; the maximum allowable deviation sigma I determining the current smoothness is set, and the maximum allowable deviation sigma V determining the rotational speed smoothness is set; during the time period T, vibration data under steady rotational speed and current are intercepted through predetermined conditions; valid three-way vibration data Acc in the time period T are extracted; the standard deviation of the three-wayvibration data is calculated, and composite time domain indexes in three directions are calculated; a threshold table is acquired through testing; and the acquired composite time domain indexes in three directions are compared with the threshold table to acquire the fault degree, and an alarm is given out.

The invention discloses a photovoltaic power generation system structure integrating energy storage and grid-connected and off-grid power supply functions and a control method, which can realize storage and conversion of renewable energy sources such as solar energy to electric energy and meanwhile have gird-connected and off-grid power supply functions. The structure comprises a photovoltaic component, a direct current-direct current booster circuit, a three-phase inverter circuit, an isolating transformer, a PCC (Programmable Computer Controller) grid-connected switch, a local load and the like. According to the control method, seamless switching between grid-connected / off-grid working modes of the system can be realized, and stepless regulation of output power of photovoltaic batteries and optimal management of accumulators can also be realized. Compared with the conventional photovoltaic grid-connected inverter, the photovoltaic power generation system has the prominent advantages of simple structure, rich function, high power supply reliability and the like, contributes to improving the utilization efficiency of renewable energy resources for power generation and has excellent application and generalization prospect.

The invention provides a method for diagnosing faults of bearings on the basis of extreme learning machines, and belongs to the field of technologies for diagnosing mechanical faults. The method includes carrying out variation mode decomposition on vibration acceleration signals to obtain IMF (intrinsic mode function) mode components; acquiring singular values of the IMF mode components by the aid of singular value decomposition (SVD) algorithms; dividing the singular values of each IMF mode component into a training sample and a test sample; utilizing the singular values of the training samples as input values of extreme learning machine (ELM) neural network models and determining input connection weights, offset values and optimal output connection weights of the ELM neural network models; utilizing the singular values of the test samples as input values of the ELM neural network models with the determined input connection weights, the determined offset values and the determined optimal output connection weights and acquiring output results which are bearing fault diagnosis results. The method has the advantages that the signals can be accurately effectively separated, component signal modes are fast in convergence and high in robustness, and the method is high in fault recognition speed and accuracy; model building can be omitted, professional requirements can be lowered, and accordingly the method is suitable for industrial application.

The invention discloses an ETC lane system compatible with weight-calculating charge and a realizing method thereof. The system comprises a non-weight-calculating charge subsystem and a weight-calculating charge subsystem, wherein the non-weight-calculating charge subsystem is used for communicating with an on-vehicle electronic label, identifying vehicle types, judging whether relative vehicle information is valid or not and permitting weight-calculating charge vehicles with valid relative vehicle information to pass or automatically reading, writing, charging and permitting non-weight-calculating charge vehicles with the valid relative vehicle information to pass; the weight-calculating charge subsystem is used for communicating with the on-vehicle electronic label, identifying the vehicle types, weighting the weight-calculating charge vehicles and automatically reading, writing, charging and permitting the weight-calculating charge vehicles to pass or permitting the non-weight-calculating charge vehicles to pass. The invention can respectively carry out the automatic charge transactions of the weight-calculating charge vehicles and the non-weight-calculating charge vehicles on the same ETC lane, controls the passage operation and improves the rapid passage capability of the ETC lane.

The invention discloses a bearing fault diagnosis method based on a deep adversarial migration network, which relates to the technical field of fault diagnosis of rotary machine vibration signals. Thediagnosis method comprises the steps: firstly, vibration frequency spectrum signals of a bearing under different working conditions (different rotating speeds and loads) are obtained, data with labels under a certain working condition serve as source domain data, and data without labels under other working conditions serve as target domain data; then a deep adversarial migration model based on agenerative adversarial neural network is then built to perform data training, two generators are adopted as a feature extraction network of a source domain and a target domain, Softmax cross entropy is adopted as a fault classifier, a discriminator is additionally adopted as a domain discrimination network, and a gradient inversion layer is added to perform domain discrimination training; and finally, network testing is carried out by adopting the residual target domain data. According to the method, the deep adversarial migration model is established by adopting the structure of the generative adversarial neural network, and fault feature migration learning and intelligent diagnosis of the bearing under different working conditions are efficiently and reliably realized.

The invention provides a method for identifying urban function areas based on WeChat data and interest point data. The method comprises the steps of extracting a people flow matrix, an out-people flow matrix and an in-people flow matrix of each base station from the WeChat data, extracting an interest point type distribution matrix of each base station from the interest point data, and performing normalization processing on the four matrixes based on a base station area element; then performing outlier deleting operations and performing urban space division, data extracting and normalization treatment on the base stations with outliers deleted to generate a new matrix, and then performing clustering analysis on the generated new matrix; finally performing space distribution area overlap ratio calculating on a clustering result and determining functions of urban areas according to overlap ratio calculating results. The method can identify the functions of each urban area accurately, better achieve functional partitioning and characteristic analysis of urban areas, provide technical support for urban structure layout and exploitation and utilization of land, and provide a realistic basis for reasonable utilization of urban space.

The invention discloses an optical imaging lens. The optical imaging lens sequentially comprises a first lens, a second lens, a third lens, a fourth lens, a fifth lens, a sixth lens and a seventh lens along the optical axis from an objective side to an image side. The first lens, the fourth lens and the fifth lens have positive focal power or negative focal power; the second lens has positive focal power; the third lens has negative focal power; at least one of the sixth lens and the seventh lens has negative focal power. The effective focal length f1 of the first lens and the effective focal length f2 of the second lens meet an inequality of f2 / |f1| 0.5.

The invention discloses a comprehensive test platform for the dynamic performance of a hydraulic cylinder of an engineering machine. The comprehensive test platform for the dynamic performance of the hydraulic cylinder of the engineering machine comprises a test platform body, a hydraulic system and an electrical test control system. The hydraulic system comprises a drive system unit and a loading system unit. The drive system unit comprises a first hydraulic pump, a first filter and three liquid inlet valve banks. Oil outlets of the three liquid inlet valve banks are connected with an oil inlet of the tested hydraulic cylinder. The loading system unit supplies oil to a loading hydraulic cylinder. The electrical test control system controls all the valve banks of the hydraulic system according to feedback signals. According to the comprehensive test platform for the dynamic performance of the hydraulic cylinder of the engineering machine, a drive system, a loading system and a gas-liquid supercharging system which are independently arranged are used for meeting test and control needs under different loads and different working conditions; and the comprehensive test platform also utilizes the feedback signals to control the test process, when the oil pressure, the flow, the filter precision, the system temperature and other indexes are not at the normal level, the system gives out an alarm to remind people and stops, and therefore system operation reliability is guaranteed.

The invention relates to a hydroelectric generating set fault diagnosis method based on deep learning. The method comprises the following steps of firstly, acquiring a vibration signal when a hydroelectric generating set runs as a sample, and establishing a database; secondly, preprocessing data, namely reconstructing the original vibration signal; thirdly, segmenting the reconstructed data set into a training set, a verification set and a test set; fourthly, training a network combining a one-dimensional convolutional neural network (1-D CNN) and a gated recurrent unit (GRU), and optimizing network parameters to avoid network overfitting; and finally, establishing a hydroelectric generating set fault diagnosis model by utilizing the trained network parameters, and inputting test set samples into the model to realize the hydroelectric generating set fault diagnosis. According to the method, the accuracy of the hydroelectric generating set fault diagnosis can be improved.

The invention discloses a permissioned blockchain constructing and controlling method based on a Chameleon hash function, wherein the method relates to the field of network security technology. The method comprises the following steps of 1, defining a blockchain control mechanism and initializing the permissioned blockchain according to the blockchain control mechanism; 2, packing transaction records of a block in the network for forming a new block, and adding the new block into the permissioned blockchain; and 3, monitoring the blocks in the permissioned blockchain according to the blockchain control mechanism, and controlling the blocks which do not accord with the blockchain control mechanism. The permissioned blockchain constructing and controlling method realizes global real-time monitoring of all nodes to malicious information and error transaction information on the block; any accessing node can report the error block to the verifying node; controlling of the whole permissionedblockchain by the verifying node is realized through constructing the permissioned blockchain; In a partially de-centering environment, controlling of the permissioned blockchain is realized. All verifying nodes perform effective modification on the blocks through calculating Chameleon hash collision and DBFT consensus, thereby realizing high safety and high controllability of the permissioned blockchain.

The invention belongs to the technical field of transformer substation network intrusion detection, and particularly relates to an intelligent transformer substation network intrusion detection systemand method based on deep learning. The system is used for intrusion detection aiming at network attacks of an IEC61850 communication protocol of an intelligent substation. The system comprises a datacollection module, a feature extraction module, a behavior analysis module and a defense behavior trigger module which are sequentially connected, wherein the data collection module is connected to an intelligent substation network to collect data, the defense behavior trigger module is connected to the intelligent substation network, the network information flow based on the IEC61850 protocol inthe intelligent substation is collected and analyzed in real time, and abnormal communication behaviors are detected and alarmed in real time.

The invention relates to an intelligent question and answer-based virtual learning environment construction method, and belongs to the technical field of man-machine interaction. The method comprisesthe following steps of: 1, acquiring and constructing a specific field teaching question and answer data set and preprocessing acquired questions and answers; 2, constructing a BI-LSTM-CRF model to carry out semantic analysis and feature extraction on the questions and answers, so as to realize word segmentation and sequence labeling of sentences; 3, constructing an LSTM network-based answer confidence calculation model, inputting question and answer pair feature vectors, balancing matching degrees of the question and answer pairs through the model, and converting and outputting the answer feature vectors with the highest scores; and 4, building a virtual learning environment by utilizing a Unity 3D-based virtual reality technology, constructing an intelligent question and answer engine, and importing a trained deep learning question and answer model to realize intelligent question and answer-based virtual learning environment construction. According to the method, deep learning is utilized to realize the intelligent question and answer of semantic comprehension layer in specific fields, and is applied to teaching-oriented virtual learning environment to expand thoughts and methodsfor virtual classrooms and man-machine interact research.

The invention provides a text classification method, a text classification device and a computer readable storage medium. The text classification method comprises the steps that text representation isconducted on a to-be-classified text to obtain a sentence set of the to-be-classified text, the sentence set is composed of word sets of all sentences in the to-be-classified text, and the word setsare composed of word vectors of words contained in corresponding sentences; based on a neural network, an attention mechanism and the word set, a feature vector of the sentence set is obtained; and the feature vectors of the sentence set is input into a text classification model to obtain a classification result of the to-be-classified text. According to the technical scheme, the text classification efficiency can be improved.

The invention belongs to the technical field of transmission line fault analysis, and especially relates to a transmission line lightning fault intelligent analysis platform and an analysis method. The transmission line lightning fault intelligent analysis platform comprises an EMS system, a relay protection information system, a power grid lighting location center, and terminal users. The transmission line lightning fault intelligent analysis platform further comprises a transmission line fault information analysis system which collects and acquires data information of the EMS system, the relay protection information system, the power grid lighting location center and the terminal users in real time. Analysis of data access, intelligent diagnosis and lightning fault information display is carried out through a front acquisition unit, a database service unit, an intelligent analysis unit and an application information display unit of the transmission line fault information analysis system. By adopting the analysis platform and the analysis method of the invention, the current application defect of transmission line lightning monitoring is improved, lightning fault analysis result information can be provided, and a basis is provided for auxiliary decision making of lightning trip-out accident post-processing.

The invention discloses a stylized image generation method, device and equipment and a storage medium. The method comprises the following steps: carrying out style conversion on an original image through different styles of selected images to obtain a stylized original image; segmenting a target region from the stylized original image through a multi-task cascaded network according to a stylization target required by the original image; and fusing the segmented target region into the original image through an MRF model to generate a stylized image having the target region. The method can accurately classify the target region through the multi-task cascaded network and adopts the MRF model when the target region is fused with the original image, so that transition between the target regionand a background image of the original image can be smoother, the stylized image is allowed to take the content as contour and have a desired style, image stylization effect is ensured, and finally, specific region stylization or multi-region stylization of the image can be realized.

The invention relates to a three-proofing and soil release textile fabric and a preparation method thereof. The method comprises a cleaning step and a three-proofing soil release finish step. The contradiction between three-proofing finish and soil release finish is solved through reasonably preparing the usage amount of each auxiliary and adopting operation steps, the superhard or supersoft hand feeling characteristic of the three-proofing and soil release textile fabric is realized, the fabric is safe and environment-friendly, has high protection level, can be used for frocks, oil field protection suits and home textile fabrics such as table clothes, curtains and kitchen clothes and can also be used for high-end fabrics such as business suits.

The invention discloses a method for controlling an inflexion point position and an upward trend of stopper stiffness. According to the method for controlling the inflexion point position and the upward trend of the stopper stiffness, an assembled structure of an inner stopper and an external stopper is adopted; a lateral portion of a longitudinal section of every elastomer rubber layer which is segregated by a metal partition is arranged into a groove structure; the groove structure comprises an arc type groove bottom edge, two symmetrical inclined side edges of the groove, two symmetrical arc transition sections which are connected with the inclined side edges of the groove and two symmetrical inclined top edges of the groove; the two inclined side edges of the groove are connected with the arc type groove bottom edge; the two symmetrical inclined top edges of the groove are connected with the arc transition sections; the inflexion point position of the stiffness is controlled by arranging the number of elastomer rubber layers which are segregated by the metal partition and the arc diameter of the arc type groove bottom edge; the upward trend of the stiffness is controlled by arranging degrees of the groove inclined lateral edges and a horizontal line and the length of the groove inclined lateral edges; changing of stiffness characters and a function of a hard stopper are achieved; and the inflexion point position and the upward trend of the stiffness are accurately controlled.

The invention relates to a method for preparing Pu'er tea and serial products by inoculating bacterial. The invention employs Yunnan bold leaf fresh primary tea or teabush fresh tea as raw material, sprays mixed bacterial and water onto tea stack, mixing uniformly tea, bacterial and water for fermentation to produce PUí»er tea. Puí»er tea capsule can be got by further process. The invention sifts out dominant bacterial from different Puí»er tea producing area and different fermentation phase, then proceeds artificial inoculation for single plant and combined bacterial fermentation, and studies the toxicology of chosen bacterial. It is studied that the chosen bacterial is safe with low toxicity; the fermentation temperature increase is fast for artificial inoculation, the growth of bacterial filament is fast, the color change of tea is earlier, and the periodic time is shortened by 2 / 3 than that of original fermentation tea, which reduces and avoids mite growth.

The invention discloses an account transferring system based on Merkle tree backtracking positioning technology, checking method and transaction method. The system comprises a center end and a clientend. A central storage module is arranged in the central end; The central storage module comprises a central database and a block chain; The central database is used for storing complete transaction records; the block chain is composed of blocks through Hash iteration, and each block comprises a block head and a block body; the block head is used for storing a root value of a system general ledgertree and a root value of a system household ledger tree of the block; the block body is used for storing transaction details of the block; A local storage module is arranged in the client end; The local storage module comprises a local database and a block head chain; The local database is used for storing individual household account trees; the block head chain is a data chain formed by all theblock heads. According to the invention, through realizing distributed total account checking and individual account checking, bidirectional checking of transaction information of the transaction party and the transaction party can be realized, so that efficient and reliable bank transactions under privacy protection are realized.

The application discloses a DGA domain name detection model construction method and device, a server and a storage medium. The method includes the following steps of: acquiring a training data set, wherein the training data set includes DGA domain names and legal domain names; dividing the training data set into a plurality of training data sub-sets, wherein each training data sub-set includes atleast one DGA domain name and at least one legal domain name; training each training data sub-set by using a classification algorithm to obtain a plurality of detection sub-models; sequentially inputting test samples into each detection sub-model to obtain a prediction label set of the test samples; and fusing the prediction label set according to a decision strategy to obtain a final label of thetest samples. According to the DGA domain name detection model construction method provided by the embodiment of the application, the plurality of detection sub-models are obtained by grouping the training data set, the complete learning of the training data set can be realized, and the characteristics of actual DGA domain names can be embodied.

The invention discloses a buck-boost composite DC / DC converter, which comprises a buck circuit, a half-bridge boost circuit, a closed-loop PWM control circuit and a driving circuit, wherein the input stages of the buck circuit and the half-bridge boost circuit are in a parallel connection mode, and the output stages are in a serial connection mode. When input ends are connected in parallel, the two circuits are mutually independent, no coupled relation exists, and the working mode depends on the magnitudes of the input voltage and the output voltage, so the problem of output oscillation of the converter is avoided. When output ends are connected in series, under the buck mode, the half-bridge boost circuit does not work, and the output voltage is approximately equal to the output voltage of the buck circuit; and under the boost mode, the buck circuit maintains a shoot-through state, and the output voltage is equal to the sum of the output voltage of the buck circuit and the output voltage of the half-bridge boost circuit. A half-bridge single circuit only provides the energy of an input and output voltage difference part, thereby increasing the efficiency of the whole converter.

The invention discloses a method using a delay line type surface acoustic wave sensor to test characteristic parameters of an article and belongs to the technical field of novel sensor testing. The method can test the characteristic parameters based on amplitude-frequency characteristics and phase characteristics of the delay line type surface acoustic wave sensor. Firstly, a signal source outputs drive signals in a certain frequency range at certain frequency space sweep frequency, the resonant frequency can be obtained by measuring the signal amplitude ratio between input drive signals and output response signals of all sensors at all frequency points in a sweep frequency range, the signal source can output fixed-frequency drive signals on the basis, and the characteristic parameters of an object to be detected can be accurately detected by measuring the phase difference between the input drive signals and the output response signals of the sensors. The method enables the delay line type surface acoustic sensor to break the lab using limit and achieves industrial online application.

The invention discloses a gram-grade material thermo-gravimetry and gas production property research experimental apparatus. The experimental apparatus comprises a console, an electronic scale, a heating furnace for heating a detected sample, a crucible for holding the detected sample, and a lifting supporting frame for supporting the electronic scale, wherein the heating furnace is fixed on the side of the console; the lifting supporting frame is of a gamma-shaped structure and is composed of a vertical bracket and a horizontal supporting plate; the bottom end of the vertical bracket of the lifting supporting frame is connected and arranged on a driving motor in the console; the electronic scale is located above the heating furnace and is arranged on the upper surface of the horizontal supporting plate of the lifting supporting frame; a reaction pipe is connected below the horizontal supporting plate of the lifting supporting frame through a fixing frame; the crucible is arranged in the reaction pipe, and is connected to a spring piece of the electronic scale through a metal wire hook which runs through the horizontal supporting plate of the lifting supporting frame. The experimental apparatus disclosed by the invention can test a great amount of samples (the scale is 0-110g in measuring range and is 0.1mg in precision), and can implement thermo-gravimetry and gas production property research on the tested samples under an instantaneous warming state.

The present invention discloses a nonlinear identification method for a rock fracture signal and a blasting vibration signal. The method comprises: step 1: importing a time sequence x(n) of a rock microseismic signal, wherein n=1, 2,..., N; step 2: performing decomposition to obtain intrinsic modality components of a normalized rock microseismic signal by EMD decomposition, and screening the intrinsic modality components to obtain main intrinsic modality components c1, c2,..., cr, wherein r is the number of the intrinsic modality components after screening; step 3: performing decomposition on a matrix [c1 c2... cr]T by SVD, so as to obtain a singular value signma i of the matrix, wherein i=1, 2,..., r; step 4:calculating a probability p(Z) of a blasting vibration signal by using a Logistic model; and step 5: identifying the rock microseismic signal, wherein p(Z)>= 0.5*(blasting vibration signal), and p(Z)<=0.58(rock fracture signal). The method has the characteristics of strong suitability and high accuracy and the like.

A lube base oil satisfying at least one of the following requirements (a) and (b). A lubricating oil composition for internal combustion engines is provided which comprises the lube base oil, an ash-free antioxidant containing no sulfur as a constituent element, and at least one member selected among ash-free antioxidants containing sulfur as a constituent element and organ omolybdenum compounds. Also provided is a lubricating oil composition for drive transmission devices which comprises the lube base oil, a poly(meth)acrylate-type viscosity index modifier, and a phosphorus compound. (a) The content of saturated matters is 90 mass% or higher and the proportion of cyclic saturated matters in those saturated matters is 10-40 mass%. (b) The lube base oil satisfies the relationship represented by the following expression (1). 1.440=n20-0.002OEv100=1.453 (1) [In the expression, n20 indicates the refractive index at 20 DEG C of the lube base oil and kv100 indicates the dynamic viscosity (mm2 / s) at 100 DEG C of the lube base oil].

The invention provides a bearing fault classification method and system based on a deep learning network, and the method comprises the steps: setting a sampling frequency, and collecting the vibrationsignal data of a bearing under different working conditions; segmenting the obtained vibration signal data to construct a plurality of samples; decomposing the vibration signal data of each sample toobtain a plurality of modal components so as to realize effective component separation; constructing a deep network with a residual error unit, and determining an appropriate network depth by using arandom search method; inputting the training set into a deep residual network for iterative training and obtaining a classification model; and inputting the test set into the classification model toobtain a fault classification result. According to the classification method provided by the invention, variational mode decomposition and a deep residual network are combined; the problems that noiseinterference exists in input data, cross aliasing exists in effective components, network deepening causes identification gradient disappearance, and performance degradation causes poor classification effect are solved, fault feature extraction not affected by rotating speed changes is achieved, and the fault classification accuracy is improved.

The invention discloses a multifunctional testing platform of the dynamic characteristics of vehicle dynamics, which comprises a rotary coder, a synchronous belt, a moment motor, a retaining ring, a bearing, a motor slide block, a shaft sleeve, a longitudinal guide rail, a transversal guide rail, a fixed square plate, a steel ball, a steel ball fixing frame, a rotating disc, a moment sensor, a brake disc, a cylinder bracket, a cylinder shaft, an outer rotor motor, a force and moment sensor, an arrester bracket, an arrester, a cylinder, a measurement and control system, a code disc, a rotating speed sensor, a centering roller bracket, a centering roller lifter and a centering roller. By the invention, the whole vehicle dynamics is comprehensively researched on the testing platform, a driving or brake moment and a steering resisting moment are applied to wheels, and the wheels are permitted to steer in rotating motion so that more working conditions can be imitated by applying driving or braking moment on wheels and permitting the wheels to steer during rotating motion. The multifunctional testing platform can test and research the dynamic characteristics of vehicle longitudinal dynamics and transversal dynamics. The attached figure is the structural front view of the invention.