138results about How to "Adaptive strong" patented technology

The invention provides a gray scale image fitting enhancement method based on local histogram equalization. The gray scale image fitting enhancement method has advantages of improving gray scale image contrast and detail information and eliminating block effect and over-enhancement. The gray scale image fitting enhancement method comprises the steps of performing segmental linear transformation on a gray scale image in an overwide dynamic range, obtaining the gray scale image in an appropriate dynamic range, dividing an image gray scale distribution interval to two segments to multiple segments, adjusting the gradient of a segmenting point and a transformation line of each image gray scale distribution interval, performing expansion or compression on a random gray scale interval; performing subblock part overlapping histogram equalization on a transformation result, obtaining the transformation function of the current subblock through performing weighted summation on a subblock transform function in the neighborhood, performing histogram equalization processing on the current subblock by means of the transformation function; and performing nonlinear fitting on the gray scale map after histogram equalization, and performing histogram distribution correction on the gray scale image after subblock part overlapping histogram equalization.

The invention relates to an optimized design method for modelling of an end wall of a high load fan / compressor. The method comprises eleven steps. As the stage pneumatic load is improved, internal flow of the fan / compressor is more severe, massive secondary flow is easily generated in an area close to the end wall, and a risk of flow stall exists. The modelling of the end wall has important influence on control over the secondary flow in an end area of the high load compressor, and becomes an important research direction. Firstly, an end wall modelling parameter defining method is researched; secondarily, based on an adaptive genetic algorithm and an artificial neural network response surface model, which are developed by the research group, an orthogonal experimental design, end wall parameter definition and a flow field value simulating technology are combined to realize automatic global optimization of the end wall of the compressor; thirdly, the effectiveness of the optimizing method is verified through different test functions; finally, a blade grid of the compressor is subjected to nonaxisymmetrical optimization based on the method. A result shows that the blade grid after modelling has good pneumatic performance.

The invention discloses a process method for preparing a derived solid fuel by using sludge, and the method comprises the following steps: feeding dehydrated wet sludge with the moisture content of 70-85% and biomass at a weight ratio of 50:(1-10) into a tempering kettle, introducing less water, evenly stirring, adding a tempering agent the mass of which is 0-20% of that of dried solid sludge, stirring for 2-10 minutes continuously, removing most of water by a dehydrator, forming, and naturally drying for 24 hours, thus obtaining the derived sludge solid fuel. The invention also discloses a device for preparing a formed sludge fuel. The device comprises a straw crusher, a feeder, the tempering kettle, the stirrer, the fuel hydrator and a fuel forming machine, wherein the stirrer is positioned at the top of the tempering kettle, a stirring shaft is coincident with the axis of the tempering kettle and inserted into the tempering kettle, the outlet of the straw crusher is connected with the inlet of the feeder, the outlet of the feeder is connected with the inlet of the tempering kettle, the outlet of the tempering kettle is connected with the inlet of the fuel dehydrator, and the outlet of the fuel dehydrator is connected with the inlet of the fuel forming machine.

The invention discloses a fast intelligent commodity recommendation system. The recommendation system provides personalized services for customers according to own demands of a commodity provider. The recommendation system comprises a merchant demand analysis module and a commodity recommendation module. A merchant demand is expressed in a form of rules; and a customer transaction database stores transaction records of a merchant. The merchant demand analysis module evaluates commodities operated by the merchant according to the merchant demand and the customer transaction database to generate a commodity library to be recommended. The commodity recommendation module generates a recommended commodity list meeting the own requirement of a current customer according to the customer transaction database and the commodity library to be recommended to provide commodity services for the current customer. The commodity recommendation generated by the system is not only customized for the customer, but also is customized for the merchant, can greatly increase the sales and the profits for the merchant, can improve the service speed of the commodity recommendation system to realize real-time service, has high expandability, and can meet the requirements of large merchants.

Disclosed is a blind restoration method for the motion blurred image; the steps are as follows: (1) the image is converted through the cepstrum method to figure out the blur extent and the blur direction of the blurred image; (2) the blur extent and the blur direction of the blurred image figured out in step (1), and the total variation (TV) method are adopted to process the restoration towards the blurred image. The method based on the total variation (TV) includes: the fixed-point iteration used as the outer-loop and the conjugate gradient method used as the inner-loop are adopted for loop iteration to obtain the restored image. The blind restoration method has the advantages of strong self-adaptation, strong anti-noise ability and good robustness; the blind restoration method has validity and practicality according to the processing effects of the simulation picture and the photographed picture.

The invention relates to a construction method of a fuzzy neural network expert system for the water quality assessment in turbot culture, which comprises neural network modeling and network model testing. The method is characterized in that the neural network modeling comprises the following steps of: setting network training parameters, wherein sensitive indexes of the growth of turbots after three-tiered classification, which include four expert data of temperature, salinity, pH and dissolved oxygen, are used as input parameters; determining the network topology: constructing a three-layer neural network by using the input layers of four input nodes, the hidden layers of two hidden nodes and the output layer of one output node; and determining training samples. The network model testing comprises the steps of: leading in tested samples and assessing the network model. The invention combines the neural network, the fuzzy system and the on-line monitoring system for the water quality assessment in industrial turbot culture for the first time, avoids the operations such as manual setting and the like in the traditional assessment method, and overcomes the influence of human factors and the like on the assessment in the traditional turbot water quality assessment.

The invention provides a motor control method based on PI parameter self-tuning. Based on a traditional motor (permanent magnet synchronous motor) servo system, a genetic controller and a fuzzy controller are added. The genetic controller is adopted to optimize a fuzzy control rule, a quantification factor and a proportion factor in the fuzzy controller, and the optimal fuzzy control rule, quantification factor and proportion factor are obtained. At the same time, the fuzzy controller which is optimized by the genetic controller is adopted to carry out PI parameter self-tuning on a speed PI regulator, and thus the fact that the system has the optimal dynamic and static performance is ensured. The motor control method has the advantages that a genetic algorithm can search the global optimum, the fuzzy algorithm has strong adaptability and does not rely on a mathematical model of a control object, and the anti-interference ability is strong, thus the motor (permanent magnet synchronous motor) servo system has better dynamic and static performance and strong adaptive ability and better robust performance.

The invention relates to a video adaptive playing method and device and a storage medium, and belongs to the technical field of Internet. The method includes the following steps: obtaining width and height information of a to-be-played video, adjusting a screen playing proportion according to the width and height information, and performing non-full-screen video playing; and determining a full-screen mode according to the screen playing proportion when receiving an instruction of full-screen video playing, and adaptively performing full-screen display. The device includes a processor and a memory. A computer program is stored on the memory. When the computer program is executed by the processor, the video adaptive playing method is implemented. The computer program is stored on the medium.When the computer program is executed by the processor, the video adaptive playing method is implemented. Compared with the prior art, the video adaptive playing method and device and the storage medium have the advantages of good playing effect, strong adaptability, wide application range and the like.

The invention relates to a mirror-like object defect detection device and a detection method thereof. The mirror-like object defect detection device comprises an optical detection system, an industrial personal computer, a trigger controller, a motion controller and a three-axis servo module, wherein the three-axis servo module can drive the optical detection system to scan a detected object under the action of the industrial personal computer and the motion controller, the trigger controller can be communicated with the three-axis servo module and the optical detection system, and the optical detection system is communicated with the industrial personal computer. The optical detection system is used for collecting and analyzing surface data of the mirror-like object and comprises a linear array camera, an LED stripe light source, a plurality of diffuse reflection light sources, a Y-direction distance measurement and chromatic aberration detection assembly and an X-direction distance measurement assembly, and the defect detection device for the mirror-like object and the detection method thereof are high in collection efficiency and imaging quality, compact in system structure and low in cost.

The invention relates to tendon link under-actuated mechanical finger device which includes the first and second finger sections, under-actuated joint. The under-actuated joint includes joint axis, drive slider, tendon line, and spring piece. The joint axis is set at the first finger section. The second one is set at the joint axis. One end of the tendon line is fixed at the end of the second finger section. Another end is passed through the upper of the first one and connected with its lower. The drive slider is embedded in the first finger section and touched with the tendon line. The spring piece is set between the first and second knuckles. The device can be used as impersonated one finger or parts, or connected in series to form high under-actuated finger. The device has the advantages of simple, reliable structure, little volume, light weight, low control system demand.

The invention provides an embedded-system-based and modularly-designed charging facility data acquisition terminal, which takes combination of various wired communications and wireless communications into consideration, supports a 5.8G wireless ad hoc networking technology with strong penetrating power, is configured with a special security module, supports automatic updating of programs and remote configuration, realizes intellectualization of operation management, and achieves secure data interaction among an electric vehicle, a charging facility and a smart power grid. The data acquisition terminal supports automatic alarm, automatic record generation, accident judgment and handling and the like, further has strong functions of on-line self-diagnosis, self-healing, self-adaption and task timing, and realizes the intellectualization of operation management.

The invention discloses a high thrust rocket high flow telemetry data processing method, aiming to solve high flow telemetry data rapidly and accurately and having a good effect in practical use. The method comprises steps of building a telemetry data preprocessing model, and selecting and classifying the telemetry data in real time; and building a bus data real-time processing model, and solving the bus data of high flow in the telemetry data in real time. The effectiveness is also verified. The model established by the method is also applicable to processing telemetry data of the rocket in active duty, and is verified accurate and efficient in actual combats of the rocket in active duty and in joint training missions of the new generation high thrust carrier rocket.

A cascaded under-driven artificial finger of robot for simulating human finger has an active slide block inlaid in the first finger segment, a middle joint with the gear axle between the first and second finger segments and fixed to the second finger segment and the gear engaged with rack bar, the small and big gears on a single axle which along with two gear axles of middle joint are on the first finger segment, a synchronizing belt with lower gear fixed to small gear axle and upper gear fixed to the final joint axle on the second finger segment, and the third finger segment on the final joint axle.

The invention provides a feature selection method for complex pattern classification. On the basis of the traditional genetic method, the method allows a species group to be divided into a plurality of sub-species groups by improving the structure of the species group into a dicyclic intelligent agent network configuration. Information is passed among the sub-species groups through the sharing intelligent agent. The genetic evolution of all sub-species groups is conducted simultaneously. The improved dynamic neighborhood competitive operation and the neighborhood adaptive crossover operating method improve the efficiency of the genetic evolution. At the same time, binary coding mode is introduced to express whether a certain feature is selected or not, thereby facilitating coding and decoding, and achieving the high efficient feature selection. Compared with the traditional feature selection, the feature selection method has the advantages of higher adaptability, and quick search in feature space with high dimension and multimodal, thereby effectively avoiding being trapped in local extremum and acquiring relatively satisfied feature selection results.

The invention relates the technical field of air-conditioners, in particular to an active protecting control method of a variable frequency air conditioner compressor. Two temperature sensors are installed on a home use variable frequency air conditioner outdoor unit. The method includes the following steps that (1) the variable frequency air conditioner compressor is started, the opening degree of an electronic expansion valve is enabled to be operated preset time by a set original value; (2) BSH values are set according to different operational modes and four intervals are divided according to the different BSH values; (3) the opening degree of the electronic expansion valve is adjusted according to the intervals, wherein the BSH values are located in the intervals, the opening degrees of the electronic expansion valve in each interval can be limited between SFmin and SFmax; (4), when the opening degree value of the electronic expansion valve reaches the smallest opening degree SFmin, but the BUH values can also meet any one of a first interval, a second interval and a third interval in the step (3), and corresponding set is conducted to the frequency of the compressor. The active protecting control method of the variable frequency air conditioner compressor can guarantee reliable rotation of the compressor and prolong service life of the compressor.

The invention discloses a furnace-front quick evaluation method of structure and performance of gray cast iron in the technical field of steel casting and computer signal processing, and is used for solving the problems existing in furnace-front quick comprehensive evaluation research on the structure and performance of gray cast iron in a casting process. The method is mainly characterized by performing furnace-front acquisition on a cooling curve of gray cast iron in a thermal analysis sample cup of which the size is fixed, then, extracting an effective solidification segment of the cooling curve, and characterizing a melt state of cast iron by the integral shape of the effective solidification segment of the cooling curve. The new furnace-front quick evaluation method of structure and performance of gray cast iron, effectively provided by the invention, is high in self-adaptability and can avoid human factors; the method is used for setting up a database and adding new standard samples at any time, is relatively high in flexibility and is in favor of improving the yield of casting pieces.

The invention provides a corner detection method based on a neural network, which comprises the following steps: S1, preprocessing the collected image; S2, extracting the edge of the preprocessed image; S3, cutting the image including the edge into a plurality of sub-images with pixel size of m * n according to a fixed step size, and recording the coordinate label of each sub-image in the originalimage; 4, carrying out dimensionality reduction processing on each sub-image by using dictionary learning to obtain a sparse representation of each sub-image; S5, respectively inputting a sparse representation of each sub-image to a pre-trained neural network, and judging whether there are corner points in each sub-image according to the output value of the neural network. The invention also provides a storage medium and an image processing system corresponding to the method. The invention still has high corner detection accuracy for noise interference, line segment interference and pixel high contrast.

The present invention provides a method for detecting biochemical oxygen demand. Active sludge, surface water, domestic waste water, or industrial waste water comprising microorganism is taken as a water sample with microorganism in the method provided by the present invention. The water sample with microorganism is cultivated to obtain a microorganism film. The blank water sample and the target water sample are made to pass through the microorganism film respectively. The dissolved oxygen reduction current values of the blank water sample and the target water sample are detected. The difference value between the dissolved oxygen reduction current value of the target water sample and that of the blank water sample is obtained. On the basis of the difference value and the predetermined standard curve, the biochemical oxygen demand of the target water sample is acquired. The method provided by the present invention adopts active sludge, surface water, domestic waste water, or industrial waste water comprising microorganism as the water sample with microorganism. The environmental adaptability of the prepared microorganism film is strong, so that one or more of tap water, well water, atmospheric water, or ground water may serve as medium to maintain the physiological activity with no need of providing a buffer solution system.

The invention relates to an air conditioner temperature control system based on an RBF neural system and a control method thereof. The system comprises a RBF neural network PID controller, a controlled object, a Smith predictive compensator and a feedforward controller, wherein the RBF neural network PID controller and the controlled object are connected between the system input end and the systemoutput end in sequence, and parameters of the PID controller are adjusted in a self-adaption mode by adapting the RBF neural network; the Smith predictive compensator is connected between the outputend and the input end of the RBF neural network PID controller; and the feedforward controller is connected between the output end of the RBF neural network PID controller and the system input end. According to the air conditioner temperature control system based on the RBF neural network and the control method thereof, the parameters of the PID controller are adjusted in the self-adaption mode based on the RBF neural network, meanwhile, the Smith predictive compensator and the feedforward controller are combined, the characteristics of high response speed, small overshoot, short adjusting time, good dynamic property, high self-adaptability and the like are achieved, meanwhile, online parameter setting is achieved, accordingly, the control performance of the system is greatly improved, anda satisfactory control effect is achieved.

The invention relates to a vehicle body paint surface defect detection device and a detection method thereof. The vehicle body paint surface defect detection device comprises a servo controller, an industrial personal computer, a vehicle body conveying mechanism, a plurality of area-array cameras, a plurality of projectors and a plurality of projection screens, wherein the industrial personal computer is connected with the servo controller, and the servo controller is connected with the vehicle body conveying mechanism; the vehicle body conveying mechanism can drive a to-be-detected vehicle to move in the length direction and the height direction under the action of the servo controller and the industrial personal computer, the area-array cameras are distributed around the to-be-detected vehicle, the industrial personal computer is connected with the projector, the projection screen is arranged on the periphery of the projector and corresponds to the projector, The vehicle body paint surface defect detection device is high in acquisition efficiency, high in imaging quality, compact in system structure and low in cost.

The invention discloses a device and method for eliminating local oscillator leakage and relates to the technical field of mobile communication. The device comprises a coupler for carrying out local oscillator leakage signal extraction processing on an up-conversion signal or a down-conversion signal output by a frequency mixer to obtain a local oscillator leakage signal; an amplitude detection and adjustment module used for carrying out amplitude adjustment on the local oscillator signal according to the amplitude of the local oscillator leakage signal to obtain a local oscillator leakage amplitude offset signal equal in amplitude with the local oscillator leakage signal; and a phase detection and adjustment module used for carrying out phase adjustment on the local oscillator leakage amplitude offset signal according to the phase of the local oscillator leakage signal to obtain a local oscillator leakage offset signal equal in amplitude but opposite in phase with the local oscillatorleakage signal.

The invention provides an adaptive PCB plate defect visual positioning detection and classification system. A whole set of processes of PCB detection is covered. The system comprises an offline pre-processing contour point attribute classification stage, online PCB whole plate alignment, defect detection and defect classification. A template matching method is used to align a whole plate, and a speed is fast and precision is high. A contour out-of-tolerance algorithm is used to detect a defect, the precision reaches a sub-pixel level, the speed is fast, and universality is high. Attribute classification is performed on contour points so as to satisfy different tolerances generated because different types of defects match with different detection standards. In the invention, a detection speed and precision of a PCB are increased, detection efficiency is effectively improved, false detection or leak detection conditions of defects are reduced, the automatic detection of PCB surface defects is realized, manpower, material resources and financial resources are reduced, and an production automation degree is increased.

An under-driven adaptive mechanical finger has the first and the second knuckles, active plate and under-driven joint consisting of big gear axle, duplicate gear axle, small gear axle and spring linked between two knuckles. The said three gear axles are sleeved on the first bnackle. Its advantages are no need of own driver, lifelike appearance similar to human finger, small size, simple structure, light weight, low requirement to control system, and several degrees-of-freedom.

The invention discloses a switched reluctance motor fuzzy adaptive control system and method. The system comprises a fuzzy adaptive fractional PI controller, a PWM module, an asymmetric half-bridge drive circuit, a switched reluctance motor, a position detection module, a current detection module, a torque calculation module and a rotation speed detection module. The method comprises the steps: input parameters are sent to the fuzzy controller for fuzzification and the output dynamic parameters are used as the input of the fractional PI controller, and then the parameters are adjusted and inputted to the controlled object for control; amplitude limiting calculation of the torque error of the switched reluctance motor is performed to obtain the duty cycle of PWM output pulse, the working region of each phase winding is judged according to the rotor position angle, and the switching state of the asymmetric half-bridge drive circuit is determined by the PWM direct torque control algorithm; and the motor operation is controlled by adjusting the voltage of each phase winding. The system and the method are simple and reliable and have high robustness and realizes reasonable adjustment ofthe motor speed and improves the dynamic operation performance of the system.

The invention belongs to the technical field and discloses a method for measuring a refrigeration capacity of an air conditioner based on a BP neural network fitting method. The method comprises the steps that data at an air return hole and an air feeding hole of an indoor unit of the air conditioner is collected and integrated; indexes such as air enthalpy values at the air return hole and the air feeding hole of the indoor unit of the air conditioner are computed; the actual refrigeration capacity of the air conditioner is computed based on an air enthalpy value method; and steps such as detection of the actual refrigeration capacity based on the BP neural network fitting model are carried out. The method disclosed by the invention has the beneficial effects that the refrigeration capacity of the air conditioner can be detected without any dismounting of the air conditioner and without use of an expensive enthalpy difference lab; in addition, in comparison with other modeling algorithms, experimental devices needed are simple, and more accurate and controllable detection results can be obtained; and the method and results are reliable.

A shape-adaptive under-driven mechanical finger for robot is composed of a first finger segment, an under-driven joint and a second finger segment. The under-driven joint consists of an active slide block inlaid in the first finger segment, a joint gear axle fixed to the second finger segment, a rack bar fixed to the said active slide block and matched with the said gear, and a spring between the first finger segment and the active slide block. It can grasp objects with different shapes.

The invention provides an online soft measurement method. The method comprises the following steps: acquiring operating data as a sample sequence; building a CM-LSSVM-PLS online soft measurement predicting model to train the model; using a model prediction measured value, and dynamically updating the model if a prediction error does not meet the requirements. According to the online soft measurement method provided by the invention, the measured value can be predicted by a CM-LSSVM-PLS method, the prediction precision can be improved, and the modeling time can be reduced; furthermore, the prediction precision can be further improved by dynamically updating the model; meanwhile, the matrix inverse operation can be carried out by a simple matrix, an algorithm is relatively simple, a result can be quickly calculated, and the model can be ensured to be applicable to online monitoring requirements; in addition, the soft measurement system is driven by real-time data, the model can be continuously updated according to the real-time data, and the online soft measurement method has the advantages of being likely to acquire data, low in extra hardware investment, high in model prediction precision, strong in self-adaption and the like.

The invention discloses a washing machine control method and system based on cloud rules. The washing machine control method comprises the steps of detecting whether a washing starting signal is received or not; when the washing starting signal is received, judging whether a weight signal sent by a weight acquisition module arranged on a top cover of the washing machine is received or not; when the weight signal is received, collecting preset parameters of the washing machine, and inputting the preset parameters and the weight signal of the washing machine into a washing mode selection model to generate a target washing mode; and detecting whether a preset washing mode is set in the washing machine or not, and if yes, judging whether the target washing mode is matched with the preset washing mode or not, and according to the washing material, fabric, weight and other parameters of the washing machine, obtaining the optimal parameters by obtaining the cloud self-adaptive algorithm rule, and achieving precise washing, so that the situation that the washing machine is damaged due to overlarge load caused by incomplete washing or overlarge amount of clothes to be washed is avoided.

The invention discloses a wavelet de-noising method of optical-phase vibration. In a localized time-frequency analyzing method of which the size of a window (i.e. the area of the window) is fixed, but the shape of the window can be changed, and a time window and a frequency window can both be changed, a low-frequency part is provided with a wider time window and higher frequency resolution, and a high-frequency part is provided with a wider frequency window and higher time resolution, so that wavelet transformation has self-adaptability for signals so as to achieve the purposes of accurate de-noising and strong self-adaptability. Therefore, optical fibers can be accurately transmitted in a complicated electromagnetic environment.

The invention discloses a locomotive traction system fault diagnosis device and method. The device comprises a vehicle-mounted part and a ground part; the vehicle-mounted part further comprises an event recording unit and a vehicle-mounted data center unit, and the ground part further comprises a fault diagnosis unit and a ground data center unit. In a locomotive running process, the event recording unit collects data of a network control system and a traction converter in real time and stores the data as an event recording file. When data analysis is needed, the event recording file is transmitted to the ground data center unit through the vehicle-mounted data center unit in a wireless transmission mode, and data analysis is carried out. And the analyzed data is input to the fault diagnosis unit, fault diagnosis is carried out by using an established neural network, and the fault diagnosis unit steadily outputs specific reasons of the locomotive traction system fault. The technical problems that an existing locomotive traction system fault diagnosis device and method need to consume a large amount of manpower and material resources, and meanwhile the result is inaccurate can be solved.