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1296 results about "Rotary machine" patented technology
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Dynamic coupling compensation method for thermal expansion and axial displacement
The invention belongs to the field of equipment coupling monitoring, and particularly relates to a dynamic coupling compensation method for thermal expansion and axial displacement, which comprises the following steps of: calculating a first characteristic value for representing reference dynamic offset of a sensor based on a three-dimensional thermal-structure coupling model by acquiring a thermal expansion parameter and axial displacement parameter sequence of a casing; calculating a second characteristic value representing the real position change of the rotor in combination with a rotor-casing axial thermodynamic model, establishing a piecewise coupling function considering a nonlinear effect, working condition self-adaption and cross interference, and eliminating the mechanical thermal inertia and measurement system lag influence through a dynamic delay compensation mechanism; an accurate axial displacement measurement total error compensation index is generated, and grading compensation actions are intelligently triggered according to error grades; the problem of measurement distortion caused by dynamic coupling of thermal expansion and axial displacement is effectively solved, and the accuracy and reliability of state monitoring of the rotating machine are remarkably improved.
Owner:SHANGHAI RUISHI INSTR & ELECTRONIC CO LTD
Method for monitoring a rotating machine in order to detect a fault in an aircraft bearing
ActiveUS20250271330A1Machine part testingInternal-combustion engine testingMachineVibration signature
A method for monitoring a rotating machine in order to detect a fault in a bearing, the method including acquiring, from the rotating machine, a vibration signal measured by a vibration sensor; determining a first-order spectrogram by first-order cyclostationary analysis of the vibration signal using a delta transform and spectral standardisation; determining a second-order spectrogram by second-order cyclostationary analysis of the vibration signal using averaged cyclic coherence, a delta transform and spectral standardisation; and detecting a vibration signature of the fault in the bearing on the basis of the first-order spectrogram and the second-order spectrogram.
Owner:SAFRAN SA +1
Rotary machine health state evaluation method based on LSTM and Transform fusion network
The invention discloses a rotating machine health state evaluation method based on an LSTM and Transform fusion network, and relates to the field of intelligent monitoring, and the method comprises the following steps: collecting and preprocessing fault data of a rotating machine, and dividing the preprocessed fault data into a training set and a test set; a fusion network model based on LSTM and Transform is constructed, and the fusion network model is trained; using the trained fusion network model to predict the health state of the rotating machine, and outputting the health degree score of the rotating machine; by comparing and analyzing the health degree score prediction value of the rotating machine and the actually collected health state data of the rotating machine, the fusion network model is retrained and subjected to parameter adjustment, and the prediction accuracy and stability are improved. According to the method, the advantages of the LSTM and Transform networks are combined, the comprehensiveness of feature extraction and the reliability of prediction results are ensured, the high prediction precision and robustness of equipment health assessment under complex working conditions are ensured, and the efficiency and stability of operation monitoring of industrial equipment can be effectively improved.
Owner:HEBEI BAISHA TOBACCO
Sliding component
There is provided a sliding component that supplies a sealed fluid to a leakage side in a gap between sliding surfaces to exhibit high lubricity and has a small leakage of the sealed fluid. A sliding component that has an annular shape and is disposed in a place where relative rotation is performed in a rotary machine, includes a plurality of dynamic pressure generating mechanisms provided in a sliding surface of the sliding component, each of the dynamic pressure generating mechanisms including a deep groove portion that communicates with a leakage side, and a plurality of shallow groove portions that communicate with the deep groove portion and are arranged in a circumferential direction in parallel relationship to each other.
Owner:EAGLE INDS
Rotary machinery vibration protection method and system of adaptive resonance neural network
The invention discloses a rotating machine vibration protection method and system of an adaptive resonance neural network, and the method comprises the steps: collecting a millisecond vibration acceleration signal of a rotating machine through a distributed piezoelectric sensor array, obtaining the real-time working condition parameter of equipment, and generating a time-work synchronous vibration signal flow; inputting the time-work synchronous vibration signal flow into a resonance neural network, and dynamically generating a frequency domain-time varying adaptive threshold group in combination with the working condition parameters; extracting a weak impact resonance characteristic tensor by using a multi-scale resonance kernel of the resonance neural network; projecting a weak impact resonance characteristic tensor to an orthogonal fault subspace through a tensor decomposition algorithm, and separating out a decoupling fault characteristic matrix; and generating a real-time protection decision instruction set based on a comparison result of the decoupling fault feature matrix and the equipment operation historical database. According to the embodiment of the invention, the method can improve the detection sensitivity and positioning precision of a weak fault under an unsteady working condition, and achieves the real-time adaptive optimization of the vibration protection of the rotating machine.
Owner:BEIJING HUAKE TONGAN MONITORING TECH CO LTD
Time-frequency analysis method for impact signal positioning based on transient scale extraction transformation
ActiveCN120558558AMachine part testingSubsonic/sonic/ultrasonic wave measurementTime–frequency analysisTransition matrices
The invention discloses a time-frequency analysis method for impact signal positioning based on transient scale extraction transformation, and belongs to the technical field of mechanical vibration signal processing. The method comprises the following steps: collecting a rotating machine fault vibration signal, and reconstructing a signal model through Hilbert transform and a Dirac function; a transition matrix is generated by using a Gaussian window function traversal model, and matching and Fourier transform are carried out in combination with a discretized scale basis function; solving a frequency partial derivative of a transformation result to generate a time redistribution operator, and redefining by a Dirac function to obtain a transient scale extraction operator; based on the sub-time-frequency representation of scale-based rotation discretization, screening optimal matching results of each time center through a maximum kurtosis value, and integrating the optimal matching results into a complete time-frequency representation; and finally, redistributing a time-frequency coefficient by using a transient extraction operator to realize accurate positioning of the impact component. According to the method, the problems of serious impact energy diffusion and insufficient positioning precision in existing time-frequency analysis are solved, and the time-frequency representation readability and the impact positioning reliability are remarkably improved.
Owner:BEIJING ZHONGYUAN RISEN TECH CO LTD
Vibration-temperature correlation fault early warning method based on multi-sensor fusion
The invention provides a vibration-temperature correlation fault early warning method based on multi-sensor fusion, and relates to the technical field of rotating machine fault diagnosis, and the method achieves the efficient diagnosis of the rotating machine fault through the three-field coupling analysis of vibration, temperature and torque. Multi-dimensional health indexes are introduced, sensor data of different dimensions are normalized into a monitorable numerical value, and the health state of equipment is reflected in real time through a dynamically optimized weight coefficient. A core depth time sequence neural network model is combined with an attention mechanism and a Transform coding layer, the problem of long-term dependence is effectively solved, and the fault recognition precision is improved. According to the method, future innovation directions such as cross-device collaborative diagnosis, quantum computing acceleration and digital twinborn visualization are also exhibited, and the method has important industrial application value.
Owner:XIAMEN NEVC ADVANCED ELECTRIC POWERTRAIN TECH INNOVATION CENT +1
Method and device for predicting service life of rotating machine based on multi-sensor spatio-temporal information fusion network
The invention discloses a rotating machine life prediction method and device based on a multi-sensor spatio-temporal information fusion network, and relates to the technical field of rotating machine health state assessment, and the method comprises the steps: obtaining multi-source monitoring signal data of a to-be-predicted rotating machine in a set time period; performing normalization processing on the multi-source monitoring signal data; constructing a monitoring data sample based on a set sliding step length and the normalized multi-source monitoring signal data by adopting a set sliding window; constructing a time information mining module, a spatial relationship modeling module, a residual connection module and a full connection network, and performing program optimization processing to obtain a life prediction model; and inputting the monitoring data sample into the life prediction model to obtain the residual service life value of the to-be-predicted rotating machine. According to the invention, the monitoring signals collected by the multi-source sensor can be fused, the time information and the spatial relationship in the multi-source monitoring signals are extracted and fused, and the prediction precision and robustness of the life prediction model are improved.
Owner:CHONGQING UNIV
Novel intelligent rotating machine fault diagnosis method
The invention provides a novel intelligent rotating machine fault diagnosis method, and belongs to the technical field of rotating machine fault diagnosis, and the method comprises the steps: obtaining vibration signals of a rotating machine under normal and different fault types; a variation mode decomposition method is adopted to pre-process and decompose the vibration signal of the rotating machine, noise is removed, and then a new signal is reconstructed and generated; the new vibration signal is converted into a two-dimensional time-frequency image through short-time Fourier transform; optimizing hyper-parameters of a convolutional neural network (CNN)-long and short term memory neural network (BiLSTM) by adopting a Sharla silver ant optimization algorithm (SSAO), wherein the hyper-parameters comprise the number of neurons of a convolutional layer, the size of a convolution kernel and the number of neurons of a BiLSTM layer; and inputting the two-dimensional time-frequency image into the CNN-BiLSTM model after the hyper-parameter optimization to realize fault diagnosis of the rotating machine. The method has very important practical significance for improving the rotating machine fault diagnosis accuracy and guiding equipment maintenance and repair.
Owner:SICHUAN UNIVERSITY OF SCIENCE AND ENGINEERING
Small sample fault diagnosis method based on two-way convolution and closed set domain self-adaption
The invention discloses a small sample fault diagnosis method based on two-way convolution and closed set domain self-adaption, vibration signals are preprocessed through maximum and minimum normalization and FFT, preprocessed frequency domain data are used as input by DPFC-FFABNet, and useful features can be fully extracted through a two-way full convolution structure. And group normalization and layer normalization are introduced, so that the robustness of the model is enhanced. A global-local feature fusion attention mechanism is utilized to consider extraction of local and global information of a feature sequence. In order to solve the problem of small sample fault diagnosis generalization, the method provided by the invention has excellent performance under different rotating mechanical parts, different rotating speed conditions and different noise interference conditions, and has good application value. And finally, on the basis of the method provided by the invention, multi-core maximum mean difference MKMMD is combined with class confusion minimization MCC, so that the fault diagnosis generalization capability of variable rotating speed and variable load is further enhanced.
Owner:CHONGQING UNIV
Rotary machinery system performance evaluation and optimization method and system based on system negentropy conversion rate
The invention provides a rotating mechanical system performance evaluation and optimization method and system based on system negentropy conversion rate, and the method comprises the following steps: carrying out the numerical simulation of a flow field of a rotating mechanical system through a computational fluid mechanics method, and obtaining the parameters of the flow field; calculating a viscous dissipation entropy yield, a turbulent dissipation entropy yield and a wall entropy yield in the fluid domain based on the flow field parameters; the total entropy yield of the system is obtained through the volume fraction and the wall area fraction of the whole fluid domain; converting the input power of the rotating machinery into an equivalent negentropy flow, and calculating the negentropy conversion rate of the system for evaluating the effective utilization degree of the input power; and evaluating the performance of the rotating machinery system based on the negentropy conversion rate, and identifying a key area of energy loss. According to the method, the negentropy conversion rate result is applied to structural design optimization, running state diagnosis and energy efficiency adjustment of the rotating machinery, and online calculation and dynamic visualization can be realized in combination with real-time monitoring data.
Owner:SUZHOU MANGRUFU EQUIPMENT TECHNOLOGY CO LTD +1
Double-track rotary manipulator cigarette packet mixed loading equipment
The utility model discloses a double-track rotary manipulator cigarette packet mixed loading device. The device comprises a cigarette packet conveying module (1), a rotary transmission module (4) and a manipulator module (5), wherein the cigarette packet conveying module (1) comprises a first track (A) and a second track (B) which are vertically arranged on the same horizontal plane; the rotary transmission module (4) is arranged at the vertical intersection of the second track (B) and the first track (A); the number of the mechanical arm modules (5) is two, and the two mechanical arm modules (5) are arranged at the two ends of the rotary transmission module (4) respectively.
Owner:CHINA TOBACCO YUNNAN IND
Rotating machine fault diagnosis method in open-set cross-domain scene, terminal and medium
PendingCN120994958AMachine part testingSubsonic/sonic/ultrasonic wave measurementFeature extractionAlgorithm
The invention relates to the technical field of rotating machine fault diagnosis, and discloses a rotating machine fault diagnosis method in an open-set cross-domain scene, a terminal and a medium. The method comprises the following steps: firstly, acquiring a one-dimensional vibration signal of the rotating machine, and converting the one-dimensional vibration signal into a two-dimensional time-frequency image after preprocessing; constructing a fault diagnosis model which comprises a feature extractor module, a classifier module, a domain discriminator module and a weight calculation module; the weight calculation module can dynamically calculate the alignment weight according to the distance between the target domain sample and the center of the source domain category. Through cross-domain adversarial training, in combination with classification loss, domain discrimination loss and weight alignment loss, feature alignment of a source domain and a target domain is realized, so that training of a fault diagnosis model is completed; and finally, inputting the two-dimensional time-frequency image into a trained fault diagnosis model, and outputting a fault type and a fault probability. According to the method, negative migration caused by alignment of unknown class features and source domain features is reduced, and the process of manually rejecting target domain unknown samples for training is omitted.
Owner:ANHUI UNIV OF SCI & TECH
Refined gap-adjustable tilting pad bearing and control method
PendingCN120889820ABearing assemblyPiezoelectric/electrostriction/magnetostriction machinesSet screwCeramic
The invention discloses a fine gap-adjustable tilting pad bearing and a control method, and belongs to the technical field of bearings, and the fine gap-adjustable tilting pad bearing comprises a bearing body, pads, pre-tightening screws, set screws, a cover plate, a displacement amplification structure, pre-tightening bolts, elastic gaskets and piezoelectric ceramic stacks. A plurality of tilting pads are arranged on the inner arc surface of the bearing body and are matched with the bearing body through a spherical support; four radial grooves are formed in the outer arc face in the circumferential direction and are opposite to the centers of the four tile blocks respectively. A notch of the radial groove is connected with a cover plate, is internally provided with a piezoelectric ceramic displacement amplification mechanism and is connected with the spherical support through a positioning pin; a piezoelectric ceramic stack is arranged between a left boss and a right boss of the mechanism and is pre-tightened by a pre-tightening bolt and an elastic gasket. According to the invention, the inverse piezoelectric effect of piezoelectric ceramics is utilized, a vibration and non-linear suppression method is provided, an advanced control algorithm is matched, the piezoelectric ceramics stack is electrified and contracted, a displacement amplification effect is generated through a displacement amplification mechanism, the tile gap is finely adjusted, and the high-performance requirement of modern rotating machinery is met.
Owner:XIAN THERMAL POWER RES INST CO LTD
Fault diagnosis method and system for rotating machine bearing
The invention discloses a fault diagnosis method and system for a rotating machine bearing, and belongs to the technical field of fault diagnosis. The method comprises the following steps: acquiring a to-be-diagnosed vibration signal of the rotary mechanical bearing; inputting the to-be-diagnosed vibration signal into a pre-constructed bearing fault diagnosis model, and outputting a fault diagnosis result of the rotating machine bearing; the bearing fault diagnosis model comprises a feature extraction network, a GMM feature enhancement module, a projection distillation module and a dynamic extensible classifier which are connected in sequence. According to the method, catastrophic forgetting can be effectively relieved, continuous diagnosis of newly-occurring accidental faults can be achieved, in the initial task, the model learns and identifies different fault types through a fault bearing data set collected in advance, a basis is provided for the subsequent increment task, the increment task is composed of a plurality of stages, and in each stage, the fault bearing data set is subjected to fault detection. The model enhances playback of old knowledge through historical category pseudo features generated by a Gaussian mixture model, and aligns feature representations of new and old models by using a projection distillation module.
Owner:SUZHOU UNIV
Key phase pulse signal synchronous acquisition and multi-axis centering analysis method
ActiveCN121092886ASubsonic/sonic/ultrasonic wave measurementMachine gearing/transmission testingElement analysisFinite elemente analyse
The invention discloses a key phase pulse signal synchronous acquisition and multi-axis centering analysis method, which belongs to the technical field of mechanical monitoring and diagnosis, and comprises the following steps of: configuring a synchronous acquisition system, acquiring a conditioned key phase pulse signal and a conditioned vibration signal, and extracting an axis speed and a load; constructing a time drift monitoring model to compensate the key phase pulse signal in real time, and ensuring the time synchronization precision; the compensation signal is input into a shaft centering correction model based on dynamics and finite element analysis, and radial deviation and axial deviation under the dynamic load are calculated; establishing a nonlinear tolerance threshold model by adopting a nonlinear regression model, and dynamically adjusting an allowable centering deviation threshold in combination with the real-time shaft speed and the load; through closed-loop comparison of the shaft centering deviation and a threshold value, a centering qualified conclusion or a correction suggestion is automatically output, and triggering signal resampling is supported to adapt to working condition changes; the real-time and self-adaptive analysis of the centering deviation of the multi-axis system is realized, and the operation stability and the maintenance efficiency of the rotating machinery are improved.
Owner:SHANGHAI RUISHI INSTR & ELECTRONIC CO LTD
Abnormal detection method for mechanical rotating equipment under varying working conditions based on feature alignment residual GAN
The present invention discloses a method for detecting abnormalities in mechanical rotating equipment under variable working conditions based on feature alignment residual GAN. The method comprises: constructing a time-frequency graph from rotating machinery data, reconstructing the time-frequency graph using an encoder GE(x) and a decoder GD(x) respectively combined with an autoencoder network of a residual module ResNet, and using a discriminator D to distinguish the authenticity of the reconstructed data and the source data to determine abnormal data. The loss function of the network contains an adversarial loss L. adv , context loss L of the generator reconstruction data error con , encoder loss L enc , and the loss L of Wasserstein distance for constructing ranking parity data classification for eigenvalue alignment w‑gan The present invention has a good effect on detecting abnormalities of rotating machinery under variable working conditions, can detect abnormalities of rotating machinery equipment in advance, ensure the long-term stable operation of industrial systems, and avoid the occurrence of serious accidents, which has important social significance.
Owner:SOUTH CHINA UNIV OF TECH
Radial adjustable brush type sealing structure with thermal response adjusting function
The invention relates to the technical field of rotary mechanical sealing, in particular to a radial adjustable brush type sealing structure with a thermal response adjusting function, which comprises a plurality of arc-shaped sealing structures, and the end surfaces of the plurality of arc-shaped sealing structures are connected to form an annular brush type sealing structure; the arc-shaped sealing structure comprises an arc-shaped sealing case, an elastic supporting assembly and an axial limiting assembly. When the rotor radially jumps or the temperature changes, the arc-shaped sealing block can adaptively move in the guide limiting assembly to adaptively adjust the sealing gap between the brush wire bundle and the rotor, so that the sealing performance is improved, and the service life of the brush wires is prolonged.
Owner:NORTHWESTERN POLYTECHNICAL UNIV
Rotary machinery data enhancement method based on SCF-CVAE-GAN network
The invention relates to the field of rotating machine fault diagnosis, in particular to a rotating machine data enhancement method based on an SCF-CVAE-GAN network, and the method comprises the steps: obtaining rotating machine vibration signals in different fault modes; the rotating machinery vibration signals are converted into a two-dimensional time-frequency image, and the SCF-CVAE-GAN network is trained by adopting the two-dimensional time-frequency image; generating a two-dimensional time-frequency image sample by adopting the trained SCF-CVAE-GAN, calculating the structural similarity and the distance score of the generated sample, and evaluating the quality of the generated sample; mixing the generated sample meeting the quality requirement and the two-dimensional time-frequency image to obtain an enhanced data set; according to the method, a double-self-correction network is provided, a frequency domain regularization strategy is integrated, global information and local textures of data are deeply mined, and the diversity and fidelity of generated samples are ensured by constraining distribution of the samples in a frequency domain.
Owner:CHONGQING UNIV OF POSTS & TELECOMM
Vehicle door switch actuating apparatus with a large actuating surface
Owner:ILLINOIS TOOL WORKS INC
Oil extraction machine ground rotating machine fault diagnosis method based on parallel diagnosis model
The invention discloses an oil extraction machine ground rotating machine fault diagnosis method based on a parallel diagnosis model, and the method constructs a double-branch fusion diagnosis model based on deformable convolution DCN and Transformer in order to solve the problems that fault features of an oil extraction machine rotating machine are difficult to extract under a strong noise condition and the anti-interference capability of a diagnosis model is insufficient. The model combines the local feature adaptive extraction capability of deformable convolution and the global time sequence modeling advantage of Transform, the diagnosis robustness in the noise environment is effectively improved through a multi-dimensional feature fusion mechanism, and the experimental result shows that the method has high average diagnosis accuracy under the condition of low signal-to-noise ratio. And the fault diagnosis precision of the rotating machine on the oil extraction machine well is obviously improved.
Owner:NANJING FUDAO OIL & GAS INTELLIGENT CONTROL TECH CO LTD
Rotary machinery fault diagnosis method based on PyramidNet and Transform
The invention discloses a rotary machine fault diagnosis method based on PyramidNet and Transform, and relates to the field of fault diagnosis, and the method comprises the following steps: carrying out the normalization preprocessing and sliding window segmentation of an original vibration signal, and generating a time sequence data segment with a fixed length; carrying out discrete wavelet transform on the time sequence, carrying out multilayer decomposition by adopting a Daubechies 4 wavelet basis function, and converting a signal from a time domain to a frequency domain; a hybrid network model based on PyramidNet and Transform is constructed, local features are extracted by increasing the number of channels layer by layer, and channel attention and space attention optimization is carried out in combination with a CBAM module; performing time sequence modeling on the output features, and capturing a long-distance dependency relationship of a time sequence through a multi-head self-attention mechanism; according to the method, the extracted global features are classified, fault categories are output, feature extraction and fault classification are carried out by adopting an improved hybrid network architecture, the defects of a traditional method in feature extraction and global dependency modeling are overcome, and the detection precision and robustness of fault diagnosis are effectively improved.
Owner:HEBEI BAISHA TOBACCO
Rotary machinery fault diagnosis method based on expansion residual network
The invention discloses a rotating machine fault diagnosis method based on an expansion residual network, and relates to the technical field of mechanical faults, and the method comprises the steps: collecting a continuous time sequence vibration signal of a rotating machine through an acceleration sensor, obtaining a high-order harmonic energy sequence set after fast Fourier transform, and determining an abnormal trend segment; then, obtaining and updating a structural anomaly candidate set based on the anomaly trend segment and the operating environment state of the rotating machine, generating a first drift vector set according to the updated structural anomaly candidate set, and identifying a structural offset section according to the first drift vector set and historical operating data; and backtracking the structural offset section to an original time domain signal to establish a second drift vector set, and finally, inputting the first drift vector set and the second drift vector set into the expansion residual network to analyze whether the rotating machinery is evolved into a fault state.
Owner:GUIZHOU JINGANG INTELLIGENT MANUFACTURING TECHNOLOGY CO LTD +1
Intelligent question and answer large language model construction method for rotating machine fault diagnosis
PendingCN120688626ANatural language data processingInference methodsLinguistic modelTheoretical computer science
An intelligent question and answer large language model construction method for rotating machine fault diagnosis comprises the steps that firstly, a large number of professional literatures, standard specifications and typical cases related to rotating machine fault diagnosis are collected and sorted, and a large model is adopted to automatically generate a high-quality question and answer pair corpus; then, a low-rank adaptation strategy is adopted to carry out efficient parameter fine adjustment on the general large language model, and injection of knowledge in the field of fault diagnosis is achieved while computing resources and labor cost are remarkably reduced; the intelligent question and answer large language model constructed by the method has relatively high mechanical term understanding capability and fault mechanism reasoning capability, and can effectively support knowledge question and answer services and the like of the rotating machinery.
Owner:XI AN JIAOTONG UNIV
Rotary machine domain confrontation fault diagnosis method based on multi-angle feature perception
The invention provides a rotating machine domain confrontation fault diagnosis method based on multi-angle feature perception, and the method comprises the steps: obtaining the original vibration signal data of a rotating machine, and constructing a label source domain data set and a multi-angle feature extraction structure; based on a multi-angle feature extraction structure, performing multi-scale parallel convolution on the original vibration signal by using three time domain branches to obtain a time domain feature vector; performing fast Fourier transform on the original vibration signal by using the three frequency domain branches to obtain a frequency domain feature vector; and splicing the time domain feature vector and the frequency domain feature vector into a fusion feature in the channel dimension, and constructing a domain adversarial learning module based on the fusion feature to perform fault diagnosis. According to the method, the essential characteristics of the signal can be deeply sensed from multi-granularity and multi-mode angles, efficient modeling of non-stationary impact, a periodic mode and a key response position is realized, and the robustness and the cross-domain generalization ability of fault diagnosis are further improved.
Owner:HARBIN INST OF TECH
Novel rotating machine fault intelligent diagnosis method
ActiveCN120670788AMachine part testingSustainable transportationVariational mode decompositionImage conversion
The invention provides a novel rotating machine fault intelligent diagnosis method, and belongs to the technical field of fault diagnosis, and the method comprises the steps: obtaining vibration signals of a rotating machine under normal and different fault types; performing preprocessing, decomposition and noise removal on the vibration signal by adopting a variational mode decomposition method VMD, and performing reconstruction to generate a new signal; the new signal is converted into a two-dimensional time-frequency image by adopting short-time Fourier transform STFT; using an interstellar fleet optimization algorithm SFA to optimize hyper-parameters of the convolutional neural network-long and short term memory network CNN-LSTM; inputting the two-dimensional time-frequency image into the CNN-LSTM model subjected to hyper-parameter optimization for training; and after noise reduction and two-dimensional time-frequency image conversion are carried out on a to-be-diagnosed rotating machine fault diagnosis signal, the signal is input into the VMD-SFA-CNN-LSTM model to realize rotating machine fault diagnosis. The method has very important practical significance for improving the rotating machine fault diagnosis accuracy and guiding equipment maintenance and repair.
Owner:SICHUAN UNIVERSITY OF SCIENCE AND ENGINEERING +1
Air compressor rotor testing method and testing device
ActiveCN120831201AStatic/dynamic balance measurementArtificial lifeFast Fourier transformDescent algorithm
The invention discloses an air compressor rotor testing method and device, and relates to the technical field of air compressor rotor testing. Vibration signal data of a rotor at multiple rotating speeds are collected, a fast Fourier transform algorithm is adopted for analysis, frequency and phase distribution is extracted, weighted analysis is carried out on the phase distribution, and the frequency and the phase distribution are extracted; and extracting the coordinates of the initial position with uneven mass distribution to realize accurate positioning of the position with unbalanced mass of the rotor. Fitting the offset by using a least square method to obtain a mass deviation coordinate, generating an initial counterweight adjustment scheme, optimizing initial counterweight parameters by combining a gradient descent algorithm to obtain an optimized counterweight adjustment scheme, and re-iterating the counterweight parameters of the optimized counterweight adjustment scheme by using a particle swarm optimization algorithm to obtain a target counterweight scheme. And the vibration signal of the rotor meets the vibration balance standard. According to the invention, the dynamic balance test efficiency and precision of the air compressor rotor are improved, and the operation stability of rotary mechanical equipment is ensured.
Owner:BEIFENG MACHINERY LIYANG
Method and system for detecting looseness of rotor bolt of high-rotating-speed hydraulic generator
The invention discloses a high-rotating-speed hydraulic generator rotor bolt looseness detection method and system, belongs to the technical field of hydropower station high-rotating-speed rotating mechanical equipment detection, and aims at solving the technical problems that hydraulic generator rotor bolt looseness detection is low in efficiency and poor in precision, real-time monitoring cannot be achieved, and safe and stable operation of a hydropower station is seriously affected. According to the invention, the image of the rotor bolt area is collected, and the image is accurately processed by using an image correction algorithm, so that image distortion is eliminated; thirdly, fusing an improved YOLOv8 target detection technology, a DeepLabV3 + semantic segmentation technology and a DeepSort multi-target tracking technology, and accurately extracting angle features of the bolt marking line; and then, a looseness identification objective function is constructed based on the angle change of the bolt, the function is solved in real time, and a detection result is output. According to the invention, high-precision, non-contact and real-time bolt looseness detection is realized, the detection efficiency and reliability are effectively improved, and a solid guarantee is provided for safe operation of a hydropower station.
Owner:CHINA YANGTZE POWER
Method for identifying blade surge characteristics based on blade tip vibration speed
PendingCN121207315AMachine part testingSubsonic/sonic/ultrasonic wave measurementStructural engineeringControl theory
The invention discloses a method for identifying blade surge characteristics based on blade tip vibration velocity, and relates to the technical field of non-contact measurement of rotating machinery rotor blades. According to the method, the vibration speed and the vibration displacement of the blade tip are monitored according to the two blade tip timing sensors installed in a small angle difference mode, the theoretical arrival time of the blade does not need to be considered when the vibration speed and the vibration displacement of the blade tip are calculated, and the calculation efficiency and the calculation accuracy are greatly improved; in combination with the time-frequency enhancement characteristic of a synchronous compression wavelet transform method, the dominant subsynchronous frequency of the blade is tracked and identified through the blade tip vibration speed, and meanwhile, a frequency ridge line is extracted for surge frequency identification and a surge interval is positioned; and finally, the vibration intensity during blade surge is judged according to a proposed intensity quantized value calculation method based on the blade tip vibration speed. The method for efficiently calculating the blade tip vibration parameters is provided, the surge frequency can be quickly recognized, the surge interval can be positioned, and the surge intensity can be quantitatively evaluated.
Owner:BEIJING UNIV OF CHEM TECH
Method and device for testing performance of rotor system excited by vibration table
The invention discloses a performance test method and device for a rotor system excited by a vibration table, and belongs to the technical field of rotary mechanical performance test. The test method comprises the following steps: carrying out resonance search on a tested rotor system; carrying out vibration and static / dynamic force loading on the rotor system; measuring performance parameters of the rotor system in a load state; calculating and stripping the relative motion influence of the measured rotor and the displacement sensor bracket, and correcting the radial error motion value of the rotor; establishing a performance state matrix of the rotor system under each working condition; forming rotor system service suggestion parameters; the testing device mainly comprises an electric vibration exciter, the top end of the electric vibration exciter is fixedly connected with a motor, and the output end of the motor is connected with a rotor system. According to the method and the device, active excitation and load loading are carried out on the rotor system under the stable / non-stable working condition, rapid and synchronous testing of rotation errors, thermal elongation, static rigidity and other performance under the load state can be achieved, and guidance is provided for improvement and optimization and service parameter setting of the rotor system.
Owner:LONGCHENG LABORATORY OF INTELLIGENT MANUFACTURING +2