522 results about "Complex matrix" patented technology

A nonwoven fabric comprises continuous polymer filaments of 0.5 to 3 denier that have been hydroentangled in a complex matrix for interconnecting filament loops, and that is otherwise substantially free of knotting, or of otherwise wrapping about one another. A process for making a nonwoven fabric comprises continuously extruding polymer filaments of 0.5 to 3 denier onto a moving support, pre-entangling the filaments with water jets, and entangling the filaments with a second set of water jets on a three-dimensional image transfer device. An apparatus for making a nonwoven fabric comprises means for continuously extruding substantially endless polymer filaments of 0.5 to 3 denier onto a moving support to form an unbonded web, a pre-entangling station for entangling the web with a plurality of water jets, and a plurality of water jets for final entanglement of the filament web on a three-dimensional image transfer device. In another aspect of the present invention, plural precursor webs, each comprising polymeric filaments, can be employed to form a laminated nonwoven fabric.

Improved systems, apparatus, methods, and programming useful for the automated analysis of complex compounds using mass spectrometers. Systems, apparatus, methods, and programming according to the invention provide for the automatic determination by a controller 54 of a mass spectrometer 14, 214 of an analysis operation to be implemented using the mass spectrometer, the analysis operation adapted specifically for analysis of one or more substances based contained within a compound based on identification of the compound and/or substances provided by a user of the spectrometer, and a database 66 or other library of information concerning suitable processes or process steps for analyzing substances.

The invention relates to a self-adaptive method for single-phase grounding fault line selection of an electric distribution network by using S transformation energy relative entropy. The method comprises the following steps: when the zero-sequence voltage instantaneous value of a bus is out of limit, starting a fault line selection device immediately; performing S transformation on zero-sequence current in 1/4 cycle after the fault of each line, and calculating transient energy under each frequency of the zero-sequence current of each line by using a complex matrix obtained by the S transformation; and calculating the S transformation energy relative entropy under each frequency of each line and solving the comprehensive S transformation energy relative entropy of each line by using the super-strong recognition capability of the relative entropy to slight differences between signals, and self-adaptively selecting out the fault line by comparing the size of the comprehensive S transformation energy relative entropy of each line under all frequencies. Theoretical analyses and a large number of emulations show that the method effectively avoids the influence caused by a CT saturation discontinuous angle on the line selection, and is applicable to the cable-wire mixed line, pure cable lines and pure aerial lines.

The invention discloses an underwater sound source positioning method based on deep learning, and the method comprises the steps: carrying out normalization operation of vector data simulated throughemploying a KRANEN program, carrying out the superposition of a 0-mean Gaussian random noise complex vector n, and obtaining the simulation sound field data p (f) at a frequency f; constructing a normalized covariance matrix H according to the analog sound field data p (f), performing Hermitian decomposition on the matrix H, and converting the complex matrix H into a real matrix capable of being processed by the convolutional neural network to obtain input data of the convolutional neural network; and training the convolutional neural network by using the input data to obtain an underwater sound source positioning prediction model, and predicting the distance and depth of the signal source according to the observed sound field data. LeNet-5 convolutional neural network and 56-layer deep residual network are used for underwater sound source positioning under single and multiple sound sources. An underwater sound source positioning algorithm with high precision and accuracy is acquired and the real-time performance of underwater sound source positioning is improved.

The invention discloses a method for locating a power distribution network 10kV feeder line fault based on matrix operation, and belongs to the technical field of power distribution network automation. The technical problem to be solved is the fault locating of a power distribution network medium voltage 10kV feeder line. The method comprises the steps that a power distribution network initial power supply path matrix H is formed according to the topological structure of the power distribution network feeder line, the H is amended to obtain an amended path matrix H' so as to solve the problem of repeated fault locating, fault information is obtained through an FTU, operation processing is carried out on the amended path matrix H' according to the fault information, then an initial judgment matrix P' is formed, a fault judgment matrix P is finally obtained, father nodes in a fault area can be judged effectively according to coherent elements in the P, and then the fault area is obtained. By means of the method, the power distribution network feeder line fault is located, the judgment principle is simple and effective, no complex matrix multiplication operation is required, and the aim of locating feeder line tail end faults can be well achieved.

The invention relates to a method for detecting an organophosphorus multi-pesticide residue in tea based on matrix effect compensation, which belongs to the technical field of safety detection of foods. The method comprises the following steps of: (1) mixing a pesticide standard solution; (2) preparing a sample solution; (3) detecting a sample to be detected by a gas chromatogram and mixing the standard solution. The method is rapid, simple and economic, has high sensitivity, effectively reduces or eliminates the interference of a complex matrix derived from the tea on the detection of organophosphorus pesticide residues and provides a scientific basis for further improving an evaluation system of the quality safety of the tea.

The invention provides a novel series-parallel connection mass spectrum device system. The system comprises mass spectrum necessary basic subsystems, such as a set of quadrupole mass filter system, a special quadrupole rod/linear ion trap mass analyzer system, an ion guidance system, a quadrupole deflector, a hyperbolic quadrupole rod mass analyzer and ion counter system, a low air pressure linear ion trap mass spectrometer and electron multiplier system, a flight time mass spectrum system, a multi-path gas flow control system, a vacuum gauge, a multi-section differential motion vacuum system and the like. Furthermore, the invention provides a method for operating above systems to perform quantitative analysis in a triplet quadrupole rod mode, qualitative analysis in a quadrupole filtering medium combined high/low air pressure ion trap mode, and quick/high-mass precision analysis in a quadrupole filtering combined flight time mass spectrum mode on ultra-trace materials in a complex matrix, a method for utilizing an effective combination of three different mass analyzers to achieve optimal ion optical parameter adjustment and a method for performing high-precision qualitative and quantitative analysis on the ultra-trace materials.

The invention relates to a power distribution network outgoing feeder fault route selecting method by S transform amplitude detection, namely, when the power distribution network generates single-phase ground fault, the bus zero sequence voltage before and after the fault can be performed for S transform to find out the moment corresponding to a module maximal value on the S transform highest frequency component position for accurately calibrating the fault moment; the each line zero sequence current before and after the fault moment can be performed for S transform to obtain the S transform complex matrix of each line zero sequence current; the amplitudes of highest frequency component at fault moment in the each line zero sequence current S transform complex matrix can be worked out, and the amplitude difference can be worked out; the integrative amplitude difference of each line zero sequence current can be worked out; the fault route selecting can be implemented by comparing the size of the integrative amplitude difference. The invention can avoid the route selecting failure caused by CT saturation and phase alternation, the invention implements the route selecting by using high-frequency components, without being influenced by arc-suppression coil compensation degree. The accurate route selecting under different fault conditions comprising small fault angle can be implemented.

The invention provides a maneuvering target ISAR (Inverse Synthetic Aperture Radar) imaging method utilizing compressed sensing. The method comprises the following steps: obtaining ISAR return wave data, and allowing the return wave data to be subjected to distance compression, motion compensation and migration correction so as to obtain a complex matrix Sd; generating a Gaussian random matrix Phi, and allowing the Sd to be subjected to reduced-order observation so as to obtain a matrix Y; obtaining a sparse basis matrix of ISAR to-be-imaged times ti; solving each column of the matrix Y through a 1-norm convex optimization equation so as to obtain ISAR image results of times ti; and traversing all imaging times, so as to realize the ISAR imaging of a maneuvering target at all periods. The imaging method lowers the requirement on imaging return wave sampling rate, realizes free imaging of the maneuvering target at all imaging times, and improves no only the azimuth imaging effect of the maneuvering target, but also the ISAR imaging quality.

A double-image encryption method based on chaotic and discrete fraction random transform comprises the steps of image expansion, chaotic scrambling, chaotic diffusion, image contraction, image reconstruction and discrete fraction random transform. According to the method, an expanded image is formed by a gray level image I1 and a gray level image I2 through the expansion step, the pixel positions and pixel intensity values are changed through the scrambling and diffusion process based on Logistic chaotic mapping, and then the expanded image is decomposed into a new image J1 and a new image J2 which are stable in white noise distribution through a contraction strategy; the image J2 is normalized and encrypted so as to form a pure phase matrix and a complex matrix J is obtained by multiplying the pure phase matrix and the image J1; finally, the complex matrix encrypted so as to form a temporary image through discrete fraction random transform based on Logistic chaos and the amplitude part is a final ciphertext image. Nonlinearity and randomness of a plaintext image in a spatial domain and a transform domain are enhanced, common attacks can be well resisted, and safety of an encryption system is improved.

The invention belongs to the technical field of wireless communications, and particularly relates to a method for reconstructing signals in an ultra-wide-band communication system by the adoption of a low-complexity improved Bayes compressed sensing algorithm. The method comprises the steps that firstly, sectioning and filtering are conducted on received signals, then a measuring matrix is used for conducting linear combination on the filtered signals again, after a series of relatively simple iterative operations, the expansion coefficient of original signals under the characteristic base can be measured, and therefore reconstruction of the original signals is realized. According to the method for reconstructing the signals, on one hand, the Bayes compressed sensing algorithm is improved by fully utilizing the characteristics of the characteristic base, the restorability is improved, more importantly, the complex matrix inversion process in the Bayes compressed sensing algorithm is avoided, and particularly, when the length of the signals is large and the order of the matrix is large, the signal restoration operation complexity can be effectively lowered.

The invention relates to a multifunctional digital signal processor for a skyborne or spaceborne radar altitude gauge, which adopts the technical scheme that an input signal passes through an isolating retainer, and is subjected to sampling through a high-speed A/D sampler under the control of a sequential control unit; a digital I/Q signal is obtained by a digital I/Q processing unit; I/Q data is stored to a data A storage under the control of a storage control unit, and after being stored fully, data of a sub-aperture is processed by a sub-aperture processing unit in a mode of a two-dimensional complex matrix; the output of sub-aperture processing is stored to a data B storage under the control of the storage control unit, and after the data of the sub-aperture is stored fully, subsequent sub-aperture observation data is processed repeatedly and sequentially and is stored to the data B storage continuously; after the data of a set number of the sub-apertures are stored fully, the data is processed by a multi-view processing unit to acquire echo power observation matrixes of resolution footprints in each azimuth finally; and a digital signal processing (DSP) general processor performs maximum likelihood estimation and prediction on each received echo power observation matrix.

The invention discloses a method for converting a boundary element by an extra-high voltage direct current transmission line mode voltage S, comprising the following steps: when the direct current line is in fault, after a protective element is started, the line mode voltage is obtained by utilizing a phase mode transformational theory according to the two-pole direct current voltage detected on a protection installation part; a dispersion line mode voltage signal is selected to perform S conversion, wherein the sample sequence length is 200 points, and the conversion result is 101*200 time frequency complex matrix; mode calculation is performed on each element in the complex matrix; the high-frequency energy and the low-frequency energy of the line mode voltage are extracted according tothe obtained mode matrix; the ratio of the high-frequency energy and the low-frequency energy of the line mode voltage is calculated; the faults in the cell and out of the cell are distinguished according to the ratio of the high-frequency energy and the low-frequency energy. A large amount of stimulated results prove that the method of the invention has better effect.

The invention relates to a single-phase permanent fault recognition method for an extra-high voltage AC transmission line using S transform energy. The method comprises the following steps: after fault occurs to an AC line, selecting a disperse voltage signal of which the recovery voltage sampling sequence length is 1,800 after the fault, and performing S transform to obtain a 901*1,800 time frequency complex matrix; and operating modulus of each element in the complex matrix to obtain the energy value under each frequency point. As too many frequency ranges are not good for recognition, every 9 rows from the 2nd row to the 901st row to obtain a 101*1 matrix, the 901 frequency ranges are integrated into 100 frequency ranges, and the frequency of each frequency range is 50 Hz. The single-phase permanent fault is judged according to the size of the first frequency range, namely the 50 Hz frequency range. A large number of simulation results indicate that the effect of the method is good.

The present disclosure provides methods and systems for improved detection and/or quantification of selenium (Se) and/or silicon (Si) in samples. In certain embodiment, the methods and systems feature the use of carbon dioxide (CO₂) as a reaction gas in a reaction cell chamber, such as a dynamic reaction cell (DRC), of an inductively coupled plasma mass spectrometer (ICP-MS). It is found that the use of CO₂ as a reaction gas effectively eliminates (or substantially reduces) interfering ionic species for the analytes Se and Si, particularly in samples with complex matrices, and/or in samples with low levels of analyte, thereby enabling more accurate detection of analyte at lower detection limits and in samples having complex matrices.

The invention relates to a method for detecting concentration of nine compound coloring agents in auxiliary materials for reconstituted tobacco. The method comprises the following steps: preparing a mixture mother liquor of nine compound coloring agents, namely, lemon yellow, amaranth, indigo blue, carmine, sunset yellow, allura red, brilliant blue, acid red and erythrosine, and a sample solution; preparing a standard operation solution; and adopting a liquid chromatogram-series triple quadrupole spectrum analyzer for analyzing and detecting the concentration of the nine compound coloring agents in the sample solution. The method provided by the invention is accurate and reliable, is high in sensitivity and is very suitable for the analysis for the nine compound coloring agents in the auxiliary materials for the complex matrix reconstituted tobacco.

The invention relates to a method for preparing a photoelectric adapter sensor for detecting 17beta-estradiol. The photoelectric adapter sensor takes a prepared cadmium selenide nano particle modified titanium dioxide nano tube as a matrix electrode; after the surface of the electrode is functionalized by chitosan and glutaraldehyde, and a 17beta-estradiol adapter is dropwise added onto the surface of the electrode so as to prepare the 17beta-estradiol photoelectric adapter sensor. Compared with the prior art, the method combines the 17beta-estradiol photoelectric adapter sensor with specific recognition capability with a supersensitive photoelectric analysis technique for detecting an environmental internal-secretion interfering-substance 17beta-estradiol, so that not only is high sensitivity acquired, but also interference of a complex matrix environment is prevented, and high selectivity is achieved; when the method is used in low-concentration 17beta-estradiol detection, a wide working curve range of 5*10<-13> mol/L to 15*10<-12> mol/L is obtained, the minimum detection limit can be 3.3*10<-14> mol/L, and moreover, the 17beta-estradiol photoelectric adapter sensor is simple in preparation method, low in cost and good in stability and repeatability.

The invention provides a method for determining multiple kinds of animal origin meat based on the liquid chromatographic-tandem mass spectrometric technology. The method includes the steps of pretreating samples, screening multiple standard meat sample feature polypeptides, and detecting feature polypeptides in meat samples to be detected through the liquid chromatographic-tandem mass spectrometric technology and the like. Components of the multiple kinds of animal origin meat can be identified by adopting the method, the scanning function of liquid chromatography-tandem mass spectrometry is brought into full play in the technology, the selected ion monitoring mode is monitored to collect signals in real time, second-level daughter ion intensity triggering is used, corresponding parent ion second-level fragmentation full-scanning spectrograms are collected to obtain a more exact qualitative information function, interference of a complex matrix is avoided, and the false positive possibility is reduced. In addition, the method is simple in pretreatment and facilitates operation on samples in batches.

The invention relates to a method for recognizing an internal fault and an external fault of an ultrahigh voltage alternating current transmission line. The method comprises the following steps of: after an alternating current line fails, starting a starting element, selecting the voltage of a fault component at the moment of 0.2ms before the fault and 0.8ms after the fault, and decoupling by using new phase mode transformation to acquire line mode voltage; performing S-transformation on the line mode voltage to acquire a result which is a time frequency complex matrix in a row -m and a column n; solving the modulus of each element in the complex matrix to acquire a modular matrix; calibrating the arrival time Tn of an initial voltage travelling wave according to an amplitude-time characteristic in the modular matrix; extracting the total high-frequency energy and the total low-frequency energy of the line mode voltage corresponding to 100 sampling points after the Tn from the modular matrix, and solving the ratio k of high-frequency energy to low-frequency energy; and distinguishing the internal fault from the external fault according to the ratio of the high-frequency energy to the low-frequency energy. In the method, sampling frequency is 250kHz, the length of a sampling sequence is 250 sampling points, the required data length is relatively short, calculated amount is low, and a real time property is relatively high. Whether the faults occur in a region is judged only by using single end amount without the usage of channels, so that the method is relatively high in applicability. A large number of simulation results prove that the method is high in transition resistance endurance capacity, is suitable for different fault types and has an obvious effect.

The invention provides an extra-high voltage direct current transmission line boundary element forming method based on a support vector machine (SVM). The method comprises the following steps: when the direct current line has fault, computing the anode line polar wave voltage and the cathode line polar wave voltage according to the direct current voltage and direct current of the two poles measured in the relay location of the line; selecting the discrete polar wave voltage signal of the fault pole, with sampling sequence length of 200, after fault to undergo S transform to obtain a 101*200 time-frequency complex matrix and computing the modules of elements in the complex matrix; computing the energy values corresponding to the first 20 frequencies according to the modular matrix obtainedthrough S transform, sticking tag values to the energy values as the characteristic quantity and inputting the characteristic quantity to the SVM to be trained; and distinguishing the area fault fromthe out-area fault according to the training result of the SVM. Lots of simulation results show the method has good effect.