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Self-mixing interferometry for speed measurement
 Open loop Hall-Effect current sensors
 Optical Reflective Gear Tooth Sensor
 Method for Measuring Current Derivative Signal
 Rotational Speed Measuring and Calibration System
 Thermal drift of open-loop Hall Effect current sensor
 Direction Detection Based on the Output Duty Cycle
 Optimization of Conductor Structural Parameters
 Offset Error reduction in Hall Current Sensors
 Zero Offset Reduction in Hall Effect Sensors
 Error Correction of Automatic Testing Systems
 Design of Hall Effect Gear Tooth Speed Sensors
 Error Compensation of Hall Effect Current Sensors
 Parameter Optimization of Hall Gear Tooth Sensors
 Split Core Closed Loop Hall Current Sensors
 Mathematical Models of Gear Tooth Sensors
 Accuracy Improvement in Measuring & Test Systems
 Frequency-selective Adaptive Filtering
 Inductive eddy current sensors for stress measurement
 Fiber optic Bragg-grating sensors
 Capacitive Sensors for Displacement Measurement
 Self-calibration measuring methods
 Precise impedance measurement
 Measuring system of position transducers
 Self-correction algorithms
 Frequency selective-adaptive filtering
 Precise Fourier-analysis
 Parameter determination of damped oscillation signals
Competent Team
 Dr.-Ing. habil. Jigou Liu
 M.Sc. Jane Chen




Frequency-selective Adaptive Filtering
for Noise Suppression of Discrete Signals



Noise suppression plays an important role in sensors, measurement technology, and telecommunications. In this paper a frequency-selective filtering is introduced for the noise reduction of discrete signals. This filtering is based on a selection of frequency components of signal by using Fourier-analysis and the autocorrelation function. The output signal results from a signal reconstruction with the help of Fourier-series using the frequency components. In order to improve the filtering accuracy, a suitable adaptive algorithm is used in this filtering process. In this way a complete suppression of uncorrelated noise parts of discrete signals can be realized. The adaptive filtering is suitable for noise reduction of periodic and periodically extended signals, the spectrum of whom is super-imposed by the noise spectrum. Theoretical fundamentals, algorithms, simulation results and application examples are shown in this paper.


Rauschunterdrückung spielt eine wichtige Rolle in der Sensorik, Messtechnik und Tele-kommunikationstechnik. In diesem Beitrag wird eine frequenzselektiv-adaptive Filterungfür Rauschunterdrückung diskreter Signale dargelegt. Diese Filterung basiert auf Selektionvon Frequenzkomponenten des Nutzsignals durch Fourier-Analyse und Autokorrelations-funktion. Das Nutzsignal ergibt sich anschließend aus einer Signalrekonstruktion mithilfeeiner Fourier-Reihe unter Nutzung der Frequenzkomponenten. Um die Genauigkeit der Fil-terung zu verbessern, wird ein geeigneter adaptiver Algorithmus in der Filterung integriert.Dadurch ist eine vollständige Unterdrückung von nichtkorrelierten Rauschanteilen diskreterSignale realisierbar. Diese Filterung eignet sich für Rauschunterdrückung periodischer undperiodisch fortgesetzter Signale, deren Spektrum sich mit dem Rauschspektrum überlagernkann. Theoretische Grundlagen, Algorithmen, Simulationsergebnisse und Anwendungsbei-spiele werden im Beitrag gegeben..


噪声抑制在传感器、测量技术和电信领域中扮演着重要角色 。本文提出一种基于频率选择性滤波的离散信号降噪方案,该滤 波技术通过傅里叶分析与自相关函数对信号频率分量进行筛选, 最终利用傅里叶级数对频率分量进行信号重建以生成输出信号。 为提升滤波精度,本方法采用适配性自适应算法。通过该机制可 实现离散信号中无关噪声成分的完全抑制。该自适应滤波技术适 用于周期性及周期扩展信号的降噪处理,其频谱被噪声频谱所覆 盖。本文阐述了理论基础、算法设计、仿真结果及应用实例。




This paper is published in Technisches Messen, tm 11/2003, pp.522-529, in German

Download the paper (PDF-file 388kB)




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