112 results about "Energy matrix" patented technology

Disclosed is an apparatus and method for searching a base station in a mobile communications system, in which a mobile station acquires slot timing synchronization from a first signal on a primary sync channel (P-SCH) out of the P-SCH and a secondary sync channel (S-SCH) used for base station search, acquires frame timing synchronization (Fsync) from a second signal on the S-SCH, and determines a primary scrambling code group (PSCG) corresponding to the scrambling codes used by the respective base stations. The method comprises calculating and accumulating P-SCH RSSI values from the first signal at every slot and comparing the accumulated P-SCH RSSI values with first and second accumulation thresholds and providing the first and second search commands; and calculating S-SCH channel received signal strength indicator (RSSI) values from the second signal at every slot in one frame, and updating S-SCH RSSI values corresponding to the one frame as energy matrix values; calculating energy hypotheses corresponding to the energy matrix values using the energy matrix values and a predetermined secondary sync code (SSC) table in response to a first search command, and determining energy hypotheses having a value higher than a predetermined threshold as passed hypotheses; and calculating energy values for the passed hypotheses using the determined passed hypotheses and the SSC table in response to a second search command, and determining an energy hypothesis having a maximum energy as the Fsync and the PSCG.

The invention discloses a variable-speed rolling bearing fault recognition method based on an order enveloping time-frequency energy spectrum. Short time Fourier transform is carried out on low-band signals in acquired rolling bearing vibration signals under a variable speed to acquire a short time spectrum, and in combination of a peak search method, instantaneous rotating frequency estimation for a bearing reference axis harmonic component is acquired; then, through a fast kurtosis spectrum technique, the optimum resonance frequency band pass parameters of the vibration signals are determined, the band pass signals after band pass filtering are subjected to Hilbert transform to acquire enveloping signals, and through short time Fourier transform, an enveloping time-frequency energy matrix is obtained; and an extraction interval is set, an order enveloping energy calculation path is obtained, order enveloping time-frequency energy in different orders is calculated through the energy calculation path and the enveloping time-frequency energy matrix, an order enveloping time-frequency energy spectrum is acquired, and through comparison between the order corresponding to the maximum order enveloping time-frequency energy and a fault order, bearing fault recognition is realized. The method has the advantages that the calculation efficiency is high, and requirements of real-time monitoring in actual engineering application can be met.

The invention discloses a stereo matching method of a double-viewpoint image. The stereo matching method of the double-viewpoint image comprises the steps of: obtaining a left view matching cost, a left view region parallax, a right view matching cost and a right view region parallax; constituting a crossed accumulation area by regarding each pixel point as a central point and respectively obtaining a matching cost after the accumulation of the left view and a matching cost after the accumulation of the right view; obtaining an initial right disparity map, a first error energy matrix, an initial left disparity map and a second error energy matrix through epipolar constraint and matching costs after the accumulation based on the left view region parallax and the right view region parallax; respectively obtaining correct matching points in the initial right disparity map and the initial left disparity map based on the initial right disparity map, the first error energy matrix, the initial left disparity map and the second error energy matrix and removing wrong matching points; and dividing the left view and the right view of a stereo image pair by adopting bandwidth parameters, and performing smoothing process based on the division result to obtain a right smooth disparity map and a left smooth disparity map.

Method for estimating and correcting a frequency offset between a local clock of a receiving transceiver and a remote clock of an emitting transceiver comprises receiving by said receiving transceiver, a signal emitted by the emitting transceiver, said signal lacking a continuous sinusoidal carrier and having at least one symbol, each symbol being emitted within a time frame having a first duration; sampling the signal by taking for each time frame a set of energy measurements of said signal; forming a matrix representative of said energy measurements; determining from said energy matrix, points of maximum of energy within each time frame; determining a line connecting a plurality of said points within each of said time frames; determining a slope of said line; calculating a frequency offset between the clocks of the emitting and receiving transceivers using the slope; and adjusting the receiving transceiver's clock frequency according to the frequency offset.

The invention relates to an image stitching method. A traditional image stitching method is not good in effect. The image stitching method includes the steps: firstly, selecting a coarse registration area and carrying out pairwise weighted average on pixel values at the positions of overlapping coordinates of initial areas of two images, obtaining a reserved image, then, scanning an energy matrix of the reserved image line by line, obtaining a minimum energy line after calculation, obtaining a strip-shaped area by serving the minimum energy line to as a center to expand to two sides, respectively finding corresponding registration areas from the initial areas of the two images, carrying out image fusion on all the pixel values in the registration area of the two images to obtain a stitching area, and then finishing image stitching. According to the image stitching method, not only can an optimal matching seam be found rapidly, but also selection of an image fusion area can be reduced, and an optimized stitching image can be obtained.

The invention discloses a transformer substation acoustic signal feature extraction method based on MFCC, and belongs to the field of monitoring. The method comprises the following steps: performing acoustic signal preprocessing, fast Fourier transform, Mel filter bank and logarithm DCT operation on a transformer acoustic signal in sequence, and extracting the characteristic quantity of the transformer acoustic signal; wherein the preprocessing comprises two steps of framing and windowing; converting the time domain signal into a frequency domain through fast Fourier transform, and calculatingan amplitude spectrum and spectral line energy of each frame; enabling the Mel filter bank to calculate energy for each frame of spectral line energy spectrum through the filter bank; carrying out logarithm DCT operation to obtain logarithms of the energy values, calculating an energy matrix and identifying the fault type in a fuzzy clustering or neural network mode. Distinguishing is carried outthrough timbre, extracted feature vectors have obvious difference, the operation speed is high, and the operation cost of a computer can be reduced; and the feature vectors are classified and markedby using a support vector machine algorithm, so that discrimination speed is high, accuracy is high and instruction is simple. The method can be widely applied to the field of operation monitoring andfault judgment of unattended substations.

The invention discloses a blind estimation method for underdetermined hybrid frequency hopping parameters based on time frequency diagram correction in order to mainly solve the problem of large estimation errors caused by a poor signal to noise ratio in the prior art. The method comprises the following implementation steps: (1) performing short-time Fourier transformation on a signal to obtain a time frequency matrix of an observed signal; (2) calculating an energy matrix of the time frequency matrix; (3) correcting the time frequency diagram; (4) estimating frequency hopping signal parameters according to the corrected time frequency diagram. The method disclosed by the invention can be used for obtaining a clear time frequency diagram at a low signal to noise ratio, has the advantage of improving the estimation precision of the frequency hopping signal parameters, and can be applied to various frequency hopping communication scenes.

The invention relates to a new alicyclobacillus strain and an application thereof in bioleaching. The conservation number of the screened alicyclobacillus strain is CGMCC 4500; and the strain is cultured at the temperature of 25-35 DEG C and grows within the pH range of 1.5-5.0. The strain can be applied in the bioleaching field such as pyrite leaching. The alicyclobacillus strain has an acidophilic character, and can grow by taking ferrous ions as an energy matrix and fixed CO2 as a carbon source and meanwhile can rapidly grow by virtue of organicnutrition, thus the strain is suitable for large-scale amplification culture so as to be applied in the bioleaching field. Studies show that the new alicyclobacillus strain has the advantages of high leaching rate, short leaching time, no environmental pollution and the like, and metal ions therein have high tolerance and are free from inhibition of organic matters in the system.

The invention discloses a circuit failure diagnosis method based on node information, which is mainly used for solving the defect that the traditional failure diagnosis method must know the known circuit schematic diagram. During diagnosis, beyond factors of the electric characteristics, the connecting relationships and the circuit structures of specific components of a circuit, with information of a circuit testing node as the basis of circuit failure diagnosis, failure diagnosis can be effectively carried out without establishing a failure dictionary, signal characteristics of circuit nodes are represented by using matrix digital forms; position distribution information, energy distribution information and correlation information of the circuit nodes are respectively presented by establishing a position matrix, an energy matrix and a correlation matrix; then state change characteristics and information transfer characteristics of the energy change matrix and the correlation change matrix are figured out; and failure nodes in state change nodes are searched through node information transfer characteristics, therefore positions of failure elements are located. The circuit failure diagnosis method has the advantages of simple method of representing the circuit node characteristics and convenience for failure analysis.

The invention discloses a measuring method of a photolithographic process window, comprising the following steps: providing a wafer with a plurality of structures to be measured in array distribution formed by photoetching a focus value and exposing energy matrixes; acquiring a line imaging chart of the structures to be measured through an electron beam microscope; analyzing the line imaging chart by a multi-pixel threshold method, acquiring a marginal distribution curve of the lines in one-dimension direction, computing the line roughness according to the marginal distribution curve, and drawing a relation curve between pixel value and line roughness; taking the marginal pixel value corresponding to the continually varying minimal line roughness as a line marginal position reference, and computing a line reference width according to the line marginal position reference; and carrying out data analysis on the line reference width and minimal line roughness of all the structures to be measured, and computing the numerical range of the photolithographic process window. The measuring method improves the accuracy in measuring the photolithographic process window.

The present invention provides a broadband large-scale MIMO (Multiple Input Multiple Output) system-based wireless positioning method and system. According to the wireless positioning method and system, the spatial angle resolution of a large-scale MIMO systems and the delay resolution of a wideband system are adopted, so that a base station side can extract an angle and delay-domain channel energy matrix from uplink channel estimation results and adopt the matrix as position fingerprint information. In an offline phase, the base station cooperates with an offline sampling mobile terminal to measure the position fingerprint information of feature points which are obtained by dividing the coverage area of a cell at intervals, stores position coordinates corresponding to the position fingerprint information into the database and hierarchically clusters the position fingerprint information in the database. In an online phase, the base station side hierarchically compares the position fingerprint information of a mobile terminal to be positioned with the position fingerprint information in the database, calculates the position coordinates of the mobile terminal to be positioned and feeds back the position coordinates to the corresponding mobile terminal. The method and system, by means of wireless communication devices, can significantly improve the positioning accuracy of the mobile terminal under complex scattering body environments such as urban buildings and indoor environments.

A method analyzes a radio signal received via a wireless channel. The radio signal includes multiple frames representing a transmitted symbol. Energy of ach frame is sampled during multiple of non-overlapping time windows. The sampled energies are stored in an energy matrix indexed by the number of frames and the number of time windows in each frame to analyze the radio signal.

The invention relates to a mechanical fault diagnosis method for a high-voltage circuit breaker. Firstly, a high-voltage circuit breaker vibration signal is acquired through an acquisition device; secondly, CEEMDAN decomposition is performed on the vibration signal, and a time-frequency matrix with equal bandwidth is constructed by adopting a frequency band division method based on the combinationof Hilbert transformation and band-pass filtering; time periods are divided to construct a block energy matrix, and time-frequency entropies are extracted from the normalized energy matrixes in the time domain direction and the frequency domain direction respectively; thirdly, normalization processing is conducted on the vibration signals of all the frequency bands through a normal state cumulative distribution function (NCDF), and the singular entropy of the time-frequency matrixes of all the blocks is extracted; and finally, an integrated extreme learning machine is used as a classifier foridentifying the mechanical fault of the small-sample high-voltage circuit breaker. Example verification proves that the method provided by the invention has relatively high identification degree.

A disparity calculating method includes generating an energy matrix according to a first image-block and a second image-block, wherein the energy matrix includes a plurality of energies of a plurality of pixels corresponding to a plurality of disparity candidates; setting the energy corresponding to a starting pixel of the plurality of pixels and a specified disparity candidate of the plurality of disparity candidates as a first predetermined value and setting the energies corresponding to the starting pixel and other disparity candidates of the plurality of disparity candidates as a second predetermined value, wherein the second predetermined value is greater than the first predetermined value; generating a path matrix according to the energy matrix; and determining a plurality of disparities of the plurality of pixels sequentially from an ending pixels of the plurality of pixels, wherein the disparity of the ending pixel is set as a third predetermined value.

The invention discloses an identity recognition method and device of identical names in multiple networks. The method comprises the following steps: obtaining user identity information and user identity corresponding relations in multiple networks, using a user identity information set with known user identity corresponding relations as a training set, establishing a lowest energy model based on user behavior similarity according to the user identity information in the training set, and obtaining energy factors and a matching relation classifier; matching two pieces of arbitrary user identity information according to the matching relation classifier, and solving the energy matrix to obtain a matching result of single prediction; integrating the matching results solved in multiple times to obtain the user identity corresponding relations. The method and the device disclosed by the invention can be used for confirming the identity of information having different user identity information while having the same names in the multiple networks to improve the accuracy of a statistical result, the adopted algorithm is efficient, the calculation process is fast, and with the increase of sample databases, the accuracy rate of a calculation result is continuously improved.

The invention relates to the technical field of power distribution networks, and specifically relates to a power distribution switch mechanical fault feature extraction method based on CEEMDAN and weighted time-frequency entropy. The method comprises the following steps of: step 1, acquiring a vibration signal through an acceleration or speed signal data acquisition system; step 2, decomposing thevibration signal through a CEEMDAN method to obtain IMF components of each order of the vibration signal; step 3, obtaining instantaneous frequencies respectively corresponding to each order of IMF components through Hilbert transformation; step 4, carrying out equal frequency band division on the IMF component through a band-pass filtering method in combination with the instantaneous frequency to construct a time-frequency matrix with a specified bandwidth; and step 5, performing equal interval division on the time-frequency matrix in the time domain direction to obtain a block time-frequency matrix, and solving the energy value of each block time-frequency matrix to construct a block energy matrix. According to the method, in view of the complexity difference of time sequences of frequency bands, the normalized sample entropy of the frequency bands is taken as the weight, and the weighted time-frequency entropy is extracted from the normalized energy matrix in the time domain direction and the frequency domain direction respectively to enhance the characterization capability of the characteristics.

The invention discloses a multi-perspective gait classification method based on multiple regression. The method comprises the steps that 1 a human body contour is extracted from a gait data set to be classified; two human body area images of inner point representation and boundary representation are constructed, and a hub energy diagram is further generated; 2 a multi-period hybrid gait energy matrix corresponding to each gait image sequence is calculated as a gait feature based on the hub energy diagram of the previous step; and 3 multi-perspective gait classification is converted into multiple regression, and a convolution neural network is constructed for solving. According to the invention, the multi-perspective gait classification method based on multiple regression uses the multi-period hybrid gait energy matrix as the gait feature; accurate gait period segmentation is eliminated; the reliance on gait period segmentation is reduced; multi-perspective gait classification is converted into multiple regression; the convolution neural network is constructed for solving; and the gait classification accuracy is improved.

The invention discloses an ultrasonic pulse Doppler imaging method and device. The method comprises the steps that an energy matrix is established for echo signals of a received transmitting sequence; a speed sequence for scanning a target is established according to pulse repetition frequency and the central frequency of a probe; energy values corresponding to all speed elements in the speed sequence are obtained according to the energy matrix; an energy spectrum of the speed sequence is generated according to the energy values; an ultrasonic image is generated according to the energy spectrum. The order of a coding compression filter can be effectively reduced, and Doppler imaging can be achieved without a large calculation amount.

The invention provides an active and passive ultrasonic composite imaging method and system for focused ultrasonic irradiation on phase change nanometer liquid drops. After passive ultrasonic originalradio frequency signals are subjected to time delay compensation processing, a cross-correlation coefficient matrix and a passive amplitude coherent wave beam forming energy matrix are obtained respectively through two complementary square wave apodizing functions and an amplitude coherent coefficient; after the two matrixes are subjected to point multiplication, a high-resolution passive ultrasonic imaging result is obtained; phase change microbubble group mother wavelets are constructed through a phase change microbubble group vibration model; active wave beam forming radio frequency signals obtained after the mother wavelets are used for performing time delay superposition on the active ultrasonic original radio signals are subjected to continuous wavelet transformation to obtain a high-contrast active ultrasonic imaging result; and a composite image is obtained after the high-resolution passive and high-contrast active ultrasonic imaging results are compounded. The method and thesystem can be used for performing whole-process monitoring on cavitation activities in the focused ultrasonic irradiation process of the phase change nanometer liquid drops and the residue phase change microbubbles when the irradiation is stopped.

The invention discloses a surface shape registration method based on a ricci flow. The method comprises the steps that a closing surface is parameterized according to an improved ricci flow method firstly; the closing surface is mapped to a spherical surface; in addition, an energy variation condition of the ricci flow is recorded in a computation process; a multi-scale ricci flow energy matrix is established, and then subjected to laplace transformation; a laplace matrix of the multi-scale ricci flow energy matrix is computed; multi-scale feature points based on ricci energy are extracted according to the laplace matrix; furthermore, global ricci flow energy are combined with local feature points; a registration equation is established; a plurality of various surfaces are subjected to registration on a spherical surface domain by utilizing the registration equation; registration results are mapped to the original surface finally; and the whole registration process is accomplished. With the adoption of the method, the computation time in a parameterization process is shortened; global attributes are effectively combined with local features; and the accuracy of the registration is improved.

The invention discloses a multi-path management method used in multi-path search, comprising that calculating a first threshold value, selecting a effective path according to the first threshold value, calculating a second threshold value, according to the second threshold value, selecting a standby path, calculating the energy matrix gravity center of a search window, using the center to judge if the search window needs adjustment, sending the effective path to a reek receiver to process multi-path demodulation, distributing the calculated search window position adjusting information to a search module to refresh search parameters. The invention manages the multi-path threshold value for calculating search window position and for reek demodulation respectively, while the one for calculating the search window position is lower than the other one. When one effective path disappears, and the standby paths are more than the effective paths, the gravity center of the search window will not change much, and the adjustment fluctuation of the search window can be reduced to confirm the property of receiver.

The invention is applicable to the technical field of signal processing, and provides a two-dimensional direction of arrival estimation method, which comprises the steps of acquiring snapshot data output by an antenna array; processing the snapshot data based on a constructed filter self-adaptive to a weighted least square method, and obtaining the estimation of an incident signal repeated amplitude; based on the estimation of the incident signal repeated amplitude, carrying out iterative computation to obtain an energy matrix of an incident signal in a specified two-dimensional space; carrying out two-dimensional spectrum peak searching on the energy matrix, and obtaining a two-dimensional direction of arrival of the incident signal. According to the two-dimensional direction of arrival estimation method provided by the invention, the problem that in the prior art, the two-dimensional direction of arrival estimation cannot be estimated under the short snapshot condition is solved, andthe combined estimation of an azimuth angle and a pitch angle of a far-field narrow-band signal can be realized by utilizing less snapshots.

The invention provides a stem cell ointment used for treating skin damages, and a preparation method thereof. The preparation method comprises following steps: mesenchymal stem cells with immunity adjusting and tissue regeneration promoting functions are prepared into blocks with uniform sizes under 3D suspension culture conditions, and are mixed with a biotoxicity-free active energy matrix so asto obtain the ointment. Stem cells are capable of living for as long as one week in the ointment at room temperature, and the biological activity is maintained. The stem cell ointment can be smeared onto skin damages directly, the stem cells in the ointment are capable of migrating into the wounds to inhibite inflammation, promote tissue regeneration, accelerate wound healing, improve healing status, and reducing scars; after restoration, the stem cells are eliminated by self immunity systems, no residual is left, the stem cell ointment is safe and stable, and is high in efficiency.

The invention discloses a radar target quick CFAR detection method based on smoothing. The method specifically comprises the steps of obtaining SAR radar imaging data; marking the SAR radar imaging data as an amplitude matrix I of an image to be detected, wherein the amplitude matrix I includes a moving object-of-interest and background clutters of the moving object-of-interest, and the moving object-of-interest in the amplitude matrix I covers a number of pixels, and the number of pixels is shown in the description; then calculating in sequence an X*Y dimension energy matrix S of an image to be detected and an M*N dimension energy matrix S of the image to be detected, calculating an A dimension frequency domain matrix to be smoothed of the image to be detected so as to further calculate a B dimension statistic matrix of which background clutters are smoothed, wherein the A dimension frequency domain matrix and the B dimension statistic matrix are shown in the description; calculating in sequence an R*G dimension clutter energy matrix of the image to be detected and an R'*G' dimension discrimination matrix of the moving object-of-interest; calculating an X'*Y' dimension effective discrimination matrix of the moving object-of-interest; obtaining the number of pixels in the moving object-of-interest corresponding to elements in the X rows and Y columns in the X'*Y' dimension effective discrimination matrix of the moving object-of-interest, wherein the number of the pixels in the moving object-of-interest is shown in the description. In this way, the moving object-of-interest in SAR radar imaging is detected.

The invention discloses an X-ray medical image objective reconstruction method based on independent component analysis. In order to solve the problems that a traditional medical X-ray image is high in noise and poor in layering, and organs and tissue overlap, image denoising and objective extraction are carried out by combining a multi-energy-spectrum X-ray imaging technology and an independent component analysis algorithm. The method comprises the steps that first, denoising preprocessing is carried out on a medical image so that the preconditions for objective separation through independent component analysis can be met; second, the thickness value of an aliasing organ in each pixel is obtained according to an X-ray attenuation energy matrix of organ and tissue; third, the independent component analysis algorithm is used for adjusting the frequency of convergence and the size of signal scales according to the thickness value of the aliasing organ, a convergence matrix is obtained, the image of each organ is separated, contrast ratio correction is carried out according to an subjective vision standard, an area of interest and marginal information stand out, and the visual and clear image applicable to medical analysis are obtained.

The invention discloses a search method and device for figure information. The search method includes the steps that figure identity information in multiple networks and figure identity corresponding relations are obtained; the figure identity information of the known figure identity corresponding relations is gathered to serve as a training set; an energy minimum model based on the figure behavior similarity degree is constructed, and then energy factors and a matching relation classifier are obtained; energy filling is performed through the energy factors to form an energy matrix, and a matching result predicted at one time is obtained through solving the energy matrix; matching results obtained through repeated solving are integrated, so that the figure identity corresponding relations are obtained, and the identity uniformity of figures with the same name is determined; an input name is received, and the identity information, in different networks, of the same figure is displayed in one webpage. The method and device can determine the uniformity of the information with different identities but the same name in the multiple networks, and the adopted algorithm is efficient and calculation is rapid in the process of displaying the identity information, in different networks, of the same figure in the webpage.

The embodiment of the invention discloses a multimedia data processing method and device. The method comprises the steps of acquiring multiple audio file samples corresponding to multimedia data, and generating target audio energy matrixes corresponding to the audio file samples respectively, wherein the audio file samples have the same frame number, and elements in each target audio energy matrix are audio energy values of different frames in a corresponding target audio file sample respectively; conducting average value processing on the audio energy values of different frames in all the target audio energy matrixes, so as to obtain a target average value matrix, wherein elements in the target average value matrix are audio energy average values of different frames; and determining a frame corresponding to the maximum audio energy average value in the target average value matrix as a target frame, and determining the refrain starting moment of the multimedia data according to the target frame. In this way, accurate position of the refrain of the multimedia data can be achieved through multiple audio file samples.

The invention discloses a rapid extraction method for small snaking operation characteristics of a high-speed train. The method aims to solve the problem that an existing method cannot quickly identify the small snaking motion state (normal operation, small convergence, small divergence and large snaking) of the high-speed train. The method comprises the following steps of: decomposing a preprocessed signal by adopting an EEMD (Empirical Mode Decomposition) method; converting the result into an energy matrix, performing joint approximate diagonalization (JAD) processing on the energy matrix under a non-stationary condition, and fusing the energy matrixes of a plurality of sensors to obtain fused characteristics of the small snaking running state of the high-speed train. The fusion featuresare put into the least square method support vector machine to be trained and identified, it is verified that the method can rapidly and accurately separate the four operation states of normal operation, small convergence, small divergence and large snaking of the high-speed train, and therefore the operation safety of the train is guaranteed.

The present invention provides an uplink synchronous tracking method and a device in TD-SCDMA systems. The method can include steps below: I. Computing threshold values for effective diameter confirmation; II. Selecting effective diameters according to the threshold value; III. Interpolating threshold value to peak value phase position of the selected effective diameter to improve precision of the peak value phase position; IV. Computing energy matrix center of gravity for the effective diameter after being interpolated with the threshold value; V. Judging variation of synchronous sequence relation according to a relation between a position of the calculated energy matrix center of matrix and a target position arranged in outer synchronous control parameters and creating synchronous deviation commands. Therefore, the method and the device make uplink synchronous tracking more reliable, thus ensuring performance of receiving sets.

The invention discloses a hydraulic turbine set fault diagnosis method based on SDAE-IELM. The method comprises the following steps: employing a complete set empirical mode decomposition algorithm CEEMDAN with adaptive noise addition to decompose a hydraulic turbine set vibration signal, and obtaining an intrinsic mode function (IMF) part reflecting the local time scale features of the signal; dividing a time-frequency matrix formed by the IMF parts according to time periods and calculating energy values of all segments, thereby converting the time-frequency matrix into an energy matrix; performing feature extraction on the energy matrix by adopting SDAE; iELM is adopted to realize classification of known fault types and detection of unknown fault types. After the unit breaks down, judgment can be made quickly and accurately, the shutdown maintenance time can be shortened, the working intensity of operation and maintenance personnel is relieved, and the working efficiency is improved.