The Experts below are selected from a list of 11190 Experts worldwide ranked by ideXlab platform
Fugee Tsung - One of the best experts on this subject based on the ideXlab platform.
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A Fast and Robust Nonparametric Monitoring Scheme for Free-Form Surface Scanning Data
IEEE Transactions on Automation Science and Engineering, 2019Co-Authors: Kai Wang, Fugee TsungAbstract:The advance of new sensing technologies, such as the 3-D laser scanning, creates a data-rich environment for quality control in modern industries. The free-form surfaces of complex manufactured parts can be quickly scanned, producing thousands of data points. To monitor these large-scale surface scanning data, three major challenges have to be solved simultaneously: 1) simple parametric models are no longer sufficient to describe free-form surfaces; 2) the massive data points need fast computations; and 3) the presence of outliers calls for robust analytics. To fulfill this task, this paper proposes a novel Monitoring Scheme where the control chart is designed based on a new robust bilateral kernel smoothing method. A fast approximation algorithm is also developed for efficient online Monitoring. This fast and robust nonparametric control chart shows significant superiority for surface Monitoring in our numerical simulations. Finally, a real case study demonstrates the effectiveness of our proposed Scheme in Monitoring the stability of a 3-D printing process. Note to Practitioners —Recently, the widespread use of 3-D laser scanners in industries enables engineers to digitize any free-form surface into thousands of data points, which provides an unprecedented opportunity for quality control of complex manufactured products. This paper proposes a Monitoring Scheme which caters to arbitrary geometric features on a surface. Practitioners need no prior and specific surface mathematical models. A robust estimate of the surface can be quickly derived from the noisy scanning data by an approximation algorithm. Then, a statistic calculating the deviation of this surface from the target one is plotted in a control chart to monitor the stability of the manufacturing process. In practice, this Monitoring Scheme can be integrated with the 3-D laser scanner as a new production module for automatic quality control and decision making.
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A Fast and Robust Nonparametric Monitoring Scheme for Free-Form Surface Scanning Data
IEEE Transactions on Automation Science and Engineering, 2019Co-Authors: Kai Wang, Fugee TsungAbstract:The advance of new sensing technologies, such as the 3-D laser scanning, creates a data-rich environment for quality control in modern industries. The free-form surfaces of complex manufactured parts can be quickly scanned, producing thousands of data points. To monitor these large-scale surface scanning data, three major challenges have to be solved simultaneously: 1) simple parametric models are no longer sufficient to describe free-form surfaces; 2) the massive data points need fast computations; and 3) the presence of outliers calls for robust analytics. To fulfill this task, this paper proposes a novel Monitoring Scheme where the control chart is designed based on a new robust bilateral kernel smoothing method. A fast approximation algorithm is also developed for efficient online Monitoring. This fast and robust nonparametric control chart shows significant superiority for surface Monitoring in our numerical simulations. Finally, a real case study demonstrates the effectiveness of our proposed Scheme in Monitoring the stability of a 3-D printing process.
Kai Wang - One of the best experts on this subject based on the ideXlab platform.
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A Fast and Robust Nonparametric Monitoring Scheme for Free-Form Surface Scanning Data
IEEE Transactions on Automation Science and Engineering, 2019Co-Authors: Kai Wang, Fugee TsungAbstract:The advance of new sensing technologies, such as the 3-D laser scanning, creates a data-rich environment for quality control in modern industries. The free-form surfaces of complex manufactured parts can be quickly scanned, producing thousands of data points. To monitor these large-scale surface scanning data, three major challenges have to be solved simultaneously: 1) simple parametric models are no longer sufficient to describe free-form surfaces; 2) the massive data points need fast computations; and 3) the presence of outliers calls for robust analytics. To fulfill this task, this paper proposes a novel Monitoring Scheme where the control chart is designed based on a new robust bilateral kernel smoothing method. A fast approximation algorithm is also developed for efficient online Monitoring. This fast and robust nonparametric control chart shows significant superiority for surface Monitoring in our numerical simulations. Finally, a real case study demonstrates the effectiveness of our proposed Scheme in Monitoring the stability of a 3-D printing process. Note to Practitioners —Recently, the widespread use of 3-D laser scanners in industries enables engineers to digitize any free-form surface into thousands of data points, which provides an unprecedented opportunity for quality control of complex manufactured products. This paper proposes a Monitoring Scheme which caters to arbitrary geometric features on a surface. Practitioners need no prior and specific surface mathematical models. A robust estimate of the surface can be quickly derived from the noisy scanning data by an approximation algorithm. Then, a statistic calculating the deviation of this surface from the target one is plotted in a control chart to monitor the stability of the manufacturing process. In practice, this Monitoring Scheme can be integrated with the 3-D laser scanner as a new production module for automatic quality control and decision making.
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A Fast and Robust Nonparametric Monitoring Scheme for Free-Form Surface Scanning Data
IEEE Transactions on Automation Science and Engineering, 2019Co-Authors: Kai Wang, Fugee TsungAbstract:The advance of new sensing technologies, such as the 3-D laser scanning, creates a data-rich environment for quality control in modern industries. The free-form surfaces of complex manufactured parts can be quickly scanned, producing thousands of data points. To monitor these large-scale surface scanning data, three major challenges have to be solved simultaneously: 1) simple parametric models are no longer sufficient to describe free-form surfaces; 2) the massive data points need fast computations; and 3) the presence of outliers calls for robust analytics. To fulfill this task, this paper proposes a novel Monitoring Scheme where the control chart is designed based on a new robust bilateral kernel smoothing method. A fast approximation algorithm is also developed for efficient online Monitoring. This fast and robust nonparametric control chart shows significant superiority for surface Monitoring in our numerical simulations. Finally, a real case study demonstrates the effectiveness of our proposed Scheme in Monitoring the stability of a 3-D printing process.
R.a. Ammar - One of the best experts on this subject based on the ideXlab platform.
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An efficient QoS distribution Monitoring Scheme
10th IEEE Symposium on Computers and Communications (ISCC'05), 2005Co-Authors: H.h. Elazhary, S.s. Gokhale, R.a. AmmarAbstract:In end-to-end Monitoring, traffic measurements are recorded at the source and destination nodes. In QoS distribution Monitoring, the measurements are recorded at several intermediate nodes along a connection. End-to-end Monitoring is conceptually simple and easy to implement, but not capable of localizing the degradation. Thus, any corrective action has to be applied end-to-end, which can be prohibitively expensive. Although QoS distribution Monitoring holds the promise of being able to localize the degradation to a single domain, prevalent QoS distribution Monitoring techniques do not consistently provide this capability. They also consume excessive resources in the Monitoring process and rely on assumptions which are unlikely to hold in practice. In this paper we describe the design tradeoffs associated with QoS distribution Monitoring and highlight the limitations of the existing research. We then describe a QoS distribution Monitoring Scheme which provides practical solutions to these challenges. Using extensive analysis we compare the efficiency of the proposed Scheme to the prevalent ones.
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ISCC - An efficient QoS distribution Monitoring Scheme
10th IEEE Symposium on Computers and Communications (ISCC'05), 2005Co-Authors: H.h. Elazhary, S.s. Gokhale, R.a. AmmarAbstract:In end-to-end Monitoring, traffic measurements are recorded at the source and destination nodes. In QoS distribution Monitoring, the measurements are recorded at several intermediate nodes along a connection. End-to-end Monitoring is conceptually simple and easy to implement, but not capable of localizing the degradation. Thus, any corrective action has to be applied end-to-end, which can be prohibitively expensive. Although QoS distribution Monitoring holds the promise of being able to localize the degradation to a single domain, prevalent QoS distribution Monitoring techniques do not consistently provide this capability. They also consume excessive resources in the Monitoring process and rely on assumptions which are unlikely to hold in practice. In this paper we describe the design tradeoffs associated with QoS distribution Monitoring and highlight the limitations of the existing research. We then describe a QoS distribution Monitoring Scheme which provides practical solutions to these challenges. Using extensive analysis we compare the efficiency of the proposed Scheme to the prevalent ones.
Chun-kit Chan - One of the best experts on this subject based on the ideXlab platform.
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A Pilot-Correlated PMD Monitoring Scheme for Direct Detection Optical OFDM System
Journal of Lightwave Technology, 2015Co-Authors: Tianwai Bo, Chun-kit ChanAbstract:A polarization mode dispersion Monitoring Scheme is proposed and demonstrated for direct-detection optical orthogonal frequency division multiplexing (DDO-OFDM) systems. A pair of data-assisted pilot subcarriers is inserted at two spectral edges of the OFDM signal spectrum. Simple data correlation technique is used to estimate the powers of the pilot subcarriers and thus retrieves the DGD value at the Monitoring unit, without the need of demodulation of the pilot subcarriers. Experiments show a DGD Monitoring range of 0 to 45 ps in a typical radio-frequency tone-assisted DDO-OFDM system. The robustness of the proposed Scheme to optical signal-to-noise ratio and accumulated chromatic dispersion is further experimentally investigated. Besides, simulations and experiments are performed to demonstrate the feasibility of using photodiodes with narrow bandwidth. By inserting one more data-assisted pilot subcarrier, the proposed Scheme becomes insensitive to the input angle of the state of polarization. The proposed Scheme provides an effective Monitoring solution for the optical OFDM signals across intermediate nodes in flexible optical network.
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PMD Monitoring Scheme for direct-detection optical OFDM systems using code-assisted optical subcarriers
2014 Conference on Lasers and Electro-Optics (CLEO) - Laser Science to Photonic Applications, 2014Co-Authors: Tianwai Bo, Chun-kit ChanAbstract:A PMD Monitoring Scheme is proposed for direct-detection optical OFDM systems by adding a pair of code-assisted optical subcarriers. Code correlation technique is used to retrieve DGD values over 0-25ps with
Steven X. Ding - One of the best experts on this subject based on the ideXlab platform.
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A New Soft-Sensor-Based Process Monitoring Scheme Incorporating Infrequent KPI Measurements
IEEE Transactions on Industrial Electronics, 2015Co-Authors: Yuri A. W. Shardt, Steven X. DingAbstract:The development of advanced techniques for process Monitoring and fault diagnosis using both model-based and data-driven approaches has led to many practical applications. One issue that has not been considered in such applications is the ability to deal with key performance indicators (KPIs) that are only sporadically measured and with significant time delay. Therefore, in this paper, the data-driven design of diagnostic-observer-based process Monitoring Schemes is extended to include the ability to detect changes given infrequently measured KPIs. The extended diagnostic observer is shown to be stable and hence able to converge to the true value. The proposed method is tested using both Monte Carlo simulations and the Tennessee-Eastman problem. It is shown that although time delay and sampling time increase the detection delay, the overall effect can be mitigated by using a soft sensor. Furthermore, it is shown that the results are not strongly dependent on the sampling time, but do depend on the time delay. Therefore, the proposed soft-sensor-based Monitoring Scheme can efficiently detect faults even in the absence of direct process information.
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A Canonical Variate Analysis Based Process Monitoring Scheme and Benchmark Study
IFAC Proceedings Volumes, 2014Co-Authors: Zhiwen Chen, Kai Zhang, Steven X. Ding, Minjia Krueger, Zhangming HeAbstract:Abstract Principal component analysis (PCA) and Partial least square (PLS) are powerful multivariate statistical tools that have been successfully applied for process Monitoring. They are efficient in dimension reduction and are suitable for processing large amount of data. Nevertheless, their application scope is restricted to static processes where the dynamics are ignored. In order to achieve improved Monitoring performance for dynamic processes, in this paper, we propose an effective dynamic Monitoring Scheme based on the canonical variate analysis (CVA) technique. Different from the standard PCA- and PLS-based techniques which rely on mean-extraction for residual generation, the proposed CVA-based Scheme takes process dynamics into account as well. The properties of all three methods are then compared in detail and finally, the improvements of the proposed method are demonstrated on the well-accepted Tennessee Eastman benchmark process.