398 results about "Composite signal" patented technology

The invention particularly relates to a leakage current testing method, device and system for an intelligent circuit breaker, and relates to the technical field of electrical safety detection. A composite signal generation and injection module; a broadband signal acquisition and conditioning module; and a line fault positioning and impedance analysis module. According to the invention, the composite signal generation module realizes the non-interference isolation injection of a leakage current signal and a high-frequency positioning signal, and guarantees the high fidelity of data through adaptive filtering, multi-channel synchronous sampling and high-precision timing. The line positioning module integrates TDR and a frequency domain impedance method, and through multi-frequency point deviation correction and topology-GIS association, the fault type is accurately identified, and the test and troubleshooting period is significantly shortened.

The invention provides an electric energy meter PCB function test method and device, a medium and equipment, and the method comprises the steps: obtaining a multi-channel signal source, automatically adjusting the characteristics of an input signal based on a feedback signal of an electric energy meter through a self-adaptive algorithm, and determining the consistency of the working characteristics of the input signal and the working characteristics of the electric energy meter; a virtual power grid environment simulation model is constructed, through integrated power simulation software and dynamic interference simulation, simulation signal source automatic adjustment signal characteristics are input into the virtual power grid environment simulation model based on the integrated power simulation software to synthesize a composite signal, and load fluctuation of an electric energy meter in actual operation is simulated based on the composite signal. Determining an electric energy meter test data set; according to the invention, the fault mode of the electric energy meter can be automatically identified, the test data can be analyzed in real time, and fault diagnosis and optimization suggestions can be automatically given. The intelligent diagnosis mode is far better than a traditional manual detection method, and the speed and accuracy of fault diagnosis can be remarkably improved.

The invention relates to the technical field of vibration test, and discloses a micro-seismic environment simulation vibration test board and a test method thereof, which realize high-fidelity simulation of multiple types of micro-seismic scenes through a multi-source composite signal generation and waveform reconstruction technology. The dynamic adjustment capability of the control strategy is improved by using disturbance compensation and an adaptive control mechanism, real-time analysis and early warning feedback are performed on the response state in the test process based on the vibration characteristic evaluation result, and an auxiliary decision basis is provided for the vibration control strategy. Besides, a hierarchical closed-loop regulation and control mechanism is logically formed based on local output regulation among multiple axes and a global control strategy, and closed-loop linkage of the control strategy, execution response, state evaluation and control correction is realized, so that the overall regulation and control precision, response sensitivity and test precision are remarkably improved; accurate simulation and stable control of a three-dimensional vibration field are realized.

The invention relates to the technical field of hydraulically-driven industrial control, and particularly discloses a self-adaptive control method and system for a hydraulically-driven guniting manipulator, which are characterized in that a pressure fluctuation signal, a flow change signal and a mechanical arm displacement signal of a hydraulic system are collected in real time, and a frequency domain decomposition processing technology is combined to realize self-adaptive control of the hydraulically-driven guniting manipulator. Separating the composite signal into a low-frequency characteristic signal reflecting load change and a high-frequency characteristic signal reflecting pressure impact; for a low-frequency signal, a dynamic weight adjustment strategy is adopted to generate a load compensation control quantity; for high-frequency signals, pressure oscillation is suppressed through differential order adjustable phase compensation processing; and finally, inputting the two paths of control characteristic values into a driving control model of the guniting manipulator, and generating an adjusting instruction of the hydraulic actuating mechanism.

The invention relates to a communication method. The communication method may comprise determining a composite signal, the composite signal representing a sum of symbols associated with frequency-time resources and of a pilot representative of at least one pulse in a delay-Doppler domain, wherein the symbols associated with frequency-time resources comprise at least data symbols and transmitting the composite signal through a radio channel.

A four wire-to-two wire lamp control method includes: inputting R, G and B lamp control signals are to corresponding oscillators which are controlled to generate R, G and B oscillation signals; the three oscillation signals being amplified and then coupled into a composite signal which is superposed onto integrated electric power to obtain composite electric power that is transmitted by a two-wire system transmission module. In this way, transformation from a four-wire lamp system to a two-wire lamp system is realized. The composite signal and power are synchronously transmitted in the two-wire system, such that the system can approximately synchronously transmit the composite signal at a low delay, and the integrated electric power can still be transmitted continuously in case of a low duty cycle of the lamp control signals, thus satisfying the requirement for driving power of a lamp.

The invention relates to the technical field of on-line monitoring, in particular to an insulation fault on-line monitoring method and system for a medical IT system control cabinet. The method comprises the following steps: selecting a non-integer frequency multiplication detection frequency according to equivalent ground distributed capacitance in a previous monitoring period, and superposing the non-integer frequency multiplication detection frequency with a fundamental frequency to form a composite signal injection system; collecting signals to calculate a voltage instantaneous harmonic distortion rate change gradient, and selecting a time window to split the leakage current according to the change gradient; on the basis of dispersion estimation signal-to-noise ratio weighted fusion current vectors, insulation resistance and distributed capacitance are calculated; constructing a four-dimensional original feature vector composed of the insulation parameter, the phase difference and the intermodulation component energy; constructing a diagonal weighting matrix based on the resistance-capacitance ratio and the gradient to transform a feature vector, and determining the fault attribution through the Mahalanobis distance calculation with the fault template library. According to the scheme, harmonic interference can be avoided, calculation stability can be improved, insulation instantaneous sudden change can be quickly responded, and different fault types can be accurately distinguished to guide maintenance.

The invention discloses a multi-modal fusion composite laminated structure low-speed impact positioning method, and relates to the technical field of impact positioning, and the method comprises the steps: obtaining impact response signals of a plurality of strain sensors on a composite laminated structure, and combining the impact response signals into a composite impact signal; taking the envelope entropy as a fitness function, and adopting a moss growth optimization algorithm to optimize a penalty coefficient of successive variational mode decomposition; performing successive variational mode decomposition on the composite impact signal based on the optimal penalty coefficient, and selecting a part of mode component with the maximum energy distribution correlation coefficient to reconstruct a de-noised signal; converting the de-noised signal into a time-frequency spectrogram, and converting an original composite signal into a two-dimensional coding diagram through a relative position matrix algorithm; constructing a multi-modal sample data set containing the time-frequency spectrogram and the coding diagram; and training the multi-modal regression model and carrying out impact positioning. According to the scheme, the modal purity of signal decomposition can be remarkably improved, and the characterization capability and fusion efficiency of multi-modal features are enhanced.

The invention discloses a speech training hearing aid system carrying an AI speech anomaly assessment algorithm, and relates to the AI speech anomaly assessment algorithm, which is characterized in that comprehensive hearing assessment is carried out by collecting a composite signal and formulating an age adaptation rule base, hearing threshold dispersion and signal-to-noise ratio attenuation are obtained, and then a hearing level assessment coefficient is obtained; daily speech evaluation is carried out by collecting speech feature data and formulating a standard speech comparison library, a daily speech anomaly evaluation model is constructed by using a convolutional neural network learning model, and then a daily speech evaluation coefficient is obtained; by collecting multi-dimensional data, professional speech evaluation is carried out, and then a professional speech evaluation coefficient is obtained; and according to the hearing level evaluation coefficient, the daily speech evaluation coefficient and the professional speech evaluation coefficient, analysis is performed to obtain an analysis result, and a comprehensive analysis scheme is formulated, so that the accuracy is greatly improved.

The invention provides a data-driven saline screw compressor unit dynamic modeling method, and belongs to the technical field of industrial intelligence and predictive maintenance. According to the method, adaptive deep denoising of original data is realized through a composite signal processing flow of fusing variational mode decomposition, permutation entropy criterion and wavelet packet transformation optimal threshold denoising; meanwhile, a sectional sampling strategy is introduced to enhance the diversity of training data. Then, a wavelet multi-scale energy entropy extraction layer is used for constructing a high-information-density feature vector; furthermore, a prediction model formed by multiple layers of stacked long and short-term memory network units is adopted, and the complex time sequence dependency relationship of the system is deeply captured. According to the method, pure and stable system dynamic representation can be extracted from high-noise industrial data, the dynamic characteristics of the system in the full working condition range are accurately described, and it is ensured that the prediction result is self-consistent physically and reliable in engineering, so that the prediction precision and generalization performance of the model are remarkably improved.

Disclosed in the present invention is a method for constructing a decoupling controller of a permanent-magnet-assisted bearingless synchronous reluctance electric motor. A decoupling controller formed by an IDBO-FNN dynamic prediction module and an IDBO-FNN system is connected to a composite controlled object, wherein the IDBO-FNN dynamic prediction module is formed by three parallel IDBO-FNN prediction modules, three parallel control increment calculation modules, three parallel prediction value calculation modules and a composite signal calculation module; and the IDBO-FNN system is formed by means of connecting a second-order difference processor and first-order difference processor of a fourth IDBO parameter optimization module before a fourth fuzzy neural network model, each IDBO parameter optimization module using an improved dung beetle optimizer to optimize the membership function width, membership function center value and weight of a fuzzy neural network. The structure of a fuzzy neural network is optimized, such that the degree of dependence of the fuzzy neural network on expert experience is reduced, the convergence speed of the weight and membership function of the fuzzy neural network is improved, high robustness is achieved, and various good static and dynamic performances such as rotor radial position control and electric motor speed control can be obtained.

The invention provides a motor bearing wear state estimation device, a motor bearing wear state estimation method, a motor bearing wear state estimation program and a shield pump, and the motor bearing wear state estimation device can estimate the wear state without manual mechanical operation intervention even if the driving condition changes. This motor bearing wear state estimation device (5, 5A) estimates the wear state of a bearing (32, 33) using a plurality of detection coils (C1-C8). The device is provided with: a storage unit (56, 56A) that stores a first learning model (M11, M21) and a second learning model (M12, M22); an acquisition unit (550) that acquires each signal; and an estimation unit (551) that estimates the wear state by inputting the first differential signal, the second differential signal, and the amplitude signal to a first learning model and inputting the thrust differential signal and the amplitude signal to a second learning model. The amplitude signal is a first amplitude signal generated on the basis of the detection signals of the first radial detection coil and / or the second radial detection coil, or a second amplitude signal generated on the basis of the first composite signal and the second composite signal.

A Global Navigation Satellite System (GNSS) receiver receives band-limited composite signals corresponding to respective satellites in the GNSS. The composite signal is composed of a direct path signal and a multipath signal. For chip edge hopping of a pseudo-random code, the receiver obtains correlation samples (I (t) samples and Q (t) samples) of the composite signal and compares them with predetermined filter characteristics (SR (t) samples) corresponding to a filter for band-limiting the composite signal. Based on the comparison, the receiver determines a phase and / or a response time error of the chip edge hopping due to the multipath signal. The receiver adjusts a pseudo-range measurement for the respective satellite and / or adjusts a carrier phase measurement for the respective satellite in accordance with the determined and / or adjusted pseudo-range measurement for the respective satellite. The receiver performs a navigation function using the adjusted pseudo-range and / or carrier phase measurements for the respective satellites.

The invention discloses a phased array radar dimension reduction four-channel main lobe and side lobe interference resisting method, and relates to the technical field of signal processing, and the method comprises the steps: generating a virtual phase gradient field through dynamic topology regulation and control by employing the non-reciprocal electromagnetic characteristics of a magnetic monopole metamaterial, and executing the non-Abel quantum interference operation, multiple paths of virtual channel signals and quantum vacuum field component composite signals are generated; constructing interlayer entanglement parameters based on the multi-path virtual channel signals and the quantum vacuum field component composite signal, and reserving quantum superposition state characteristics with interference correlation through guidance of the interlayer entanglement parameters to generate a dimension reduction tensor; a curvature response geodesic projection operator is constructed in the hyperbolic Riemann space according to the dimensionality reduction tensor, main lobe strong interference and side lobe dispersion interference are separated through a local interference rejection field, and an interference component set is generated; according to the method, the inter-layer entanglement parameter is constructed and the dimension reduction tensor with the interference correlation maintaining capability is generated, so that synchronous identification and suppression of main lobe and side lobe interference are realized.

The invention discloses a power equipment multi-band signal comprehensive detection method, which comprises the following steps: deploying a multi-band sensor, and synchronously coupling and collecting an original composite signal; distributing a unified clock signal to each monitoring point based on an optical fiber synchronous network, and controlling an acquisition channel to synchronously acquire an original composite signal; preprocessing and performing frequency band separation on the original composite signal, and outputting a plurality of sub-frequency bands; and extracting signal features from the sub-bands, outputting a multi-dimensional feature vector to a pre-trained deep learning diagnosis model, outputting a combined diagnosis result, and calculating spatial position coordinates of the discharge source. Electrician frequency, overvoltage and partial discharge signals are integrally acquired through the multi-frequency-band sensor, high-precision time alignment acquisition of multi-parameter signals is realized in combination with a subnanosecond optical fiber synchronization technology, intelligent analysis is performed by adopting a double-branch deep neural network for parallel processing of time domain and frequency domain characteristics, and the accuracy and the reliability of the system are improved. And the combined diagnosis precision and the early warning capability of complex insulation defects and overvoltage events are obviously improved.

The invention discloses a broadband current transformer testing method, device and equipment and a medium, and relates to the technical field of transformer verification. First, first frequency signals of standard current and current to be measured are synchronously obtained, the frequency of the signal to be measured is tracked in real time through a high-speed comparator, and a second frequency signal is accurately generated through the digital frequency synthesis technology. The method comprises the following steps: firstly using a high-order digital filter to measure a broadband signal frequency spectrum, then using an analog mixing technology to shift the signal frequency spectrum, generating a composite signal containing a difference frequency component and a sum frequency component, finally accurately filtering the sum frequency component through the high-order digital filter, and only measuring the difference frequency signal to obtain a ratio error and an angular error of the broadband signal. By converting the measurement of the broadband signal into the measurement of the fixed low-frequency signal, the technical bottleneck of direct sampling in a high-frequency band in the traditional sampling technology is broken through, and the actual measurement ratio error and angular error precision of the broadband current transformer is effectively improved. The system power consumption and the hardware cost are significantly reduced while the measurement precision is ensured, and the reliability and the accuracy of the broadband current transformer test are ensured.

According to one embodiment, a transmitter device includes: a digital processing circuit generating n-phase first and second digital signals, the second digital signal shifted from the first digital signal by a first phase; a delay circuit generating an n-phase second clock signal shifted from an n-phase first clock signal by a second phase being 0 or more and being the first phase or less; a first multiplexer converting the first digital signal into a single-phase third digital signal based on the first clock signal; a second multiplexer converting the second digital signal into a single-phase fourth digital signal shifted from the third digital signal by a sum of the first phase and the second phase based on the second clock signal; and a first driver outputting a composite signal of first and second analog signals based on the third and fourth digital signals.

The present invention discloses a fully wireless ocular surface pressure monitoring system based on a multi-frequency phase-shift decoupling self-calibration algorithm, relating to the technical field of intelligent ophthalmic detection. The system comprises a wearable three-layer contact lens, wherein the outer layer is embedded with a capacitive eyelid pressure sensor and a first spiral coil, and the inner layer is embedded with a piezoresistive intraocular pressure sensor and a second spiral coil, which are respectively tuned to different center frequencies to modulate pressure changes into radio frequency signals. Externally powered receiving glasses or eye masks comprise a multi-frequency transmitting coil, a rectifier circuit and a receiving coil, which supply energy to the sensing structure in the contact lens and sense and obtain a composite signal formed by spatial superposition, which is transmitted to a processing circuit and then sent to a mobile computing terminal. The terminal performs multi-frequency decoupling, sparse matrix separation and temporal self-calibration processing to generate calibration curves of eyelid pressure and intraocular pressure, thereby realizing real-time perception of dual parameters in the eyes-closed state. The system has the advantages of compact structure, high signal separation accuracy and high degree of wirelessness.

The invention discloses a non-intrusive sensor with an external excitation source and a voltage measurement method, and the non-intrusive sensor comprises an induction signal collection unit, an induction signal conditioning unit, and a main control unit. The main control unit is respectively connected with the induction signal conditioning unit and the cable power supply, the induction signal conditioning unit is connected with the induction signal acquisition unit, and the induction signal acquisition unit is in non-contact inductive coupling connection with a cable to be detected; the main control unit is used for injecting the specific excitation signal into an alternating current loop of a cable power supply to form a composite signal, analyzing the composite signal based on a preset excitation source amplitude parameter, and calculating the power supply voltage of the to-be-detected cable; the induction signal acquisition unit generates a corresponding induction signal by capturing electric field energy generated by a composite signal in the to-be-detected cable; the induction signal conditioning unit carries out standardization processing on the induction signal. According to the invention, the technical problems of low external excitation voltage measurement precision, low system integration and single excitation source generation mode in the prior art are solved.

The invention relates to a communication method, comprising: determining a composite signal, the composite signal representing a sum of symbols associated with frequency-time resources and of a pilot representative of at least one pulse in a delay-Doppler domain; wherein the symbols associated with frequency-time resources comprise at least data symbols and transmitting the composite signal through a radio channel.

The invention discloses a motor bearing fault diagnosis method and system based on multi-source information fusion, relates to the technical field of bearing fault diagnosis, and solves the technical problem that the existing bearing fault diagnosis technology cannot effectively extract the characteristics of a composite signal and is difficult to adapt to uncertain factors, so that the diagnosis effect is poor. The method comprises the following steps: synchronously acquiring vibration signals and sound signals of a motor bearing through multiple channels, dynamically distributing multi-channel signal weights by using an entropy weight method, and performing data fusion on the same kind of signals of the multiple channels; respectively extracting low-frequency features of the vibration signals and high-frequency features of the sound signals; and finally, inputting the low-frequency features of the vibration signals and the high-frequency features of the sound signals into a double-flow depth separable convolutional network to extract spatio-temporal features, and outputting a diagnosis result of a fault category. A multi-source dynamic fusion mechanism is used, and adaptive weight distribution of the vibration and sound signals of a data-level fusion layer is realized based on an entropy weight method; manual deviation setting is avoided, and the features of the composite signal are effectively extracted.

This application relates to the field of unmanned aerial vehicle (UAV) communication technology, and discloses a UAV communication method and a UAV based on low-Earth orbit (LEO) satellite communication. The method includes: establishing a communication subnet to share satellite measurement information, comprehensively evaluating multiple indicators with weights, and selecting the optimal primary serving satellite; calculating phase compensation based on a virtual phase center to achieve in-phase signal superposition, employing multi-user MIMO technology to transmit composite signals, and combining a cooperative interference cancellation algorithm to separate target data; when satellite visibility is predicted to be unavailable, forwarding unacknowledged data packets through newly connected satellite nodes or the node with the longest visibility time within the subnet to avoid data loss due to handover; discretizing spectrum units and randomly testing and evaluating their quality, marking high-quality spectrum units, and then dynamically adjusting the operating frequency band using a probabilistic migration method. This invention can effectively solve problems such as link instability, low spectrum utilization, and communication interruption caused by high dynamism in LEO satellite scenarios.

The invention relates to the technical field of optical fiber sensing, in particular to a low-altitude and ground unmanned equipment monitoring method and system based on optical fiber sensing, and the method comprises the following steps: laying an anti-interference fading DAS system in a monitoring area to obtain a signal dynamic component and a composite signal in the monitoring area; converting the signal dynamic component into a dynamic characteristic matrix; performing noise suppression on the dynamic feature matrix by using a noise suppression model to obtain a clean dynamic feature map; positioning a vibration source by using the clean dynamic feature map, and further obtaining a vibration signal spectrogram in combination with a vibration signal generation model; and constructing a vibration source classification and recognition model by using a convolutional neural network, and further performing classification and recognition on a vibration source by using the vibration signal spectrogram and the vibration source classification and recognition model. According to the method, the signal stability is improved through the anti-interference fading DAS system, and high-precision monitoring and identification of low-altitude and ground unmanned equipment can be realized in combination with multi-strategy noise suppression, CycleGAN signal extraction and convolutional neural network classification.

The invention provides a digital beam forming method and device based on multiple time delays and scale correction, and the method comprises the steps: determining a reference time delay group based on a plurality of reference positions divided from a corresponding breadth range in a distance direction; on the basis of the reference time delay group, performing finite impulse response (FIR) time delay filtering processing, scale transformation processing and pulse compression processing on an echo signal in sequence; and on the basis of an error compensation function, receiving scanning SCORE weighting is carried out on the signal after pulse compression, and a digital beam forming DBF composite signal is obtained. Therefore, the problems of inter-channel time delay and scale mismatch caused by view angle change in a large-breadth SAR system are effectively suppressed, the signal-to-noise ratio and the target positioning precision are improved, meanwhile, residual phase errors introduced by scale change are eliminated through an error compensation mechanism, and finally high-precision digital beam forming is achieved.

The utility model discloses an environment-friendly photoelectric composite signal cable, which comprises an optical unit, a control signal wire core and a pair wire group which are arranged on the outer side of the optical unit, and a filler arranged between the control signal wire core and the pair wire group, the control signal wire core, the optical unit, the paired wire group and the filler are twisted to form a cabling cable core; each control signal wire core comprises a first conductor, a first insulating layer and a first braid layer, the first insulating layer is arranged outside the first conductor, and the first braid layer is arranged outside the first insulating layer; by arranging the isolation layer structure in the control wire core, the conductor and the insulation layer are effectively isolated, so that on one hand, the flexibility of the cable is improved, and on the other hand, the integrity and brightness of the conductor are effectively protected; the signal transmitting unit detects the power supply states of the first wire and the second wire, feeds back the detection result to the signal receiving end, obtains the value transmitted by the cable, and then judges the working state of the cable.

The invention provides an electrochemical impedance spectroscopy measurement method for an energy storage battery, which comprises the following steps: step 1, respectively optimizing M frequencies fi excited by current into optimally corrected frequencies which are multiples of an optimal fundamental frequency; 2, the amplitude Ai corresponding to the frequency fi is optimized to be Ai ', so that the response voltage signal amplitudes of the energy storage battery to be measured under different frequencies fi are all V; step 3, sampling the current excitation in the step 1A to obtain a discrete multi-sine composite signal sequence, and then performing phase iterative optimization on the current excitation in the step 1A based on the multi-sine composite signal sequence and Ai; step 4, applying the optimized current excitation to the energy storage battery to be tested to obtain a response voltage signal and a current signal of the battery end; and step 5, calculating the complex impedance of the battery under different frequencies fMi, and finally obtaining the complete impedance spectrum of the energy storage battery to be measured in the selected frequency range. The method is high in measurement speed and high in measurement precision.

The invention discloses a BNCT target disc temperature detection system and method. The method comprises the steps that a magneto-optical film with the thickness of 20 + / -1 nm grows on the back surface of a rotating lithium target through magnetron sputtering; a dual-wavelength laser interference light source is introduced into a vacuum target chamber through a coaxial optical fiber probe to form a dual-cavity interference link; the magneto-optical film generates nanoscale displacement by using centrifugal force generated when the rotary lithium target rotates, so that the instantaneous temperature rise of the rotary lithium target is amplified into a phase polarization composite signal capable of being optically detected; the integrated micro slip ring coupling optical path is used for coupling the phase polarization composite signal to a static end photoelectric detector; a phase polarization composite signal output by the photoelectric detector is input into the field programmable gate array, and the transient micro-area temperature field of the rotating lithium target is solved in real time; and the generated transient micro-area temperature field is used as a boundary condition for driving, so that closed-loop verification and temperature control protection of the rotating lithium target are realized. According to the invention, millisecond-level temperature control protection of the ultrathin rotary lithium target can be realized.

The invention provides an inclined shaft gas-liquid slug flow ultrasonic flow velocity monitoring and calculating method and system, and the system comprises an ultrasonic flow velocity monitoring probe array module, a signal collection and preprocessing module, and a data processing and calculating module. The method comprises the following steps: performing variational mode decomposition on a signal, separating characteristic components of different flow structures in slug flow, realizing real-time discrimination of a liquid slug and a liquid film section and accurate capture of liquid phase apparent velocity, and accurately calculating gas phase apparent velocity through a unified mechanism model. Through the multi-angle same-direction array design, the measurement deviation caused by non-uniform cross section flow velocity distribution of the inclined shaft is overcome; the composite signal in the slug flow is effectively separated through variational mode decomposition, and the frequency shift extraction precision is improved; the innovative real-time flow state discrimination method based on the signal-to-noise ratio realizes the self-adaption of the measurement model to the flow structure, and significantly improves the measurement accuracy under the complex intermittent flow.

The invention discloses a strip vibration information detection method and system based on strip shape roller monitoring, and relates to the technical field of strip rolling process monitoring. A strip shape static component and a vibration dynamic component are stripped from a composite signal by collecting a strip shape roller force sensor signal in real time, combining wrap angle area characteristics of a strip on a strip shape roller and utilizing a signal frequency domain separation and envelope analysis technology; according to the method, vibration information is extracted by innovatively utilizing high-frequency vibration sensitive characteristics of a wrap angle entering area, and a rolling interface vibration transmission model is constructed by combining a plate shape reference signal of a tension stable area, so that vibration state inversion of a non-intrusive rolling mill system is realized. According to the method, existing plate shape detection equipment is reused, the installation limitation of a traditional vibration sensor is broken through, and a new monitoring dimension is provided for rolling stability control.

The present document relates to a method of performing acoustic scanning probe microscopy for imaging structures underneath a substrate surface, comprising: applying an acoustic input signal to the substrate having a frequency above 1 gigahertz, detecting a return signal, and analyzing the return signal for obtaining information on the embedded structures. The step of applying the acoustic input signal comprises applying a plurality of acoustic signal components which each include a selected frequency. The step of detecting includes detecting a response signal for each of the plurality of acoustic signal components. The frequencies are selected such that the components provide a composite signal being a pulse signal of limited time duration. The invention is further directed at a scanning probe microscopy system and a computer program product.