Data processing: measuring – calibrating – or testing – Measurement system in a specific environment – Electrical signal parameter measurement system
Reexamination Certificate
2001-01-02
2001-10-30
Hoff, Marc S. (Department: 2857)
Data processing: measuring, calibrating, or testing
Measurement system in a specific environment
Electrical signal parameter measurement system
C702S125000
Reexamination Certificate
active
06311138
ABSTRACT:
BACKGROUND OF THE INVENTION
Oscilloscopes are one of the more common examples of electrical test and measurement equipment. This class of devices makes primary measurements of time varying signals. In most instances, these measurements are of the signal's voltage as a function of time, even though the detected voltage may be indicative of some other measurement of interest such as electrical current through a resistive element or temperature in the case of a thermistor, in two arbitrary examples. The oscilloscope is useful because it enables the visualization of the time varying character of signals, using a vertical axis representing level and horizontal axis representing time.
The digital storage oscilloscope (DSO) is a subclass of oscilloscopes in which the time varying nature of the sampled signals is represented digitally within the device. The main advantage is that non-simultaneous signal events can be stored in the device for subsequent comparison. Additionally, parameters can be derived from the digital data of the primary measurements, such as statistical features of the signals.
In the typical implementation, the DSO works by waiting for the satisfaction of some trigger condition. When the trigger event is received, the primary measurements of the voltage, for example, of the signal are made, and the resulting measurement data are stored in a waveform memory. Successive positions in the waveform memory hold the digitized level of the signal at increasing time delays from the triggering event. Under current technology, DSOs can capture signals at a rate of up to 8 gigasamples/second (GS/s) with waveform memories of up to 16 million storage locations.
Where oscilloscopes are time domain instruments, spectrum analyzers make primary measurements in the frequency domain. In the typical configuration, these devices plot the magnitude of the signal energy as a function of frequency-signal magnitude or level being on the vertical axis with the frequency on the horizontal axis. These devices typically operate by scanning a very narrow notch-bandpass filter across the frequency spectrum of interest and measuring energy in the frequency bins. In this way, spectrum analyzers are useful in identifying the spectral distribution of a given signal.
For certain signal analysis problems, however, oscilloscopes and spectrum analyzers are not well suited to the task. For example, when trying to isolate infrequent anomalies in a signal such as that required for digital/analog circuit analysis/debugging or when trying to identify trends in signals such as when analyzing modulated signals, both oscilloscopes and spectrum analyzers are less useful. Since spectrum analyzers operate by scanning filters across the spectrum, any short term changes in the signals are lost; and in most oscilloscopes, such infrequent anomalies will scroll by on the display at a rate that is too fast for the operator to analyze. Only DSOs retain the relevant information on the signals, but in order to analyze it, the operator must scan through long arrays of data to find events that may not be readily apparent from the primary measurements alone.
In order to fill this gap, electronic counters such as modulation domain analyzers have been developed. These devices operate by performing primary measurements of the signal, i.e., detecting the signal's crossing time of a set threshold, and then generating plots of parameters derived from the primary measurements, such as the signal's frequency, phase, or time interval as a function of time. For example, the frequency/phase versus time analysis are very useful in analyzing frequency-shift-key and phase-shift-key, respectively, modulated transmissions; time interval analysis is useful for analyzing pulse-width modulated signals.
SUMMARY OF THE INVENTION
While being somewhat useful in analyzing obvious, recurrent trends in modulated signal transmission applications, modulation analyzers are less useful in identifying and tracing specific anomalies in those signals and addressing the wide range of signal analysis that would be desired. Modulation domain analyzers do not enable the operator to compare the derived parameters such as frequency/phase to the actual primary measurement of the signals such as its level, e.g., voltage. Modulation analyzers do not store the primary measurements, simply calculating the parameters on-the-fly. As a result, it is still difficult for the operator to find the highly infrequent anomalous event. Moreover, there is no way of identifying the location of the anomalous event in terms of the actual signal, even if it can be found. Still further, modulation domain analyzers require that the threshold be preset. Once a measurement is made, there is no way to select a different threshold. And, the number derived parameters that are offered by the devices is typically limited to phase, frequency, or time interval versus time.
The present invention concerns a digital oscilloscope that has been augmented with capabilities to derive and display parameters based on its primary measurements. In the preferred embodiment, the oscilloscope is a digital storage-type oscilloscope that measures a time varying voltage. The derived parameters are calculated from the primary measurements and simultaneously displayed with those measurements on the same time axis. This enables the oscilloscope operator to correlate features found by reference to the derived parameters directly to the primary measurements of the signal. Moreover, since the derived parameters are preferably calculated based upon stored data from the measurements, a large spectrum of different parameters can be calculated and different thresholds, for example, applied to the same data set.
In general, according to one aspect, the invention features a method for presenting information on a digital oscilloscope. The method comprises making primary measurements of a signal. In the typical instance, this comprises measuring the signal's voltage as a function of time, although the voltage can be indicative of some other time varying phenomenon, e.g., current, acceleration, or any transduced signal. The data from the primary measurement is then displayed as a function of time. In one typical implementation, the horizontal axis of the display represents time. According to the invention, parameters of the signal are also derived based upon the primary measurement data. These derived parameters are then also displayed as a function of time on the display. In the preferred implementation, the primary measurements and the derived parameters are displayed on a common display with a common time axis.
In specific embodiments, the derived time-varying parameters are generated based upon a number of operations. For example, the derived parameters can be generated by comparing the primary measurement data to a threshold. Such an operation yields parameters such as the time over which the primary measurement falls below or rises above a threshold as a function of time.
Additional features in further implementations derive parameters by first identifying cycles in the signal and then calculating the parameters for each of these cycles. Such operations are useful when, for example, plotting the time between minima/maxima and minima/maxima in previous or subsequent cycles, the time of local minima and/or maxima, period, per-cycle frequency, rise time, cycle fall time, over-shoot/pre-shoot, change in period, or change in pulse width from cycle-to-cycle.
In additional or alternative features, the derived parameters can be generated based upon first identifying cycles in the signal and then comparing the primary measurements in each cycle to a threshold. These operations are useful when determining peak-to-peak variation in amplitude, duty factor, and change in duty factor from cycle-to-cycle, for example.
In still further implementations, the derived parameters can be generated by first identifying cycles in the signal and then comparing each cycle to an absolute time reference. This is useful in commu
Hamilton Brook Smith & Reynolds P.C.
Hoff Marc S.
LeCroy S.A.
Raymond Edward
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