时间和频率的基本原理-毕业设计外文翻译.docx

中北大学2011届毕业设计说明书外文文献原文Fundamentals of Time and FrequencyIntroductionTime and frequency standards supply three basic types of information： time-of-day， time interval， and frequency. Time-of-day information is provided in hours， minutes， and seconds， but often also includes the date (month， day， and year). A device that displays or records time-of-day information is called a clock. If a clock is used to label when an event happened， this label is sometimes called a time tag or time stamp. Date and time-of-day can also be used to ensure that events are synchronized， or happen at the same time. Time interval is the duration or elapsed time between two events. The standard unit of time interval is the second(s). However， many engineering applications require the measurement of shorter time intervals， such as milliseconds (1 ms = 10 -3 s) ， microseconds (1 s = 10 -6 s) ， nanoseconds (1 ns = 10 -9 s) ， and picoseconds (1 ps = 10 -12 s). Time is one of the seven base physical quantities， and the second is one of seven base units defined in the International System of Units (SI). The definitions of many other physical quantities rely upon the definition of the second. The second was once defined based on the earths rotational rate or as a fraction of the tropical year. That changed in 1967 when the era of atomic time keeping formally began. The current definition of the SI second is the duration of 9，192，631，770 periods of the radiation corresponding to the transition between two hyperfine levels of the ground state of the cesium-133 atom. Frequency is the rate of a repetitive event. If T is the period of a repetitive event， then the frequency f is its reciprocal， 1/T. Conversely， the period is the reciprocal of the frequency， T = 1/f. Since the period is a time interval expressed in seconds (s) ， it is easy to see the close relationship between time interval and frequency. The standard unit for frequency is the hertz (Hz) ， defined as events or cycles per second. The frequency of electrical signals is often measured in multiples of hertz， including kilohertz (kHz)， megahertz (MHz)， or gigahertz (GHz)， where 1 kHz equals one thousand (103) events per second， 1 MHz equals one million (106) events per second， and 1 GHz equals one billion (109) events per second. A device that produces frequency is called an oscillator. The process of setting multiple oscillators to the same frequency is called synchronization.Of course， the three types of time and frequency information are closely related. As mentioned， the standard unit of time interval is the second. By counting seconds， we can determine the date and the time-of-day. And by counting events or cycles per second， we can measure frequency. Time interval and frequency can now be measured with less uncertainty and more resolution than any other physical quantity. Today， the best time and frequency standards can realize the SI second with uncertainties of 1×10-15.Physical realizations of the other base SI units have much larger uncertainties.Coordinated Universal Time (UTC) The worlds major metrology laboratories routinely measure their time and frequency standards and send the measurement data to the Bureau International des Poids et Measures (BIPM) in Sevres， France. The BIPM averages data collected from more than 200 atomic time and frequency standards located at more than 40 laboratories， including the National Institute of Standards and Technology (NIST). As a result of this averaging， the BIPM generates two time scales， International Atomic Time (TAI)， and Coordinated Universal Time (UTC). These time scales realize the SI second as closely as possible. UTC runs at the same frequency as TAI. However， it differs from TAI by an integral number of seconds. This difference increases when leap seconds occur. When necessary， leap seconds are added to UTC on either June 30 or December 31. The purpose of adding leap seconds is to keep atomic time (UTC) within ±0.9 s of an older time scale called UT1， which is based on the rotational rate of the earth. Leap seconds have been added to UTC at a rate of slightly less than once per year， beginning in 1972. Keep in mind that the BIPM maintains TAI and UTC as paper time scales. The major metrology laboratories use the published data from the BIPM to steer their clocks and oscillators and generate real-time versions of UTC. Many of these laboratories distribute their versions of UTC via radio signals which section 17.4 are discussed in.You can think of UTC as the ultimate standard for time-of-day， time interval， and frequency. Clocks synchronized to UTC display the same hour minute， and second all over the world (and remain within one second of UT1). Oscillators simonized to UTC generate signals that serve as reference standards for time interval and frequency. Time and Frequency MeasurementTime and frequency measurements follow the conventions used in other areas of metrology. The frequency standard or clock being measured is called the device under test (DUT). A measurement compares the DUT to a standard or reference. The standard should outperform the DUT by a specified ratio， called the test uncertainty ratio (TUR). Ideally， the TUR should be 10：1 or higher. The higher the ratio， the less averaging is required to get valid measurement results. The test signal for time measurements is usually a pulse that occurs once per second (1 ps). The pulse width and polarity varies from device to device， but TTL levels are commonly used. The test signal for frequency measurements is usually at a frequency of 1 MHz or higher， with 5 or 10 MHz being common. Frequency signals are usually sine waves， but can also be pulses or square waves if the frequency signal is an oscillating sine wave. This signal produces one cycle (360 or 2 radians of phase) in one period. The signal amplitude is expressed in volts， and must be compatible with the measuring instrument. If the amplitude is too small， it might not be able to drive the measuring instrument. If the amplitude is too large， the signal must be attenuated to prevent overdriving the measuring instrument. This section examines the two main specifications of time and frequency measurementsaccuracy and stability. It also discusses some instruments used to measure time and frequency.Accuracy Accuracy is the degree of conformity of a measured or calculated value to its definition. Accuracy is related to the offset from an ideal value. For example， time offset is the difference between a measured on-time pulse and an ideal on-time pulse that coincides exactly with UTC. Frequency offset is the difference between a measured frequency and an ideal frequency with zero uncertainty. This ideal frequency is called the nominal frequency. Time offset is usually measured with a time interval counter (TIC). A TIC has inputs for two signals. One signal starts the counter and the other signal stops it. The time interval between the start and stop signals is measured by counting cycles from the time base oscillator. The resolution of a low cost TIC is limited to the period of its time base. For example， a TIC with a 10-MHz time base oscillator would have a resolution of 100 ns. More elaborate Tics use interpolation schemes to detect parts of a time base cycle and have much higher resolution1 ns resolution is commonplace， and 20 ps resolution is available. Frequency offset can be measured in either the frequency domain or time domain. A simple frequency domain measurement involves directly counting and displaying the frequency output of the DUT with a frequency counter. The reference for this measurement is either the counters internal time base oscillator， or an external time base. The counters resolution， or the number of digits it can display， limits its ability to measure frequency offset. For example， a 9-digit frequency counter can detect a frequency offset no smaller than 0.1 Hz at 10 MHz (1×10-8). The frequency offset is determined as Where fmeasur is the reading from the frequency counter， and fnominal is the frequency labeled on the oscillators nameplate， or specified output frequency. Frequency offset measurements in the time domain involve a phase comparison between the DUT and the reference. A simple phase comparison can be made with an oscilloscope. The oscilloscope will display two sine waves. The top sine wave represents a signal from the DUT， and the bottom sine wave represents a signal from the reference. If the two frequencies were exactly the same， their phase relationship would not change and both would appear to be stationary on the oscilloscope display. Since the two frequencies are not exactly the same， the reference appears to be stationary and the DUT signal moves. By measuring the rate of motion of the DUT signal we can determine its frequency offset. Vertical lines have been drawn through the points where each sine wave passes through zero. The bottom of the figure shows bars whose width represents the phase difference between the signals. In this case the phase difference is increasing， indicating that the DUT is lower in frequency than the reference. Measuring high accuracy signals with an oscilloscope is impractical， since the phase relationship between signals changes very slowly and the resolution of the oscilloscope display is limited. More precise phase comparisons can be made with a TIC. If the two input signals have the same frequency， the time interval will not change. If the two signals have different frequencies， the time interval wills change， and the rate of change is the frequency offset. The resolution of a TIC determines the smallest frequency change that it can detect without averaging. For example， a low cost TIC with a single-shot resolution of 100 ns can detect frequency changes of 1 × 10 -7 in 1 s. The current limit for TIC resolution is about 20 ps， which means that a frequency change of 2 ×10 -11 can be detected in 1 s. Averaging over longer intervals can improve the resolution to <1 ps in some units 6. Since standard frequencies like 5 or 10 MHz are not practical to measure with a TIC， frequency dividers or frequency mixers are used to convert the test frequency to a lower frequency. Divider systems are simpler and more versatile， since they can be easily built or programmed to accommodate different frequencies. Mixer systems are more expensive， require more hardware including an additional reference oscillator， and can often measure only one input frequency (e.g.， 10 MHz) ， but they have a higher signal-to-noise ratio than divider systems. If dividers are used， measurements are made from the TIC， but instead of using these measurements directly， we determine the rate of change from reading to reading. This rate of change is called the phase deviation. We can estimate frequency offset as follows：Where t is the amount of phase deviation， and T is the measurement period. To illustrate， consider a measurement of +1 s of phase deviation over a measurement period of 24 h. The unit used for measurement period (h) must be converted to the unit used for phase deviation (s). The equation becomesAs shown， a device that accumulates 1 s of phase deviation/day has a frequency offset of 1.16 × 10 -11 with respect to the reference. This simple example requires only two time interval readings to be made， and t is simply the difference between the two readings. Often， multiple readings are taken and the frequency offset is estimated by using least squares linear regression on the data set， and obtaining t from the slope of the least squares line. This information is usually presented as a phase plot， as shown in Fig. 17.6. The device under test is high in frequency by exactly 1×10 -9， as indicated by a phase deviation of 1 ns/s.Dimensionless frequency offset values can be converted to units of frequency (Hz) if the nominal frequency is known. To illustrate this， consider an oscillator with a nominal frequency of 5 MHz and a frequency offset of +1.16 10 -11. To find the frequency offset in hertz， multiply the nominal frequency by the offset： (5 ×106) (+1.16×10 -11) = 5.80×10 -5 =+0.0000580 Hz Then， add the offset to the nominal frequency to get the actual frequency： 5，000，000 Hz + 0.0000580 Hz = 5，000，000.0000580 Hz Stability Stability indicates how well an oscillator can produce the same time or frequency offset over a given time interval. It doesnt indicate whether the time or frequency is “right” or “wrong，” but only whether it stays the same. In contrast， accuracy indicates how well an oscillator has been set on time or on frequency. To understand this difference， consider that a stable oscillator that needs adjustment might produce a frequency with a large offset. Or， an unstable oscillator that was just adjusted might temporarily produce a frequency near its nominal value. Figure 17.7 shows the relationship between accuracy and stability. Stability is defined as the statistical estimate of the frequency or time fluctuations of a signal over a given time interval. These fluctuations are measured with respect to a mean frequency or time offset. Short-term stability usually refers to fluctuations over intervals less than 100 s. Long-term stability can refer to measurement intervals greater than 100 s， but usually refers to periods longer than 1 day. Stability estimates can be made in either the frequency domain or time domain， and can be calculated from a set of either frequency offset or time interval measurements. In some fields of measurement， stability is estimated by taking the standard deviation of the data set. However， standard deviation only works with stationary data， where the results are time independent， and the noise is white， meaning that it is evenly distributed across the frequency band of the measurement. Oscillator data is usually no stationary， since it contains time dependent noise contributed by the frequency offset. With stationary data， the mean and standard deviation will converge to particular values as more measurements are made. With no stationary data， the mean and standard deviation never converge to any particular values. Instead， there is a moving mean that changes each time we add a measurement. For these reasons， a non-classical statistic is often used to estimate stability in the time domain. This statistic is sometimes called the Allan variance， but since it is the square root of the variance， its proper name is the Allan deviation. The equation for the Allan deviation (y() is where yi is a set of frequency offset measurements containing y1， y2， y3， and so on， M is the number of values in the yi series， and the data are equally spaced in segments seconds long. Or Where xi is a set of phase measurements in time units containing x1， x2， x3， and so on， N is the number of values in the xi series， and the data are equally spaced in segments