Because of the sensitivity of the Kalman framework to gross errors, proper techniques for detection of gross errors are necessary. By integrating the selection of quasi-accurate observations and the Kalman framework, ...Because of the sensitivity of the Kalman framework to gross errors, proper techniques for detection of gross errors are necessary. By integrating the selection of quasi-accurate observations and the Kalman framework, a new filter called the quasi-accurate filter (QUAF) is developed. The expansibility and implementation scheme of the new algorithm are then discussed in detail, and the reliability matrix for the Kalman filter is proposed to analyze the reliability of the filters with different detection technologies. Finally, the experimental results from a real world case study are used to validate the conclusions. The QUAF carries out the preliminary selection of the quasi-accurate observations (QAOs) using the innovation of the Kalman filter, and use the check QAOs to determine reasonable observations. This causes the QUAF to handle more easily and possess wider expansibility. QUAF can be reformulated to the special cases of several common detection methods, such as the innovation method, robust estimation and quasi-accurate detection (QUAD). Since only reasonable observations are used, the QUAF has better detection accuracy and stronger avoidance of gross errors than the innovation method and robust estimation. Meanwhile, compared with QUAD methods, QUAF introduces the state-predicted model, requiring fewer quasi-accurate observations and making it more suitable for systems with complicated observation structures or sparse observations.展开更多
A novel mixed integer linear programming (NMILP) model for detection of gross errors is presented in this paper. Yamamura et al.(1988) designed a model for detection of gross errors and data reconciliation based on Ak...A novel mixed integer linear programming (NMILP) model for detection of gross errors is presented in this paper. Yamamura et al.(1988) designed a model for detection of gross errors and data reconciliation based on Akaike information cri- terion (AIC). But much computational cost is needed due to its combinational nature. A mixed integer linear programming (MILP) approach was performed to reduce the computational cost and enhance the robustness. But it loses the super performance of maximum likelihood estimation. To reduce the computational cost and have the merit of maximum likelihood estimation, the simultaneous data reconciliation method in an MILP framework is decomposed and replaced by an NMILP subproblem and a quadratic programming (QP) or a least squares estimation (LSE) subproblem. Simulation result of an industrial case shows the high efficiency of the method.展开更多
An NT-MT combined method based on nodal test (NT) and measurement test (MT) is developed for gross error detection and data reconciliation for industrial application. The NT-MT combined method makes use of both NT and...An NT-MT combined method based on nodal test (NT) and measurement test (MT) is developed for gross error detection and data reconciliation for industrial application. The NT-MT combined method makes use of both NT and MT tests and this combination helps to overcome the defects in the respective methods. It also avoids any artificial manipulation and eliminates the huge combinatorial problem that is created in the combined method based on the nodal test in the case of more than one gross error for a large process system. Serial compensation strategy is also used to avoid the decrease of the coefficient matrix rank during the computation of the proposed method. Simulation results show that the proposed method is very effective and possesses good performance.展开更多
Wavelet theory is efficient as an adequate tool for analyzing single epoch GPS deformation signal. Wavelet analysis technique on gross error detection and recovery is advanced. Criteria of wavelet function choosing an...Wavelet theory is efficient as an adequate tool for analyzing single epoch GPS deformation signal. Wavelet analysis technique on gross error detection and recovery is advanced. Criteria of wavelet function choosing and Mallat decomposition levels decision are discussed. An effective deformation signal extracting method is proposed, that is wavelet noise reduction technique considering gross error recovery, which combines wavelet multi-resolution gross error detection results. Time position recognizing of gross errors and their repairing performance are realized. In the experiment, compactly supported orthogonal wavelet with short support block is more efficient than the longer one when discerning gross errors, which can obtain more finely analyses. And the shape of discerned gross error of short support wavelet is simpler than that of the longer one. Meanwhile, the time scale is easier to identify.展开更多
Due to some shortcomings in the current multiple hypothesis solution separation advanced receiver autonomous integrity monitoring(MHSS ARAIM)algorithm,such as the weaker robustness,a number of computational subsets wi...Due to some shortcomings in the current multiple hypothesis solution separation advanced receiver autonomous integrity monitoring(MHSS ARAIM)algorithm,such as the weaker robustness,a number of computational subsets with the larger computational load,a method combining MHSS ARAIM with gross error detection is proposed in this paper.The gross error detection method is used to identify and eliminate the gross data in the original data first,then the MHSS ARAIM algorithm is used to deal with the data after the gross error detection.Therefore,this makes up for the weakness of the MHSS ARAIM algorithm.With the data processing and analysis from several international GNSS service(IGS)and international GNSS monitoring and assessment system(iGMAS)stations,the results show that this new algorithm is superior to MHSS ARAIM in the localizer performance with vertical guidance down to 200 feet service(LPV-200)when using GPS and BDS measure data.Under the assumption of a single-faulty satellite,the effective monitoring threshold(EMT)is improved about 22.47%and 9.63%,and the vertical protection level(VPL)is improved about 32.28%and 12.98%for GPS and BDS observations,respectively.Moreover,under the assumption of double-faulty satellites,the EMT is improved about 80.85%and 29.88%,and the VPL is improved about 49.66%and 18.24%for GPS and BDS observations,respectively.展开更多
Principle component analysis (PCA) based chi-square test is more sensitive to subtle gross errors and has greater power to correctly detect gross errors than classical chi-square test. However, classical principal com...Principle component analysis (PCA) based chi-square test is more sensitive to subtle gross errors and has greater power to correctly detect gross errors than classical chi-square test. However, classical principal component test (PCT) is non-robust and can be very sensitive to one or more outliers. In this paper, a Huber function liked robust weight factor was added in the collective chi-square test to eliminate the influence of gross errors on the PCT. Meanwhile, robust chi-square test was applied to modified simultaneous estimation of gross error (MSEGE) strategy to detect and identify multiple gross errors. Simulation results show that the proposed robust test can reduce the possibility of type II errors effectively. Adding robust chi-square test into MSEGE does not obviously improve the power of multiple gross error identification, the proposed approach considers the influence of outliers on hypothesis statistic test and is more reasonable.展开更多
A new idea and a distinctive method have been proposed, which concern real errors and their estimators. By using the idea of 'Quasi-Stable Adjustment' created by Prof. Zhou Jiangwen for reference, the rank-def...A new idea and a distinctive method have been proposed, which concern real errors and their estimators. By using the idea of 'Quasi-Stable Adjustment' created by Prof. Zhou Jiangwen for reference, the rank-deficient equations on real errors are resolved by adding the conditions under which the minimum of the norm of the real errors of the quasi-accurate observations is restrained.展开更多
Mixed integer linear programming(MILP) approach for simultaneous gross error detection and data reconciliation has been proved as an efficient way to adjust process data with material,energy,and other balance constrai...Mixed integer linear programming(MILP) approach for simultaneous gross error detection and data reconciliation has been proved as an efficient way to adjust process data with material,energy,and other balance constrains.But the efficiency will decrease significantly when this method is applied in a large-scale problem because there are too many binary variables involved.In this article,an improved method is proposed in order to generate gross error candidates with reliability factors before data rectification.Candidates are used in the MILP objective function to improve the efficiency and accuracy by reducing the number of binary variables and giving accurate weights for suspected gross errors candidates.Performance of this improved method is compared and discussed by applying the algorithm in a widely used industrial example.展开更多
Data reconciliation technology can decrease the level of corruption of process data due to measurement noise, but the presence of outliers caused by process peaks or unmeasured disturbances will smear the reconciled r...Data reconciliation technology can decrease the level of corruption of process data due to measurement noise, but the presence of outliers caused by process peaks or unmeasured disturbances will smear the reconciled results. Based on the analysis of limitation of conventional outlier detection algorithms, a modified outlier detection method in dynamic data reconciliation (DDR) is proposed in this paper. In the modified method, the outliers of each variable are distinguished individually and the weight is modified accordingly. Therefore, the modified method can use more information of normal data, and can efficiently decrease the effect of outliers. Simulation of a continuous stirred tank reactor (CSTR) process verifies the effectiveness of the proposed algorithm.展开更多
Digital elevation model(DEM)matching techniques have been extended to DEM deformation detection by substituting a robust estimator for the least squares estimator,in which terrain changes are treated as gross errors.H...Digital elevation model(DEM)matching techniques have been extended to DEM deformation detection by substituting a robust estimator for the least squares estimator,in which terrain changes are treated as gross errors.However,all existing methods only emphasise their deformation detecting ability,and neglect another important aspect:only when the gross error can be detected and located,can this system be useful.This paper employs the gross error judgement matrix as a tool to make an in-depth analysis of this problem.The theoretical analyses and experimental results show that observations in the DEM matching algorithm in real applications have the ability to detect and locate gross errors.Therefore,treating the terrain changes as gross errors is theoretically feasible,allowing real DEM deformations to be detected by employing a surface matching technique.展开更多
文摘Because of the sensitivity of the Kalman framework to gross errors, proper techniques for detection of gross errors are necessary. By integrating the selection of quasi-accurate observations and the Kalman framework, a new filter called the quasi-accurate filter (QUAF) is developed. The expansibility and implementation scheme of the new algorithm are then discussed in detail, and the reliability matrix for the Kalman filter is proposed to analyze the reliability of the filters with different detection technologies. Finally, the experimental results from a real world case study are used to validate the conclusions. The QUAF carries out the preliminary selection of the quasi-accurate observations (QAOs) using the innovation of the Kalman filter, and use the check QAOs to determine reasonable observations. This causes the QUAF to handle more easily and possess wider expansibility. QUAF can be reformulated to the special cases of several common detection methods, such as the innovation method, robust estimation and quasi-accurate detection (QUAD). Since only reasonable observations are used, the QUAF has better detection accuracy and stronger avoidance of gross errors than the innovation method and robust estimation. Meanwhile, compared with QUAD methods, QUAF introduces the state-predicted model, requiring fewer quasi-accurate observations and making it more suitable for systems with complicated observation structures or sparse observations.
基金Project supported by the National Creative Research Groups Science Foundation of China (No. 60421002)the National "Tenth Five-Year" Science and Technology Research Program of China (No.2004BA204B08)
文摘A novel mixed integer linear programming (NMILP) model for detection of gross errors is presented in this paper. Yamamura et al.(1988) designed a model for detection of gross errors and data reconciliation based on Akaike information cri- terion (AIC). But much computational cost is needed due to its combinational nature. A mixed integer linear programming (MILP) approach was performed to reduce the computational cost and enhance the robustness. But it loses the super performance of maximum likelihood estimation. To reduce the computational cost and have the merit of maximum likelihood estimation, the simultaneous data reconciliation method in an MILP framework is decomposed and replaced by an NMILP subproblem and a quadratic programming (QP) or a least squares estimation (LSE) subproblem. Simulation result of an industrial case shows the high efficiency of the method.
基金Supported by the National Creative Research Groups Science Foundation of China (No.60421002) and the National "TenthFive-Year" Science and Technology Research Program of China (2004BA204B08).
文摘An NT-MT combined method based on nodal test (NT) and measurement test (MT) is developed for gross error detection and data reconciliation for industrial application. The NT-MT combined method makes use of both NT and MT tests and this combination helps to overcome the defects in the respective methods. It also avoids any artificial manipulation and eliminates the huge combinatorial problem that is created in the combined method based on the nodal test in the case of more than one gross error for a large process system. Serial compensation strategy is also used to avoid the decrease of the coefficient matrix rank during the computation of the proposed method. Simulation results show that the proposed method is very effective and possesses good performance.
基金Supported by National High Technology Research and Development Program of China （863 Program） （2006AA040308）, National Natural Science Foundation of China （60736021）, and the National Creative Research Groups Science Foundation of China （60721062）
基金Supported by Specialized Research Fundfor the Doctoral Programof Higher Educationin China(No.20040290503) Science and Technology Fundationof CUMT(No.2005B020) .
文摘Wavelet theory is efficient as an adequate tool for analyzing single epoch GPS deformation signal. Wavelet analysis technique on gross error detection and recovery is advanced. Criteria of wavelet function choosing and Mallat decomposition levels decision are discussed. An effective deformation signal extracting method is proposed, that is wavelet noise reduction technique considering gross error recovery, which combines wavelet multi-resolution gross error detection results. Time position recognizing of gross errors and their repairing performance are realized. In the experiment, compactly supported orthogonal wavelet with short support block is more efficient than the longer one when discerning gross errors, which can obtain more finely analyses. And the shape of discerned gross error of short support wavelet is simpler than that of the longer one. Meanwhile, the time scale is easier to identify.
基金National Natural Science Foundation of China(No.4130403341504006+2 种基金41604001)The Grand Projects of the Beidou-2 System(No.GFZX0301040308)The Foundation of State Key Laboratory of Geo-information Engineering(No.SKLGIE2017-Z-2-1)。
文摘Due to some shortcomings in the current multiple hypothesis solution separation advanced receiver autonomous integrity monitoring(MHSS ARAIM)algorithm,such as the weaker robustness,a number of computational subsets with the larger computational load,a method combining MHSS ARAIM with gross error detection is proposed in this paper.The gross error detection method is used to identify and eliminate the gross data in the original data first,then the MHSS ARAIM algorithm is used to deal with the data after the gross error detection.Therefore,this makes up for the weakness of the MHSS ARAIM algorithm.With the data processing and analysis from several international GNSS service(IGS)and international GNSS monitoring and assessment system(iGMAS)stations,the results show that this new algorithm is superior to MHSS ARAIM in the localizer performance with vertical guidance down to 200 feet service(LPV-200)when using GPS and BDS measure data.Under the assumption of a single-faulty satellite,the effective monitoring threshold(EMT)is improved about 22.47%and 9.63%,and the vertical protection level(VPL)is improved about 32.28%and 12.98%for GPS and BDS observations,respectively.Moreover,under the assumption of double-faulty satellites,the EMT is improved about 80.85%and 29.88%,and the VPL is improved about 49.66%and 18.24%for GPS and BDS observations,respectively.
基金The National Natural Science Foundation of China(No 60504033)
文摘Principle component analysis (PCA) based chi-square test is more sensitive to subtle gross errors and has greater power to correctly detect gross errors than classical chi-square test. However, classical principal component test (PCT) is non-robust and can be very sensitive to one or more outliers. In this paper, a Huber function liked robust weight factor was added in the collective chi-square test to eliminate the influence of gross errors on the PCT. Meanwhile, robust chi-square test was applied to modified simultaneous estimation of gross error (MSEGE) strategy to detect and identify multiple gross errors. Simulation results show that the proposed robust test can reduce the possibility of type II errors effectively. Adding robust chi-square test into MSEGE does not obviously improve the power of multiple gross error identification, the proposed approach considers the influence of outliers on hypothesis statistic test and is more reasonable.
文摘A new idea and a distinctive method have been proposed, which concern real errors and their estimators. By using the idea of 'Quasi-Stable Adjustment' created by Prof. Zhou Jiangwen for reference, the rank-deficient equations on real errors are resolved by adding the conditions under which the minimum of the norm of the real errors of the quasi-accurate observations is restrained.
基金Supported by the National High Technology Research and Development Program of China (2007AA40702 and 2007AA04Z191)
文摘Mixed integer linear programming(MILP) approach for simultaneous gross error detection and data reconciliation has been proved as an efficient way to adjust process data with material,energy,and other balance constrains.But the efficiency will decrease significantly when this method is applied in a large-scale problem because there are too many binary variables involved.In this article,an improved method is proposed in order to generate gross error candidates with reliability factors before data rectification.Candidates are used in the MILP objective function to improve the efficiency and accuracy by reducing the number of binary variables and giving accurate weights for suspected gross errors candidates.Performance of this improved method is compared and discussed by applying the algorithm in a widely used industrial example.
基金Supported by the National Outstanding Youth Science Foundation of China (No. 60025308) and Key Technologies R&DProgram in the 10th Five-year Plan (No. 2001BA204B07)
文摘Data reconciliation technology can decrease the level of corruption of process data due to measurement noise, but the presence of outliers caused by process peaks or unmeasured disturbances will smear the reconciled results. Based on the analysis of limitation of conventional outlier detection algorithms, a modified outlier detection method in dynamic data reconciliation (DDR) is proposed in this paper. In the modified method, the outliers of each variable are distinguished individually and the weight is modified accordingly. Therefore, the modified method can use more information of normal data, and can efficiently decrease the effect of outliers. Simulation of a continuous stirred tank reactor (CSTR) process verifies the effectiveness of the proposed algorithm.
基金This research is supported by the National High Technology Plan(863)of the People’s Republic of China,Project No.2009AA12Z207.
文摘Digital elevation model(DEM)matching techniques have been extended to DEM deformation detection by substituting a robust estimator for the least squares estimator,in which terrain changes are treated as gross errors.However,all existing methods only emphasise their deformation detecting ability,and neglect another important aspect:only when the gross error can be detected and located,can this system be useful.This paper employs the gross error judgement matrix as a tool to make an in-depth analysis of this problem.The theoretical analyses and experimental results show that observations in the DEM matching algorithm in real applications have the ability to detect and locate gross errors.Therefore,treating the terrain changes as gross errors is theoretically feasible,allowing real DEM deformations to be detected by employing a surface matching technique.
