397 results about "Vibratory signal" patented technology

An apparatus for applying a cosmetic, such as mascara to eyelashes, includes a handle, a stem, and an applicator head coupled to the stem and supported for rotation relative to the handle. An actuator moves the applicator head in a vibrational motion. Additionally or alternatively, the applicator head may include a first set of protrusions having a first stiffness and a second set of protrusions having a second stiffness, wherein the first stiffness is greater than the second stiffness. The actuator may further be coupled to the handle to provide a tactile vibratory signal to the user.

An apparatus for diagnosing a fault in a dynamic system includes a controller which controls the dynamic system through use of a control input signal and vibrates the dynamic system through use of an vibration signal irrelevant to the internal state quantity of the dynamic system; an observer for estimating, on the basis of a response output from the vibration dynamic system, total disturbance which is a sum of an internal disturbance vector stemming from a fault in the dynamic system and a vibration disturbance vector occurring in the dynamic system through vibration; a correlation calculation unit which calculates cross-correlation between the thus-estimated total disturbance and the internal state quantity of the dynamic system and separates a component related to the internal disturbance from the total disturbance; and a diagnostic unit for diagnosing a fault in the dynamic system on the basis of the thus-separated component related to the internal disturbance. Since the dynamic system is vibrated, the response output can be increased even when there exists small external disturbance. As a result, a fault or a variation in air pressure in a tire can be highly accurately diagnosed.

The invention relates to a cutter damage and abrasion state detecting method, which comprises the following steps that 1, vibration signals in the cutter cutting and grinding processes are measured; 2, the vibration signals are subjected to mode filtering calculation; 3, time-frequency wavelets of the vibration signals are subjected to classification sorting and feature extractions; and 4, the time-frequency wavelets are subjected to classification, collection and signal separation processing, various kinds of time-frequency wavelets are subjected to signal reconstruction, the kurtosis index (Cq) and the peak index (Ip) of various kinds of signals are then counted, the cutter damage and abrasion state and the machine tool operation state are detected under the dynamic distribution condition of a Cq-Iq plane according to various kinds of separation signal index parameters, and the identification detection and the quantitative early warning and forecast of the cutter damage and abrasion state are realized. Through single monitoring equipment, the detection of the cutter damage and abrasion state is realized, the signal identification stability is good, the mechanical processing production safety is ensured, the precision of processing parts is improved, and the production rate and the utilization rate of a machine tool are improved.

An entertainment system according to an embodiment of the present application includes a portable media device configured to produce an audible output signal, and a plurality of individual vibratory output signals representative of individual recorded tracks of a musical piece and a plurality of actuators positioned at various locations on a user's body, each actuator configured and operable to receive one of the plurality of individual vibratory signals and to vibrate based on the received vibratory signal.

The invention provides a method for predicting the service life of a screw pair of a numerical control machine on the basis of a performance degradation model. The method comprises the following steps of: acquiring vibration signals, carrying out time-frequency domain analysis, extracting the sensitive characteristic data vectors of the performance degradation of the screw pair, and forming a sensitive characteristic matrix in a time-sequence manner; calculating the load Pi of the screw pair and recording the operating time ti at the same time; calculating the rated life time Lhi, the total time t' that the screw pair has run under the current working condition, and the expected residual life LDi according to Pi, and forming an expected residual life vector T of the expected residual life in a time-sequence manner; and fitting the mapping relation between the inputted sensitive characteristic matrix and the expected residual life vector by using a degradation model formed by a double-layer dynamic fuzzy neural network, and outputting the prediction result of the service life. By taking the impact on the performance degradation of the screw pair caused by the load change thereof under various working conditions of the numerical control machine into consideration, the method of the invention can achieve the prediction of the residual life when the screw pair is used, and ensure the high prediction accuracy and high value in actual application.

The invention discloses a flutter online monitoring method for machining equipment. The method comprises the steps that a proper sampling window is selected; empirical mode decomposition is carried out on sampled vibration signals; decomposed eigen modalities are screened to obtain a characteristic eigen modality; Hilbert transformation is carried out on the characteristic eigen modality to obtain a time-frequency spectrum; statistical pattern analysis is carried out on the time-frequency spectrum to obtain characteristic parameters; the statistical characteristic parameters are compared with a set characteristic threshold value and the statistical characteristic parameter of a historical adjacent signal, and the vibration state of a system is judged. The flutter online monitoring method aims to solve the problems that a flutter detecting method is strong in sample dependency and poor in generalization ability, threshold value measurement is difficult, and judgment is not carried out in time, the method combining Hilbert-Huang transformation and statistical pattern recognition is provided, statistical modeling and clustering analysis are carried out on the time-frequency spectrum of the vibration signal based on the aggregation character of energy on frequency in the fluttering process, the characteristic parameters are utilized, the physical characteristic of cutting flutter is represented essentially, the cutting vibration state is effectively monitored in real time, and the judgment result is accurate and visual.

A method and apparatus for qualitative sensory signal, capnography-guided intubation is provided. A qualitative sensory signal, such as an audible signal, is generated during intubation of a patient to provide an audible indication of carbon dioxide levels, so as to facilitate proper placement of an intubation tube. The frequency of the audible signal corresponds to measured carbon dioxide levels, thereby providing a simple, easy-to-interpret, audible indication of the current position of an endotracheal tube during intubation, as well as confirmation of proper placement of the tube. Alternatively, the qualitative sensor signal may be an omni-directional visual signal or a palpable vibratory signal.

The invention relates to a method of detecting damage in a bearing supporting at least one rotary shaft of an engine in rotation, the method consisting in: defining a measurement period corresponding to a range of speeds of rotation of the shaft during renewable activity at low speeds of operation of the engine; acquiring over the entire measurement period a vibratory signal representative of acceleration of components of the engine; sampling the vibratory signal as a function of the speed of rotation of the shaft during the measurement period; transforming the sampled vibratory signal into a frequency signal to obtain frequency spectrum lines as a function of the speed of rotation of the shaft; calculating the mean of the amplitudes of the spectrum lines; determining amplitude peaks around multiples of the theoretical frequency of a damaged roller; calculating the ratio between each amplitude peak and the amplitude level determined for a sound bearing; and comparing the ratio that is obtained with at least one predetermined damage threshold.

The invention relates to a characteristic-signal-based elevator safety checking device and an elevator safety checking method. The elevator safety checking device comprises a signal detection unit, a data acquisition unit and a microprocessor, which are connected in turn, wherein the signal detection unit is used for detecting the vibration information and noise information of the elevator; the data acquisition unit is used for acquiring a signal from the signal detection unit; the microprocessor is used for extracting the characteristic signals of the vibration information and the noise information under different working conditions of the elevator and processing the signals; and the signal detection unit is arranged on an elevator tractor unit. The device is widely applied, and can effectively give a fault alarm or early warning for elevators of different specifications and from different manufacturers. According to the elevator safety checking method based on the device, the characteristics of the vibration signal are extracted by using wavelet transform, the set working conditions of the elevator can be identified, an expert policy knowledge library can be built, consequently the functions of noncontact remote monitoring, fault diagnosis and the like can be realized, and the safety of the elevator can be improved.

The invention discloses an on-line monitoring method of cold rolled heating furnace roller running state. The method comprises the following steps: using a vibration sensor to collect vibration signalof the furnace roller and bearing, performing signal reconstruction to the vibration signal to obtain a vibration characteristic signal of the furnace roller and bearing, wherein the characteristic signal comprises the vibration frequency spectrum of each part of the bearing and the rotary frequency of the furnace roller in every frequency multiplication; calculating failure factor of each part of the bearing to compare with a set value and judge bearing failure; calculating total vibration value of the furnace roller, comparing the value with vibration amplitude values of the rotary frequency of the furnace roller in 1 and 2 frequency multiplication to judge whether the furnace roller is abnormal; building vibration waveform aggregate to the original vibration signal to obtain the fractal dimension of furnace roller vibration, obtaining the conclusion that the furnace roller is abnormal when the fractal dimension changes violently; and finally judging whether the furnace roller surface is over abrasion by comparing the basic furnace roller vibration amplitude value with the on-line furnace roller total vibration value.

The invention discloses a tool abrasion state monitoring method based on a vibration signal and a Stacking ensemble model. The vibration signal of a machine tool spindle in the machining process is utilized, and the vibration signal is subjected to feature extraction through time-domain analysis, frequency-domain analysis and ensemble empirical mode decomposition (EEMD); then extracted features are screened through a Relief F-SVM algorithm to obtain an optimal feature set; the width of a tool abrasion blade belt serves as the abrasion label value, and an ensemble monitoring model is built based on a Stacking ensemble strategy through the optimal feature set and the abrasion label value; and after the model is built, the vibration signal in the machining process is monitored and processed to obtain the signal feature set to be input into the ensemble monitoring model, and the tool abrasion label value, namely the tool abrasion state is obtained. The tool abrasion state can be monitoredbased on the vibration signal and the Stacking ensemble model.

The invention relates to a tool abrasion state identification method based on multi-feature fusion. A plurality of methods are utilized for extracting feature information of vibration acceleration signals and cutting force signals, optimization is conducted on a feature set based on singular value decomposition, and the tool abrasion state identification precision is improved. According to the tool abrasion state identification method, mainly, the cutting force signals and the vibration signals are fused for feature extraction, the feature set is optimized through the singular value decomposition method, then, the feature set is input into a least squares support vector machine tool abrasion state identification model optimized on the basis of the genetic algorithm for identification, andthe tool abrasion state is output. According to the tool abrasion state identification method based on multi-feature fusion, the cutting force signals and the vibration acceleration signals are fusedfor feature extraction to serve as input, and the tool abrasion state identification precision is improved.

Sound pressure information indicated by a sound signal and belonging to a frequency range above an upper limit that enables at least a user to perceive a vibration is converted into sound pressure information belonging to a frequency range less than or equal to the upper limit or belonging to a low-frequency range, and a vibration signal is generated using the sound pressure information after the conversion. This makes it possible to generate a vibration signal.

An active vibration reduction control apparatus and method of a hybrid vehicle are provided to generate a reference signal of a first motor that corresponds a vibration signal extracted from a second motor. An amplitude and phase of the reference signal is adjusted based on frequency characteristic of a drive system transfer function to generate vibration reduction torque of a first motor within the hybrid vehicle. The first motor, a torsional damper, an engine, a connector (a belt-pulley, a chain, a gear, and so on), and the second motor are sequentially connected within the hybrid vehicle.

The invention discloses an escalator fault diagnosis method based on the sequential probability. The escalator fault diagnosis method based on the sequential probability comprises the steps that vibration signals of key components of an escalator are collected through accelerator sensors mounted on the components of the escalator in vertical direction and the horizontal direction; the vibration signals are treated, and the peak values of the processed signals are used for characteristic values, namely indicator data of the actual operating state of the escalator; the indicator data are calculated through a sequential probability ratio algorithm to obtain a likelihood ratio; and the likelihood ratio is compared with the threshold value of a monitoring node, and fault diagnosis of an escalator mechanical system is conducted. According to the escalator fault diagnosis method based on the sequential probability, a wavelet packet algorithm is used for achieving smoothening and noise reduction of escalator data at different frequencies; and for the escalator in different operating states, the characteristic parameters are calculated through the sequential probability ratio algorithm, andthus differences caused by different operating states of the escalator are eliminated. In the detection process, the number of samples used for diagnosis does not need to be preset, the influence ofsample deficiencies or sample redundancy on the diagnosis result is avoided, the checking efficiency and accuracy are improved, and safety operation of the escalator is ensured.

A method and apparatus for minimizing interference between seismic systems. The method may generally include: (a) actuating a plurality of first sources associated with a first seismic system to generate a first plurality of phase-encoded vibratory signals; (b) actuating a plurality of second sources associated with a second seismic system to generate a second plurality of phase-encoded vibratory signals that are at least partially frequency separated from the first plurality of phase-encoded vibratory signals generated in (a); and (c) detecting the first and second plurality of phase-encoded vibratory signals utilizing a first receiver positioned at a location remote from the first and second sources.

The invention relates to a method having application to combustion control of an internal-combustion engine for real-time estimation of engine combustion parameters from vibratory signals. A vibratory signal representative of the engine vibrations is continuously acquired as a function of the crank angle, from a vibration detector. Real-time filtering of this vibratory signal and real-time estimation of the Fourier decomposition coefficients for the acquired vibratory signal is carried out by inverting the dynamics of the filter which is used. Finally, real-time estimation of combustion parameters allowing the combustion to be qualified is carried out from these coefficients.

The invention discloses ultrasonic-assisted multi-beam laser wire-melting type additive manufacturing equipment. The equipment comprises a laser device, a wire feeding mechanism, a base plate, a wireguide head, an electromagnetic ultrasonic generator, an electromagnetic ultrasonic probe, a controller and a protective gas protection box, wherein the laser device comprises a laser light source, anoptical fiber and a laser head, the laser light source is connected with the laser head through the optical fiber, the electromagnetic ultrasonic generator is arranged at an inlet of the wire guide head, the electromagnetic ultrasonic probe is arranged on the base plate, and is used for receiving a vibration signal of an accumulated body and transmitting the vibration signal to the controller so that monitoring of a droplet transfer state in the additive manufacturing process can be realized, and the base plate, the wire guide head, the electromagnetic ultrasonic generator and the electromagnetic ultrasonic probe are all located in the protective gas protection box. According to the equipment, the flexibility of the additive manufacturing process can be greatly improved so that the accumulated layers are not prone to collapse, then the mechanical property of the accumulated body can be improved, the deformation can be inhibited, and the speed of the additive process can be increased.

This invention relates to continuous casting dross detection method and device based on vibration detection. On section if the end of motion arm far away the long nozzle, assemble multiple vibration sensors with different directions to collect vibration signals of different directions; form sampled signal after amplifying, filtering, sampling and A/D transform; take off-line process for the ,mass collected signals to form norm eigen vector; use effective vector quantization algorithm to train codebook corresponding to all states used as codebook KB of all casting states when recognizing on line; by wavelet analysis method, obtain eigen vector of sampled signals; through the search and calculation for code word, decide which codebook that current state belongs to and give dross information. The advantage of this invention is that it needs just to set multiple vibration sensors on motion arm and treat the signal real time, and needs no other auxiliary device.