Data processing: measuring – calibrating – or testing – Measurement system in a specific environment – Electrical signal parameter measurement system
Reexamination Certificate
2002-06-26
2004-10-26
Hoff, Marc S. (Department: 2857)
Data processing: measuring, calibrating, or testing
Measurement system in a specific environment
Electrical signal parameter measurement system
C702S076000, C702S077000, C702S078000, C702S079000, C702S105000, C702S182000, C702S183000
Reexamination Certificate
active
06810341
ABSTRACT:
FIELD OF THE INVENTION
The invention relates generally to signal analysis systems or test and measurement systems, and more particularly to a system and method for analyzing order components of a signal generated by a physical system, e.g., a mechanical system containing one or more rotating elements, without necessarily requiring use of a tachometer to indicate the rotation speed of the system.
DESCRIPTION OF THE RELATED ART
Scientists and engineers often use test and measurement systems and data acquisition systems to perform a variety of functions, including laboratory research, process monitoring and control, data logging, analytical chemistry, test and analysis of physical phenomena and analysis or control of mechanical or electrical machinery, to name a few examples. One example of hardware to implement such measuring systems is a computer-based measurement system or data acquisition (DAQ) system. Another example of a measurement system is a dedicated instrument, such as a dedicated oscilloscope or signal analyzer.
A measurement system typically may include transducers for measuring and/or providing electrical signals, signal conditioning hardware which may perform amplification, isolation and/or filtering, and measurement or DAQ hardware for receiving digital and analog signals and providing them to a processing system, such as a processor or personal computer. The computer-based measurement system or dedicated instrument may further include analysis hardware and software for analyzing and appropriately displaying the measured data.
One example where measurement and data acquisition systems are used is in the field of rotating machinery analysis. This involves the analysis of physical signals such as vibration or acoustic signals from a rotating machine. A physical signal acquired from a rotating machine may be sampled or digitized. Typically, samples of the physical signal are equidistant in time. However, rotating machines generate signals which are periodic with respect to shaft rotation, i.e., rotation angle of an underlying rotating element (e.g. a crank shaft of an engine). These rotation-periodic signals are referred to herein as order components. When the rotation rate changes in time, the order components change correspondingly in frequency. For example, when the rotation rate increases, the order components increase in frequency. Thus, a traditional analysis method such as the Discrete Fourier Transform (DFT), when applied to the physical signal, displays a frequency smearing of order components. The frequency smearing makes it very difficult to derive meaningful information about the order components. Thus, traditional signal analysis methods such as the Fourier Transform of the time domain input signal are not well suited for analyzing order components generated by rotating machines.
In order to better analyze the performance and characteristics of rotating machines, certain prior art systems convert the time-samples, i.e., the samples of the physical signal which are equally spaced in time, to angle-samples, i.e., samples which are equally spaced in shaft angle. For example, U.S. Pat. No. 4,912,661 assigned to Hewlett-Packard discloses an interpolation method for estimating angle-samples from time-samples. The method disclosed in U.S. Pat. No. 4,912,661 performs an interpolation of the time domain signal, followed by a decimation, in order to produce samples equally spaced with respect to shaft angle. The order components may then be analyzed by performing a traditional analysis method such as the Discrete Fourier Transform on the angle-samples. However, this method is expensive in terms of computational resources and may not be very accurate.
One prior art system known as the Vold-Kalman filter allows the user to track the frequency of an order component given a sufficiently accurate model, i.e., a stochastic model, for the physical signal. The Vold-Kalman filter performance may be strongly sensitive to model accuracy. In other words, the tracking performance is likely to be degraded when an inaccurate signal model is supplied to the filter. Furthermore, the Vold-Kalman filter provides no mechanism for the user to evaluate the accuracy of the frequency tracking for an order component.
Therefore, there exists a need for a system and method which can more accurately and robustly analyze order components of a physical signal, and reconstruct desired order components in the time-domain.
In some applications, such as engine diagnostics, a sensor, e.g., a tachometer may be utilized to track the fundamental frequency. This information may then be utilized to extract individual time-varying harmonics. However, for many applications, a tachometer signal is not available. For example, for sound recorded during takeoff or landing of an airplane or helicopter, there is generally no tachometer information available. As another example, for sounds generated by a human voice or whales, no tachometer information is available. Thus, it would be desirable to provide a system and method for performing time-varying harmonic analysis when no tachometer information is available.
SUMMARY
One embodiment of the present invention comprises a method for analyzing order components present in a physical signal X acquired from a physical system. Measurement information for the physical signal X may be received, where the measurement information includes information indicating a plurality of order components of the physical signal X. For example, where the physical system generates sound, the measurement information may include digitized samples of the sound.
The measurement information may be processed to create time frequency plot information for the physical signal X. In one embodiment, processing the measurement information may include performing an invertible joint time-frequency transform on the measurement information. The time frequency plot information may be displayed on a display device. The time frequency plot information may include a plurality of points visually indicating the order components of the physical signal X. For example, each order component may appear as an order curve on the display device.
User input selecting one or more of the visually indicated order components may be received. In various embodiments, the user input may be received in any of various ways. The user input may be received directly to the displayed time frequency plot information. For example, in one embodiment selecting each order component may include receiving user input selecting one or more points proximate to the order component, i.e., proximate to (or on) the corresponding order curve, as described in detail below. The actual order component may then be determined based on the one or more selected points proximate to the order component, as also described below.
A time domain signal may be created based on the one or more selected order components. In one embodiment, the one or more selected order components may be suppressed from the time domain signal. In another embodiment, the time domain signal may consist only of the one or more selected order components.
The time domain signal may then be presented to a user on a presentation device. Presenting the time domain signal on the presentation device may enable the user to analyze the physical signal X or the physical system. For example, where the physical signal X is an audio signal and the selected order components were suppressed from the time domain signal, presenting the time domain signal on the presentation device may allow the user to listen to the sound generated by the physical system without the sound corresponding to the selected order components.
The method described above may be employed to analyze any of various types of physical signals acquired from any of various types of physical systems. In one embodiment, the physical system may include a rotating element. The method may enable order components of the signal to be analyzed even when no rotation speed information (e.g., tachometer information) for the rotating elem
Qian Shie
Shao Hui
Zhang Nanxiong
Burgess Jason L.
Hoff Marc S.
Hood Jeffrey C.
Meyertons Hood Kivlin Kowert & Goetzel P.C.
National Instruments Corporation
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