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УДК 681.5.08
USING DIGITAL FILTERS OF LABVIEW IN MEASURING TECHNIQUES
© 2010 г. N.M. Cuong
Южно-Российский государственный технический университет (Новочеркасский политехнический институт)
South-Russian State Technical University (Novocherkassk Polytechnic Institute)
Одной из сложных проблем в измерительной технике является выделение сигналов, несущих измерительную информацию из широко спектра входных сигналов. Предлагается использовать для этой цели цифровые фильтры. Рассмотрена возможность создания таких фильтров в среде Labview. Предложен алгоритм выбора фильтра в зависимости от поставленной измерительной задачи. Экспериментальные исследования по выделению сигнала dB/dt с выхода индукционного преобразователя цифровыми фильтрами, построенными в среде Labview, показал их высокую эффективность.
Ключевые слова: цифровой фильтр; Labview; магнитная индукция.
One of the most important in measurement is filtering. The paper introduces digital filters in Labview and how to select appropriate filter for individual targets. Simulation results offiltering of differential signal of magnetic induction dB/dt are presented.
Keywords: digital filter; Labview; magnetic induction.
Introduction of Labview
Labview is called program graphical language. In Labview, instead of using command lines, symbols, wires, blocks are used, that combines execute required tasks. Labview programs are called virtual instruments, or VIs, because their appearance and operation imitate physical instruments, such as oscilloscopes and multimeters. LabVIEW contains a comprehensive set of tools for acquiring, analyzing, displaying, and storing data, as well as tools to help you troubleshoot your code [1].
Use LabVIEW to communicate with hardware such as data acquisition, vision, and motion control devices and GPIB, PXI, VXI, RS-232, and RS-485 instruments.
System Components for Taking Measurements with Virtual Instruments
Different hardware and software components can make up a virtual instrumentation system. There is a variety of hardware components to monitor or control a process or to test a device. As long as you can connect the hardware to the computer and understand how the hardware takes measurements, you can incorporate hardware into a virtual instrumentation system.
3
Figure 1. Scheme for retrieving, processing, indicating data Where:
1. Signal/transducer: Thermocouples, RTDs, Strain Gages...
2. Signal condition block.
3. Aquiring Device.
4. Virtual instruments (VIs).
VIs perform required tasks, one of them is signal filtering.
Applications in particular targets (measure magnetic parameters and characters) can see in [3, 4].
Digital Filters in Labview
In Labview, common filters were built, but user can design own filters that meet special commands.
In Labview, there are available digital filters:
FIR filters with the following characteristics
• FIR filters can achieve linear phase because of filter coefficient symmetry in the realization.
• FIR filters are always stable.
• FIR filters allow to filter signals using the convolution.
IIR Filters
Digital IIR filter designs come from the classical analog designs and include the following filter types:
• Butterworth filters;
• Chebyshev filters;
• Chebyshev II filters, also known as inverse Chebyshev and Type II Chebyshev filters;
• Elliptic filters;
• Bessel filters.
Nonlinear filters
Nonlinear filters provide specific filtering characteristics that are difficult to obtain using linear techniques.
Selecting filters
To select a filter for an application, pay attention to following parameters: Type of filter, ripple in the stop band (pass band), phase respond, frequency of signal... According to parameters, we use following flowchat as a reference [2]:
FIR
Filter
Figure 2. Selection algorithm of filters
Results of simulations and discusses
Simulation signals of differential of magnetic induction dB/dt are used as sources of signal with noise. According to flowchat, FIR filter and Butterworth filter are
used. Parameters of filters were adjusted with different values so that obtain required output signal. Figure 3 shows filtering result with FIR filter, and figure 4 shows result with Butterworth filter.
Figure 3. Input signal dB/dt with noise and output signal dB/dt after filtering by FIR filter
Butt er worth filter
О 200 400 600 BMJ 10G0
tüne(ms)
Figure 4. Output signal dB/dt after filtering by Butterworth filter
To evaluate quality of signal after filtering, two VIs «Amplitude and levels.vi» and «Spectral measure-ments.vi» had been used to analyze signal spectrum and to compute level of signal. «Spectral measurements.vi» performs FFT-based spectral measurements, such as the averaged magnitude spectrum, result showns that FIR filter can filter un-useful signal slightly better then Butterworth. «Amplitude and levels.vi» returns the amplitude, high state level, and low state level of a waveform, figure 5 shows result computed by this VI.
-Analyze implilui« of filtered ligfnili;-
Amplitude of signal Amplitude signal after A n-pStucte signal after
Figure 5. Amplitude of filtered signals
Поступила в редакцию
Obviously, signal amplitude after Butterworth filter fairly greater then signal after FIR filter. According to what is priority (signal spectrum or signal magnitude) you can choose appropriate filter. With our experiences, for dB/dt signal, Butterworth is suggested.
Conclusion
Filtering is very difficult. To obtain desired digital filters, many parameters are considered: sample rate, attenuation, filter type, cutoff frequency.Sometimes have to decide compromission between requirements of signal. In this paper, amplitude of dB/dt signal is priority so that Butterworth filter is an optimal choice.
Literatur
1. Labview manual, National Instrument, July 2000 Edition.
2. Laview Analysis concepts, National Instrument, March 2004 Edition.
3. Edoardo Carinati, Alessandro Ferrero. A virtual instrument for the measurement of the characteristics of magnetic materials // IEEE Trans. Instru. Meas. 1992. Vol. 41. № 6, Dec.
4. Leone D' Alessandro and Alessandro Ferrero. A method for the determination of the parameters of the hysteresis model of magnetic materials // IEEE Transactions on Instrumentation and Measurement. 1994. Vol. 43. № 4, August
24 декабря 2009 г.
Кыонг Нгуен Манх - аспирант, кафедра «Информационно-измерительная и медицинская техника», ЮжноРоссийский государственный технический университет (НПИ). Тел. (8635)255-214.
Cuong Nguyen Manh - post-graduate student, department «Information-Measuring and Medical Technics», South-Russia State Technical University (Novocherkassk Polytechnic Institute). Тел. (8635)255-214._
