Real-Time Riser Fatigue Monitoring Routine: Architecture, Data and Results

2013 ◽  
Author(s):  
Scot McNeill ◽  
Puneet Agarwal ◽  
Dan Kluk ◽  
Kenneth Bhalla ◽  
Tomokazu Saruhashi ◽  
...  
Keyword(s):  
Real Time ◽  
Fatigue Damage ◽  
Water Depth ◽  
Angular Rate ◽  
Measured Data ◽  
Automated System ◽  
Time Data ◽  
Joint Rotation ◽  
Computational Environment ◽  
Fatigue Monitoring

Recently, the Modal Decomposition and Reconstruction (MDR) algorithm was developed to accurately estimate fatigue damage in marine risers based on measured acceleration and angular rates at several locations. The greatest benefit for drilling risers can be derived by incorporating the method in an online, fully automated system. In this way, fatigue damage estimates are available to the crew on the rig in real-time for risk quantification and mitigation. To this end, the MDR routine was implemented for online assessment of fatigue damage along the entire riser from acceleration and angular rate measurements at typically 5–10 elevations. This paper discusses the architecture, highlights some measured data and provides results for modes, stress and fatigue damage rate for the Chikyu drilling vessel during two scientific drilling campaigns. These campaigns occurred at the Shimokita site (1180-meter water depth) and the Nankai trough site (1939-meter water depth). To the authors’ knowledge, real-time fatigue monitoring of the entire riser has not been accomplished previously. Robust incorporation of the MDR algorithm into an online computational environment is detailed, including incorporation of top tension and mud weight data from the rig, detection and removal of data errors, and streamlined flow of the data through the computational modules. Subsequently, it is shown by example how the measured accelerations and angular rates are used to determine excited modes, participating modes, stress distribution and fatigue damage along the entire Chikyu drilling riser in an online setting. The technology highlighted advances riser integrity management two steps forward by first using measured data at 5–10 locations and the MDR algorithm to reconstruct stress and fatigue damage along the entire riser, and secondly integrating this approach into a fully automated, real-time computational environment. As a result, drilling engineers are empowered with a tool that provides real-time data on the integrity of the drilling riser, enabling informed decisions to be made in adverse current or wave conditions. Measured data also serves as a benchmark for analytical model calibration activities, reducing conservatism in stress and fatigue in future deployments. Furthermore, cumulative fatigue damage can be tracked in each riser joint, enabling more effective joint rotation and inspection programs.

Efficient Modal Decomposition and Reconstruction of Riser Response due to VIV

2011 ◽  
Author(s):  
S. I. McNeill ◽  
P. Agarwal
Keyword(s):  
Fatigue Damage ◽  
Traveling Wave ◽  
Angular Rate ◽  
Normal Modes ◽  
Structural Response ◽  
Measured Data ◽  
Vibration Monitoring ◽  
Wave Number ◽  
Modal Decomposition ◽  
Basis Vectors

Vortex-Induced-Vibrations (VIV) due to ocean currents can consume a sizable portion of the allotted fatigue life of marine risers. Vibration monitoring and concurrent estimation of fatigue damage due to VIV can significantly enhance the safe and reliable operation of risers. To this end, riser response can be characterized by using sensors (e.g. accelerometers and/or angular rate sensors) to measure the motion of the riser at a few locations. Fatigue damage can be predicted along the entire length of riser from measured data using the method of modal decomposition and reconstruction. In this method the structural response of interest, such as stress and fatigue damage, is expressed by modal superposition, where the modal weights are estimated using measured data and analytical modeshapes. However the accuracy of this method declines as the sensor density (number of sensors per unit riser length) decreases, especially when the riser vibrates in high-order modes and exhibits traveling wave behavior. In this paper, an efficient frequency-domain methodology allowing for accurate reconstruction of the riser response along the entire riser using a limited number of sensors is proposed. We first identify the excited VIV modes (natural frequency and modeshape) using principal vectors of the cross spectral density. Modal decomposition and reconstruction is performed separately for each VIV band surrounding each excited mode. This allows us to use several (as many as the number of sensors) participating modes in each band, and thus improve the accuracy. Since the stress distribution is sensitive to the chosen set of participating modes, we optimize over several candidate sets, selecting the set of modes that result in the lowest prediction error. In order to improve the reconstruction of complex modes, particularly traveling waves, the modeshapes can be augmented with additional basis vectors. The additional basis vectors are obtained by shifting the phase of the normal modes by 90 degrees at every wave number using the Hilbert transform. Though developed in the context of VIV, the method can be used to estimate fatigue damage due to vibrations regardless of the excitation mechanism. The methodology is demonstrated using the NDP (Norwegian Deepwater Program) test data on a 38 meter long slender riser, using data from eight accelerometers. Results show that the proposed algorithm can reconstruct stresses and fatigue damage accurately along the length of the riser in the presence of traveling wave behavior using relatively few sensors.

A Method for Determining Quasi-Static and Dynamic Riser Inclination Using Collocated Accelerometers and Angular Rate Sensors

2014 ◽  
Author(s):  
Scot McNeill ◽  
Paul Angehr ◽  
Dan Kluk ◽  
Tomokazu Saruhashi ◽  
Ikuo Sawada ◽  
...  
Keyword(s):  
Real Time ◽  
Monitoring System ◽  
Body Force ◽  
Angular Rate ◽  
Low Frequency ◽  
Monitoring Systems ◽  
Rate Data ◽  
Fatigue Monitoring ◽  
Inclination Angles ◽  
Force Components

A method is described for determining quasi-static and dynamic riser angles using measured data typically found in a riser fatigue monitoring system, specifically acceleration and angular rate data. Quasi-static riser inclination and orientation of the inclination plane are determined from the low frequency triaxial accelerations, containing measurement of the gravitational body force. Components of the gravitational body force along the accelerometer axes vary slowly with the riser quasi-static response. The slowly varying Euler angles are determined from the components of gravity along the three axes. Dynamic riser inclination along and transverse to the quasi-static inclination plane are determined by integration of the angular rates, followed by transformation into a coordinate system aligned with the quasi-static inclination plane. The quasi-static and dynamic inclination angles are combined to arrive at the time trace of riser inclination angles. Following implementation of the method in Matlab®, the procedure was validated and the program verified using laboratory test data. A double-gimbaled platform was constructed, on which were mounted a triaxial accelerometer, biaxial angular rate and biaxial inclinometer (reference sensor). A battery of static and dynamic tests was carried out on the platform. Machinists’ levels and angle gauges were used to set the inclination in the various tests. The angles derived from the acceleration and angular rate data were compared to those of the reference inclinometer. Angle estimates were shown to match the reference angles with negligible error. The method was then implemented into the real-time Riser Fatigue Monitoring System (RFMS) aboard the Chikyu drillship. The algorithm was run using data from an emergency disconnect event that occurred in November, 2012. Quasi-static riser inclination angles were quite large due to high currents near the sea surface. Dynamic riser inclination angles proved to be significant due to Vortex Induced Vibration of the lower portion of the riser that immediately followed the disconnect event. It is important to note that the method uses data that is typically already included in real-time riser monitoring systems. Therefore only a software update is required to provide real-time riser angle information. If the method is built into data processing routines for real-time riser monitoring systems, the need for additional instrumentation, such as inclinometers near flex joints, may be circumvented. On the other hand, if inclinometers already exist, the method serves as an independent source of riser angle information at several locations on the riser. The method can also be used to calculate riser and Blow out Preventer (BOP) stack angles from data recorded using stand-alone, battery-powered loggers.

Aerocraft Real-Time Measured Data Processing Method Based on Combined Filtering

2014 ◽  
Vol 716-717 ◽  
pp. 983-986
Author(s):  
Yan Li ◽  
Hua Jun Liu ◽  
Guang Lang Bian ◽  
Miao Hui Liu
Keyword(s):  
Data Processing ◽  
Real Time ◽  
Measured Data ◽  
Control Procedure ◽  
Time Data ◽  
The Real ◽  
Data Processing Method ◽  
Real Time Data ◽  
Processing Accuracy ◽  
Real Time Data Processing

To solve the problems that resulted from using a certain filtering method alone to process the real-time data measured on aerocraft, a new method combined filter and Savitzky-Golay smoothing filter is proposed to process the real-time measuring data, which could classify and segment the measured data of aerocraft trajectory according to its priority and time domain. It could provide useful principle and control procedure of combined filters on different conditions to improve the filter efficiency, and the combined filtering results meet the needs of aerocraft real-time data processing accuracy in different measured sections.

Comparison of Real-Time Measured and Predicted Wellhead Fatigue Performance in a Deepwater Drilling Operation

2015 ◽  
Author(s):  
James Mackenzie ◽  
Neil Murdoch ◽  
Stuart Killbourn
Keyword(s):  
Real Time ◽  
Monitoring System ◽  
Fatigue Damage ◽  
Angular Rate ◽  
Fe Analysis ◽  
Processing Unit ◽  
Real Time Monitoring ◽  
Drilling Operation ◽  
Motion Data ◽  
Vessel Motion

This paper discusses the use of a real-time monitoring system to track wave driven fatigue damage at critical locations in a subsea well during a 290-day drilling operation in the Mediterranean Sea. Real-time monitoring was employed due to up-front finite element (FE) analysis predicting fatigue damage rates of sufficient magnitude that the required safety factor would not be met. LMRP/BOP motions were recorded using two subsea monitoring units (each containing accelerometers and angular rate sensors). These were installed on the LMRP and above the lower flex joint. The accelerometer signals were used to deduce the static inclination of the well and the angular rate signals the dynamic inclination due to vessel motion and wave loading on the riser. Data was transmitted in real-time to a central processing unit on board the vessel. This converted the motion data into fatigue damage accumulation using non-linear transfer functions derived from the FE model. The damage was displayed in a simplified format for use in decision-making. The recorded data revealed the motions of the LMRP/BOP and hence the damage rates in the well to be considerably less than predicted by the FE analysis. The damage rates derived from the monitoring system therefore served as a continuously updating demonstration that an acceptable margin of safety against suffering a fatigue failure was being maintained thus permitting drilling to proceed safely. A subsequent benchmarking study which additionally involved processing of recorded vessel motion data, current data and seastate data was undertaken to identify possible reasons for the differences between the predicted and measured LMRP/BOP motions. This showed that conservative assumptions made on the soil stiffness (due to limited availability of data), differences between the predicted and measured riser natural periods and differences between the predicted and measured vessel motions all contributed to the LMRP/BOP motions and hence the damage rates predicted by the up-front FE analysis being larger than measured in the field. The systematic identification of the factors which contributed to the differences between the predicted and measured response is described in this paper. Areas where further work would be of value to help improve the reliability of up-front, analytically predicted fatigue damage rates are also discussed.

scholarly journals IoT Open-Source Architecture for the Maintenance of Building Facilities

2021 ◽  
Vol 11 (12) ◽  
pp. 5374
Author(s):  
Valentina Villa ◽  
Berardo Naticchia ◽  
Giulia Bruno ◽  
Khurshid Aliev ◽  
Paolo Piantanida ◽  
...  
Keyword(s):  
Open Source ◽  
Real Time ◽  
Preventive Maintenance ◽  
3D Visualization ◽  
Predictive Maintenance ◽  
Information Modeling ◽  
Automated System ◽  
Building Structures ◽  
Time Data ◽  
Time Operation

The introduction of the Internet of Things (IoT) in the construction industry is evolving facility maintenance (FM) towards predictive maintenance development. Predictive maintenance of building facilities requires continuously updated data on construction components to be acquired through integrated sensors. The main challenges in developing predictive maintenance tools for building facilities is IoT integration, IoT data visualization on the building 3D model and implementation of maintenance management system on the IoT and building information modeling (BIM). The current 3D building models do not fully interact with IoT building facilities data. Data integration in BIM is challenging. The research aims to integrate IoT alert systems with BIM models to monitor building facilities during the operational phase and to visualize building facilities’ conditions virtually. To provide efficient maintenance services for building facilities this research proposes an integration of a digital framework based on IoT and BIM platforms. Sensors applied in the building systems and IoT technology on a cloud platform with opensource tools and standards enable monitoring of real-time operation and detecting of different kinds of faults in case of malfunction or failure, therefore sending alerts to facility managers and operators. Proposed preventive maintenance methodology applied on a proof-of-concept heating, ventilation and air conditioning (HVAC) plant adopts open source IoT sensor networks. The results show that the integrated IoT and BIM dashboard framework and implemented building structures preventive maintenance methodology are applicable and promising. The automated system architecture of building facilities is intended to provide a reliable and practical tool for real-time data acquisition. Analysis and 3D visualization to support intelligent monitoring of the indoor condition in buildings will enable the facility managers to make faster and better decisions and to improve building facilities’ real time monitoring with fallouts on the maintenance timeliness.

Spectral Formulations for Vortex Induced Vibration Modal Decomposition and Reconstruction

2012 ◽  
Vol 134 (4) ◽  
Author(s):  
S. I. McNeill
Keyword(s):  
Fatigue Damage ◽  
Angular Rate ◽  
Computational Cost ◽  
Time History ◽  
Computational Effort ◽  
Measured Data ◽  
Scale Model ◽  
Mode Shapes ◽  
Modal Decomposition ◽  
Vortex Induced Vibration

Modal decomposition and reconstruction (MDR) of marine riser vortex induced vibration (VIV) is a technique where vibration is measured using accelerometers and/or angular rate sensors, the modal displacements are solved for and the stress and fatigue damage is reconstructed along the riser. Recent developments have greatly increased the accuracy and reliability of the method. However the computational burden is onerous due to stress time history reconstruction and rainflow cycle counting at every desired location along the riser. In addition, fully synchronous data are required to reconstruct the stress histories. Dirlik’s method for obtaining rainflow damage for Gaussian random stress using only spectral information (four spectral automoments) has proven to be quite accurate with a significant reduction in computational effort. In this paper two spectral formulations of MDR are introduced. The first method is applicable when all the measured data are synchronous. In this method, spectral cross moments of the modal displacements are solved from the spectral cross moments of the measured data using basis vectors consisting of normal mode shapes. The spectral automoments of stress are obtained from the modal displacement cross moments and analytical stress mode shapes. Dirlik’s method is then applied to obtain rainflow damage. The second method is a generalization of the first, where the measured data cross moments are only partially known. This method is applicable when measured data are partially synchronous or asynchronous. A numerical root-finding technique is employed to solve for the modal response cross moments. The method then proceeds in the same manner as the first. The spectral methods are applied to simulated VIV data of a full-scale deepwater riser and to Norwegian Deepwater Program (NDP) scale-model test data on a 38 m long slender riser. Comparisons of reconstructed fatigue damage versus simulated or measured damage indicate that the method is capable of estimating fatigue damage accurately for Gaussian VIV even when data are not fully synchronous. It is also shown that computational cost is greatly reduced.

Ambulatory Assessment

2009 ◽  
Vol 14 (2) ◽  
pp. 109-119 ◽  
Author(s):  
Ulrich W. Ebner-Priemer ◽  
Timothy J. Trull
Keyword(s):  
Real Time ◽  
Clinical Psychology ◽  
Real Life ◽  
Ambulatory Assessment ◽  
Computer Assisted ◽  
Affective Valence ◽  
Time Data ◽  
Physiological Processes ◽  
Context Specific ◽  
Questionnaire Studies

Convergent experimental data, autobiographical studies, and investigations on daily life have all demonstrated that gathering information retrospectively is a highly dubious methodology. Retrospection is subject to multiple systematic distortions (i.e., affective valence effect, mood congruent memory effect, duration neglect; peak end rule) as it is based on (often biased) storage and recollection of memories of the original experience or the behavior that are of interest. The method of choice to circumvent these biases is the use of electronic diaries to collect self-reported symptoms, behaviors, or physiological processes in real time. Different terms have been used for this kind of methodology: ambulatory assessment, ecological momentary assessment, experience sampling method, and real-time data capture. Even though the terms differ, they have in common the use of computer-assisted methodology to assess self-reported symptoms, behaviors, or physiological processes, while the participant undergoes normal daily activities. In this review we discuss the main features and advantages of ambulatory assessment regarding clinical psychology and psychiatry: (a) the use of realtime assessment to circumvent biased recollection, (b) assessment in real life to enhance generalizability, (c) repeated assessment to investigate within person processes, (d) multimodal assessment, including psychological, physiological and behavioral data, (e) the opportunity to assess and investigate context-specific relationships, and (f) the possibility of giving feedback in real time. Using prototypic examples from the literature of clinical psychology and psychiatry, we demonstrate that ambulatory assessment can answer specific research questions better than laboratory or questionnaire studies.

399-P: Nurse-Driven Intervention Using Real-Time Data to Improve Hypoglycemia Rates in a Respiratory Care Unit

Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 399-P
Author(s):  
ANN MARIE HASSE ◽  
RIFKA SCHULMAN ◽  
TORI CALDER
Keyword(s):  
Real Time ◽  
Respiratory Care ◽  
Time Data ◽  
Real Time Data
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