• Title/Summary/Keyword: Standard least square method

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An Application of the Instrumental Variable Method(IVM) to a Parameter Identification of a Noise Contaminated Bearing Test Rig (IV 방법을 이용한 잡음이 포함된 베어링 실험 장치의 동특성 파라미터 추출)

  • 이용복;김창호;최동훈
    • Journal of KSNVE
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    • v.6 no.5
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    • pp.679-684
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    • 1996
  • The Instrumental Variable Method(IVM), modified from least square algorithm, is applied to parameter identification of a noise contaminated bearing test rig. The signal to noise ratio included in Frequency Response Function(FRF) can cause significant errors in parameter identification. Therefore, among several candidates of parameter identification method, results of the applied IVM were compared with noise-contaminated least square method. This study shows that the noise-contaminated least square method can have indonsistent accuracy depending on the degree of noise level, while the IVM has robuster performance to signal to noise ratio than least square method.

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Development of Nonlinear Fatigue Model Based on Particle Filter Method (파티클 필터기법을 통한 비선형 피로모델 개발 연구)

  • Mun, Sungho
    • International Journal of Highway Engineering
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    • v.18 no.4
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    • pp.63-68
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    • 2016
  • PURPOSES : The nonlinear model of fatigue cracking is typically used for determining the maintenance period. However, this requires that the model parameters be known. In this study, the particle filter (PF) method was used to determine various statistical parameters such as the mean and standard deviation values for the nonlinear model of fatigue cracking. METHODS : The PF method was used to determine various statistical parameters for the nonlinear model of fatigue cracking, such as the mean and standard deviation. RESULTS : On comparing the values obtained using the PF method and the least square (LS) method, it was found that PF method was suitable for determining the statistical parameters to be used in the nonlinear model of fatigue cracking. CONCLUSIONS : The values obtained using the PF method were as accurate as those obtained using the LS method. Furthermore, reliability design can be applied because the statistical parameters of mean and standard deviation can be obtained through the PF method.

Quasi Steady Stall Modelling of Aircraft Using Least-Square Method

  • Verma, Hari Om;Peyada, N.K.
    • International Journal of Aerospace System Engineering
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    • v.7 no.1
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    • pp.21-27
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    • 2020
  • Quasi steady stall is a phenomenon to characterize the aerodynamic behavior of aircraft at high angle of attack region. Generally, it is exercised from a steady state level flight to stall and its recovery to the initial flight in a calm weather. For a theoretical study, such maneuver is demonstrated in the form of aerodynamic model which consists of aircraft's stability and control derivatives. The current research paper is focused on the appropriate selection of aerodynamic model for the maneuver and estimation of the unknown model coefficients using least-square method. The statistical accuracy of the estimated parameters is presented in terms of standard deviations. Finally, the validation has been presented by comparing the measured data to the simulated data from different models.

Optimal Fuzzy Models with the Aid of SAHN-based Algorithm

  • Lee Jong-Seok;Jang Kyung-Won;Ahn Tae-Chon
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.6 no.2
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    • pp.138-143
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    • 2006
  • In this paper, we have presented a Sequential Agglomerative Hierarchical Nested (SAHN) algorithm-based data clustering method in fuzzy inference system to achieve optimal performance of fuzzy model. SAHN-based algorithm is used to give possible range of number of clusters with cluster centers for the system identification. The axes of membership functions of this fuzzy model are optimized by using cluster centers obtained from clustering method and the consequence parameters of the fuzzy model are identified by standard least square method. Finally, in this paper, we have observed our model's output performance using the Box and Jenkins's gas furnace data and Sugeno's non-linear process data.

Optimization of Detection Method Using a Moving Average Estimator for Speech Enhancement (음성강화를 위한 이동 평균 예측량 기반의 검출방법 최적화)

  • Lee, Soo-Jeong;Shin, Kye-Hyeon;Kim, Soon-Hyob
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.44 no.3
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    • pp.97-104
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    • 2007
  • Adaptive echo canceller(AEC) has become an important component in speech communication systems, including mobile phones and speech recognition. In these applications, the acoustic echo path has a long impulse response. We propose a moving-averge least mean square(MVLMS) algorithm with a detection method for acoustic echo cancellation. Using, the result of the tests that used colored input models clearly shows that the MVLMS detection algorithm has convergence performance superior to the least mean square(LMS) detection algorithm alone. Although the computational complexity of the new MVLMS algorithm is only slightly greater than that of the standard LMS detection algorithm, the new algorithm confers a significant improvement in stability.

Nondestructive Quantification of Intact Ambroxol Tablet using Near-infrared Spectroscopy (근적외분광분석법을 사용한 암브록솔 정제의 비파괴적 정량분석)

  • 임현량;우영아;김도형;김효진;강신정;최현철;최한곤
    • YAKHAK HOEJI
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    • v.48 no.1
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    • pp.60-64
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    • 2004
  • Near-infrared (NIR) spectroscopy was used to determine rapidly and nondestructively the content of ambroxol in intact ambroxol tablets containing 30 mg (12.5% m/m nominal concentration) by collecting NIR spectra in range 1100-1750 nm. The laboratory-made samples had 10.3∼15.9% m/m nominal ambroxol concentration. The measurements were made by reflection using a fiber-optic probe and calibration was carried out by partial least square regression (PLSR) with autoscaling. Model validation was performed by randomly splitting the data set into calibration and validation data set (7 samples as a calibration data set and 5 samples as a validation data set). The developed NIR method gave results comparable to the known values of tablets in a laboratorial manufacturing Process, standard error of calibration (SEC) and standard error of prediction (SEP) being 0.49% and 0.49% m/m respectively. The method showed good accuracy and repeatability NIR spectroscopic determination in intact tablets allowed the potential use of real time monitoring for a running production process.

The evaluation of correction methods and effect of kaolinite on quantitative analysis of quartz in respirable dust by FTIR direct-on-filter method (직접필터법을 이용한 석영 분석시 고령석의 영향 및 보정방법 평가)

  • Phee, Young Gyu
    • Journal of Korean Society of Occupational and Environmental Hygiene
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    • v.19 no.1
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    • pp.1-7
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    • 2009
  • To establish the Fourier-Transform Infra-Red spectrophotometry(FTIR) Direct-On-Filter(DOF) technique as a useful analytical method for quartz in respirable dust samples, an influence of the kaolinite should be corrected. Respirable dust, created in a dust chamber containing the standard material of quartz and kaolinite were collected using a cyclone equipped with a 25 mm, $0.8\;{\mu}m$ pore size DM filter as a collection medium. This study was designed to compare three methods of correction for kaolinite when quantifying the content of quartz, including the least square, the optimum choice and the spectral subtraction methods. The content of quartz in the respirable dust samples was overestimated by 6.2% when mixed with kaolinite(35.5% by weight). The content of quartz containing kaolinite(72.8% by weight) were overestimated by 32%. The spectral subtraction method underestimated the quartz content by 1.5%, while the other two correction methods, the optimum choice and the least square method, overestimated the quartz content by 1.9% to 6.4% and 0.04 to 1.1%, respectively. The results of this study are suggested that, when correcting for effects of kaolinite on quantitative analysis of quartz in respirable dust by FTIR direct-on-filter method, the least square method produce the most unbiased results be compared with those of other correction methods.

A Study on the Dynamic Characteristics of Air Foil Bearings Using LS(Least Square)/IV(Instrumental Variable) Method (LS/IV 기법을 이용한 공기 포일 베어링의 동특성 계수에 관한 연구)

  • Jo, Jun-Hyeon;Ryu, Keun;Kim, Chang-Ho;Lee, Yong-Bok
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2004.11a
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    • pp.677-684
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    • 2004
  • This paper describes a method for identifying the dynamic characteristics of air foil bearings for high speed turbomachinerys with the LS/IV method. In fact identifying the characteristics of air foil bearings is very difficult work, and it is tried to identify it. Experiments were conducted to determine the structural dynamic and hydrodynamic characteristics of air foil bearings. Numerical predictions compare the static and dynamic force performances. The housing of the bearing on the journal was driven by the impact hammer which were used to simulate impact force acting on air foil bearings. The characteristics of air foil bearings were extracted from the frequency response function (FRF) by LS(Least Square) method and IV(Instrumental Variable) method. The experiment was tested at 0 rpm and $10000\sim16000rpm$. And the test results were introduced about the dynamic characteristics of air foil bearings, and also compared with theoritical results.

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Non-uniform Weighted Vibration Target Positioning Algorithm Based on Sensor Reliability

  • Yanli Chu;Yuyao He;Junfeng Chen;Qiwu Wu
    • Journal of Information Processing Systems
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    • v.19 no.4
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    • pp.527-539
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    • 2023
  • In the positioning algorithm of two-dimensional planar sensor array, the estimation error of time difference-ofarrival (TDOA) algorithm is difficult to avoid. Thus, how to achieve accurate positioning is a key problem of the positioning technology based on planar array. In this paper, a method of sensor reliability discrimination is proposed, which is the foundation for selecting positioning sensors with small error and excellent performance, simplifying algorithm, and improving positioning accuracy. Then, a positioning model is established. The estimation characteristics of the least square method are fully utilized to calculate and fuse the positioning results, and the non-uniform weighting method is used to correct the weighting factors. It effectively handles the decreased positioning accuracy due to measurement errors, and ensures that the algorithm performance is improved significantly. Finally, the characteristics of the improved algorithm are compared with those of other algorithms. The experiment data demonstrate that the algorithm is better than the standard least square method and can improve the positioning accuracy effectively, which is suitable for vibration detection with large noise interference.

A New Least Mean Square Algorithm Using a Running Average Process for Speech Enhancement

  • Lee, Soo-Jeong;Ahn, Chan-Sik;Yun, Jong-Mu;Kim, Soon-Hyob
    • The Journal of the Acoustical Society of Korea
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    • v.25 no.3E
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    • pp.123-130
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    • 2006
  • The adaptive echo canceller (AEC) has become an important component in speech communication systems, including mobile station. In these applications, the acoustic echo path has a long impulse response. We propose a running-average least mean square (RALMS) algorithm with a detection method for acoustic echo cancellation. Using colored input models, the result clearly shows that the RALMS detection algorithm has a convergence performance superior to the least mean square (LMS) detection algorithm alone. The computational complexity of the new RALMS algorithm is only slightly greater than that of the standard LMS detection algorithm but confers a major improvement in stability.