230results about How to "Have pursuasive power" patented technology

The invention discloses a power transmission and transformation equipment state overhauling system based on risk evaluation. The system consists of a software supporting module, an equipment information collecting module, an equipment state diagnosing and evaluating module, an equipment risk evaluating and analyzing module, an equipment overhauling strategy auxiliary decision making module and an evaluating and checking module. The six modules are sequentially connected and mutually supported from bottom to top to form a pyramid type decision making flow path. The invention implements one set of complete system on the data information and equipment maintenance of a power network, makes a dynamic, timely, high-reliability and economic maintenance plan for the power transmission and transformation equipment under the condition of carrying out quantitative calculation on risks, greatly reduces the unnecessary maintenance, decreases the equipment damage caused by maintenance, saves the maintenance and management cost, and enhances the reliability of the power network.

The invention relates to a method for identifying abnormal microblog users. The method comprises the steps of obtaining a plurality of users' microblog data, storing the microblog data into a database, taking statistical distribution of time intervals of user behaviors as behavior time characteristics of the users according to the microblog data of the users, generating behavior time characteristic vectors and defined parameters, calculating Kullback-Leibler divergence between the behavior time characteristic vectors of the normal users and the behavior time characteristic vectors of the users to be detected, judging the users to be detected with the calculated Kullback-Leibler divergence exceeding the defined parameters as the abnormal users, and extracting and showing keywords of contents of the abnormal users. The invention further provides a system for identifying the abnormal microblog users corresponding to the method. According to the method and system, the keywords of the blog article contents of the abnormal users can be extracted quickly, promulgators of junk information such as marketing and advertisements can be identified accurately, and the method and the system are applicable to detection of multiple microblog service platforms, and has the advantages of high accuracy and efficiency and wide applicability.

The invention discloses a method, a device and a system for testing the connectivity of switches by connecting all ports of a switch to be tested with a testing switch respectively. Broadcast messages are sent to a port to be tested on the switch to be tested and the number of the broadcast messages sent is recorded; the number of the broadcast messages received which are forwarded by the switch to be tested is recorded at all ports of the testing switch; the number of the broadcast messages received and the number of the broadcast messages sent are compared, if the numbers are the same, the port to be tested of the switch to be tested has no fault, or otherwise, the port to be tested of the switch to be tested is at fault. The proposal provided by the embodiment of the invention can effectively improve the connectivity testing efficiency of switches and the testing result is more convictive.

The invention discloses an omni-mobile balance capacity assessing and training system of stroke patients. The omni-mobile balance capacity assessing and training system structurally comprises a fixingdevice, a safe device, a moving device, a data collecting device, a data processing and displaying device and a visual interference device; on the basis of multi-mode signal collecting and processingand by combining friendly human-computer interaction between voice prompt and the tested persons, a human body balance capacity assessing virtual task based on the Unity 3D design is completed by thestroke patients, information such as age, gender, stature, weight, pressure center path, heart rate, blood pressure, electromyographic signal and joint angle of the stroke patients are obtained accurately, and balance capacity assessing results of the stroke patients are comprehensively given; the system can further automatically formulate a corresponding training scheme according to the assessing results, and balance capacity training of the stroke patients is achieved by combining a balance capacity training game in VR glasses; and the omni-mobile balance capacity assessing and training system is simple in structure, easy and convenient to operate, capable of moving omni-directionally and high in reliability, and has good promotional value.

The invention discloses a multifunctional electrical characteristic testing device and a multifunctional electrical characteristic testing method for a high-voltage circuit breaker. The testing device consists of a dynamic resistance detection module, a non-synchronism detection module, a displacement sensor, Hall current sensors, a data acquisition card, an industrial control computer and an industrial display screen, wherein a super capacitor is used as a power supply for the detection of loop resistance, and impact current with a peak value of 1,000A is used as detection current. The testing device is a multifunctional testing instrument integrating the detection of loop resistance, closing resistance, closing resistance running time and mechanical characteristics of the high-voltage circuit breaker.

The invention discloses a motor vehicle exhaust smoke video identification system. The motor vehicle exhaust smoke video identification system comprises a video acquisition unit, a video data processing unit and a data center unit, wherein the video acquisition unit comprises an industrial network camera, the video data processing unit comprises an industrial control computer, and the industrial control computer comprises a vehicle tracking and processing module, a license plate identification and processing module, a vehicle speed measuring module and a vehicle exhaust monitoring module. The motor vehicle exhaust smoke video identification system has properties of simple structure, good robustness and no linkage equipment and has no equipment linkage coupling problem. Multi-lane monitoring, excessive vehicle discharge monitoring and license plate recording can be accomplished at one step, position recording is intelligible, and video recording is more persuasive. According to the motor vehicle exhaust smoke video identification system, the industrial network camera and the industrial control computer are only needed to realize processing on the lanes such as vehicle exhaust monitoring, license plate identification, smoke detection, vehicle velocity measurement, cost for equipment and mounting is greatly saved, and smoke detection efficiency is improved.

The invention discloses an assembly time evaluating method based on an artificial neural network and a virtual assembly. The method comprises the step of establishing a virtual working platform, planning a DELMIA assembly sequence and a DELMIA path and generating an assembly path, the step of generating the assembly sequence through a constraint matrix method and establishing the constraint relation among components, the step of preassembling the product components through a DELMIA assembly module, establishing a priority dismounting matrix, extracting the assembly sequence meeting the condition from the priority dismounting matrix and planning the assembly sequence through the strong data collecting capacity of the matrix, the step of establishing a virtual assembly work environment and the virtual assembly action process, the step of measuring the assembly path and calculating the assembly time, the step of establishing an assembly time evaluating model, the step of establishing the model and standardizing a sample, and the step of evaluating the sample. The assembly time evaluating method solves the problems that the product assembly period is long, cost is high, and the effect is poor.

The invention relates to a method for determining the position and the agglomeration intensity of a city core area. A city built-up area geometric centroid, a city population distribution centroid and a city road traffic accessibility centroid are determined in a map for the city built-up area, every two centroids are connected together to obtain an area, namely the city core area position; and the size of the core area corresponds to the agglomeration intensity of each centroid, that is, the smaller the size of the core area is, the higher the agglomeration intensity of the center area is. The invention provides a technology method for determining the position of the city core area, with the characteristics of integrity of theoretical basis, objectivity of data selection, scientificalness of calculation method, pertinency of space types or the like. The method used for determining the position and the agglomeration intensity of the city core area has more scientificalness, rationality and operability and provides a good platform for research on the core area.

The invention provides a finite element modeling method based on a real material microstructure. According to the method, various kinds of digital image technical processing are carried out on SEM scanned pictures, conversion from bitmaps to vector diagrams is achieved, and accordingly the real material microstructure can be mapped into a two-dimensional finite element model. By means of threshold segmentation, gray processing, binarization processing, repeated switch-off and switch-on operations and the technology converting the bitmaps into the vector diagrams, defects presented in the images or reinforcements are clearly segmented from a substrate, and besides attributes of the defects or the reinforcements can be respectively defined in finite element software. According to the method, a high-precision finite element model of the real material microstructure is built directly through the SEM pictures, a digital model is close to a real structure, and authenticity of the finite element model in the calculation process and in calculation results is improved. The method can be widely used in the field of optimization design field taking the defects and heterogeneous material performance judgment into consideration.

The invention discloses a robot joint reducer test bed. The robot joint reducer test bed is characterized by comprising a driving motor, a measured robot joint reducer, a loader, an output tray, a torsion spring, a turntable device, an angle sensor and a control system, the turntable device applies an initial turning angle on the torsion spring, the output tray applies torque to the measured reducer, the driving motor drives the measured reducer to rotate, the loader applies radial force on the measured reducer, and input and output test parameters of the measured reducer are respectively acquired by the aid of a sensor and the angle sensor. Real working conditions of the robot joint reducer can be simulated, experimental reliability is increased, energy consumption is reduced, and automatic control performance is improved.

The invention provides a system and a method for subjective assessment of stereoscopic videos. The system comprises a server, a client side and a comprehensive assessment system, wherein the server is used for storing assessment task information and video sequences; the client side is used for acquiring the assessment task information in the server, acquiring a plurality of corresponding video sequences from the server according to the assessment task information, recording user information and playing current to-be-assessed video sequences according to user's choices so as to store assessment scores after the user completes assessment of the current to-be-assessed video sequences, and uploading the user's assessment score of each video sequence of the video sequences and the user information to the server; and the comprehensive assessment system connected with the server is used for making statistics on user number according to the user information and analyzing all the assessment scores according to the user number so as to obtain final assessment results. According to the embodiment, mutual interference among assessment staff is lowered, and assessment objectivity is guaranteed so that the assessment results are more authoritative and persuasive.

The invention relates to a big-data analysis system. According to the system, various data collection manners can be utilized to collect data; an encrypted data signal is formed by the collected datathrough encryption processing; the encrypted data signal is transmitted to a data storage module through a data transmission module; the encrypted data signal is transmitted to a data analysis serverby the data storage module; and in the data analysis server, firstly, the encrypted data signal is decrypted through a data decryption module, detection, marking, classification and analysis are sequentially carried out on a decrypted data signal through a data detection module, a data marking module, a data classification module and a data analysis module, then a data analysis result is obtained,the data analysis result obtained by the data analysis module is evaluated through an evaluation module, and finally, deviation correction is carried out on an unqualified data analysis result through a correction module. Accuracy of the big-data analysis system is improved.

The invention provides an experience route generation method based on probe vehicle data. Firstly, original probe vehicle data are extracted and processed, and invalid and abnormal points belonging to a light condition and at the positions which do not belong to service scopes of a target starting point and a target terminal point are removed; a model is built according to the principle that direction element weighting is higher than distance element weighting to enable locating points to be matched on a road section; then an experience route threshold value is calculated according to numbers of the location points and the length of a shortest path which are matched to the road section, the road section is considered to be an experience route section if the matched locating point number per kilometer exceeds the experience route threshold value, and an experience route net is composed of each experience route section; and finally a simple loop-free route calculation algorithm is loaded on the experience route net to obtain an experience route. The experience route generation method combines characteristics of sparsity, drifting, magnanimity and the like of the probe vehicle data, a generated route set can be used for guiding a traveler to reasonably select traveling routes, reasonable route set references can be provided for traffic designers, and the method serves as a tool for traffic administrators to formulate route induction strategies.

The invention discloses an evaluation method and device of microblog-platform-oriented topic recommendation. The method includes the following steps that multiple pieces of microblog text in a microblog platform are obtained from the internet; the multiple pieces of microblog text are subjected to word dividing; word frequencies of the multiple pieces of microblog text subjected to word dividing are obtained to obtain the microblog content; according to the microblog content, unsupervised topic recommendation information is obtained; according to the Euclidean distance between the word vector of the unsupervised topic recommendation information and the word vector of a preset integrated testing topic, and the evaluation result is obtained. By means of the evaluation method in the embodiment, the recommendation topic obtained with the unsupervised method can be automatically evaluated, the unsupervised topic recommendation method of the microblog platform is effectively and automatically evaluated and detected, the effectiveness of the unsupervised method is determined accordingly, labor can be saved, and the evaluation result is more persuasive.

The invention discloses an overhead line fault probability prediction method based on a comprehensive state health degree. The overhead line fault probability prediction method is characterized by comprising calculation of four factors of an overhead line, wherein the factors comprise aging, health degree, external weather and operation conditions. On the basis of data completeness, an algorithm can be used for calculating the fault probabilities of all lines at a time at each monitoring interval, early warning can be conducted on the lines with the high fault probabilities, the parts with many deduction items are displayed to serve as early warning reasons, and the health degree evaluation method is digitalized in rule and does not depend on evaluation after manual observation any more. The data acquisition difficulty is low, the information is comprehensive, the evaluation interval is small, and the risk change condition of the line can be continuously reflected; and the prediction result is more persuasive, and the expansibility of the proportional risk model is stronger.

The invention discloses a cold supplement asphalt mixture low temperature working performance testing device and testing method. The testing device comprises a temperature chamber and a penetrometer, wherein the temperature chamber is used for keeping the cold supplement asphalt mixture at the constant temperature during the whole testing process, and the penetrometer is used for testing the low temperature working performance of the asphalt mixture; a charging basket used for accommodating a cold supplement asphalt mixture sample is arranged on the temperature chamber, a penetration hole is formed in the top of the temperature chamber, and a glass tubular column capable of preventing the penetrometer from moving left and right during falling is mounted in the penetration hole; the penetrometer extends into the asphalt mixture in the charging basket via the penetration hole. The cold supplement asphalt mixture low temperature working performance testing device is designed for testing the low temperature working performance of the cold supplement asphalt mixture, so that the device can quantitatively test the low temperature working performance of the cold supplement asphalt mixture and the testing result has stronger persuasion. The testing device is simple and easy to take along, the operation is convenient, the testing process is fast, the test can be conducted at any time, and the device is more suitable for testing the low temperature working performance of the on-site cold supplement asphalt mixture.

The invention relates to a method for establishing a mathematical model of damage rate evolution of recycled concrete under freeze-thaw, Because of the application of damage mechanics, The freeze-thawdamage degree of recycled concrete is defined by dynamic elastic modulus, and the freeze-thaw damage experiment of recycled concrete is designed. Then the relationship model between freeze-thaw damage degree of recycled concrete and different freeze-thaw cycles is established by quick freezing method, and the damage rate evolution mathematical model of recycled concrete under freeze-thaw is obtained. Therefore, the method for establishing a mathematical model of damage rate evolution of recycled concrete under freezing and thawing is based on macroscopic damage mechanics theory, and has a solid mechanics theory foundation compared with previous research methods, and the result accords with objective law and mechanics principle, and the conclusion obtained is accurate, clear and convincing. Compared with the previous research methods, the process of the damage rate evolution mathematical model established by the invention is controllable, the period is short, and the time and the costare greatly saved.

The invention provides a particle swarm optimization algorithm based thermal generator set primary frequency modulation parameter optimization method, and relates to the technical field of thermal generator set primary frequency modulation. According to the invention, an optimization algorithm is introduced into primary frequency modulation control parameter configuration, and mathematical modeling, constraint conditions, an objective function and optimization procedures of the particle swarm optimization algorithm based thermal generator set primary frequency modulation parameter optimization method are provided. Primary frequency modulation dead zone and rotating speed diversity factor parameter configuration taking that the additional economic expenditure required by increasing the coal consumption in the process of primary frequency modulation to be minimum, that is, the primary frequency modulation control economy, as an objective and taking the stability as a constraint is realized, thereby positively responding to the policy of energy conservation and emission reduction under the premise of ensuring the power grid frequency security, and exploring the economy in primary frequency modulation.

Provided is a solar cell life prediction method based on current attenuation. The method comprises: performing modeling analysis on current attenuation of solar cells, providing two kinds of mathematics models of linear and power function, and then through the two models, respectively performing prediction on residual life of a solar cell. The method performs analysis and degeneration modeling from a current angle, and observation is easy and calculation is convenient, and results can be obtained through quantitative analysis. The method accurately and visually analyzes variation trend of current, and the variation trend is supported by reliable models, so results are more accurate, persuasive, and are better in adaptability. The method can be widely used in life tests of solar cells. The basic models can be widely used in life prediction of various kinds of solar cell pieces.

The invention provides an automatic simulation impact force determination device for high-pressure water jet punching. The automatic simulation impact force determination device comprises a fixed device, a pressure determination and confining pressure simulation device and an automatic lifting device. The automatic simulation impact force determination device is suitable for carrying out test determination on punching pressure, punching flows and test piece damage degrees by different coals under different confining pressures and different punching angles. Evidences are provided for selecting outburst-prevention pressure flows of underground high-pressure water punching. The device has a simple structure, and the automation of height adjustment is realized; the confining pressure is relatively convenient to adjust; and data acquisition, recording and processing are relatively intelligent. The device is convenient to fix, mount and debug, and has low requirements on operators.

The invention discloses an electric charge risk prevention and control model construction method based on a logistic regression algorithm, and belongs to the technical field of electric power operation. In the prior art, a scientific and objective evaluation method cannot be carried out on superior and inferior customers, so that effective encouragement or punishment measures cannot be provided for customer behaviors, one-household-one-strategy cannot be implemented in a targeted manner, and maintenance of rights and interests of power supply enterprises is not facilitated. According to the invention, based on customer electricity utilization direct behaviors, association behaviors and the like, a data mining algorithm is adopted to calculate and output the factual risk clients and the potential risk clients, and risk assessment is carried out respectively, so that the power supply enterprises can actively deal with the electric charge recovery risk, the electric charge recovery risk is ensured to be controllable, controllable and controllable, the electric charge management is ensured to be standard and efficient, one-household-one-strategy is convenient to implement, maintenanceof rights and interests of the power supply enterprises is facilitated, and the scheme is feasible and convenient to program.

The invention discloses a performance evaluation method for a self-adaptive cruise control system. Firstly, for a high-grade road, a self-adaptive cruise control system performance test scene based onfront vehicle speed time varying is established; secondly, for comprehensively and accurately obtaining vehicle motion parameters in the testing process, the testing method is improved on the aspectof the methodology, and motion state parameters such as the position and the speed of a vehicle are accurately estimated through an improved self-adaptive Kalman filtering algorithm; and finally, based on the accurate recursive vehicle motion state parameters, multi-dimensional self-adaptive cruise control system performance evaluation indexes are proposed and quantified, and the self-adaptive cruise control system performance evaluation index system is constructed. According to the evaluation method provided by the invention, the defects that the test scene does not accord with the reality,the evaluation index is relatively single and the like in an existing method are overcome, and high-precision, reliable and comprehensive scientific quantitative evaluation of the performance of the self-adaptive cruise control system in a complex scene is realized.

The invention relates to a method for detecting softness of hairiness on surface of clothing and a detection apparatus thereof, and relates to a method for detecting quality of a weaving product and an apparatus thereof, and especially relates to a method for detecting quantity and softness of hairiness on surface of clothing and the detection apparatus thereof. The method comprises the following steps: selecting a model of human body, embedding a touch force sensor, obtaining the touch force data and contact form image data generated by contact of hairiness on the surface of clothing and the model of the human body, and quantification performance index for reflecting softness of hairiness on surface of clothing and evaluating wearing comfort level of the clothing is constructed through data analysis. According to the method and the apparatus, the high-precision touch force sensor is employed for obtaining the data, a contact state image of the hairiness on the surface of the clothing and the model of human body can be obtained by an optical image collection unit, operation is convenient and simple, experiment data is objective, precision is high, and reliability is strong; the touch force sensor is used for directly obtaining contact force of fiber and skin but not frictional force, and the contact force is closer to the contact force influence of real wearing hairiness of the clothing and the human body.

The invention relates to a movie recommendation method, in particular to a cross collaborative filtering recommendation method. According to a project-based collaborative filtering algorithm (Intem-based CF) principle, an inter-movie similarity calculation strategy is designed, and a serialized similarity dictionary of each movie is solved; model-based collaborative filtering algorithm (Model-based CF)- A Slope One algorithm is combined with a local similarity principle to carry out scoring data filling on an unscored movie, so that the sparsity of a scoring matrix is greatly reduced; and on the basis, providing a user comprehensive similarity calculation model fusing the score similarity and the average weighted interest similarity among the users, and then finishing movie recommendationof the target user by applying a user-based collaborative filtering algorithm (CF). Compared with similar methods, the movie recommendation accuracy can be remarkably improved.

The invention discloses an ore dressing comprehensive index prediction method based on an ore blending product property. The ore dressing comprehensive index prediction method of the invention can determine an ore blending product property affecting a comprehensive index of the ore dressing product by combining with a site condition and professional experience, collects history data of the ore blending product property and the ore dressing comprehensive index, fits out a relation between the ore blending product quality and the ore dressing comprehensive index through a BP neural network algorithm and stores the relation as a function, and inputs various properties of the ore blending product to obtain a prediction value of the ore dressing comprehensive property. The ore dressing comprehensive index prediction method based on the ore blending product property is based on data modeling, combines an optimal algorithm with the professional experience, fast and accurately predicts the ore dressing comprehensive property and provides a basis for formulating an ore dressing strategy. Meanwhile, the ore dressing comprehensive index prediction method changes the current prediction method relaying on artificial experience determination and improves enterprise working experience.

The invention provides a gas pipeline leakage recognition method based on deep learning in a strong background noise environment. Firstly, valve leakage and gasket leakage are simulated on a laboratory pipeline leakage simulation system and a leakage sound signal is acquired, meanwhile, a strong background (fan) noise signal is acquired in an actual pipe rack, and the leakage signal and the actualbackground signal are mixed to simulate the leakage condition in the actual pipe rack. Each each type of audio data is segmented to obtain a large number of short-term audio signals, short-time Fourier transform is performed on the audio signals, then feature enhancement processing is performed, and an enhanced feature matrix is mapped into a time-frequency map to form a dataset for underground comprehensive pipeline rack leakage detection. Then, a convolutional neural network model suitable for gas leakage detection is constructed. The feature enhancement and neural network are combined to constitute a complete and effective gas pipeline leakage detection scheme. The gas pipeline leakage recognition method can effectively improve the leakage recognition accuracy under the interference ofstrong background noise.

The invention discloses an experimental device of torsion of big-opening ships sailing in waves and an operation method. The experimental device comprises a sink, a ship model, a sensor system, a signal conditioning and sampling system and a terminal, wherein the ship model is provided with a big opening; the terminal is provided with a display unit; the ship model is connected with sink walls at the two ends of the sink by an axle longitudinally penetrating through the torsion center of the ship model; the ship model can carry out torsion with the axle as the center; a plurality of baffles are arranged in the space from the ship model to the sink walls and the sink bottom surface; one ends of the baffles are fixed on the sink and the other ends are connected with the ship model by flexible films; and the space is divided into a plurality of unit watertight cavities surrounding the ship model by the baffles and the flexible films. The experimental device can be used for vividly and intuitively demonstrating and verifying the harms of torsion to big-opening ships to attract attentions of students to torsion of the big-opening ships, so that the students more intuitively know the knowledge that the ships are subjected to torsion in waves, thus effectively improving the teaching effects.

The invention relates to a compression fault zone structure well logging recognition method. The compression stress environment is analyzed, target well drilling and logging curves are selected, crack sensitivity parameters are worked out, all the parameters are subjected to normalization computing, and a synthetic discriminant parameter FZI of a fault zone internal structure is established. According to the method, the fault zone internal structure can be effectively recognized through well logging data, and the selected curve type is conventional standard well logging, so that the method has quite high operability.

The invention discloses a multi-protocol high-speed pseudorandom signal loopback test system based on an FPGA. The system comprises an FPGA part and an upper computer part; the FPGA part is connectedwith the upper computer part through a USB interface, and the FPGA part comprises an FPGA chip, two four-channel small optical fiber pluggable transceivers, eight single-channel optical fiber pluggable transceivers, a dual-channel USB chip and a programmable crystal oscillator; the upper computer part comprises a flow rate control module, a random number seed generation module, a data flow direction definition module, a programmable crystal oscillator control module, a rate error rate calculation module, a data flow protocol redefinition module, a USB data framing module, a USB data de-framingmodule, a USB driver and a graphical user interface display module. The invention provides three different loopback test modes to meet the requirements of different tested systems, and has a very high application value in the performance test of a high-speed communication system.

The invention discloses a detection method for a copper grade of a copper block. The method comprises the steps of (1) acquiring images and extracting ROI; (2) extracting texture features from the ROI; (3) judging quality of the ROI; (4) calculating a color vector angle; (5) determining types of a to-be-detected copper block; and (6) calculating the copper grade. The detection method can automatically finish copper block section positioning and ROI acquisition under a complex background, select out the ROI with qualified quality base on the texture features and finally estimate the copper grade rapidly by mixed Gaussian regression with relatively high precision. The invention also discloses a detection system for the copper grade. The detection system is based on an embedded platform of ARM + DSP dual-core chips and acquires the image by using an industrial camera. The detection system is easy to carry, greatly reduces cost, is very suitable for productization, and has the advantages of full automation, no contact, no damage, continuation, real time and high accuracy.