81results about How to "To achieve effective detection" patented technology

The invention discloses a method for handling radio link failure, comprising the following steps that: a relay node (RN) detects RLF (radio link failure) of an Un interface according to a preset RLF detection judging condition; the RN chooses to return back to a radio resource control (RRC) idle state when detecting that the UN interface has RLF, and rebuilds a RRC connection of the Un interface performing a random access operation again, or chooses to recover the RRC connection of the Un interface through a RRC connection rebuilding program under a RRC connection state. The invention further discloses a relay node. With the method and the relay node provided by the invention, effective detection on the RLF of the Un interface by the RN is implemented, and the RLF is handled well.

The invention discloses a semi-supervised mechanical fault diagnosis method based on an adaptive migration neural network, and the method comprises the steps: firstly obtaining a plurality of source domain fault data sets composed of source domain fault training samples and corresponding tags, and a plurality of target domain fault data sets composed of target domain fault data without tags, wherein the target domain fault data is divided into a target domain fault training sample and target domain fault test data; normalizing the data; constructing an adaptive migration neural network diagnosis model, supervising the training model and constructing a classifier loss function by using the source domain fault data set, constructing a classifier discrimination loss function, and performing adversarial training on the feature extractor and the classifier by using the target domain fault training sample; inputting the target domain fault test data into the trained model, and summing and averaging the two output probability values to obtain a final classification diagnosis result. The method can improve the discrimination capability of the fault data of the target domain, and effectively improves the intelligent fault diagnosis task under the actual variable working condition.

The invention discloses a method for manufacturing a high-strength X100 steel grade spiral seam submerged arc welded pipe. The method comprises the following steps: uncoiling, flattening, edge milling, pre-springing, molding, inside welding, outside welding, pipe end belling, base metal layering ultrasonic examination, weld seam X ray inspection, hydrostatic test, weld seam ultrasonic inspection, pipe end chamfering and finished product inspection. In the technical steps of the preparation method, double edge milling process, pre-springing process and pipe end belling process are added so as to successfully solve the technical problems that the high-strength X100 steel grade spiral seam submerged arc welded pipe has poor molding stability, the welding joint performance cannot meet technical requirement and the like.

The invention provides a method for detecting a long-distance barrier and belongs to the technical field of robots. The method particularly comprises the following steps: image acquisition, image pre-processing, scene image segmentation, appearance characteristic extraction, topographic pattern judgment, topographic sample database maintenance, topographic pattern statistics modeling, statistics model parameter training and statistics model inference. The invention achieves the effective detection of a multi-mode barrier, improves the accuracy of barrier detection under the condition of unbalanced samples and improves the adaptability of the barrier detection to the changes in online real-time scenes; the topographic pattern modeling integrates the independent smooth characteristic functions and eliminates the pattern ambiguity caused by characteristic overlapping; the topographic pattern modeling integrates the correlation smooth characteristic functions and improves the online self-adaptability of the barrier detection results to the changes in real-time illumination; and the topographic pattern statistics modeling not only integrates the characteristics of the scene areas, but also theoretically integrates the spatial relationship between the scene areas and improves the stability of barrier detection under the condition of mapping deviation.

The invention discloses a video heart rate detection method removing interference of ambient light variation. Firstly a face area-of-interest data set and a background area data set are obtained, a united blind source separation technology is utilized to process the two data sets, and signal sources of ambient light variation that the data sets both have are extracted and set to zero, thereby obtaining a face area-of-interest data set free of interference of ambient light variation; secondly, face area-of-interest data of an optimal color channel is selected, and an ensemble average empirical mode decomposition method is utilized to obtain intrinsic mode components; and then all local intrinsic mode components of which frequency corresponding to maximum amplitude values are in a set heart rate range are determined to be a candidate intrinsic mode component set, the intrinsic mode component corresponding to the largest maximum amplitude value is determined to be the optimal intrinsic mode component, and a video heart rate is obtained through a peak detection algorithm. The video heart rate detection method provides a relatively accurate algorithm for non-contact heart rate detection, and has important application prospects in the aspects of clinical disease diagnosis and daily medical care.

The invention discloses a class attendance abnormal detection method based on illumination generation antagonism network, includes collecting real class head posture data, rendering illumination classhead posture data, building illumination generation antagonism network, generating antagonism samples, building head posture detection model, class head posture detection, class attendance abnormal detection. By using the depth neural network, the invention improves the positioning accuracy of the head area and reduces the interference of the non-head area to the judgment of the non-attending state.

The invention discloses an acid-proof X70MS steel-grade spiral welded pipe and a manufacturing method thereof. The spiral welded pipe is made of X70MS steel-grade plate coils. The processing process for the spiral welded pipe comprises the following steps of: uncoiling, flattening, milling edges, prebending, molding, internally welding, externally welding, expanding the end of the pipe, performing laminated ultrasonic inspection on a base material, performing X-ray inspection on welding seams, performing a hydrostatic test, performing ultrasonic inspection on the welding seams, chamfering theend of the pipe and inspecting a finished product. The X70MS steel-grade spiral seam submerged-arc welding pipe has high intensity and high acid resistance and is suitable for conveying acid oil gas media.

The invention discloses an air conditioner fan failure detection method. The method comprises the following steps: recording the temperature of a fan coil when the state of the air conditioner fan changes as the change temperature, and recording the temperature of the fan coil a preset time period after the state of the air conditioner fan changes as the continuous temperature; judging whether the temperature difference between the change temperature and continuous temperature is less than the preset temperature difference; and if so, judging that the air conditioner fan fails. The invention also discloses an air conditioner fan failure detection device. The method avoids long-time operation of the air conditioner when the fan fails, avoids the problems of overhigh temperature of the indoor fan coil, poor refrigerating effect or incapability of refrigeration, refrigerant reflux, diluted lubricating oil and the like due to the failure of the air conditioner fan, and prevents the air conditioner from being damaged due to the problem of the fan failure.

A high spectral image object detection method based on tensor principal constituent analysis dimension reduction is provided; an existing high spectral image object detection method cannot fully consider enhanced space constraint characteristics under high resolution conditions, cannot excavate information from the three dimensional data integral body, and is low in detection precision; the high spectral image object detection method based on tensor principal constituent analysis dimension reduction can solve said problems, and comprises the following steps: 1, obtaining third order object, third order background and detected third order test sample tensor blocks; 2, obtaining a projection matrix on three dimensions including the object, background and detected test sample; 3, projecting the object, background and detected test sample to a preset tensor subspace; 4, calculating the total distance from each detected test sample to the background and an object template; 5, using the distance ratio as a gray value, and determining the central point pixel as the object if the gray value is bigger than a threshold value, otherwise determining the central point pixel as the background. The method is applied to the image processing field.

The invention provides a mineralized alteration remote sensing information extraction method and device. The method comprises the following steps: first, obtaining remote sensing image data and usingmask technology to process and form basic data; 2, performing histogram calculation on that basic data in a selected area to determine the modeling data, extract abnormal information from the modelingdata by adopting the principal component analysis method, and sequentially cutting and verify the abnormal information by using a normal distribution method and a multiple linear regression method; Thirdly, according to the eigenvector algorithm extracted from the abnormal information, the eigenvector satisfying the check being obtained and mapped to the new abnormal information extracted in a large range as an extracting parameter, and then the new abnormal information is cut and output. This method can realize the striding alteration remote sensing anomaly extraction in different landscapeareas, which is beneficial to the quicker and more accurate selection of prospecting target areas, and can save time and manpower and material resources for mineral resources investigation.

The invention provides a hyperspectral image target detection method based on tension linear discrimination analysis dimension reduction. The objective of the invention is to solve problems that in the current hyperspectral image target detection method, characteristics of spatial constraint enhancement under the condition of high scores are not fully considered, information excavation cannot be performed on the whole three-dimensional information and the detection precision is quite low. The method comprises steps of 1, acquiring three-order target tension blocks, three-order background tension blocks and three-order to-be-detected test sample tension blocks; 2, allowing sub-space after the projection of the target tension blocks, the background tension blocks and the to-be-detected test sample tension blocks to have the biggest separability; 3, projecting the target tension blocks, the background tension blocks and the to-be-detected test sample tension blocks to a tension sub-space with the biggest separability; 4, calculating the total distance from each to-be-detected test sample to the background and the target; and 5, setting a threshold value and if the gray scale value is larger than the threshold value, determining the pixel of the central point as the target, or else, determining pixel of the central point as the background. According to the invention, the method is applicable to image processing field.

The invention relates to the technical field of image processing, and provides an image imaging jitter compensation method, system and device, and the method comprises the steps: installing a gravitysensor at a parallel position of a camera assembly, and obtaining the jitter acceleration data of the camera assembly in real time through the gravity sensor; adopting an SOC chip as a main control module, and utilizing the operation function of the SOC chip to perform logic operation on collected moving images and jitter acceleration data to obtain correction coordinates of a target object. According to the invention, the simple and low-cost gravity sensor is additionally arranged, so the shaking displacement of the target object is effectively detected; the SOC chip with highly integrated circuits and comprehensive functions is adopted to perform data operation, and direct output from moving images and jitter acceleration data to correction coordinates is realized, so the effective compensation of jitter displacement of a target object is realized on the basis of ultra-low manufacturing cost, and the accuracy of image imaging is greatly improved.

The invention relates to a malicious encrypted channel detection method based on process behavior analysis. The method comprises the following steps: step 1, acquiring encrypted session flow data and classifying processes; comprising the steps of encrypted traffic data acquisition, preprocessing and process classification; 2, constructing a process file encryption communication behavior feature tree; constructing a three-level feature tree of a meta feature of the encrypted session, namely an IP layer, a TCP segment load length sequence feature, namely a TCP layer, and an SSL message state transition feature, namely an SSL recording layer; step 3, anomaly detection based on the feature tree; comprising the steps of collecting normal encrypted communication behavior data; constructing a normal encryption communication behavior benchmark; constructing a target PEF encrypted communication behavior model; calculating the dissimilarity degree between the feature trees; and performing anomaly detection based on a threshold value. By means of an anomaly detection method, the limitation that malicious encrypted channels are detected purely from the session level is broken through, and effective detection of malicious process files is achieved.

The invention discloses a constructional engineering quality acceptance intelligent detection management system based on big data analysis, and the system comprises an outer wall detection point laying module, an outer wall structure layer thickness detection module, a storage database, an outer wall structure quality coefficient analysis module, an outer wall flatness analysis module, an outer wall structure detection terminal, a central server, and a display terminal. The external wall structure is detected through the designed external wall structure detection terminal, the external wall structure parameters are obtained, meanwhile, the external wall structure quality influence coefficient and the wall surface flatness coefficient are intelligently analyzed, then the external wall comprehensive quality evaluation coefficient is obtained, and effective detection of the building external wall quality parameters is achieved; according to the method, the comprehensive quality of the building external wall can be intelligently evaluated, meanwhile, the obtained external wall comprehensive quality evaluation coefficient achieves quantification of the quality of the building external wall, a parameter basis is provided for judging whether the building external wall meets the acceptance requirement, and the defects existing in the manual acceptance process mentioned in the background technology are overcome.

The invention relates to the field of control over the perpendicularity of drilled pile bodies, in particular to a device and method for rapidly and precisely measuring the perpendicularity of a drilled pile body. By applying the device, the problem that the pile-diameter perpendicularity after hole forming of an existing drilled pile cannot be measured effectively can be solved, the blanks of theprior art are filled up, and the construction quality of the drilled pile is improved. The device comprises a centered connecting plate and four measuring rulers fixed to the centered connecting plate and having measuring ruler scale values, the central lines of two of the measuring rulers are located on the same straight line and are in the same direction as the transverse radial direction of asteel casing, the central lines of the other two measuring rulers are located on the same straight line and are in the same direction as the longitudinal radial direction of the steel casing, and thetwo measuring rulers located on the transverse radial direction of the steel casing are perpendicular to the two measuring rulers located on the longitudinal radial direction of the steel casing. Themeasuring process of the method is simple, the perpendicularity can be measured rapidly and precisely, operability is high, the measuring result is more accurate, and the construction quality of the pile body is ensured. The manufacturing cost of the complete device is low, recycling can be achieved, and thus the construction cost is lowered.

The invention discloses a method and a device for detecting MP3 file authenticity. The method comprises the steps of: extracting the horizontal curve fluctuation characteristic value of an MP3 file to be detected after Fourier transform of a quantized and improved MDCT (Modified Discrete Cosine Transform) coefficient histogram sequence; and comparing the horizontal fluctuation characteristic value with a preset threshold, and if the value is larger than the preset threshold, determining that the MP3 file is subjected to dual compression. According to the method and device provided by the invention, through analyzing MP3 quantized MDCT coefficient statistic distribution, and the curve fluctuation characteristic after Fourier transform of the quantized MDCT coefficient histogram sequence is extracted, so that dual MP3 compression is effectively detected, judgment and comparison are carried out by a one-dimensional characteristic only, and the detecting accuracy is improved.

The invention discloses a detection reagent and a detection method of alpha-amylase. The detection reagent comprises 10mmol/L-40mmol/L of malt pentose, 1000U/L-5000U/L of alpha-glucosidase, 10mmol/L-30mmol/L of calcium chloride and 1mmol/L-50mmol/L of a buffer solution. The detection method comprises the following steps: adding an alpha-amylase solution into the detection reagent and performing catalytic reaction to obtain a reaction product; detecting the reaction product by virtue of a portable glucose detection instrument; recording the readings of the detection instrument; and calculating the concentration of the alpha-amylase solution. The detection reagent can quickly and quantitatively detect the alpha-amylase; the detection method is easy and convenient to operate, quick, high in sensitivity and good in selectivity, the used instrument is portable, and the alpha-amylase can be quickly detected by people who do not accept professional training.

The purpose of the present invention is to provide a dynamic detection and evaluation method for connection states of joints in a pile beam structure. The pile beam structure comprises a plurality of pile beam connection portions formed by pile foundation sections and beam sections. The method comprises the following steps: determining layout positions of a plurality of detection points on each connection portion, and installing a detection device on the pile beam structure for monitoring each detection point; determining a corresponding vibration point according to the layout position to generate a vibration wave through the vibration point; and according to the time when the vibration wave reaches to each detection point and which is detected by the detection device, and the layout position, respectively obtaining the propagation velocity of the vibration wave on each beam section and the propagation velocity of the vibration wave from each beam section to the corresponding pile foundation section, and analyzing the propagation velocity of the vibration wave according to the mathematical statistics method to obtain an abnormal velocity threshold, so that the abnormal pile beam connection portion can be determined, and detection and evaluation can be carried out on the abnormal pile beam connection portion. Compared with the prior art, the method provided by the present invention can implement effective detection on the connection state of the pile beam structure and evaluation on overall structural performance of the pile beam structure.

A switch transistor power loss and automatic adjusting circuit in switching power supply is characterize in that that circuit comprises a filter, a differential operational amplifier, a comparator anda sampling judger; One end of the input side of the differential operational amplifier is connected with the output end of the filter, and the other end is connected with the output voltage signal ofthe switching power supply; One end of the input side of the comparator is connected with the output end of the differential operational amplifier, and the other end is inputted with a threshold constant; The output end of the comparator is connected with the input end of the sampling decider. The invention realizes the effective detection of the loss of the power tube in the switching power supply and the automatic adjustment of the on-resistance of the power tube.