376results about How to "Reduce the effects of noise" patented technology

An equipment fault diagnosis method successively comprises fault diagnosis training steps and fault diagnosis operation steps. The method focuses on a data form characteristic essence and combines a multi-dimensional segmentation fitting algorithm and an optimized dynamic time warping algorithm based on equipment fault data to carry out pattern expression of modeling and distance threshold extraction, and extract form characteristics from the found equipment abnormity data to carry out mode matching, so that an equipment data fault type can be identified and a reason diagnosis function is realized. In this way, the difficulties in current fault diagnosis technologies that similarity degrees among the fault data can hardly be described efficiently and accurately can be solved.

The invention discloses an equipment fault diagnosis method based on multidimensional segmentation fitting. The method successively comprises a fault diagnosis training step and a fault diagnosis operation step. The method realizes mode expression and distance threshold extraction functions of modeling through combining a multidimensional segmentation fitting algorithm and an optimized dynamic time bending algorithm by focusing on the essence of data form characteristics on the basis of equipment fault data, and realizes equipment data fault type identification and cause diagnosis functions by performing mode coupling through extracting form characteristics of discovered equipment abnormal data, thereby solving the problem of incapability of efficiently and accurately describing the similarity degree between fault data by use of a conventional fault diagnosis technology.

The invention discloses a random sampling consistency-based characteristic line detection method for a three-dimensional point cloud. The method comprises the following steps of: detecting a plurality of planes in the point cloud based on random sampling consistency; and applying the random sampling consistency to boundary points, which are taken as candidate points, of each plane parameterization area so as to obtain a final characteristic line. Therefore, the influences of noise, exterior points and data loss are reduced effectively, the detection robustness of the characteristic line is enhanced greatly and time efficiency is improved.

The invention relates to systems for receiving a digital radio signal and, more particularly, to receivers of radio signals, coded with a pseudo-noise sequence, which are used in global positioning system GPS (USA) and GLONASS (Russia), allowing a compensation effect for the narrow-band interference by using a device, controlled by the processor, with an automatic gain control, multilevel analog-to-digital converter, and additional correlation channel for detection of sinusoidal interference consisting of the digital generator having quadrature mixers and accumulators. Information from output of the of accumulators is read by a processor, in which is detected the presence (or absence) of interference, and the amplitude is evaluated. Therefore, the processor generates control signal directing amplification in the device using an automatic gain control.

The invention relates to RMB counterfeit identifying technologies, and provides a counterfeit identifying method and a counterfeit identifying system based on zebra crossing infrared image characteristics. The counterfeit identifying method comprises the steps of A, acquiring an infrared image of RMB and carrying out preprocessing on the acquired infrared image; B, extracting HOG characteristics of the preprocessed infrared image and selecting HOG characteristics which satisfy preset conditions from the extracted HOG characteristics; and C, carrying out counterfeit identifying according to the selected HOG characteristics. The counterfeit identifying method based on the zero crossing infrared image characteristics acquires a zebra crossing anti-counterfeit image of the RMB by adopting infrared light, and carries out processing and identifying on the zebra crossing anti-counterfeit image by using an improved HOG and a support vector machine, thereby being capable of effectively eliminating noise effects and improving the performance of infrared image counterfeit identifying, and being capable of improving the accuracy in counterfeit identification for authentic and counterfeit banknotes.

The invention discloses a method for detecting the structural damage of a beam based on a Teager energy operator-wavelet transformation curvature mode. The method comprises the following specific steps: measuring a vibration shape signal of the beam under inherent frequency; performing wavelet transformation on a vibration shape through Mexico wavelet to obtain a wavelet transformation curvature mode; applying a Teager energy operator to the wavelet transformation curvature mode to obtain the Teager energy operator-wavelet transformation curvature mode; judging the structural damage of the beam by judging whether a singular value peak occurs on a large scale in the Teager energy operator-wavelet transformation curvature mode, and determining the damage position along the scale. The method can be used for analyzing the vibration shape signal of a beam structure so as to judge whether the damage exists or not and position the damage. Compared with a conventional curvature mode based method, the method has the obvious effects that the environment noise influence is eliminated, and the characteristics of the damage are strengthened. The method can be matched with an advanced sensor such as a laser scanning vibration meter and is widely applied to detection on the structural damage in a noise environment.

The invention provides a non-destructive testing system for testing the internal quality of a fruit by using near-infrared spectra. The non-destructive testing system comprises a collector and a microcomputer, wherein the collector comprises a collecting probe (3) and an optical fiber probe (6) which penetrates through the interior of the collector; an elastic light-shading pad (11) and a correcting wheel (1) are arranged on the collecting probe (3); the correcting wheel (1) is connected with a step motor (2); and the step motor (2) is connected with the microcomputer (22). A whiteboard and a blackboard which can be automatically switched and a through hole are designed inside a light path of the collecting probe to automatically collect the total reflection reference spectrum, a dark spectrum and a sample spectrum and automatically calibrate the spectra, so that noise influence on a detector is reduced; the elastic light-shading pad is arranged at the front part of the collecting probe to prevent interference of ambient light to the near-infrared spectra; and an automatic collecting switch is triggered by a force generated during contact of the elastic light-shading pad and a tested object, thus achieving automatic collection of the spectra.

The invention relates to a method for beam hardening correction in medical image. Beam hardening within the context of medical imaging projection image profiles are split up into a basic profile which is assigned to a homogeneous object area and into a detailed profile which is assigned to an inhomogeneous object area. On the basis of the basic profile and of the difference profile the mass occupancy of the different components in the object to be examined can be approximately determined. On the basis of the approximately determined mass occupancy the correction of the beam hardening can then be performed directly on the projection data.

The invention discloses an anti-noise quick fuzzy-clustering digital image segmentation method. The method includes the steps of performing feature extraction of an image to be segmented to obtain a feature data set X of the image; using the feature data set X and neighborhood information of the image to perform anti-noise pretreatment of an original image; initializing a cluster center by a K-means algorithm; calculating a fuzzy membership matrix; updating the fuzzy membership matrix through a space function based on space information construction; calculating the cluster center and a targeted function value used for implementing cluster segmentation based on the updated fuzzy membership matrix; performing loop iteration; and acquiring probability of data points belonging to a certain type according to a fuzzy membership matrix subjected to cluster output, and segmenting the image by performing classification markup to each data point according to the maximum probability principle. Satisfactory image segmentation effect can be obtained with few iterative times, influence of noise is eliminated well, and quality of image segmentation and stability of segmentation effect are increased.

The invention provides a differential absorption spectrum air quality inspecting system, which comprises a photo source, a photo source launching device, a photo source receiving device, a spectroscope, photovoltaic conversion equipment and a data processing system. The photo source launching device and the photo source receiving device are separately positioned on the two sides of the photo source, a light path which goes through the gas to be inspected is formed of the light sent out by the photo source through the photo source launching device and the photo source receiving device, and the light signal produced is imported into the spectroscope through optical fiber, and the light signal is then transformed into electrical signal through the photo electricity commutating equipment; Finally, the data processing system adopts the signal analysis method of the Fourier transformation to process the spectrum, and the absorbance curve line of the gas inspected is obtained; and the density of the gas inspected can be obtained according to the intensity of the absorbance curve line and the Lambert-beer law.

The present invention provides a radiographic imaging including, provided at an insulating substrate, sensor portions for radiation detection that generate charges due to receive radiation or light converted from radiation, first signal lines that are connected to the sensor portions for radiation detection and through which flow electric signals that correspond to the charges generated at the sensor portions for radiation detection, and second signal lines having a substantially same wiring pattern as the first signal lines. Detection of radiation is carried out on the basis of a difference between an electric signal flowing through the first signal line and an electric signal flowing through the second signal line, or a difference between values of digital data obtained by digitally converting an electric signal flowing through the first signal line and an electric signal flowing through the second signal line, respectively.

The invention relates to a FiberBragg grating(FBG) signal self-adapting restoration method based on compressed sensing, and belongs to a signal restoration technology field of an optical fiber sensing system. The FBG signal self-adapting restoration method comprises steps that step 1: EMD combination mutual information is used for self-adapting denoising processing of spectral signals; step 2, segmented testing of a denoising signal is carried out, and the signal is divided into k segments, and sample databases corresponding to the signals are acquired by calculating Euclidean distances among various segments of signals and samples, and self-adapting dictionaries D corresponding to the signals are acquired by adopting a K-SVD dictionary learning method; step 3, measured signals are used to acquire observation matrixes R and observation signals xi; step 4, the observation signals are reconstructed by adopting an improved regularized orthogonal matching pursuit algorithm to acquire complete reconstructed signals. The FBG signal self-adapting restoration method is advantageous in that problems such as interferences of noises on the signals, targeted dictionary learning, and the signal self-adapting reconstruction are considered, and each part represents the self-adaptability of the algorithm, and can be flexibly used in practical engineering, and then influences caused by manual misoperation are reduced.

The invention provides a channel estimation method and a channel estimation system to improve the accuracy of channel estimation. The method comprises the following steps of: calculating a channel response estimation value at a pilot signal position; performing iterative filtering on the channel response estimation value at the pilot signal position to obtain a final channel response estimation value at the pilot signal position; and estimating channel response estimation values of all subcarriers and symbols according to the final channel response estimation value at the pilot signal position. Through multiple iterations, the method and the system can reduce the influence of noise on the channel response estimation values so as to improve the accuracy of the channel estimation.

The invention discloses a data aggregation method based on compressed sensing in a wireless sensor network. The method includes: uniform clustering of the sensor network is performed, a node with the most residual energy is selected as a cluster head node, member nodes independently select whether to participate in sampling with the probability ptx, and the cluster head node always participate in sampling; then sampling nodes obtain original signals f and obtain sparse representations x thereof through transform of sparse transform bases, x are projected in a measuring matrix phi, sparse measuring signals y are obtained and sent to the cluster head node, and the cluster head node merges the collected measuring signals to a signal Y by employing vectorization operators and sends the signal Y to a fusion center; and finally the fusion center performs reconstruction on the signals one by one by employing an adaptive weight GPSR algorithm and recovers the sparse representations X thereof. According to the method, the characteristics of noise-containing signals, large data bulk, and high timeliness requirement of the wireless sensor network are completely achieved, the adaptive weight GPSR algorithm does not need to know the signal sparsity in advance, and all high-dimensional signals can be accurately reconstructed in a short period.

The invention discloses a projection-type capacitive touch screen system time domain noise reduction method by space differentiation. The method includes the steps that (1), a plurality of identical artificial circuit processing elements and relevant selection controllers are arranged inside a touch screen control chip; (2), a reference inducing line set of any target touch screen inducing line set to be processed in a touch screen inducing line array is selected according to space distribution; (3), identical imitation processors are used for driving and reading a target sensor and a reference sensor simultanously; (4), information of the target sensor and the reference sensor is judged; (5), the steps of (2), (3) and (4) are repeated until all target inducing lines of the touch screen are processed to finish one frame; (6) according to the distribution of status values of the inducing lines of the frame, finger touch points are calculated and judged, and time or space misinformation touch points are eliminated according to former frame information; and (7), according to the state of a current frame, the step (2) is returned or other operation is performed. According to the projection-type capacitive touch screen system time domain noise reduction method by the space differentiation, the system performance can be effectively improved, and the power consumption is reduced.

The invention discloses an imaging method and a device on the basis of orthogonal multi-frequency ultrasonic steady echo signal. The method uses an orthogonal frequency division multiplexing modulation type to form multi-frequency continuous baseband signals which are orthogonal with each other; the multi-frequency continuous baseband signals are modulated as multi-frequency ultrasonic continuous emission signals and sent out by an ultrasonic probe; the ultrasonic probe detects the steady echo signals which are reflected back; the steady echo signals are equivalent to the superposing signals; the received multi-frequency continuous baseband signals after modulation are orthogonally decomposed, each path of receiving signals are decomposed by the characteristic that each path of signals are orthogonal with each other, the amplitude of each interface reflection echo and the position thereof corresponding to the incident interface are calculated so as to carry out the image forming. The device of the invention comprises an ultrasonic probe, a control unit, and an operation unit, a receiving/emitting unit, a processing unit and a display unit which are respectively connected with the control unit; the ultrasonic probe is connected with the receiving/emitting unit; the processing unit is respectively connected with the receiving/emitting unit and the display unit; the method and the device of the invention has precise image forming and good anti-interference performance, and reduces the cost by adopting a single probe.

The invention discloses a text real-time positioning recognition method based on a deep learning attention mechanism. The method comprises the following steps: establishing a text image acquisition system, collecting a training sample, carrying out manual marking, establishing an OCR data set, carrying out the preprocessing of an image according to the characteristics of the OCR data set, then providing a deep saliency attention network to locate a text region, and enabling a text to be separated from a complex background; and finally, identifying the text by utilizing deep convolution cyclicattention to realize real-time detection and identification of the text image. According to the method, the characters do not need to be segmented, the detection and recognition precision of the OCR system can be effectively improved, and the method has good real-time performance and mobility and has wide application prospects.

A semiconductor device comprises a semiconductor substrate; a diffusion layer formed on the semiconductor substrate; at least two wiring layers formed opposite to each other over the semiconductor substrate; signal lines for transmitting a signal maintaining a predetermined voltage, each of the signal lines being formed in each of the two wiring layers; shield lines fixed to a constant voltage to shield the signal lines, each of the shield lines being formed adjacent to each of the signal lines in the two wiring layers; and a gate electrode formed over the semiconductor substrate via an insulation film. In the semiconductor device, at least one of the signal lines formed in a lower wiring layer of the at least two wiring layers is electrically connected to the gate electrode opposed in a stacking direction.

Characterizing material properties using a simple and inexpensive measurement circuit is disclosed. It allows measurement of the transfer function change of an acoustic wave device without necessitating detailed knowledge of the resonant frequency, by integrating the transfer function. If one examines the integral of the transfer efficiency of an acoustic wave device as the acoustic wave is damped, one sees that the magnitude of the total signal transfer decreases with increasing damping allowing derivation of the material parameters from the results of simple integration.

The invention relates to a method for measuring the acoustic impedance of an organism based on ultrasound steady state reflected waves, which comprises that (1) multiple frequency continuous baseband signals which are mutually orthometric are structured by using orthogonal frequency division multiplexing modulation mode; (2) an ultrasonic probe sends out the multiple frequency continuous baseband signals; (3) an ultrasound transducer detects reflected state echo signals; and finally the amplitude of reflected waves of a no uniform reflecting interface and phase difference opposite to incident waves are found out by solving equations set. A device realizing the method comprises an ultrasonic probe, a control unit, a transceiving unit, a processing unit and a display element which are respectively connected with the control unit. The ultrasonic probe is connected with the transceiving unit. The processing unit is respectively connected with the transceiving unit and the display element. The method has high calculation accuracy, good anti-interference, good anti-noise capability. Only one probe is needed, thus causing that the cost of development devices is reduced. And the measuring method is simple and can be used in vivo experiment.

An electronic circuit, preferable as a sensor node, has a highly sensitive radio function and is capable of performing a low-power-consumption operation. The electronic device has a board; a connector for connecting a sensor; a first signal processor circuit receiving an input of sensor data from the sensor through the connector and forming transmission data; and a second signal processor circuit converting a transmission signal from the first signal processor circuit into a high-frequency signal. The connector and the first signal processor circuit are mounted on a first surface of the board, and the second signal processor circuit is mounted on a second surface of the board.

An image recognizing apparatus and method is provided for recognizing behavior of a mobile unit accurately with an image of external environment acquired during the mobile unit is moving.

Behavior command output block 12 outputs behavior commands to cause the mobile unit 32 move. Local feature extraction block 16 extracts features of local areas of the image from the image of external environment acquired on the mobile unit 32 when the behavior command is output. Global feature extraction block 18 extracts feature of global area of the image using the features of local areas. Learning block 20 calculates probability models for recognizing behavior given to the mobile unit 32 based on the feature of global area of the image. After learning is finished, behavior of the mobile unit 32 may be recognized rapidly and accurately by applying the probability models to an image of external environment acquired in mobile unit 32 afresh.