The Experts below are selected from a list of 48 Experts worldwide ranked by ideXlab platform
Dayang Laila Abang Abdul Majid - One of the best experts on this subject based on the ideXlab platform.
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condition Structural index using principal component analysis for undamaged damage and Repair conditions of carbon fiber reinforced plastic laminate
Journal of Intelligent Material Systems and Structures, 2014Co-Authors: Khairul Dahri Mohd Aris, Mohd Sapuan Salit, Faizal Mustapha, Dayang Laila Abang Abdul MajidAbstract:This article deals with the data reduction technique using the principal component analysis applied to the carbon fiber–reinforced plastic panels for Structural health monitoring approaches. Two carbon fiber–reinforced plastic panels subjected to damage and Repair coincide with typical aircraft Repair procedures found in the aircraft Structural Repair Manual. The panels were simulated with 30 mm diameter of partial and full penetration damages using a diamond-coated router. The data (50 observations) were captured for the undamaged, damaged, and Repaired conditions by placing lead zirconate titanate smart sensors at 100 mm across the damaged and Repaired structures. A time-based data response was captured for post analysis during the interrogation on the structure at each condition. The raw data were captured in a Lamb waveform, and the interested features were extracted using Morlet wavelet analysis to evaluate the Condition Structural Index and Amplitude-Based Assessment for each condition retrieved from the Gaussian-like distribution. The results were evaluated using the principal component analysis technique in order to distinguish the characteristic of the undamaged, damaged, and Repaired conditions. The results showed that in all cases considered, it was possible to distinguish the conditions of undamaged, damaged, and Repaired states with promising accuracy and repeatability of the data.
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Condition Structural Index using Principal Component Analysis for undamaged, damage and Repair conditions of carbon fiber–reinforced plastic laminate
Journal of Intelligent Material Systems and Structures, 2013Co-Authors: Khairul Dahri Mohd Aris, Mohd Sapuan Salit, Faizal Mustapha, Dayang Laila Abang Abdul MajidAbstract:This article deals with the data reduction technique using the principal component analysis applied to the carbon fiber–reinforced plastic panels for Structural health monitoring approaches. Two carbon fiber–reinforced plastic panels subjected to damage and Repair coincide with typical aircraft Repair procedures found in the aircraft Structural Repair Manual. The panels were simulated with 30 mm diameter of partial and full penetration damages using a diamond-coated router. The data (50 observations) were captured for the undamaged, damaged, and Repaired conditions by placing lead zirconate titanate smart sensors at 100 mm across the damaged and Repaired structures. A time-based data response was captured for post analysis during the interrogation on the structure at each condition. The raw data were captured in a Lamb waveform, and the interested features were extracted using Morlet wavelet analysis to evaluate the Condition Structural Index and Amplitude-Based Assessment for each condition retrieved from the Gaussian-like distribution. The results were evaluated using the principal component analysis technique in order to distinguish the characteristic of the undamaged, damaged, and Repaired conditions. The results showed that in all cases considered, it was possible to distinguish the conditions of undamaged, damaged, and Repaired states with promising accuracy and repeatability of the data.
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A condition Structural index (CSI) using principal component analysis (PCA) for normal, damage and Repair conditions of CFRP laminate
2012Co-Authors: Khairul Dahri Mohd Aris, Mohd Sapuan Salit, Faizal Mustapha, Dayang Laila Abang Abdul MajidAbstract:The paper deals with data reduction technique by using the principle component analysis (PCA) applied to the carbon fiber reinforced plastic (CFRP) panels for Structural health monitoring study. Two CFRP panels were subjected to damage and Repair coincide with typical aircraft Structural Repair Manual (SRM). Data was taken at normal/ undamaged, damaged and Repaired condition by placing PZT smart sensors at predetermined distanced across the damaged and Repaired structure. A time-based data response was captured for post analysis during the interrogation on the structure at each condition. The raw data was captured in a Lamb wave form and only the interested intervals were selected by using Morlet wavelet analysis to evaluate the Condition Structural Index (CI) and Amplitude Based Assessment (ABA) for each conditions. The results were evaluated by using the PCA technique in order to distinguish the characteristic of the normal, damage and Repair conditions. The results showed that in all cases considered, it was possible to distinguish the conditions of normal, damaged and Repaired states with promising accuracy and repeatability of the data.
Khairul Dahri Mohd Aris - One of the best experts on this subject based on the ideXlab platform.
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condition Structural index using principal component analysis for undamaged damage and Repair conditions of carbon fiber reinforced plastic laminate
Journal of Intelligent Material Systems and Structures, 2014Co-Authors: Khairul Dahri Mohd Aris, Mohd Sapuan Salit, Faizal Mustapha, Dayang Laila Abang Abdul MajidAbstract:This article deals with the data reduction technique using the principal component analysis applied to the carbon fiber–reinforced plastic panels for Structural health monitoring approaches. Two carbon fiber–reinforced plastic panels subjected to damage and Repair coincide with typical aircraft Repair procedures found in the aircraft Structural Repair Manual. The panels were simulated with 30 mm diameter of partial and full penetration damages using a diamond-coated router. The data (50 observations) were captured for the undamaged, damaged, and Repaired conditions by placing lead zirconate titanate smart sensors at 100 mm across the damaged and Repaired structures. A time-based data response was captured for post analysis during the interrogation on the structure at each condition. The raw data were captured in a Lamb waveform, and the interested features were extracted using Morlet wavelet analysis to evaluate the Condition Structural Index and Amplitude-Based Assessment for each condition retrieved from the Gaussian-like distribution. The results were evaluated using the principal component analysis technique in order to distinguish the characteristic of the undamaged, damaged, and Repaired conditions. The results showed that in all cases considered, it was possible to distinguish the conditions of undamaged, damaged, and Repaired states with promising accuracy and repeatability of the data.
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Condition Structural Index using Principal Component Analysis for undamaged, damage and Repair conditions of carbon fiber–reinforced plastic laminate
Journal of Intelligent Material Systems and Structures, 2013Co-Authors: Khairul Dahri Mohd Aris, Mohd Sapuan Salit, Faizal Mustapha, Dayang Laila Abang Abdul MajidAbstract:This article deals with the data reduction technique using the principal component analysis applied to the carbon fiber–reinforced plastic panels for Structural health monitoring approaches. Two carbon fiber–reinforced plastic panels subjected to damage and Repair coincide with typical aircraft Repair procedures found in the aircraft Structural Repair Manual. The panels were simulated with 30 mm diameter of partial and full penetration damages using a diamond-coated router. The data (50 observations) were captured for the undamaged, damaged, and Repaired conditions by placing lead zirconate titanate smart sensors at 100 mm across the damaged and Repaired structures. A time-based data response was captured for post analysis during the interrogation on the structure at each condition. The raw data were captured in a Lamb waveform, and the interested features were extracted using Morlet wavelet analysis to evaluate the Condition Structural Index and Amplitude-Based Assessment for each condition retrieved from the Gaussian-like distribution. The results were evaluated using the principal component analysis technique in order to distinguish the characteristic of the undamaged, damaged, and Repaired conditions. The results showed that in all cases considered, it was possible to distinguish the conditions of undamaged, damaged, and Repaired states with promising accuracy and repeatability of the data.
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A condition Structural index (CSI) using principal component analysis (PCA) for normal, damage and Repair conditions of CFRP laminate
2012Co-Authors: Khairul Dahri Mohd Aris, Mohd Sapuan Salit, Faizal Mustapha, Dayang Laila Abang Abdul MajidAbstract:The paper deals with data reduction technique by using the principle component analysis (PCA) applied to the carbon fiber reinforced plastic (CFRP) panels for Structural health monitoring study. Two CFRP panels were subjected to damage and Repair coincide with typical aircraft Structural Repair Manual (SRM). Data was taken at normal/ undamaged, damaged and Repaired condition by placing PZT smart sensors at predetermined distanced across the damaged and Repaired structure. A time-based data response was captured for post analysis during the interrogation on the structure at each condition. The raw data was captured in a Lamb wave form and only the interested intervals were selected by using Morlet wavelet analysis to evaluate the Condition Structural Index (CI) and Amplitude Based Assessment (ABA) for each conditions. The results were evaluated by using the PCA technique in order to distinguish the characteristic of the normal, damage and Repair conditions. The results showed that in all cases considered, it was possible to distinguish the conditions of normal, damaged and Repaired states with promising accuracy and repeatability of the data.
Faizal Mustapha - One of the best experts on this subject based on the ideXlab platform.
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Fabrication Technique for Bio-Composite Patch Repair on Laminated Structures of CFRP Plate
Applied Mechanics and Materials, 2014Co-Authors: M. K. H. Muda, Faizal Mustapha, K.d. Mohd Aris, Mohamed Thariq Hameed SultanAbstract:Laminated structures are assembled so that the fibre orientation provides most of desired mechanical properties and the matrix largely determines the environmental performance. Composites laminate structures are used in a wide range of applications in aerospace, marine, automotive, surface transport and sports equipment markets. Damage to composite components is not always visible to the naked eye and the extent of damage is best determined for Structural components by suitable Non Destructive Test (NDT) methods. Alternatively the damaged areas can be located by simply tapping the composite surface and listening to the sound. The damaged areas give a dull response to the tapping, and the boundary between the good and damaged composite can easily be mapped to identify the area for Repair. Awareness of and inspection for composite damage should be included in the regular maintenance schedules for composite structures. Particular attention would be made to areas which are more prone to damage. The Repair can be done by using composite itself or bio-composite. Bio-composite is a reinforcement of natural fibre such as plant and a material that formed by matrix or resin. Then Repairs to aircraft structures are controlled and should be carried out according to the Aircraft Structural Repair Manual (SRM). For other applications the Repaired components would normally be expected to meet the original specifications and mechanical performance requirements. This paper presents the fabrication technique including patch Repair by using bio-composite which is kenaf and its aim to give a general approach to composite fabrication on patch Repair in all applications. Through the described approach, the life of the structure is expanded and met the properties requirements such as low cost, fairly good mechanical properties, high specific strength, non-abrasive, eco-friendly and bio-degradability characteristics.
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condition Structural index using principal component analysis for undamaged damage and Repair conditions of carbon fiber reinforced plastic laminate
Journal of Intelligent Material Systems and Structures, 2014Co-Authors: Khairul Dahri Mohd Aris, Mohd Sapuan Salit, Faizal Mustapha, Dayang Laila Abang Abdul MajidAbstract:This article deals with the data reduction technique using the principal component analysis applied to the carbon fiber–reinforced plastic panels for Structural health monitoring approaches. Two carbon fiber–reinforced plastic panels subjected to damage and Repair coincide with typical aircraft Repair procedures found in the aircraft Structural Repair Manual. The panels were simulated with 30 mm diameter of partial and full penetration damages using a diamond-coated router. The data (50 observations) were captured for the undamaged, damaged, and Repaired conditions by placing lead zirconate titanate smart sensors at 100 mm across the damaged and Repaired structures. A time-based data response was captured for post analysis during the interrogation on the structure at each condition. The raw data were captured in a Lamb waveform, and the interested features were extracted using Morlet wavelet analysis to evaluate the Condition Structural Index and Amplitude-Based Assessment for each condition retrieved from the Gaussian-like distribution. The results were evaluated using the principal component analysis technique in order to distinguish the characteristic of the undamaged, damaged, and Repaired conditions. The results showed that in all cases considered, it was possible to distinguish the conditions of undamaged, damaged, and Repaired states with promising accuracy and repeatability of the data.
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Condition Structural Index using Principal Component Analysis for undamaged, damage and Repair conditions of carbon fiber–reinforced plastic laminate
Journal of Intelligent Material Systems and Structures, 2013Co-Authors: Khairul Dahri Mohd Aris, Mohd Sapuan Salit, Faizal Mustapha, Dayang Laila Abang Abdul MajidAbstract:This article deals with the data reduction technique using the principal component analysis applied to the carbon fiber–reinforced plastic panels for Structural health monitoring approaches. Two carbon fiber–reinforced plastic panels subjected to damage and Repair coincide with typical aircraft Repair procedures found in the aircraft Structural Repair Manual. The panels were simulated with 30 mm diameter of partial and full penetration damages using a diamond-coated router. The data (50 observations) were captured for the undamaged, damaged, and Repaired conditions by placing lead zirconate titanate smart sensors at 100 mm across the damaged and Repaired structures. A time-based data response was captured for post analysis during the interrogation on the structure at each condition. The raw data were captured in a Lamb waveform, and the interested features were extracted using Morlet wavelet analysis to evaluate the Condition Structural Index and Amplitude-Based Assessment for each condition retrieved from the Gaussian-like distribution. The results were evaluated using the principal component analysis technique in order to distinguish the characteristic of the undamaged, damaged, and Repaired conditions. The results showed that in all cases considered, it was possible to distinguish the conditions of undamaged, damaged, and Repaired states with promising accuracy and repeatability of the data.
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A condition Structural index (CSI) using principal component analysis (PCA) for normal, damage and Repair conditions of CFRP laminate
2012Co-Authors: Khairul Dahri Mohd Aris, Mohd Sapuan Salit, Faizal Mustapha, Dayang Laila Abang Abdul MajidAbstract:The paper deals with data reduction technique by using the principle component analysis (PCA) applied to the carbon fiber reinforced plastic (CFRP) panels for Structural health monitoring study. Two CFRP panels were subjected to damage and Repair coincide with typical aircraft Structural Repair Manual (SRM). Data was taken at normal/ undamaged, damaged and Repaired condition by placing PZT smart sensors at predetermined distanced across the damaged and Repaired structure. A time-based data response was captured for post analysis during the interrogation on the structure at each condition. The raw data was captured in a Lamb wave form and only the interested intervals were selected by using Morlet wavelet analysis to evaluate the Condition Structural Index (CI) and Amplitude Based Assessment (ABA) for each conditions. The results were evaluated by using the PCA technique in order to distinguish the characteristic of the normal, damage and Repair conditions. The results showed that in all cases considered, it was possible to distinguish the conditions of normal, damaged and Repaired states with promising accuracy and repeatability of the data.
Mohd Sapuan Salit - One of the best experts on this subject based on the ideXlab platform.
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condition Structural index using principal component analysis for undamaged damage and Repair conditions of carbon fiber reinforced plastic laminate
Journal of Intelligent Material Systems and Structures, 2014Co-Authors: Khairul Dahri Mohd Aris, Mohd Sapuan Salit, Faizal Mustapha, Dayang Laila Abang Abdul MajidAbstract:This article deals with the data reduction technique using the principal component analysis applied to the carbon fiber–reinforced plastic panels for Structural health monitoring approaches. Two carbon fiber–reinforced plastic panels subjected to damage and Repair coincide with typical aircraft Repair procedures found in the aircraft Structural Repair Manual. The panels were simulated with 30 mm diameter of partial and full penetration damages using a diamond-coated router. The data (50 observations) were captured for the undamaged, damaged, and Repaired conditions by placing lead zirconate titanate smart sensors at 100 mm across the damaged and Repaired structures. A time-based data response was captured for post analysis during the interrogation on the structure at each condition. The raw data were captured in a Lamb waveform, and the interested features were extracted using Morlet wavelet analysis to evaluate the Condition Structural Index and Amplitude-Based Assessment for each condition retrieved from the Gaussian-like distribution. The results were evaluated using the principal component analysis technique in order to distinguish the characteristic of the undamaged, damaged, and Repaired conditions. The results showed that in all cases considered, it was possible to distinguish the conditions of undamaged, damaged, and Repaired states with promising accuracy and repeatability of the data.
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Condition Structural Index using Principal Component Analysis for undamaged, damage and Repair conditions of carbon fiber–reinforced plastic laminate
Journal of Intelligent Material Systems and Structures, 2013Co-Authors: Khairul Dahri Mohd Aris, Mohd Sapuan Salit, Faizal Mustapha, Dayang Laila Abang Abdul MajidAbstract:This article deals with the data reduction technique using the principal component analysis applied to the carbon fiber–reinforced plastic panels for Structural health monitoring approaches. Two carbon fiber–reinforced plastic panels subjected to damage and Repair coincide with typical aircraft Repair procedures found in the aircraft Structural Repair Manual. The panels were simulated with 30 mm diameter of partial and full penetration damages using a diamond-coated router. The data (50 observations) were captured for the undamaged, damaged, and Repaired conditions by placing lead zirconate titanate smart sensors at 100 mm across the damaged and Repaired structures. A time-based data response was captured for post analysis during the interrogation on the structure at each condition. The raw data were captured in a Lamb waveform, and the interested features were extracted using Morlet wavelet analysis to evaluate the Condition Structural Index and Amplitude-Based Assessment for each condition retrieved from the Gaussian-like distribution. The results were evaluated using the principal component analysis technique in order to distinguish the characteristic of the undamaged, damaged, and Repaired conditions. The results showed that in all cases considered, it was possible to distinguish the conditions of undamaged, damaged, and Repaired states with promising accuracy and repeatability of the data.
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A condition Structural index (CSI) using principal component analysis (PCA) for normal, damage and Repair conditions of CFRP laminate
2012Co-Authors: Khairul Dahri Mohd Aris, Mohd Sapuan Salit, Faizal Mustapha, Dayang Laila Abang Abdul MajidAbstract:The paper deals with data reduction technique by using the principle component analysis (PCA) applied to the carbon fiber reinforced plastic (CFRP) panels for Structural health monitoring study. Two CFRP panels were subjected to damage and Repair coincide with typical aircraft Structural Repair Manual (SRM). Data was taken at normal/ undamaged, damaged and Repaired condition by placing PZT smart sensors at predetermined distanced across the damaged and Repaired structure. A time-based data response was captured for post analysis during the interrogation on the structure at each condition. The raw data was captured in a Lamb wave form and only the interested intervals were selected by using Morlet wavelet analysis to evaluate the Condition Structural Index (CI) and Amplitude Based Assessment (ABA) for each conditions. The results were evaluated by using the PCA technique in order to distinguish the characteristic of the normal, damage and Repair conditions. The results showed that in all cases considered, it was possible to distinguish the conditions of normal, damaged and Repaired states with promising accuracy and repeatability of the data.
Ramzyzan Ramly - One of the best experts on this subject based on the ideXlab platform.
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Stress analysis of riveted and bonded patch Repairs on a stiffened panel / Ramzyzan Ramly
2005Co-Authors: Ramzyzan RamlyAbstract:There are a few thousands commercial aircrafts operating today. Many of those aircrafts are considered old or aging and will experience damages whether little or large. Damages in aircraft structures are classified as negligible a~d intolerable. Since commercial aircrafts are constructed to be in Damage Tolerant Design (DTD), negligible damage is not threatening and the aircraft can still operate under some limitations. Intolerable damage however, should be Repaired to prevent growth of the damage and to maintain airworthiness of the aircraft. One of the damages that is covered in this research is a crack damage and the Repair on it. The damage location in this research is on the skin next to the top hat stringer section on a stiffened panel. The case study simulated the rear fuselage stiffened panel of a Boeing 737. Most damage Repair methods and procedures are prescribed in the Structural Repair Manual (SRM). The SRM provides details procedures of Repair using bolts and rivets. The damage case in this research is not part of the SRM. Eyen though extensive stress analysis has been done by the manufacturer before the Repair procedure is documented, however, there is no strength analysis reported in the SRM. This research conducted a stress analysis on the structure before damaged, after damaged, and after Repaired conditions, in which riveted patch was used in one case, and bonded patch in the other. Two methods of analyses were conducted namely finite element analysis using ANSYS software, and experimental method using strain gages and Universal Testing Machine. The stress distributions of all conditions were compared between the finite element and the experimental methods. In addition to the above, theoretical analysis was used to predict the static strength of the structure all four conditions. The static strengths of all conditions were compared between theoretical and experimental methods. It was expected that both Repair methods would restore the original strength of the structure. Based on the comparison between FEA and experimental results, there were agreements on the graph pattern. However, there were extreme values in the readings of the strain gages near the jigs or load application points. This was mainly due to the $etting of the jigs which produced local effect high stress area. Based on the static strength· analysis, it was found that the riveted patch Repair was weaker than the original condition by 15%. The bonded patch Repair failed at more than 20% less than the original strength. This was due to the limited resources of bonding Repair facilities which made the bonding process not properly done so that the patch· was not perfectly bonded to the skin.
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Stress analysis of a riveted Repair on a stiffened panel (aircraft stiffened skin structure) / Ramzyzan Ramly and Prof. Madya Dr. Ir. Wahyu Kuntjoro
2004Co-Authors: Ramzyzan Ramly, Wahyu KuntjoroAbstract:There are a few thousands commercial aircraft:s operating today. Many of those aircrafts are considered old or aging aircrafts. It is expected that all old or aging aircrafts will experience damages whether little or large. Damages in aircraft structures are classified as negligible and intolerable. Since commercial aircrafts are constructed to be in Damage Tolerant Design (DTD), negligible damage is not threatening and the aircraft can still operate under some limitations. Intolerable damage however, should be Repaired to prevent growth of the damage and to maintain airworthiness of the aircraft. One of the damages that will be covered in this research is crack damage and the Repair on it. The damage location in this research will be on the skin next to the stringer section. Most damage Repair methods and procedures are prescribed in the Structural Repair Manual (SRM). This research will conduct strength/stress analysis on the section before damaged, after damaged, and after Repaired conditions, using rivets. The analyses will be conducted using numerical method with Finite Element Analysis software called ANSYS, and experimental method using strain gauges and Universal Testing Machine. The results showed that the Repaired structure's strength is restored. Both methods show agreement in the results pattern. However, there are some irregularities in the initial part of the results. This is mainly due to the mounting of the specimen during testing.
