87results about How to "Overcome blindness" patented technology

The invention discloses an arranging method for a sensor for detecting fatigue stress of a steel box girder bridge based on a fatigue damage degree index, comprising the following steps: calculating fatigue stress of at a steel box girder candidate measure point area through the finite element model technology; constructing the fatigue damage degree index based on an S-N curve and a Miner linear damage accumulation theory provided by design specifications; and determining an arranging position of the sensor for detecting fatigue stress of the steel box girder bridge according to size of the fatigue damage degree index. The method provided by the invention effectively ensures analysis precision for fatigue stress of the steel box girder bridge by using the finite element model analysis technology, constructs the fatigue damage degree index of the steel box girder bridge on that basis, and provides reasonable evidence for selecting the arranging position of the sensor, so that subjectivity, empirical property and blindness for arranging the traditional steel box girder fatigue stress sensors are effectively overcome, and the method will be certainly applied and popularized widely.

The present invention relates to a method of coal blending for coking, in particular to a method of coal blending for coking, by which high-heat-intensity coke is produced. The present invention mainly resolves the technical problems of the prior coal blending method, such as inappropriate parameter selection and difficulty in promotion caused by the application of active components and inert components in ensuring the caking property of coal blending. The technical scheme of the method is as follows: the method of coal blending for coking, by which high-heat-intensity coke is produced, adopts rich coal, coking coal, gas coal and 1 / 3 coking coal, which are blended together; after blending, the microcosmic strong caking ratio is kept larger than 55 percent; the maximum thickness of the gelatinous layer is between 14mm and 18mm; and the caking index is between 80 and 85. The method is mainly used for the production of high-heat-intensity coke.

The invention discloses a least squares support vector machine electric shock current detection method based on parameter optimization. First, the total leakage current and electric shock current waveform of an organism in the process of electric shock at the peak moment, zero-crossing moment and any moment of power voltage are acquired on a residual current action protection device electric shock physical test system platform through a fault recorder, and signal data of 800 sampling points of the cycle before electrical shock and the three cycles after electrical shock is taken as electric shock test sample data; and then, filtering preprocessing is performed on the electric shock test sample data, and the total leakage current of multiple sample sampling points after preprocessing is combined into a feature vector input least squares support vector machine. As a new tool for pattern identification, the least squares support vector machine has superiority unmatched by other identification tools. A new detection method is provided for identifying electric shock current of an organism from total leakage current.

The invention discloses a method for predicting the remaining useful life of a steel box girder bridge top plate-longitudinal rib welding detail subjected to fatigue cracking in an operating state. The method comprises the following steps of: detecting the fatigue crack of the steel box girder bridge top plate-longitudinal rib welding detail by an ultrasonic non-destructive detection technology, determining the position of the welding detail subjected to fatigue cracking, and measuring the extension depth of the fatigue crack in a top plate; and arranging a strain sensor on the top plate at the welding detail subjected to fatigue cracking to acquire a fatigue load effect spectrum under the action of an actual operating vehicle, establishing a fatigue fracture limit state equation of the welding detail according to a linear elastic fracture mechanics theory, and calculating the remaining useful life of the top plate-longitudinal rib welding detail. By the method, the respective advantages of the non-destructive detection technology and a health monitoring technology can be fully exerted to meet the fatigue evaluation requirement of the steel box girder bridge top plate-longitudinal rib welding detail in the operating state, and the defects of subjectivity and blindness of the traditional fatigue damage evaluation method for a steel box girder bridge are effectively overcome.

The present invention provides a two-dimensional clothes gravure three-dimensional method and device. The method comprises: obtaining a plurality of two-dimensional clothes gravures and human being models corresponding to the clothes to be displayed; determining the stitching areas of each two-dimensional clothes gravure; performing triangle subdivision processing of each two-dimensional clothes gravure, and building the corresponding three-dimensional clothes gravure; and building a particle spring model corresponding to each three-dimensional clothes gravure, performing stitching processing of the stitching area matching each three-dimensional clothes gravure according to the quality spring model when the three-dimensional clothes gravure is moved to the stitching position matching the human being models, and obtaining the three-dimensional clothes on the human being model for displaying. The two-dimensional clothes gravure three-dimensional method and device can process the two-dimensional clothes gravures to the three-dimensional clothes gravures and stitch the two-dimensional clothes gravures into the human being models so as to avoid the limitation that the effect only can be seen after the stitching sampling clothes is completed, overcome the blindness and the hysteresis quality, save the invested cost of stitching the sampling clothes and producing the human being models and improve the display efficiency.

The invention discloses an optical fiber state prediction method for optimizing a neural network based on an improved firefly algorithm, relates to the technical field of optical fiber line state prediction, and solves problems that the prior art cannot achieve the analysis and prediction of the tendency of the state of a line, and cannot avoid the possible faults. The method carries out the optimization of parameters in an Elman neural network prediction model through employing the improved firefly algorithm, accurately predicts the future state tendency of the line, predicts the possible faults of the line, forms a maintenance strategy in advance, avoids the faults, and meets the requirements of uninterrupted transmission of optical fiber communication. The method carries out the optimization of parameters of the Elman neural network prediction model through employing the improved firefly algorithm, enables the model to have good prediction precision and stability, solves a problem that a conventional Elman neural network is liable to be caught in conditions of local optimization and slow convergence speed, and achieves the better prediction of the state of light.

The invention discloses an atomic force microscope imaging method and an atomic force microscope (AFM) imaging device of a microscopic monitoring type selectable region. Microscopic monitoring and selectable region AFM imaging of an AFM scanning region are realized by using a method for combining optical microscopic monitoring with AFM microscopic imaging and combining an AFM scanner and a two-dimensional step micropositioner. The device is provided with an AFM probe and an AFM imaging and control system, wherein the AFM probe comprises a laser device, a semi-transparent semi-reflective prism, a microprobe, a position sensitive element, a sample, a sample table, a scanner, a microscope objective, a CCD (Charge Coupled Device), a two-dimensional step micropositioner and the like; and the AFM imaging and control system comprises a preamplifier, an XY scanning and Z feedback control unit, an XYZ high-voltage amplifying module, a step control module, a video acquisition module, a computer, a hardware interface and the like. The method and the device have the advantages that real-time monitoring and region selection of a micro / nano sample scanning region are realized, adjustment and alignment of an optical path and an approximation process of the sample and the microprobe can be monitored, and the randomness, the blindness and the limitation of the conventional AFM technologies in the aspects are overcome.

The present invention relates to a flexible sheet structure impact load identification method based on combination of a distributed SNS (Single-mode-No core-Single mode) multiple-mode interference fiber optic sensor and an automatic encoder deep learning algorithm, belonging to the technical field of structure health monitoring impact monitoring. The method comprises the following steps of: the step 1: layout of an SNS fiber optic sensor; the step 2: construction of a distributed SNS fiber optic sensor sheet structure impact load monitoring system; the step 3: real-time monitoring and collection of impact response dynamic signals, and recording of an impact test data to generate a sample bank through impact test for different positions and different energy; the step 4: preprocessing for the sheet structure SNS fiber optic sensor impact sample bank data; the step 5: selection of an automatic encoder as a deep learning model, construction of a network structure, and training of a deep learning neural network; and the step 6: through adoption of a trained model obtained in the step 5, processing of the SNS fiber optic sensor impact response data to achieve identification for the impact load position and energy.

The invention provides a neural network based crop disease identification method comprising the following steps: the category of diseased leaf images is estimated via use of a constructed self-adaptive global pooled convolutional neural network; the self-adaptive global pooled convolutional neural network is formed by orderly connecting one input layer, one batch normalization layer, six hidden layers and one classification output layer; each of the first four of the hidden layers includes convolution operation, activation operation, maximum pooling operation, and local response normalizationoperation; a fifth hidden layer includes convolution and activation operation, and a sixth hidden layer is global pooling operation; self-adaptive learning rates adopted in the method disclosed in theinvention can help greatly shorten time required for training and overcome problems of insufficient learning and trapping in local optimum caused by fixed learning rates; convergence speed, generalization ability and stability of a network can be improved.

The invention relates to the method for groundwater pollutant hydraulic capture scheme optimization, and provides a method for hydraulic capture scheme optimization. According to the technical scheme, a groundwater pollutant hydraulic capture optimization method through orthogonal design and GMS coupling includes the following steps: (1) determining the location and the scale of a pollution source, and determining main pollutants in groundwater, (2) collecting hydrogeologic resources of a researched area, and determining hydrogeologic parameters of the researched area, (3) generalizing hydrogeologic conditions of the researched area, (4) selecting factors influencing the hydraulic capture effect by means of the orthogonal design method, (5) carrying out scenario simulation on different hydraulic capture schemes selected through the orthogonal design by means of a groundwater simulation system (GMS), (6) determining the hydraulic capture effect of the optimal scheme, and (7) determining the hydraulic capture scheme suitable for practical conditions according to the hydrogeologic conditions of a site. The method is mainly applied to water pollutant hydraulic capture.

The invention discloses an autonomous non-overshoot state switching method of a ship inertial navigation system, comprising the following steps of: determining the damping ratio of a correction link; determining the time domain parameter during the calibration process; determining the cut-off frequency during the correction link; determining the system bandwidth; determining two handover frequencies during the correction link; determining a low-frequency band during the correction link; determining a high-frequency band during the correction link; determining the convergence frequency band of the correction link; determining the transmission function during the correction link; determining the switching time; determine the switching step length; determining the velocity variable before and after the correction; acquiring acceleration and angular velocity of the inertial device output; compensating for the inertia device output according to the error source of the inertial device; integrating the acceleration information to obtain the speed; acquiring a velocity correction value; acquiring speed after the correction; acquiring angular velocity information after the correction and feeding back by the Shura loop; and integrating the speed after the correction to obtain the position after the correction. By the adoption of the method provided by the invention, overshoot errors generated during the state switching process can be inhibited without depending on the external speed.

The invention relates to a method to improve the yield of streptomycete antibiotics and the breeding selection of high yield streptomycete strain. The method includes: cloning the section containing nsdA gene to gain the recombination carrier containing nsdA gene section, constructing the destroyed recombination carrier of nsdA gene, transplanting the carrier to streptomycete, fitering and gainin streptomycete strain that the nsdA gene is destroyed, ttesting the strain to gain high yield strain. The invention supplies a new approach to improve streptomycete antibiotics.

The invention provides a method for optimizing mutual compensation of a surface-shape error of an optical system. The method specifically comprises the steps of firstly, establishing an approximate analysis relation of influence of surface-shape errors of different optical surface types on the wave aberration of the optical system so that the influence of the surface-shape error on the system wave aberration is obtained through directly analysis and calculation independently of an optical structure without light ray tracking calculation by taking the optical structure into account when the rotation angle of an optical element is optimized, secondly, taking the weighted average of the wave aberration,caused by the surface-shape error, of each field-of-view point as an error function of optimization design, and finally, optimizing the rotation angles of all optical elements, and taking the rotation angle, corresponding to that an error evaluation function is minimized, of each optical element as the optimal rotation angle for assembly, and thus realizing mutual compensation optimization of the surface-shape error of the optical system. The assembly efficiency of the optical system is greatly improved by the method.

The invention relates to a method for performing diagnosis on the working condition of a rod pumped well upon a neural network. An oil well fault diagnosis method based on the neural network comprises the following steps: S1, acquiring indicator diagram displacement and load data through a load and displacement sensor, and uploading the data to a database through a remote RTU (remote terminal unit) polished rod module; S2, performing the following processing shown in the specification on information in the database to obtain a feature vector; S3, establishing the radial basis function neural network to perform judgment. According to the method disclosed by the invention, blindness and nondeterminacy caused by simply depending on the graph geometrical characteristic are overcome; the diagnosis accuracy can be improved, and the production practice requirement is met.

The invention discloses a cigarette for detoxification, wherein, tobacco shreds are composed of tobacco and lotus leaves absorbing ingredients of a detoxification drug, and the tobacco accounts for 10 to 50 percent of the total mass of the tobacco shreds. The invention further discloses a preparation method of the cigarette for detoxification. The cigarette for detoxification of the invention can allow drug aerosol to be absorbed by the human inner mucosa in the ionic state with the help of a smoking mode of the cigarette by the people, thus having significant efficacy, rapid effectiveness and facilitating the fine adjustment and control of the dose of the psychotropic drug; furthermore, the preparation method is simple and easy to realize, thus having broad market prospect.

The present invention relates to a gastrointestinal bioelectric information following therapeutic equipment integrating gastrointestinal electric information detection and following therapy into one body. Said therapeutic equipment has the circuits of body surface detection, electric information collection, information processing conversion, following through and display. The output end of detector is connected with input end of collection circuit, the output end of the collection circuit is connected with input end of conversion circuit, and the output end of the conversion circuit is respectively connected with display circuit and input end of following technology circuit, and the output end of following therapy circuit is connected with detector. Said invention also provides its application method and its action.

The invention provides an intelligent matching method and system for power outage handling plans. The method comprises the following steps of: establishing a plan library based on characteristic attributes of power outage events; and comparing the characteristic attributes of one power outage event with those of the plans in the plan library to obtain similarity S of the power outage event Cobject to the plan C by, and carrying out plan matching based on the similarity S. According to the method and the system, the power outage handling plans are established, managed and applied, a power outage handling plan matching rule model is established, and a search strategy with the sum of same characteristic weights serving as a similarity index is proposed, so that an accurate and comprehensive accident handling scheme is generated in an emergency condition, the risk and the blindness caused by the pure independence on experience are overcome, the prevention and the power outage handling efficiency are improved, the electric power casualty loss is reduced, the power utilization reliability and economic and social development are ensured, and thus the method and the system have important theoretical and practical significance.

The invention relates to a bridge gambling party sample generation method. The bridge gambling party sample generation method comprises the steps of S1, establishing a gambling party constrained mathematical model, and conducting gambling party encoding; S2, establishing an initial population; S3, calculating population fitness; S4, storing k better individuals in parents and offsprings, and thenjudging a terminal condition, wherein terminal condition judgment comprises the steps of S41, judging whether or not distributed time is run out and S42, judging whether or not the fitness of each individual in the population meets the requirement; S5, executing genetic algorithm operation; S6, outputting a generated gambling party sample. The bridge gambling party sample generation method has theadvantages that a genetic algorithm is utilized to give full play to the generated gambling party sample, the fast and stable bridge gambling party sample generation method is provided, and comparedwith a method of randomly generating a gambling party sample, the method can generate the bridge gambling party sample faster and more stably.

The invention discloses a transformer detection system. The system comprises an oil temperature detection unit, a noise detection unit, a current and voltage detection unit, a central processor, an early warning unit and a wireless communication module. The oil temperature detection unit is used for detecting oil temperature in a transformer in real time. The noise detection unit is used for detecting vibration signals and sound signals of the transformer in real time. The current and voltage detection unit is used for detecting high voltage operation voltage, high voltage load current and high voltage end screen current values of the transformer in real time. According to the invention, detection data is transmitted to a monitoring center along with a detection network, so real-time monitoring of the transformer is achieved; different information is combined and integrated to judge faults, so an information fusion effect is achieved; maintenance plans are reduced; defects of blindnessand enforceability are overcome; a large number of manpower and materials are saved; and damage to other aspects of the transformer in the maintenance process is avoided.

The invention provides a back-to-back paired mounting angular contact ball bearing parameter combination measuring device and aims at overcoming uncertainty and blindness in manual assembly and calibration processes. The back-to-back paired mounting angular contact ball bearing parameter combination measuring device is composed of a drawing and sensory detection mechanism, a transmission and rotation friction torque measuring mechanism and a bearing installation base. The drawing and sensory detection mechanism is arranged on a rolling linear guide rail pair of the bearing installation base in connection mode through a column, and the position of the drawing and sensory detection mechanism is determined by a positioning block, a stroke limit block and a back limit block. The transmission and rotation friction torque measuring mechanism is arranged on a base disposed in the bearing installation base portion through a motor base, drives a drawing sleeve arranged in the bearing installation base and a bearing inner ring to rotate through a coupler and a transmission rod, and is used for measuring rotating friction torque. By adopting the back-to-back paired mounting angular contact ball bearing parameter combination measuring device, under certain axis accuracy and practical lubricating conditions, values of pretightening force, relative displacement and rotating friction torque of paired mounting angular contact ball bearings can be accurately determined.

In order to solve above technical problems, the invention provides a navigation system used for shaft fracture intramedullary reduction. The system comprises a marrow cavity endoscope, an image display module, a computer, an electromechanical control module, and a mechanical traction frame. The image display module is electrically connected between the marrow cavity endoscope and the computer. The electromechanical control module is electrically connected between the mechanical traction frame and the computer. The marrow cavity endoscope acquires image signals of proper positions, and transmits the image data to the computer through the image display module. After the image data is displayed, analyzed and processed on the computer, a displacement instruction is transmitted to the electromechanical control module. The electromechanical control module drives the mechanical traction frame to complete corresponding displacement operation. The system is characterized in that operation is simple, axial alignment and rotation alignment are realized, X-ray radiation damages are prevented, the system monitors reduction state in real time, and is high in precision, and can maintain a satisfied closed reduction state for a long time.

The intelligent cerebrospinal fluid replacing instrument consists of two parts, including a disposable replacing cylinder and a driving and controlling device capable of being reused. Inside the replacing cylinder with replacing port for the drainage pipe to be connected on and sucker, artificial cerebrospinal fluid is held. The driving and controlling device includes mainly a mechanical driving unit and an automatic control unit. The present invention has a program driven pushing and sucking pump with constant speed and constant displacement, and parameters capable of being set based on disease condition, so that it has intelligently controlled speed, time and pushing and sucking amount of the replaced cerebrospinal fluid and is scientific, accurate, safe and efficient.

The invention provides an underwater structured environment line feature extraction method based on forward looking sonar. The method comprises steps: dynamic threshold segmentation is carried out onforward looking sonar data to acquire the total number of high echo intensity points and polar coordinates in a carrier system; within the limited cycle times, two not-isolated and not-adjacent pointsare randomly selected from the high echo intensity points to form a straight line, points with the distances with the straight line smaller than a preset threshold are selected to form a candidate point set, the ratio of the potential of the candidate point set to the total point number is calculated, if the ratio is no smaller than the threshold, the straight line is used as an auxiliary straight line, and the cycle is stopped; based on the parameters of the auxiliary straight line and the corresponding candidate point set distribution features, the voting space for structured environment line feature parameters is constructed, and a voting algorithm is used to extract line feature parameters; and based on the distribution condition of points near the line features, the line features arecut to line section features. The blindness of random sampling and the inefficiency of the voting algorithm can be overcome effectively.

The invention provides an application of a relA gene in increase of the moenomycin yield of streptomyces bambergiensis, as well as obtained relA gene blocking engineering bacteria, namely, streptomyces bambergiensis 1203 for producing moenomycin and an application of the streptomyces bambergiensis 1203, wherein the strain is preserved in China General Microbiological Culture Collection Centre, the preservation number is CGMCC No. 7237, and the collection date is January 31, 2013. According to the application and the strain provided by the invention, relA homologous genes on streptomyces bambergiensis chromosomes are blocked by virtue of a molecular biological technique, thus increasing the moenomycin yield, and overcoming the defects of blindness, high screening workload and the like of mutagenesis adopting traditional physical and chemical methods.

The invention relates to a power supply mode selection method of an area without electricity supply based on a load distance and a load characteristic. Based on a survey of a present situation of the area without electricity supply, an appropriate power supply mode is provided. Each mode lists each characteristics and a suitable scope. The method is characterized by: measuring and calculating load and line power supply distances of the area without electricity supply; calculating and determining whether the distances satisfy a load distance requirement; determining the corresponding power supply mode according to the load and the load characteristic. By using the method, a set of selection process of the power supply modes of the area without electricity supply can be established. A selection difficulty of the power supply modes of the area without electricity supply can be substantially reduced. A feasible scientific technology which can solve a power supply problem of the area without electricity supply can be provided. In the invention, the method is combined with the actual area without electricity supply. The area without electricity supply and a power distribution network of the adjacent power supply area can be deeply analyzed. A bottleneck of implementing power grid extension power supply can be found and a power supply problem of the area without electricity supply can be effectively solved.

The invention discloses an active power distribution network voltage control method and system based on a virtual cluster, and belongs to the field of distributed power supply control. Distributed power supplies in an area are integrated and controlled, so that the control quantity can be remarkably reduced, and the "dimension disaster" brought for a centralized controller due to the fact that thedistributed power supplies are connected to a power distribution network in a high-permeability mode can be effectively avoided. A distributed power supply master station control center, a distributed power supply cluster and a distributed power supply station are used for carrying out layered optimization control on active and reactive outputs of the distributed power supplies connected to the power distribution network in a dispersed mode; the master station control center generates a cluster control instruction; and a cluster management and control device receives the cluster control instruction and distributes the cluster control instruction to the distributed power supply station, so that safe and economic operation of the power distribution network is achieved. Meanwhile, in view ofthe randomness and volatility of the outputs of the distributed power supplies, autonomous control is carried out by the distributed power supply station, and a method of PI control with dynamic optimization is adopted, so that the safety and stability of a master station cluster control interval station are guaranteed.

The invention discloses a device and a method for recognizing a parameter of an executive mechanism in an electro-hydraulic angular speed servo system. The recognition device consists of a step current signal generator, an electro-hydraulic servo valve, a hydraulic motor, a mechanical load, an angular speed detection sensor, a recording instrument and a hydraulic source. The recognition method comprises the following steps of: inputting a step current signal into the electro-hydraulic servo valve; driving the hydraulic motor and the mechanical load to rotate through the hydraulic source; recording the variation process of the amplitude value of the step current signal and an angular speed signal along with time until the angular speed signal reaches a steady-state value; dividing the amplitude value of the step current signal by the steady-state value of the angular speed signal to acquire the equivalent viscous damping coefficient of the executive mechanism; and multiplying the equivalent viscous damping coefficient by a time value corresponding to the intersection point at which a tangent line at the zero hour position of an angular speed signal curve is intersected with the steady-state value of the angular speed signal to acquire the equivalent inertia of the executive mechanism. By the device and the method, time and labor can be saved when the electro-hydraulic angular speed servo system is debugged, and good static and dynamic properties can be acquired by the electro-hydraulic angular speed servo system.

The invention discloses a method for excavating natural hybridization germplasm and breeding new varieties of kiwi fruits and relates to the field of plant genetic breeding and biotechnology. The method comprises the steps of (1) surveying distribution conditions of mixed populations of species in a naturally overlapped distribution region of actinidia plants and collecting samples; (2) analyzing populations for assisting in positioning in a hybridization band through molecular markers; (3) collecting germplasm of the hybridization band and performing artificial domestication on the germplasm in a breeding garden; (4) commenting on and performing large-scale regional trial on superior plants or varieties obtained through artificial domestication; (5) registering and applying for new varieties. Compared with traditional artificial hybridization breeding, by means of the method, the breeding cycle is shortened greatly, the excavation geographic area of the target hybridization germplasm is narrowed down, blindness and randomness in utilization of the traditional natural germplasm of the kiwi fruits can be overcome, singular germplasm unexpected by traditional artificial breeding can be screened and domesticated, and problems caused by biosecurity are avoided.

The invention discloses a K-means initial clustering center optimization method on the basis of neighborhood information and the mean difference degree. The method includes the steps that 1, a sampleset X={X1, X2, ..., Xi, ..., Xn} with n objects is input, the clustering number K is determined, and the current determined initial clustering center number k=0 is initialized; 2, a distance matrix Dis formed; 3, the neighborhood radius value delta is determined; 4, the number Ni of samples in the delta neighborhood of each sample point Xi is calculated, and a matrix N is formed; 5, the sample point Xi corresponding to the maximum sample number Ni in the delta neighborhood in N is regarded as the first clustering center C1, k=k+1, and the corresponding Ni in N is set as 0; 6, the sample pointXj corresponding to the maximum sample number Nj in the delta neighborhood in N is searched for, the distances between Xj and the clustering centers {C1, C2, ..., Ck} are calculated, and the corresponding Nj in N is set as 0; 7, if the distances between Xj and the clustering centers are not less than the mean difference degree M, k=k+1, C(k+1)=Xj, or Step 6 is returned to; 8, if the current clustering center number k is equal to the clustering sort number K, K initial clustering centers are output, or Step 6 is returned to; 9, the whole sample set is clustered by means of the K-means clustering algorithm, and a clustering result is output.