• Journal of Sensor Science and Technology
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• v.22 no.1
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• pp.28-37
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• 2013

This paper presents a fault-tolerant control technique for wind turbine systems with sensor and actuator faults. The control objective is to maximize power production and minimize turbine loads by calculating a desired pitch angle within their limits. Any fault with a sensor and actuator can cause significant error in the pitch position of the corresponding blade. This problem may result in insufficient torque such that the power reference cannot be achieved. In this paper, a fault-tolerant control technique using a robust dynamic inversion observer and control allocation is employed to achieve successful pitch control despite these faults in the sensor and actuator. The observer based detection method is used to detect and isolate sensor faults by checking whether errors are larger than threshold values. In addition, the control allocation technique is adopted to tolerate actuator fault. Control allocation is one of the most commonly used fault-tolerant control techniques, especially for over-actuated systems. Further, the control allocation method can be used to achieve the power reference even in the event of blade actuator fault by redistributing the lost torque due to erroneous pitch position into non-faulty blade actuators. The effectiveness of the proposed method is demonstrated through simulations with a benchmark model of the wind turbine.

• Journal of the Korean Society for Railway
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• v.12 no.3
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• pp.412-419
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• 2009

How to efficiently and accurately detect the damages generated in a structure has become an important issue for structural health monitoring (SHM). Most existing SHM techniques require the baseline data which should be measured before a structure get damaged. Thus, this paper presents a new pitch-catch method-based SHM technique which will not require the baseline data any more. In the proposed SHM technique, the imaging method is also utilized to visualize damage locations. The proposed SHM technique is then validated through the damage detection texts for damaged aluminum plates.

• Proceedings of the Acoustical Society of Korea Conference
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• 1994.06a
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• pp.963-970
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• 1994

In speech signal processing, it is very important to detect the pitch exactly. The algorithms for pitch extraction that have been proposed until now are not enough to detect the fine pitch in speech signal. Thus we propose the new algorithm which takes advantage of the G-peak extraction. It is the method to find MZCI(maximum zer-crossing interval) which is defined as cut-off bandwidth rate of LPF (low pass filter)and detect the pitch period of the voiced signals. This algorithm performs robustly with a gross error rate of 3.63% even in 0 dB SNR environment. The gross error rate for clean speech is only 0.18%. Also it is able to process all course with speed.

• Speech Sciences
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• v.7 no.4
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• pp.3-10
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• 2000

This paper presents a time-based Pitch Determination Algorithm (PDA) for the reliable estimation of Pitch Period (PP) in speech signals. Based on the Dyadic Wavelet Transform (DyWT) , the proposed PDA detects the presence of Glottal Closure Instants (GCI) and uses the information to determine the pitch period. We also examine the problem of conventional PDAs based on DyWT; their performance is compared with the proposition of this paper. The effectiveness of the proposed method is tested with real speech signals containing a transition between the voiced and the unvoiced interval where the energy of the voiced signal is unsteady. The result shows that the proposed method provides good performance in estimating both the unsteady GCI positions as well as the steady parts.

• Journal of IKEEE
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• v.27 no.4
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• pp.472-476
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• 2023

Fundamental frequency/pitch period are major characteristics of speech signals. They are used in many speech applications like speech coding, speech recognition, speaker identification, and so on. In this paper, some of inflection points are used to estimate the pitch which is the inverse of the fundamental frequency. The inflection points are defined as points where local maxima, local minima or the slope changes occur. The speech signal is preprocessed to remove unnecessary inflection points due to the high frequency components using a low pass filter. Only the inflection points from local maxima are used to get the pitch period. While the existing pitch estimation methods process speech signals in blockwise, the proposed method detects the inflection points in sample and produces the pitch period/fundamental frequency estimates along the time. Computer simulation shows the usefulness of the proposed method as a fundamental frequency estimator.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2455-2458
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• 2003

In this paper, the Classification of Energy Labeling has been Proposed. Energy Parameters of input signal which is extracted from each phoneme is labelled. And groups of labelling according to detected energies of input signals are detected. Next, DTW processes in a selected group of labeling. This leads to DTW processing faster than a previous algorithm. In this Method, because an accurate detection of parameters is necessary on the assumption in steps of a detection of speeching duration and a detection of energy parameters, variable windows which are decided by pitch period is used. Extract algorithms don't search for exact frame energy, because 256 frame window-sizes is fixed. For this reason, a new energy extraction method has been proposed. A pitch period is detected firstly; next window scale is decided between 200 frames and 300 frames. The proposed method make it possible to cancel an influence of windows.

• The Journal of the Acoustical Society of Korea
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• v.18 no.1E
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• pp.27-31
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• 1999

Recent linguistic researches have brought into focus the relations between prosodic structures and syntactic, semantic or phonological structures. Most of them prove that prosodic information is available for understanding syntactic, semantic and discourse structures. But this result has not been integrated yet into recent Korean speech recognition or understanding systems. This study, as a part of integrating prosodic information into the speech recognition system, proposes an automatic detection technique of Korean accentual phrase boundaries by using one-stage DP, and the normalized pitch pattern. For making the normalized pitch pattern, this study proposes a method of modified normalization for Korean spoken language. For the experiment, this study employs 192 sentential speech data of 12 men's voice spoken in standard Korean, in which 720 accentual phrases are included, and 74.4% of the accentual phrase boundaries are correctly detected while 14.7% are the false detection rate.

• Science of Emotion and Sensibility
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• v.8 no.1
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• pp.1-7
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• 2005

This paper reports several emotion detecting methods based on various attributes of human voice. These methods have been developed at our Engineering Systems Laboratory. It is noted that, in all of the proposed methods, only prosodic information in voice is used for emotion recognition and semantic information in voice is not used. Different types of neural networks(NNs) are used for detection depending on the type of voice parameters. Earlier approaches separately used linear prediction coefficients(LPCs) and time series data of pitch but they were combined in later studies. The proposed methods are explained first and then evaluation experiments of individual methods and their performances in emotion detection are presented and compared.

• Speech Sciences
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• v.7 no.3
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• pp.153-165
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• 2000

During the phonation of voiced sounds, instants exist where the glottis is opened or closed, due to the periodic vibration of the vocal cord. When closed, this is called the glottal closure instant(GCI) or epoch.. The correct detection of the GCI is one of the important problems in speech processing for pitch detection, pitch synchronous analysis, and so on. Recently, it has been shown that the local maxima points of the wavelet transformed speech signal correspond to the GCIs of speech signal. In this paper, we investigate the accuracy of Gels estimated from this wavelet transformed speech signal. For this purpose we compare them with the negative peak points of the differentiated EGG signal that represents the actual GCIs of speech signal.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.4
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• pp.740-749
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• 1994

This paper presents method for improving the performance of the VSELP speech coder. The hybrid method is employed for pitch period searching. Pitch searching time is reduced and pitch detection error, caused by quantization error of excitation signal of encoder in VSELP coder, is reduced by this method. This paper also adopts a pitch period enhancement filter and an adaptive first order filter. In this result, pitch period searching time is reduced to 26%, and MOS of reconstructed speech signal is increased by 3.19 to 4.04.