34results about How to "Reduce false alarm probability" patented technology

The invention discloses a fault reconstruction method for a simple redundancy flight control system of a long-endurance unmanned aerial vehicle. The redundancy is formed for the measurement of key navigation information by using two devices of main and backup sensors on the basis of the non-similarity principle, and two redundancies are guaranteed on an execution mechanism, so that the simple redundancy flight control system is formed. A comparison is made between information of the main sensor and the information of the backup sensor; when the times of the deviation of the information of the main and backup sensors greater than the threshold in unit time are more frequency, one sensor is broken down; the fusion is implemented through other normal navigation information for locating the broken device; and when one execution mechanism is broken down, the influence of the broken mechanism is complemented through the rest normal execution mechanisms to guarantee the flight safety.

The invention discloses a power distribution network information physical side risk early warning method and system, and the method comprises the steps: obtaining a risk factor feature set from a riskdata source of a power distribution network information physical side based on a risk factor category, and carrying out the screening, and obtaining an optimal risk factor feature set; substituting the optimal risk factor feature set into a pre-constructed risk level online prediction model to obtain a current power distribution network information physical side operation risk level; and performing early warning processing based on the risk operation level. According to the scheme, risk data of an information side and a physical side of the power distribution network are fully considered forscreening to obtain an optimal number risk factor feature set, so that the calculation efficiency and the early warning precision of risk level prediction of the information physical system of the power distribution network are improved; based on various risk data of the information side and the physical side of the power distribution network, different types of different risk data are considered,so that independent screening is carried out, the risk prediction precision of the information physical side of the power distribution network is improved, and the probability of error early warningis reduced.

The embodiment of the invention discloses a power transmission line channel hidden danger target distance measurement method, and the method comprises the steps: obtaining two-dimensional image data and three-dimensional point cloud data of a power transmission line channel, and obtaining the two-dimensional position information of a hidden danger target according to a target segmentation network model; if the two-dimensional position information of the hidden danger target is in the preset channel three-dimensional protection area, mapping the two-dimensional position information of the hidden danger target into three-dimensional point cloud data through a preset ground data mapping model to obtain three-dimensional coordinate position information of the hidden danger target; and according to the three-dimensional coordinate position information of the hidden danger target and a preset lead data mapping model, obtaining distance information between the hidden danger target and a lead. According to the method, the dense information advantage of the two-dimensional image data and the precision advantage of the three-dimensional point cloud data are comprehensively utilized, and more effective early warning information is provided for the safety of the transmission line channel.

The invention relates to a method applied to equipment fault diagnosis and intelligent early warning of a monitoring system. The method comprises the following steps that 1, an independent alarm analysis logic and an independent restoration analysis logic are established on the basis of a fault model of each alarm; 2, the alarm logics and the restoration logics are controlled to be executed in a mutually exclusive mode; 3, delay processing is conducted on alarm events and restoration events; and 4, alarm events generated after delay processing are subjected to cascade relation establishment, alarm cascade groups are established according to the relation among different alarm events, whether or not the alarms in the same cascade group exist simultaneously in a certain time is automaticallyjudged by taking generation of the alarm events as a triggering condition, and association information among the alarm events is generated. Compared with the prior art, the method has the advantages of decreasing the false alarm generation probability and the invalid alarm number, reducing the storage space overhead, the system CPU consumption and the workload of maintenance personnel and the like.

A method of detecting a received signal, which is received by a receiving side of a communication system, is disclosed. The present invention includes comparing signal quality relevant information of the received signal to a prescribed reference value, selecting a pre-processing scheme to be applied to the received signal according to a result of the comparing step, and detecting a signal by applying the selected pre-processing scheme to the received signal. Thus, a pre-processing scheme for received signal detection can be differently applied according to a size of quality relevant information of a received signal. Accordingly, the present invention lowers a false alarm probability and/or a miss occurrence probability of the received signal, thereby raising a signal detection probability.

The embodiments of the invention disclose an application layer slow-speed attack detection method and a correlation apparatus. The application layer slow-speed attack detection method comprises the following steps: obtaining a flow entering a server; based on the obtained flow entering the server, counting the quantity of transmission layer empty chains initiated to the server within preset duration; and if the counted quantity of the transmission layer empty chains is greater than or equal to a first threshold and the quantity of application layer data packets carrying a destination internetworking protocol address i and a public network gateway interface identification j in the flow entering the server within k periods accords with a preset threshold condition, performing application layer slow-speed attack alarm on the destination internetworking protocol address i and the public network gateway interface identification j, wherein the destination internetworking protocol address i is one of internetworking protocol addresses of the server. According to the technical scheme provided by the embodiments of the invention, the accuracy of the application layer slow-speed attack alarm is improved.

The invention discloses an automatic gain control system and method for an active phase scanning ground reconnaissance radar. The system comprises an array antenna, a T/R assembly, a frequency synthesizer receiver, a wave control board, an electronic compass and a signal processing unit. The amplitude characteristics of fixed ground object echoes under different wave beam orientations in a radar scanning range after intermediate frequency digitization, down-conversion decimation filtering, pulse compression and the like are measured by presetting the receiver gain, and a receiver gain controlcode in each direction is determined, thereby realizing an automatic gain control system for adaptively adjusting the receiver gain along with the change of the ground object environment where the radar is located. The receiver gain can be adaptively adjusted according to the ground object echo power when the antenna beam points to different orientations so that overflow distortion of strong ground object orientation echo sampling is ensured not to occur and weak ground object orientation echo cannot be attenuated, the quantization performance of the AD chip can be fully utilized, the detection performance of the radar can be enhanced and the false alarm probability can be reduced.

The invention discloses a digital channelization receiver pulse detection system, comprising: a channel, a module (1) for obtaining a maximum value, a module (2) for obtaining a maximum value, and a threshold detection module (3). Wherein the number of modules (1) is equal to the number of channels, the signal amplitudes of each channel are calculated by using the I and Q signals of n channels, the maximum values of the n signal amplitudes are searched for, the maximum values are compared with a fixed threshold, the signal is judged to be present when the threshold is passed, otherwise no signal is obtained. The invention belongs to the technical field of signal processing. According to the characteristics of the signal, the invention judges whether the signal exists or not by comparing the maximum amplitude value with the threshold value, reduces the false alarm probability, and saves a large amount of hardware resources at the same time.

The invention relates to a fault identification and positioning method and system of an intelligent photovoltaic power generation system. The fault identification and positioning method comprises the following steps: S1, obtaining an association coefficient of a photovoltaic power generation unit relative to other photovoltaic power generation units; S2, establishing a fault determination basis of the photovoltaic power generation unit; and S3, carrying out fault identification and positioning on a faulted photovoltaic power generation unit. According to the invention, on the basis of discrimination of distances among all units and real-time combined generation efficiencies of all the units of the photovoltaic power generation system, data analyses are carried out to realize accurate identification and positioning of faults of the intelligent photovoltaic power generation system, thereby substantially reducing the false fault alarm probability and improving fault identification accuracy and fault positioning precision of the intelligent photovoltaic power generation system. Meanwhile, no extra professional fault diagnosis device is needed for the photovoltaic power station and thus costs are lowered. The method and system have broad application prospects.

The invention provides an early warning method and device for equipment performance and monitoring equipment. The early warning method comprises the steps: determining S performance periods of to-be-monitored equipment in a sampling time period according to the change trend of the performance data, collected in the sampling time period, of the to-be-monitored equipment along with the time; dividing any one performance period Ti in the S performance periods into m sub-time intervals, and determining a first fluctuation interval corresponding to the jth sub-time interval according to the performance data of the to-be-monitored equipment in the jth sub-time interval in each performance period; and determining a second fluctuation interval corresponding to the jth sub-time interval according to the similarity between the Tijth sub-time interval and each Tkjth sub-time interval. According to the early warning method, the current performance data of the to-be-monitored equipment is collected, and whether the performance of the equipment is early warned or not is determined according to the current performance data, the first fluctuation interval and the second fluctuation interval, so that the early warning missing probability is reduced while the early warning range is expanded, and the early warning accuracy is improved.

The invention discloses a Radon-Fourier transformation (RFT) blind speed side lobe (BSSL) suppression method. The method comprises the steps that a radar system alternately transmits three linear frequency modulation signals of different pulse recurrence intervals (PRIs), radar echo signals are received, and demodulation and pulse compression are conducted; according to the principle of RFT, the radar echo signals corresponding to the three PRIs are subjected to RFT processing, and thus three sets of long-time phase-coherent accumulation speed-distance two-dimensional results are obtained; theminimum values of the three sets of RFT processing results are taken in pairs for processing, and three sets of minimum value results are obtained; and the maximum value of the three sets of minimumvalue results is taken, and thus a final processing result is obtained, and BSSL suppression is achieved. According to the method, BSSL suppression is achieved, the false alarm probability is decreased, and thus the system detection probability is increased.

The invention relates to a magnetic anomaly multi-feature information extraction method based on Hilbert-Huang transform. Non-linear and non-stationary magnetic anomaly signals are processed through Hilbert-Huang Transform (HHT), magnetic anomaly multi-feature information based on instantaneous energy density and marginal spectrum is extracted by conducting empirical mode decomposition and Hilbert spectrum analysis on the signals, and effective feature information selection is provided for magnetic anomaly detection based on a machine learning framework. According to the invention, the multi-feature information of the magnetic anomaly signal in the time-frequency domain can be obtained through the Hilbert-Huang transform processing of the signal, and the feature information selection in the magnetic anomaly detection is enriched. In the magnetic anomaly detection method based on the machine learning framework, the time-frequency domain multi-feature information of the magnetic anomaly signal is helpful to improve the detection capability of a magnetic target under a low signal-to-noise ratio, and the false alarm probability of target detection is reduced.

A data fusion based safety surveillances system has a first through N^th virtual monitoring systems and a data fusion and decision device. The data fusion and decision device defines an i^th detection model of the i^th virtual monitoring system, and estimates an i^th detection loss probability of the i^th virtual monitoring system according to detection loss sample numbers of batches of i^th monitored data of the i^th virtual monitoring system under conditions corresponding to the locations, batches of context data and existence of intruder, the i^th detection model, the batches of i^th monitored data corresponding to locations of the i^th virtual monitoring system and the batches of context data. The data fusion and decision device determines a fusion parameter set according to the first through N^th detection loss probabilities, and performs data fusion on a first through N^th detection results to generate a decision result.

The invention discloses an on-off target passing signal conditioning and checking device which comprises a CPLD checking control unit (1) and a signal conditioning unit (2). The CPLD checking controlunit (1) is used for producing 32 sets of single-pulse signals through a CPLD so as to check the system time interval measuring accuracy. Two paths of single-pulse signals are included in each set, and the time interval between the signals is certain. The signal conditioning unit (2) is used for conditioning external input pulse signals and CPLD output signals by setting a comparator threshold level, eliminating noise influences in a circuit and avoiding spurious triggering. The output end of the CPLD checking control unit (1) is connected with the input end of the signal conditioning unit (2). According to the on-off target passing signal conditioning and checking device, the triggering probability is ensured, and the false alarm probability is low.

The invention belongs to the technical field of tracking and positioning, and discloses a patient position tracking system. The patient position tracking system comprises a monitoring terminal, a positioning terminal and a positioning base station, wherein the number of the positioning base stations is multiple, and the positioning base stations are in communication connection with the positioning terminal and are arranged in a monitoring area constructed by the monitoring terminal; calibration information is preset in the positioning base station, the calibration information comprises a preset position and a preset positioning height of the positioning base station, and the positioning base station is used for positioning the positioning terminal within the preset positioning height in real time and transmitting the real-time positioning position to the positioning terminal in a communication manner; the number of the positioning terminals is multiple, and the positioning terminals are in communication connection with the monitoring terminal and are worn on the body of a patient; and the positioning terminal comprises a position processing module, and the positioning terminal is used for processing the real-time positioning position through the position processing module and transmitting the processed position to the monitoring terminal in a communication manner.

The invention discloses a high-frequency ground wave radar clutter classification method based on a U-Net network, and belongs to the field of radar clutter classification. The high-frequency ground wave radar clutter classification method solves the problem that an existing high-frequency ground wave radar clutter classification method is not high in accuracy. The method comprises the following steps: acquiring a distance Doppler spectrum of a high-frequency ground wave radar echo; preprocessing the distance Doppler spectrum to obtain an ionized layer clutter enhancement spectrum and a first-order sea clutter enhancement spectrum; training the ionosphere clutter recognition network and the first-order sea clutter recognition network by using the training set to obtain a trained ionosphere clutter recognition network and a trained first-order sea clutter recognition network; inputting high-frequency ground wave radar clutters to be classified into the trained ionized layer clutter recognition network and the first-order sea clutter recognition network at the same time, and obtaining two clutter recognition results; and combining the ionized layer clutter recognition result and the first-order sea clutter recognition result to obtain a clutter classification result of the high-frequency ground wave radar echo distance Doppler spectrum. The invention is used for high-frequency ground wave radar clutter classification.

The invention discloses a false alarm suppression method for an emplacement radar, and the method comprises the steps: firstly extracting the trace point features of a target, and carrying out the trace point filtering processing; secondly, extracting track characteristics according to a target track, and extracting ballistic characteristics such as an emergence angle, an emergence direction and a speed by using the track; and generating a confidence coefficient matrix according to the track features and the trajectory features, and then performing processing by using an SVM algorithm to identify a real target and a false alarm. In a strong clutter and interference environment, the false alarm probability of the emplacement radar can be obviously reduced; extra information does not need to be obtained, processing can be completed on the basis of existing target information, and the design requirement for the radar is reduced; reliability of the radar is greatly improved, and economic cost and time resources are saved.

The invention discloses an LAA method and an LAA device of wireless communication. UE is used to receive high-level signaling, and K carriers are determined. First information is transmitted on a first carrier. UCI related to a target carrier can be transmitted on the K carriers, and K is a positive integer greater than one. The first carrier is one of the K carriers, and the first information comprises at least one of first HARQ-ACK and first CSI. The first HARQ-ACK is used to indicate whether a transmission block on the target carrier is correctly decoded, and the first CSI aims at the target carrier. The stability of the HARQ-ACK transmission is guaranteed, and consumption of uplink resources of authorized carriers is reduced, and integrated frequency spectrum efficiency of a system is improved.

The invention discloses a wireless network positioning method with high target identification performance based on a GMP (Greed Matching Pursuit) algorithm. Through the method, the target identification performance under the condition of unknown target number is enhanced. The method comprises the following two positioning stages: acquiring the possible positions of most targets by using a conventional GMP algorithm, introducing a redefined threshold value, and selecting the possible positions of more targets from the rest of grids in order to lower the loss probability of the targets; and removing certain abnormal values from target position estimation values by using a least square (LS) method in order to lower the false alarm probability of the targets. As proved by an experimental result, compared with a conventional GMP method, the method has higher target identification capability under the situation of unknown target number.

The invention discloses a DTMF signal detection device. The system comprises a total energy threshold judgment unit, a Goertzel algorithm DFT amplitude calculation unit, a DFT amplitude basic criterion unit, a sub-band FFT energy calculation unit, a sub-band FFT energy enhancement criterion unit and a DTMF double-audio-frequency retrieval unit which are connected in sequence. The invention also discloses a DTMF signal detection method. According to the DTMF signal detection method and device, the accuracy and the stability of DTMF signal detection in a complex environment, namely an interference condition, are improved through a dual judgment mode of DFT operation and judgment and FFT operation and judgment, and the false alarm probability is reduced.

The invention discloses a method for preventing real-time system false alarm. An automation system is adopted in the method, wherein the automation system designs a temporary cache region, the automation system designs an equipment state variable, and the automation system designs the retention time of the temporary cache region. The method comprises the following steps that the automation systemacquires the equipment state; the automatic system records the equipment state in the temporary cache region, and the equipment state record storage duration of the temporary cache region is the retention time of the temporary cache region; the automation system records the latest state of the equipment in the equipment state variable; after the timing of the temporary cache region is finished, the automatic system compares the value in the temporary cache region with the value of the equipment state variable; and an equipment alarm is generated. The retention time of the temporary cache region is 5 seconds, and a temporary cache region state retention timer is designed by the automatic system.