1639 results about "Resonance" patented technology

The invention provides a high-precision five-axis rotary table cooperative control method and system based on multi-closed-loop feedback, and the method comprises the steps: obtaining a real-time acceleration signal of a five-axis rotary table, carrying out the spectrum analysis of the acceleration signal, determining a current resonant frequency drift range and a main frequency component, and carrying out the frequency spectrum analysis; dynamically simulating the turntable structure by adopting a pre-established finite element model, and predicting the vibration mode change trend of the structure by comparing the deviation between the modal frequency obtained by simulation and the actually measured signal spectrum; according to the vibration mode change trend, matching similar vibration mode modes from a pre-established rotary table vibration mode database, obtaining corresponding vibration energy transmission path distribution, and determining an energy transmission abnormal region by analyzing the distribution of energy on each transmission path to obtain vibration energy transmission characteristics; according to an optimized motion instruction of a five-axis turntable, the dynamic response of the turntable is estimated, vibration frequency domain characteristics are extracted, and frequency domain compensation parameters are generated in combination with a preset frequency domain error matrix.

The invention discloses a large-span bridge vibration response prediction method based on data driving, and relates to the technical field of bridge vibration response prediction, and the method comprises the following steps: arranging a plurality of sensors at a plurality of key structure parts of a bridge, collecting vibration response data of the bridge during operation in real time based on an initial sampling frequency set based on the inherent frequency of the bridge structure; performing frequency domain analysis on the collected vibration response data, extracting a main excitation frequency component under the current working condition, and constructing a current excitation frequency spectrum; the method comprises the following steps: calling structural modal parameters obtained in a design stage, a static load test or a modal test of a bridge, extracting the natural vibration frequency of each order of structure, and constructing a bridge inherent frequency feature library; according to the method, the resonance state is dynamically identified through frequency domain analysis and the fuzzy risk index, the sampling frequency is intelligently adjusted, high-frequency response accurate capture and resource efficiency optimization are realized, and the sensitivity, the real-time performance and the safety of a bridge health monitoring system are remarkably improved.

The invention belongs to the technical field of bearing fault diagnosis, and particularly relates to a transmission casing typical small bearing fault weak vibration signal extraction method, which comprises the following steps: reconstructing a bearing vibration signal to obtain a modulation impact signal, and calculating a weighted kurtosis value based on the modulation impact signal to improve a Protugram algorithm; noise interference is added to a bearing fault signal, and extraction of a small bearing fault weak impact signal is realized by optimizing a filtering frequency band based on a weighted kurtosis value improved Protugram algorithm; bearing impact characteristics can be enhanced based on a simulation sensor resonance enhancement algorithm (SPM); the impact quantification of the bearing can eliminate the influence of different rotating speeds and load working conditions, and realizes the quantitative diagnosis of bearing faults. And finally, the fault data of the rolling body, the inner ring and the outer ring of the flight attachment case small bearing part test bed are verified, and effective extraction and enhancement of bearing fault weak signals can be realized.

The invention provides a multi-parameter fusion drilling tool state intelligent diagnosis method, device and equipment, and the method comprises the steps: determining a stable working period through obtaining basic operation parameters of a drilling tool, and applying specific frequency excitation vibration to the drilling tool in the stable period to form an active propagation wave; a multi-point monitoring technology is adopted to obtain a response vibration signal and extract a time sequence, and a time sequence offset is obtained through differential processing; identifying a signal propagation delay section based on the time sequence offset, extracting actual propagation time, comparing the actual propagation time with standard propagation time to generate a time delay abnormal value, and determining an internal state change position; a high-damage section is determined by combining energy dissipation analysis, and fault positioning information is generated through spatial superposition; performing frequency sensitivity analysis by utilizing the damage characteristic parameters, capturing a resonance response peak value through frequency sweep excitation, and forming a secondary diagnosis result in combination with the wear severity; and finally, determining a fault development rate, generating a partition maintenance instruction, and completing intelligent diagnosis of the drilling tool state.

The invention relates to the technical field of converters, in particular to a multi-module converter resonance suppression method and system for a mobile energy storage system. The dynamic response of the system is optimized through the controller, it can be ensured that the system can keep good stability and performance under different operation conditions, the robustness of the multi-module converter system under different working conditions can be improved through mathematical modeling and accurate design of a control algorithm, and the real-time monitoring and frequency recognition mechanism is adopted, so that the reliability of the multi-module converter system is improved. A control strategy can be adjusted according to frequency characteristics of resonance, active intervention can be performed on the resonance phenomenon of the system by adjusting the on-off state of the converter in real time and a control algorithm, the system can automatically adapt according to different loads, environment conditions and equipment states by adjusting control parameters in real time, long-term stable operation is ensured, and the system is safe and reliable. By actively suppressing resonance and reducing excessive oscillation of the system, energy waste and equipment loss caused by resonance can be significantly reduced.

The invention relates to the technical field of resonance suppression, and discloses an active damping control LC resonance suppression method and device. The method comprises the following steps: performing parameter identification processing based on bus voltage to obtain an inductance value, a capacitance value and a resonance frequency of an LC circuit; extracting a resonant current component of the current signal based on the resonant frequency; calculating damping power according to the resonance current component, and converting the damping power into a voltage compensation instruction under an alpha-beta coordinate system; generating a PWM control signal according to the voltage compensation instruction and a voltage reference instruction; and performing on-off control on the inverter based on the PWM control signal, and injecting power opposite to the resonant current component into the LC circuit to generate a virtual damping effect. Virtual impedance characteristics are seamlessly integrated into inverter control, rapid response of the whole process from resonance detection to power injection is ensured, the resonance peak value is effectively suppressed, and the current quality is improved.

The invention provides a joint denoising method and system based on multi-source noise suppression and sparse representation, and belongs to the technical field of noise suppression in ultrasonic detection of power equipment, and the method comprises the steps: synchronously collecting an ultrasonic echo signal, a vibration signal and an electromagnetic signal of a composite insulator; decomposing the ultrasonic echo signal into a plurality of modal components and undecomposed signal margins; extracting a dominant frequency component in the vibration signal, and identifying a resonance noise feature overlapped with the frequency band of the ultrasonic signal; detecting a pulse interference event in the electromagnetic signal, marking occurrence time and a frequency range, and generating a pulse event feature; performing frequency band suppression and time domain threshold processing on the modal component according to the resonance noise characteristics and the pulse event characteristics; performing sparse representation coding on the processed modal components, executing multiple rounds of iterative screening and orthogonalization processing, and screening an atom set matched with defect echoes; and reconstructing the de-noised ultrasonic signal by using the screened atom set, and combining the de-noised ultrasonic signal with the undecomposed signal margin to output a final result.

The invention relates to a bridge structure vibration monitoring and analysis method based on artificial intelligence, and the method specifically comprises the following steps: setting an acceleration sensor network at a key part of a bridge, collecting and marking a vibration signal sample, and forming a data set; a high-resolution time-frequency matrix of sample adaptive optimal kernel time-frequency distribution is calculated, a damage sensitive resonance frequency band is positioned according to spectrum kurtosis, and the time-frequency matrix is enhanced by the resonance frequency band subjected to adaptive gain enhancement; dividing a matrix frequency axis multi-scale binary tree, calculating and normalizing sub-band average energy, quantifying energy distribution uniformity through information entropy, and splicing multi-scale entropy values into feature vectors; then constructing and training a bridge detection data model; and finally, preprocessing new data, inputting the preprocessed new data into the trained model, and automatically analyzing to obtain a bridge health monitoring result. Through time-frequency optimization, multi-scale entropy and deep learning technologies, the problems of large noise, difficult feature extraction and low automation and accuracy of traditional monitoring can be solved.

The invention relates to a rolling bearing early fault early warning and diagnosis method, which comprises the steps of extracting an envelope component from a bearing vibration signal, constructing a time-delay feedback stochastic resonance optimal model by taking an improved signal-to-noise ratio INSR as an optimization objective function, obtaining an output signal, obtaining a first reconstruction signal through CEEMDAN adaptive decomposition and IMF component screening, and obtaining a second reconstruction signal through the CEEMDAN adaptive decomposition and IMF component screening. Calculating the signal-to-noise ratio ISNR of the vibration signal at the fault characteristic frequency, comparing the signal-to-noise ratio ISNR with a preset initial threshold value, judging whether an early warning is given out or not, and if the early warning is given out, processing the vibration signal by using a multi-wavelet adjacent coefficient adaptive threshold value method to obtain a denoised signal; processing the denoised signal by combining a fast spectral kurtosis method and an ensemble empirical mode decomposition method to obtain a second reconstructed signal; and processing by using improved fast spectrum correlation to obtain a corresponding enhanced envelope spectrum, and comparing the enhanced envelope spectrum with a fault characteristic frequency for identification. Compared with the prior art, accurate early warning and diagnosis can be carried out on early weak faults of the rolling bearing.

The invention provides a joint denoising method and system based on adaptive large neighborhood search and modal decomposition, and belongs to the technical field of signal processing and nondestructive detection.The method comprises the steps that an ultrasonic signal and a vibration signal of a detected insulator are synchronously collected and preprocessed; dynamically estimating the noise level based on the preprocessed ultrasonic signal power spectral density, and optimizing decomposition parameters by adopting an adaptive large neighborhood search algorithm; on the basis of the optimized decomposition parameters, wavelet packet decomposition and ensemble empirical mode decomposition are executed in parallel, and effective intrinsic mode function components are screened through cross-correlation verification; extracting the resonance frequency of the preprocessed vibration signal, performing target frequency band weighted enhancement on the low-frequency sub-band, and dynamically adjusting the threshold parameter of the high-frequency sub-band and the low-frequency sub-band according to the resonance frequency; and generating a preliminary de-noised signal from the fused signal, performing affine projection algorithm filtering and multi-modal cross validation, and outputting the verified ultrasonic signal as a final de-noising result.

The invention relates to the field of industrial pipeline systems, in particular to a displacement analysis evaluation and compensation method for optimizing pipeline thermal expansion. The method comprises the following steps: collecting multi-temperature thermal state snapshots to form a thermal state change sequence; determining a thermal expansion constraint boundary according to the thermal state change sequence, and forming boundary condition data; fixed points and free points of the pipeline system are identified according to the boundary condition data, and a degree-of-freedom distribution diagram is constructed; based on the degree-of-freedom distribution diagram, analyzing a displacement transfer relation of each pipe section, and generating displacement transfer chain data; identifying a thermal expansion concentrated release area through displacement transfer chain data, and performing node resonance detection to form vibration risk assessment data; and designing a thermal stress digestion path based on vibration risk assessment data, and setting flexible constraints to form a balanced stress network. The thermal expansion displacement transmission path is tracked in real time through displacement transmission chain analysis, the resonance frequency is synchronously recognized in combination with vibration mode detection, and dynamic association of the thermal expansion process and the vibration mode is achieved.

The invention discloses a loss tuning method of a power transformer, which is applied to a transformer body sleeved with a winding and comprises the following steps: applying scanning current excitation containing fundamental waves and harmonic waves to the winding, synchronously acquiring a body vibration signal and converting the body vibration signal into a frequency spectrum; extracting a formant from the frequency spectrum, matching the formant with a theoretical electromagnetic force wave and a structure inherent frequency library, and identifying a coupling formant to be optimized; aiming at each formant, installing a vibration exciter in a corresponding area, sending out an anti-phase periodic pulse force, and dynamically and finely adjusting a pulse force parameter by monitoring a vibration response in real time and taking equivalent mechanical impedance minimization as a target; when the optimal damping state is achieved, the vibration exciter output rod is locked, and static pre-tightening force is formed; and after all formants are adjusted and optimized in sequence and the prestress is locked, final pressing and fixing of the transformer body are completed in the state that the pretightening force is kept. According to the invention, the dynamic loss source of the individual transformer can be actively inhibited and cured before assembly and curing, the operation loss and noise are effectively reduced, and the structural stability is improved.

The invention discloses a micro-grid electric energy quality global optimization method, which comprises the steps of collecting real-time data, dividing the real-time data into a plurality of segments according to frequency, and calculating harmonic compensation capacity of each frequency band according to the real-time data; according to the harmonic compensation capacity obtained through calculation, priority distribution is carried out on the compensation sequence of the polluted nodes in the micro-grid; the virtual impedance and the injection damping resistance of the inverter are adjusted, and the harmonic current and the resonance phenomenon in the micro-grid are suppressed in different frequency bands; and according to the adjusted virtual impedance and damping resistance, updating a node admittance matrix, monitoring the compensation capacity of the inverter in real time, comparing real-time monitoring data with a threshold value, if the real-time monitoring data exceed the threshold value, correcting the inverter, otherwise, not changing. Through frequency-band-divided control, pertinence and effect of harmonic suppression are improved, frequency-band-divided suppression of micro-grid harmonic and high-frequency resonance is realized, residual capacity of an inverter and harmonic compensation requirements are dynamically matched, and safe and stable operation of a system is ensured.

Systems, methods, and other embodiments associated with ML-based detection of amplification of vibration due to resonance are described. In one embodiment, a method includes recording vibrations of a reference asset while the reference asset is operated based on a test pattern that sweeps over a range of workload for the reference asset. Cross power spectral densities between the recorded vibrations and the test pattern are determined at intervals to identify resonance frequencies of the reference asset. Vibrations of a target asset are monitored at the resonance frequencies with a machine learning model trained to generate estimated values at the resonance frequencies that are consistent with the reference asset. Resonant vibration amplification is detected based on a dissimilarity between vibration values for the target asset at the resonance frequencies and the estimated values. And, an electronic alert that the target asset is undergoing the resonant vibration amplification is generated.

The invention discloses a method for dynamically adjusting the frequency of a resonant cavity of a cyclotron and a tuning circuit, which are applied to the field of cyclotrons and solve the problem that when the frequency of the resonant cavity of the cyclotron is adjusted by judging the magnitude of reflection power, due to the fact that the reflection power can change in multiple stages in a single macro pulse period, the frequency of the resonant cavity of the cyclotron is adjusted. And an accurate numerical value is difficult to obtain through a simple amplitude sampling circuit. According to the invention, through determining the stable resonance time period of the resonant cavity, the phase difference between the incident power signal and the reflection power signal is sampled in the corresponding stable resonance time period of the resonant cavity, and the change value of the phase difference between the incident power signal and the reflection power signal is dynamically compared. According to the conversion relation between the phase difference change value and the frequency change value, the resonant cavity frequency change value is obtained through conversion, then the resonant cavity tuning device is adjusted to enable the resonant cavity frequency to be consistent with the frequency of the incident power signal all the time, and the dynamic tuning method of the resonant cavity is achieved.

The invention discloses a multistage safety response control method of an industrial and commercial liquid cooling energy storage system, and relates to the technical field of electric energy storage systems, a sensor network collects an operation state data time sequence matrix, and abnormal data cleaning is carried out on the time sequence matrix; the method comprises the following steps: preprocessing a vibration signal of a cooling system, extracting characteristic data of abnormal vibration through Fourier transform and energy distribution analysis, and positioning a time-frequency distribution abnormal region; generating a time sequence multivariable data set according to the characteristic data of the abnormal vibration, determining a cause label according to the fused time sequence multivariable data set, obtaining the inherent frequency and the resonant frequency of the cooling system in combination with simulation analysis, and matching and determining the cause of the abnormal vibration; an LSTW neural network is used for predicting the abnormal resonance risk, and corresponding countermeasures are taken for the cooling network according to the prediction result; unnecessary vibration caused by error adjustment is avoided, the relation between cooling efficiency and safety is balanced, and unnecessary power loss is reduced.

The invention discloses a symmetrical structure S-band filter based on GaAs IPD, which belongs to the technical field of microwaves and comprises a first-order series resonance circuit, a coupling capacitor C1, a grounding inductor L2, a coupling capacitor C2, a second-order parallel resonance, a third-order parallel resonance, a grounding capacitor C6, a coupling capacitor C7, a fourth-order parallel resonance, a grounding capacitor C66, a fifth-order parallel resonance, a coupling capacitor C22 and a grounding inductor L22. And a coupling capacitor C11 and a sixth-order series resonance. The third-order parallel resonance and the fourth-order parallel resonance can improve the low-frequency out-of-band suppression degree of the band-pass filter; the first-order series resonance and the sixth-order series resonance as well as the second-order parallel resonance and the fifth-order parallel resonance can improve the high-frequency out-of-band suppression degree of the band-pass filter.

Embodiments include a system for material detection and identification. The system may include an RF transmit device configured to transmit into an environment an RF signal at a resonance frequency. The system may also include an RF receiver device configured to receive a response signal from the environment. The system may further include a communication device connecting the RF transmit device and the RF receiver device. The communication device may include a control module. The system may include a geolocation device. The control module may be configured to receive geolocation data from the geolocation device, analyze the response signal for resonance characteristics that indicate a presence of a material, and identify the material to a user when the presence of the material is indicated by the resonance characteristics. Methods for material detection and identification are also described. Methods may involve obtaining geolocation data.

The invention discloses a method and system for measuring the ultrasonic proportionality coefficient of the thickness of a lubricating film of a sliding bearing, and the method comprises the steps: firstly, obtaining the comprehensive response coefficient of sound waves in a transition combination layer of a substrate and a lining through calculating the proportionality coefficient of a reflection echo signal of a bearing bush in an air medium and a reflection echo signal of a substrate-lining interface; characterizing the propagation rule of sound waves in a base body and lining combination layer; secondly, a proportionality coefficient is constructed based on a lubricating film reflection echo signal and a matrix-lining interface reflection echo signal, a lubricating film reflection coefficient is calculated in combination with a comprehensive response coefficient of sound waves in a matrix-lining transition combination layer, and finally the thickness of the lubricating film is solved through a resonance model method or a composite model method. According to the invention, the influence of the change of the binding force between the sensor and the substrate and the unstable voltage of ultrasonic pulse emission equipment on the reference signal can be avoided, the robustness is high, and the long-term reliable monitoring of the thickness of the lubricating film of the sliding bearing is facilitated.

Provided in the present invention application is a test identification method and apparatus for vibration-involved dynamic parameters of a bearing pedestal and using additional masses. The method comprises: simplifying a dynamic model of a bearing pedestal into a single-degree-of-freedom system; applying an excitation force to the bearing pedestal, testing a response, plotting a frequency spectrogram, and obtaining a resonance frequency; adding additional masses to the bearing pedestal, and testing inherent frequencies under different additional masses; calculating vibration-involved masses on the basis of test results; plotting a curve of the vibration-involved masses changing with the additional masses, performing fitting by using the least-squares method, and performing extrapolation, so as to obtain a vibration-involved mass for when the additional mass is 0 and use same as a vibration-involved mass of the bearing pedestal; adding additional masses to the bearing pedestal, and testing damped vibration responses under different additional masses, so as to obtain logarithmic decrements and damping factors; plotting a curve of the damping factors changing with the additional masses, obtaining a damping factor in the same manner to use as a damping factor of the bearing pedestal, and performing calculation on the basis of the damping factor and the mass to obtain a vibration-involved stiffness coefficient of the bearing pedestal. The present invention using the solution can realize accurate identification of vibration-involved dynamic parameters of a bearing pedestal.

The invention provides a data center cooling system performance evaluation method and system. The method comprises the following steps: acquiring operation data of data center cooling equipment and power load data of a server, and combining service time and maintenance records of the equipment to determine a performance baseline; calculating resonance frequency points caused by harmonic waves under different working conditions based on the vibration characteristics of the base line and the current harmonic characteristics in the electric energy quality in combination with equipment structure parameters and a working condition empirical formula; frequency sweeping is performed by actively adjusting the rotating speed of equipment, the dominant harmonic frequency and the contribution proportion thereof are verified, and a proportional relation model of harmonic and vibration characteristics is established; adjusting equipment parameters according to the model, and calculating the deviation degree of a harmonic component and a performance baseline; and finally, combining harmonic change characteristics with deviation degree correlation, and constructing energy efficiency and health state evaluation indexes of the cooling system. According to the invention, collaborative evaluation of the energy efficiency and the health state of the data center cooling system is realized.

A superconducting device includes a frequency-tunable device including a first conductive pad and a second conductive pad which are connected to each other by a Josephson junction, a ferromagnet having a magnetic domain wall, and a control circuit configured to apply a current to the ferromagnet to adjust a position of the magnetic domain wall of the ferromagnet, and to control a resonance frequency of the frequency-tunable device.

Embodiments described relate to a system for material detection and identification, The system may include a transmitter unit configured to transmit an RF signal at a resonance frequency for a material. The system may also include a phased array antenna assembly, the phased array antenna assembly configured to receive a response signal. The system may also include a receiver unit configured to analyze the response signal and to identify the material to a user if the presence of the material is indicated by the resonance characteristics. The techniques described herein relate to a method for material detection and identification. The method may include configuring a transmit signal for parameters to detect a material; sending the transmit signal to a phase shifter; transmitting, using a phased array antenna assembly, an RF signal at a resonance frequency for the material; processing the response signal; and outputting an identification of the material.

The invention discloses an electromagnetic ultrasonic resonance thickness measuring method capable of adaptively regulating and controlling sweep frequency step length, which comprises the following steps of: exciting a continuous sweep frequency signal of a certain frequency band by an electromagnetic ultrasonic probe at a variable frequency step length, forming ultrasonic waves on the surface of a workpiece, penetrating the workpiece, and reflecting on the other surface of the workpiece to measure the thickness of the workpiece. The electromagnetic ultrasonic probe receives the reflected time domain signal, time-frequency conversion is conducted on the time domain signal based on the Fourier transform principle, a spectrogram is obtained, and wall thickness information of the current measuring point is calculated according to the frequency difference. However, due to the fact that the processes of frequency sweeping excitation, ultrasonic wave receiving and data processing of a series of waveforms are slow, the real-time performance of measurement can be affected, according to the electromagnetic ultrasonic resonance thickness measurement method oriented to ultrathin wall thickness measurement, frequency domain segmentation is achieved based on signal amplitude recognition, the frequency sweeping step length is shortened near the resonance frequency, and the measurement accuracy is improved. The step length is increased in other frequency bands, full-band equal-step-length frequency sweeping is replaced by variable-step-length frequency sweeping, the frequency sweeping step number is reduced, and therefore the measurement efficiency is improved.

The invention discloses a low-rigidity heavy-load permanent magnet synchronous motor flexible system structure resonance suppression method, and relates to the technical field of permanent magnet synchronous motor control, and the method comprises the steps: carrying out the dynamic filtering of an input position signal through setting a TD tracking differentiator, and generating a smooth planning instruction and a differential signal thereof; based on the planned instruction differential signal, a speed feed-forward control method is adopted to introduce feed-forward compensation in a position closed loop; constructing a disturbance observer according to the electromagnetic torque equation of the motor, estimating the actual wheelbase of the system in real time, and performing disturbance compensation; based on system resonance characteristics, an IP control method is adopted to perform pole assignment, and proportional gain and integral gain are set to suppress structure resonance and optimize closed-loop response. According to the method, a relatively good resonance suppression effect can be achieved without displacement, speed or acceleration signals of a load end and information such as very accurate load resonant frequency, relatively good dynamic response is achieved, and the requirement on hardware is reduced.

A method includes detecting interaction by a user with an entry detector; collecting credentials from the user; and, if the credentials indicate that the user is authorized to enter, accessing a material database associating each of a set of materials with one or more corresponding resonance frequencies; and for each material of the set of materials: transmitting, into an environment associated with the user, an RF signal at a first resonance frequency for a material of the set of materials; receiving a response signal from the environment; analyzing the response signal from the environment for resonance characteristics that indicate a presence of the material; and in response to the presence of the material being indicated: determining whether an action is required for the material; and if the action is required for the material, actuating an access apparatus to perform the action.

The invention relates to the technical field of vibrator control, in particular to a driving voltage calibration method and device, electronic equipment, a medium and a program product, and is characterized in that residual vibration parameters and driving frequency of a vibrator are acquired, and the residual vibration parameters comprise a quality factor, an electromechanical coupling coefficient and resonance frequency; based on the residual vibration parameter and the driving frequency, the vibration parameter of the vibrator under the corresponding driving frequency can be calculated, and the vibration parameter can comprise one or more of acceleration, speed and displacement of vibration of the vibrator. The comparison result between the determined vibration parameters of the vibrator under different driving frequencies and the preset vibration parameters serving as the reference can be used for calibrating the driving voltage under the corresponding driving frequency, so that the vibrator is driven by the calibrated driving voltage, and the vibration consistency of the vibrator and the reference vibrator can be ensured.

The invention discloses a resonance type flow field MEMS sensor based on PT symmetry and a preparation method thereof, and the method comprises the steps: two double-end fixed tuning fork resonators are coupled, are in mirror symmetry in structure, and are equal in mass; the two double-end fixed tuning fork resonators are positioned on the same straight line; the comb tooth capacitors are symmetrically distributed on two sides of each double-end fixed tuning fork resonator; the two adjustable damping circuits are connected with the electrode layer through leads, so that the two adjustable damping circuits are correspondingly connected with the two double-end fixed tuning fork resonators; the equivalent damping of the two adjustable damping circuits is opposite in sign and equal in size; the cilium supporting structure is suspended at one end of a double-end fixed tuning fork resonator; the micro lever is connected with the cilium supporting structure and the double-end fixed tuning fork resonator; the cilia is arranged on the cilia supporting structure; glass serves as a substrate of the sensor. According to the invention, the resonance type flow field MEMS sensor can obtain perturbation response performance with higher sensitivity, and sensitive measurement of weak flow velocity is realized.

A method for material detection may include extracting, from a material database, a resonance frequency for the target material. The method may further include comparing an application type to entries in a scan database. The scan database may store pre-defined scanning patterns and corresponding application types. The method may include extracting, from the scan database, a scan sequence for the application type. Also, the method may include instructing a gimbal to follow positions in the scan sequence. The method may also include transmitting into an environment an RF signal when the gimbal is at the positions in the scan sequence. The method may further include receiving a response signal from the environment. The method may include generating a haptic feedback to indicate a directionality or a proximity to the target material. The method may include analyzing the response signal for resonance characteristics that indicate a presence of the target material.

The invention provides a harmonic reducer fault diagnosis method and system combining SAH with SSET under a time-varying rotating speed, and belongs to the field of harmonic reducer fault diagnosis. The invention aims to solve the problems of large time-frequency ridge line extraction error and inaccurate fault feature order extraction caused by the non-stable and signal modulation characteristics of a harmonic reducer vibration signal under a time-varying rotating speed. According to the SAH construction method based on sub-band rearrangement dual-tree complex wavelet packet transformation, a band elimination filter is designed according to an optimal frequency band, and a resonance frequency band where a fault impact component is located is filtered out; a time-frequency ridge extraction method combining SAH-SSET with a fast path optimization algorithm is provided, a frequency ambiguity phenomenon is improved, order analysis is carried out based on the frequency ambiguity phenomenon, and then the fault type of the harmonic reducer is judged according to an envelope order spectrum.