242results about How to "Reduce the possibility of misjudgment" patented technology

The embodiment of the invention discloses a method for time domain noise reduction of a noise image and a related device. According to the embodiment of the invention, quantizing noise of a first block to which a first pixel point belongs can be combined to carry out moving and motionlessness judgment, the probability of erroneous judgment is very small, frame difference threshold values suitable for different zones with moving and motionlessness and different frame difference calculation modes are respectively set and adopted for the moving and motionlessness judgment of the first pixel point, integration factors suitable for the different zones with moving and motionlessness are selected aiming at the frame difference threshold values suitable for the different zones with moving and motionlessness and the frame difference calculation modes, and noise reduction and integration modes are selected aiming at the integration factors and the frame difference calculation modes suitable for the different zones with moving and motionlessness and a pixel value of the first pixel point on the current frame, so that noise reduction can be carried out aiming at different zones with moving and motionlessness of the noise image, the probability of error detection is very small, and the method and the device can be applied to various noise scenes.

The invention relates to an intelligent diagnosis method for bridge telescopic seam injury based on girder end longitudinal displacement. The long-term monitoring data of main girder longitudinal displacement, temperature and vertical acceleration after a bridge is built are obtained by mounting a small number of sensors on the bridge; a relevance model of the main girder longitudinal displacement, the bridge temperature and the vertical acceleration in a healthy state is established step by step; the influence of the main girder temperature and the vertical acceleration on the longitudinal displacement can be eliminated on the basis of the relevance model, and the environment condition uniformization displacement which can reflect a working state of a telescopic seam is obtained. When the method is applied to the injury diagnosis of the telescopic seam, the monitoring data in an unknown state are processed just by adopting the established relevance model, and finally, the environment condition uniformization displacement of the healthy state and the unknown state is simultaneously input into a mean value control map; and if the telescopic seam generates injury, a sample point of the control map can exceed a control line, thereby realizing the intelligent recognition on the injury of the telescopic seam.

The invention discloses a moving target tracking recovery method used for tracking a moving target. The method comprises the steps of: detecting the foregrounds of a current image when a tracked target is lost, obtaining foreground targets, and obtaining a pre-estimated position of the tracked target according to the lost position of the tracked target; when the tracked target is determined to be lost, matching characteristics of candidate targets with characteristics of the tracked target, and obtaining a matching value of each candidate target by means of calculation; and according to the matching values and distances to the pre-estimated position, obtaining the candidate target largest in a weight value, using the candidate target as the original tracked target, and carrying out tracking continuously. The invention further discloses a device corresponding to the method. The method and the device have the advantages that under the condition that the tracked target is lost, matching and pre-estimating are carried out according to the detected foreground target, the foreground target which is most likely to be the original tracked target is obtained, and tracking is continued, so that the tracking continuity is good.

A reverse detection method and device of an air conditioner compressor. The method comprises: determining that an air conditioner runs in a heating non-defrosting mode, a refrigeration mode, or a dehumidifying mode; collecting compressor air discharging temperature (Tt) and an air conditioner running current (It); calculating an air discharging temperature difference (ΔΤ); and determining whether the air discharging temperature difference (ΔΤ) is higher then a preset temperature difference and whether the air conditioner running current (It) is within a preset current range, and if yes, determining that the compressor runs in reverse. Also provided is a reverse detection device of an air conditioner compressor. The method and the device ensure safe and stable running of a compressor, and therefore ensure safe and stable running of an air conditioning system.

The present invention provides a method and an apparatus of determining video image jitter and camera device jitter. The video image jitter determining method comprises the steps of acquiring multiple feature points in a video image at a first moment; tracking the multiple feature points, and determining at a second moment whether content in the image moves drastically according to tracked feature points; if the content in the image does not move drastically, determining a quantity of unmatched feature points in the tracked feature points; and determining, according to the quantity of the unmatched feature points, whether the video image at the second moment jitters compared with the video image at the first moment.

The invention discloses a detection method for repeated position defects in a batch of wafers. The method comprises the steps that the batch of wafers which needs defect detection is provided, and all the wafers are provided with identical coordinate systems; all defect positions of each wafer are obtained, and corresponding defect coordinates are obtained according to the coordinate system; a random defect coordinate of the wafer is compared with defect coordinates of all the other wafers to mark defect coordinates which are repeated for at least one time as repeated defect coordinates; and according to all the repeated defect coordinates , a simulated defect distribution map is generated. The method can be used to clearly identify repeated circuit defects, and the possibility of engineering determination errors is greatly reduced.

The embodiment of the invention provides an adaptive real-time video data anti-cheating method and apparatus. The method comprises: an IP address of real-time video data and a plurality of corresponding playing users are obtained; the IP address is obtained, and a first risk probability and a second risk probability are generated adaptively according to a video playing frequency value at the IP address within a first preset time period and a video playing frequency value of each of a plurality of playing users within the first preset time period; whether the first risk probability exceeds a first preset threshold value is determined to determine whether the IP address is a cheating IP address and whether the second risk probability exceeds a second preset threshold value is determined to determine whether the user is a cheating user; and then the cheating IP address and the cheating user are added into a black list base and the real-time video data of the cheating IP or cheating user are filtered. Therefore, the degree of identifying whether the real-time data are cheating data can be improved; the large-IP multi-user wrong determination possibility can be reduced; and re cheating of a high-risk playing user can be prevented.

The invention provides a learning state determination system and method. The system is composed of an eye movement detecting device and an intelligent terminal. The eye movement detecting device is suitable for detecting eye movement data of a learner within a preset period of time and sending the eye movement data to the intelligent terminal. The intelligent terminal is used for dividing a gazingarea and analyzing a division result and the eye movement data to obtain concentration and / or attention distribution of the learner. The gazing area is divided based on the learning content and the eye movement data and the division result are analyzed to obtain the concentration degree of the leaner, so that the concentration degree of the leaner is observed well. Meanwhile, on the basis of theanalysis of the eye movement data and the division result within the time, the possibility of false determination caused by determination based on the state at a certain time is reduced.

The invention relates to a power system transient state voltage stability evaluating method based on misclassification cost classified learning, which belongs to the power system stability analyzing and evaluating field. Based on dynamic measurement datum of a synchronous phasor measuring unit, a key subsequence closely related to the power system state is extracted from a time sequence constituted of a large amount of dynamic measurement datum; by setting different misclassification costs of stable power system and unstable state, a weight coefficient is introduced into a learning sample; a decision-making tree algorithm infused with the sample weight coefficient is used to perform classified learning so as to acquire a decision-making tree model; and the decision-making tree is used for online monitoring to implement evaluation to the power system transient state voltage stable situation.

The invention relates to a method and system for measuring the frequency of a single coil vibrating instrument, wherein the method comprises the following steps: firstly, exerting alternating swept-frequency exciting signals on the two ends of a frequency measurement coil in the single coil vibrating instrument so as to drive a steel string to perform mechanical vibration; then, canceling the swept-frequency exciting signals, and forming induced voltage signals at the two ends of the frequency measurement coil, wherein the frequency of each induced voltage signal is consistent with that of the mechanical vibration of the steel ring; carrying out data acquisition on the induced voltage signals by virtue of an AD (analog-digital) converter, and carrying out FFT (fast fourier transform algorithm) spectrum analysis on the signals (acquired by the AD converter) by virtue of a digital signal processor; and finally, extracting the basic frequency signals in the spectrum according to a maximum value method, and then obtaining the frequency measurement value. The method provided by the invention has the advantages of increasing the anti-interference capacity, and improving the accuracy and reliability of frequency measurement of the single coil vibrating instrument.

The invention relates to a method for jointly evaluating the insulation state of oil paper by using multiple statistical parameters, characterized by comprising the following steps of: using an ultra-wideband partial discharge detection system to perform partial discharge detection on the oil paper insulation in a power device; collecting and extracting the partial discharge statistical parameters of the oil paper insulation; by analyzing the change trends of seven statistical parameters, evaluating the insulation state of the oil paper insulation in the power device; and if NpSEC and Hn_Sk present a monotone increasing trend and the alfa, beta, Qmax, Hn_mean and Hqn_Kur present a monotone decreasing trend, judging that the oil paper insulation in the power device is in a deterioration state. The method can be used for forecasting the hazard degree of the partial discharge before the insulation has fault. The method can be used for preventing the insulation fault and reducing the fault possibility of the power device caused by insulation fault, has high accuracy and low dispersivity, is convenient to realize, and does not influence running of the power device.

The invention provides a monitoring method for running safety of an electric vehicle. The method comprises steps as follows: firstly, determining the torque requirement, and then calculating the power requirement for meeting the torque requirement; secondarily, calculating and taking one or more kinds of actual torque and / or one or more kinds of nominal torque of a current electric drive system as a torque parameter, and then calculating and taking one or more kinds of actual power of the electric drive system as a power parameter; finally, comparing the torque requirement with the torque parameter and / or comparing the power requirement with the power parameter for failure judgment, so that the running safety of the electric vehicle is monitored. The safety performance of the vehicle is judged by using two characteristics, namely, torque and power, problems that only the torque characteristic is used, the judging method is single and erroneous judgment and missing judgment can be caused easily in the prior art are solved, the vehicle safety is monitored by using the power characteristic and the torque characteristic, multi-aspect redundancy check can be performed by using various signals, the failure detection sensitivity is increased, and the detection credibility is increased through mutual check.

The invention provides a gesture identification method and apparatus. An input image of a target scene comprising a hand portion is obtained, an image of the hand portion is extracted from the input image, a to-be-identified gesture classification result is obtained by classifying the image of the hand portion by use of a classifier, a rule feature is extracted from the image of the hand portion, and a gesture identification result is obtained by applying the rule feature to the to-be-identified gesture classification result. In such a way, weak classifier and strong rule determination technologies are integrated, the classifier is not directly applied to final identification of various gestures, and the various different gestures are further distinguished by applying a strong rule to the to-be-identified gesture classification result of the classifier, such that advantages of the rule feature and a classifier feature complement each other, while the gesture identification accuracy is improved, the possibility of misjudgement is reduced, and robust identification of static gestures is realized.

The invention belongs to the field of manufacturing and assembling of numerical control machine tools and discloses a diagnosis method for feed shaft assembly faults based on instruction domain analysis. The diagnosis method includes the steps that a, a machine tool runs according to a designated code G aiming at manufacturing resources to collect working task data and feed shaft running state data; b, target data is extracted from the running state data according to line numbers, and feature vectors are calculated; c, feature vector sample sets of different fault tasks are established; d, a feature vector judgment model is established; e, feature vectors of actual faults are calculated and substituted into the judgment model for classification and diagnosis. According to the method, the numerical control machine tool collects the running state data through a numerical control system, the collected data is good in stability and low in cost, mechanization and intelligence of fault diagnosis are achieved by establishing the feature vector sample sets and the judgment model, labor intensity is reduced, and detection accuracy and robustness are improved.

The invention relates to a microsatellite instability detection device capable of improving result accuracy, computer equipment and a computer storage medium. The microsatellite instability detectiondevice screens out a sensitive MS site consistent with existing sensitive MS site data from screened credible MS loci according to the existing sensitive MS site data; filtering the screened sensitiveMS site, and screening unstable MS sites; and carrying out scoring analysis on the unstable MS sites of a tumor sample. According to the microsatellite instability detection method, the problems existing in the traditional technology are fully considered, on the basis of sensitive MS site data established in the earlier stage, a more accurate result can be obtained by using a lower sequencing data volume, and due to the small data volume, the whole processing flow is faster and higher in efficiency, and the occurrence of false positive and false negative results can be effectively reduced.

The invention provides a method and a system for detecting the deformation of a transformer winding. The method comprises: acquiring response end voltage and exciting end voltage of the transformer winding to be detected under different frequency; calculating a transfer function module value of the transformer winding to be detected according to the response end voltage and the exciting end voltage; drawing a frequency response curve in a coordinate system according to the transfer function module value under different frequency, and drawing a frequency response curve in the coordinate system when the transformer winding is normal; pre-processing the two frequency response curves by using an erosion method to obtain curve data satisfying a preset condition, and calculating relevant coefficients of the two frequency response curves; and judging the deformation condition of the transformer winding to be detected according to the magnitude of the relevant coefficients and relevant coefficient preset values. According to the method, the two frequency response curves drawn in the coordinate system are pre-processed by using the erosion method, so that burrs are removed, interference of noise such as electromagnetic signals and the like is avoided, the accuracy of diagnosis is improved, and the probability of misjudgment is reduced.

The invention discloses a single-phase grounding fault line selection method based on discrete orthogonal S transform and information divergence. The method includes the following steps that: voltagecollecting devices are installed on lines respectively so as to collect the transient voltage signals of each feeder line during a line fault; a data processing module is connected with the voltage collecting devices and converts the transient voltage signals into zero-mode voltage components; the data processing module sends fault starting signals to an upper computer, and a zero-sequence currentcollecting module installed on the lines collects the zero-sequence current signals of each feeder line and sends the zero-sequence current signals to the upper computer, discrete orthogonal S transform is performed on the zero-sequence current signals, so that the information divergence of each feeder line is obtained, a line with the largest information divergence is a single-phase grounding fault line. With the method of the invention adopted, the information divergence is solved through initial-half-wave zero-sequence current parameters, so that the selection of a single-phase grounding fault line in power distribution lines can be realized; the capacity of the discrete orthogonal S transform to divide the frequency bands of the transient signals and the capacity of the information divergence to distinguish the small differences of the signals are comprehensively considered, and therefore, the reliability of line selection is improved.

The invention discloses a cell empty carport identification system based on RFID signal intensity and assistant camera video, which comprises cell roadside carports, active RFID tags distributed at the roadside carports, monitoring cameras, an RFID reader, a network switch and a PC server, wherein the active RFID tags are distributed at the roadside beside the carports; the RFID reader is distributed at the roadside opposite to the cell roadside carports and is provided with an Ethernet interface; and the tracking network cameras are provided with Ethernet interfaces and connected with the PC server via the network switch. The 2.4 GHz RFID reader reads changes of RSSI values of the RFID tags arranged at the roadside beside the carports, and with the help of video analysis of the cell monitoring cameras, empty carports at the roadside can be accurately and quickly identified.

The invention discloses an intelligent alarming method and an intelligent alarming system. The method comprises the following steps: enabling a first terminal to establish a short distance communication connection with a second terminal, acquiring the wireless signal strength of the short distance communication connection, if the currently acquired wireless signal strength is lower than the preset alarm threshold value of the wireless signal strength, reading the stored wireless signal strength acquired last time, according to the currently acquired wireless signal strength and the acquired wireless signal strength acquired last time, acquiring an attenuation ratio of the wireless signal strength, and if the attenuation ratio is less than the preset proportion threshold value, giving out an alarm. According to the intelligent alarming method disclosed by the invention, the short distance communication connection is established between the two terminals, so as to realize communication or information exchange; the alarming accuracy can be improved to a greater extent by judging whether the surroundings interfere the communication or the distance between the two terminals exceeds the prompting range according to the attenuation ratio of the wireless signal strength, and further the possibility of misjudgment can be reduced as far as possible.

The embodiment of the invention provides a fault diagnosis method and device based on an action current curve of a switch machine. According to the method, feature data corresponding to current curvesamples marked with a fault type is pre-stored, target feature data of the action current curve of the switch machine about to be subject to fault diagnosis is acquired, target current curve samples similar to the current curve are screened out of the current curve samples according to the target feature data and the feature data corresponding to all the current curve samples marked with the faulttype, a target fault type is determined according to the fault type corresponding to all the target current curve samples, and the target fault type is the type of a fault of the switch machine. Through comparison with the current curve samples marked with the fault type, automatic recognition of the fault of the switch machine is realized, the accuracy of fault recognition is improved, the possibilities of missing judgment and misjudgment are lowered, and fault recognition efficiency is improved.

The invention provides an auxiliary control method and device for lowering the fan load under the gust condition and a fan controller, and relates to the technical field of wind power generation. Themethod includes the steps that whether gust occurs or not is judged according to rotating speed acceleration; when gust occurs, a pitch variation rate is calculated according to pneumatic resultant moment of a fan and pneumatic features of blades; and the blades are regulated according to the pitch variation rate. The rotating speed acceleration of the fan is selected as a threshold value variablefor judging occur of gust, thresholds under different wind speeds are obtained through comprehensive calculation according to operation power, a pitch angle and other variables of the fan, and thus the possibility of missed judging and erroneous judging can be reduced to the maximum extent. Meanwhile, the variation intensity of the speed of gust is represented by air moment, and thus output of apitch angle instruction is controlled according to the air moment; time delay is reduced in the control process, reaction is more sensitive, control is more timely and effective, the pitch angle control process for involving in or exiting normal power generation is smooth, and the influence on the pitch angle in normal operation is small.

The invention relates to the field of automobile safety, and discloses a triggering method of automatic emergency braking system based on prediction, comprising methods for triggering primary alarm, secondary alarm and emergency brake, and meanwhile, the invention also discloses a movement locus predication algorithm of the current automobile and a front automobile. According to the invention, three stages after the system is started is divided according to three stages, namely, primary alarm, secondary alarm and emergency brake, according to the operation mode of the automatic emergency braking system, and meanwhile, a deceleration curve of the automatic emergency braking system is designed according to the difference of the secondary alarm manner of the system and the response characteristic of the vehicle brake system; and in the actual operation process, triggering of various difference stages of the automatic emergency braking system is realized by performing predication computation on the current vehicle and the front vehicle, and therefore, the triggering method has the advantages of being accurate and reliable in triggering, and low in erroneous judgement and missed judgement rate.

The invention relates to an on-site relay protection reliability control apparatus and a relay protection method. A starting control module is used for performing starting logic discrimination according to received corresponding data information; a main control module is used for performing protection logic discrimination and starting logic discrimination according to received corresponding data information; and when the starting logic discrimination performed by the starting control module and the main control module are both in action, and the protection logic discrimination performed by the main control module is in action, a protection action signal is output. The relay protection way is performed by two layers of logic discrimination; and firstly, a condition that the two starting logic discrimination are both in action is satisfied, and the protection action signal is output according to the protection logic discrimination only after the two starting logic discrimination are in action, so that the relay protection method lowers possibility of on-site protection faulty action, thereby still satisfying relay protection high-reliability requirement in an extremely severe operation environment.

The invention belongs to the field of short text auditing, particularly relates to a short text auditing method and device fusing variant word recognition, and aims to solve the problem of how to fusea variant word recognition technology into a harmful text auditing task and realize automatic updating of a model. The method comprises the steps of constructing a configuration word bank, obtainingto-be-audited text data based on a social media platform, screening the to-be-audited text data to obtain suspicious text data, removing meaningless information, and calculating a text feature vectorand a statistical feature vector; and performing feature fusion on the text feature vectors and the statistical feature vectors, obtaining harmful texts through a trained harmful text classification model based on a support vector machine, obtaining sensitive words of the harmful texts by utilizing a preset keyword extraction algorithm, and writing the sensitive words into a configuration word bank. According to the method, the variant word recognition technology is fused into text feature and statistical feature calculation to carry out harmful text auditing tasks, automatic model updating isachieved, and the text auditing accuracy and updating speed are improved.

The invention relates to a method for detecting probe wear and a probe, in particular to a method for online real-time detecting probe wear, the probe and the manufacturing method of the probe. The probe comprises: a probe main body, which comprises at least one needle head; a detecting layer, which coats the needle head or the whole probe main body; and an impact-resistant layer, which is formed on the detecting layer and coats the detecting layer, in order to increase the degree of impact resistance of the probe. The detecting layer with eye-catching color is manufactured inside the probe, which leads the detecting layer of the probe to be exposed after the probe wears, while, the eye-catching color of the probe at the detecting layer serves as a mark, therefore, the online personnel can easily and instantly judge whether the probe wears.

The invention discloses a method for diagnosing defects of an intelligent substation secondary system based on multi-parameter information fusion. The method comprises the following steps of: 1) establishing an information fusion model for diagnosing the defects of the secondary equipment; 2) establishing an expert database for diagnosing and analyzing the defects of the secondary equipment; 3) collecting original data information of the secondary equipment; 4) performing information fusion; and 5) outputting a diagnosing result. According to the method disclosed by the invention, on the basis of reference to the existing information fusion method, according to the collected reference data and electric power test data, a self-adaptive algorithm is utilized to optimize a network and information induction-deduction technique; the defects of the electric secondary equipment are comprehensively diagnosed; the relation network is constructed by dividing the defect characteristic parameters according to the logic relation between different defect characteristic information; the defect reasons of the secondary equipment can be reflected from different sides; the elementary probability distribution assignment for an evidence is improved according to the output of uncertain reasoning of the evidence; the reliability of the evidence for recognizing single disabled mode is fully reflected.

The invention discloses a mold detection method for an electric injection molding machine. The method comprises the steps of obtaining a residue-free rectangular standard mold image as a standard template image, removing a background region of the standard template image to obtain a mold region, normalizing the size of the standard template image to LXL, segmenting the standard template image into m sub-template images with the sizes of WXW, and extracting an eigenvalue of each sub-template image; collecting a to-be-detected mold image after mold opening, extracting an edge image of the to-be-detected mold image, and segmenting out the mold region of the image; normalizing the to-be-detected mold image to LXL, segmenting the to-be-detected mold image into m sub-images with the sizes of WXW, and extracting an eigenvalue of each sub-image; and comparing the eigenvalues of the sub-template images of the standard template image with the eigenvalues of the sub-images of the to-be-detected mold image to obtain a status of residues of the to-be-detected mold image. According to the method, the status of the residues in a mold can be quickly and accurately detected, so that the detection efficiency is improved and the automation degree of the mold processing industry is increased.

The invention provides a method for detecting indoor and outdoor scenes. The method includes: obtaining satellite positioning information about a mobile terminal by detecting a satellite positioning system; determining whether the mobile terminal is currently in an indoor environment or an outdoor environment based on a historical detection result recording situations that the mobile terminal is in an indoor or outdoor scene and the satellite positioning information. The method of the invention can improve the detection accuracy of the indoor and outdoor scenes.