909 resultados para measurement error models


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Multi-frequency Eddy Current (EC) inspection with a transmit-receive probe (two horizontally offset coils) is used to monitor the Pressure Tube (PT) to Calandria Tube (CT) gap of CANDU® fuel channels. Accurate gap measurements are crucial to ensure fitness of service; however, variations in probe liftoff, PT electrical resistivity, and PT wall thickness can generate systematic measurement errors. Validated mathematical models of the EC probe are very useful for data interpretation, and may improve the gap measurement under inspection conditions where these parameters vary. As a first step, exact solutions for the electromagnetic response of a transmit-receive coil pair situated above two parallel plates separated by an air gap were developed. This model was validated against experimental data with flat-plate samples. Finite element method models revealed that this geometrical approximation could not accurately match experimental data with real tubes, so analytical solutions for the probe in a double-walled pipe (the CANDU® fuel channel geometry) were generated using the Second-Order Vector Potential (SOVP) formalism. All electromagnetic coupling coefficients arising from the probe, and the layered conductors were determined and substituted into Kirchhoff’s circuit equations for the calculation of the pickup coil signal. The flat-plate model was used as a basis for an Inverse Algorithm (IA) to simultaneously extract the relevant experimental parameters from EC data. The IA was validated over a large range of second layer plate resistivities (1.7 to 174 µΩ∙cm), plate wall thickness (~1 to 4.9 mm), probe liftoff (~2 mm to 8 mm), and plate-to plate gap (~0 mm to 13 mm). The IA achieved a relative error of less than 6% for the extracted FP resistivity and an accuracy of ±0.1 mm for the LO measurement. The IA was able to achieve a plate gap measurement with an accuracy of less than ±0.7 mm error over a ~2.4 mm to 7.5 mm probe liftoff and ±0.3 mm at nominal liftoff (2.42±0.05 mm), providing confidence in the general validity of the algorithm. This demonstrates the potential of using an analytical model to extract variable parameters that may affect the gap measurement accuracy.

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Much of the bridge stock on major transport links in North America and Europe was constructed in the 1950s and 1960s and has since deteriorated or is carrying loads far in excess of the original design loads. Structural Health Monitoring Systems (SHM) can provide valuable information on the bridge capacity but the application of such systems is currently limited by access and bridge type. This paper investigates the use of computer vision systems for SHM. A series of field tests have been carried out to test the accuracy of displacement measurements using contactless methods. A video image of each test was processed using a modified version of the optical flow tracking method to track displacement. These results have been validated with an established measurement method using linear variable differential transformers (LVDTs). The results obtained from the algorithm provided an accurate comparison with the validation measurements. The calculated displacements agree within 2% of the verified LVDT measurements, a number of post processing methods were then applied to attempt to reduce this error.

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Inverse simulations of musculoskeletal models computes the internal forces such as muscle and joint reaction forces, which are hard to measure, using the more easily measured motion and external forces as input data. Because of the difficulties of measuring muscle forces and joint reactions, simulations are hard to validate. One way of reducing errors for the simulations is to ensure that the mathematical problem is well-posed. This paper presents a study of regularity aspects for an inverse simulation method, often called forward dynamics or dynamical optimization, that takes into account both measurement errors and muscle dynamics. The simulation method is explained in detail. Regularity is examined for a test problem around the optimum using the approximated quadratic problem. The results shows improved rank by including a regularization term in the objective that handles the mechanical over-determinancy. Using the 3-element Hill muscle model the chosen regularization term is the norm of the activation. To make the problem full-rank only the excitation bounds should be included in the constraints. However, this results in small negative values of the activation which indicates that muscles are pushing and not pulling. Despite this unrealistic behavior the error maybe small enough to be accepted for specific applications. These results is a starting point start for achieving better results of inverse musculoskeletal simulations from a numerical point of view.

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In recent years, depth cameras have been widely utilized in camera tracking for augmented and mixed reality. Many of the studies focus on the methods that generate the reference model simultaneously with the tracking and allow operation in unprepared environments. However, methods that rely on predefined CAD models have their advantages. In such methods, the measurement errors are not accumulated to the model, they are tolerant to inaccurate initialization, and the tracking is always performed directly in reference model's coordinate system. In this paper, we present a method for tracking a depth camera with existing CAD models and the Iterative Closest Point (ICP) algorithm. In our approach, we render the CAD model using the latest pose estimate and construct a point cloud from the corresponding depth map. We construct another point cloud from currently captured depth frame, and find the incremental change in the camera pose by aligning the point clouds. We utilize a GPGPU-based implementation of the ICP which efficiently uses all the depth data in the process. The method runs in real-time, it is robust for outliers, and it does not require any preprocessing of the CAD models. We evaluated the approach using the Kinect depth sensor, and compared the results to a 2D edge-based method, to a depth-based SLAM method, and to the ground truth. The results show that the approach is more stable compared to the edge-based method and it suffers less from drift compared to the depth-based SLAM.

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Hybrid simulation is a technique that combines experimental and numerical testing and has been used for the last decades in the fields of aerospace, civil and mechanical engineering. During this time, most of the research has focused on developing algorithms and the necessary technology, including but not limited to, error minimisation techniques, phase lag compensation and faster hydraulic cylinders. However, one of the main shortcomings in hybrid simulation that has pre- vented its widespread use is the size of the numerical models and the effect that higher frequencies may have on the stability and accuracy of the simulation. The first chapter in this document provides an overview of the hybrid simulation method and the different hybrid simulation schemes, and the corresponding time integration algorithms, that are more commonly used in this field. The scope of this thesis is presented in more detail in chapter 2: a substructure algorithm, the Substep Force Feedback (Subfeed), is adapted in order to fulfil the necessary requirements in terms of speed. The effects of more complex models on the Subfeed are also studied in detail, and the improvements made are validated experimentally. Chapters 3 and 4 detail the methodologies that have been used in order to accomplish the objectives mentioned in the previous lines, listing the different cases of study and detailing the hardware and software used to experimentally validate them. The third chapter contains a brief introduction to a project, the DFG Subshake, whose data have been used as a starting point for the developments that are shown later in this thesis. The results obtained are presented in chapters 5 and 6, with the first of them focusing on purely numerical simulations while the second of them is more oriented towards a more practical application including experimental real-time hybrid simulation tests with large numerical models. Following the discussion of the developments in this thesis is a list of hardware and software requirements that have to be met in order to apply the methods described in this document, and they can be found in chapter 7. The last chapter, chapter 8, of this thesis focuses on conclusions and achievements extracted from the results, namely: the adaptation of the hybrid simulation algorithm Subfeed to be used in conjunction with large numerical models, the study of the effect of high frequencies on the substructure algorithm and experimental real-time hybrid simulation tests with vibrating subsystems using large numerical models and shake tables. A brief discussion of possible future research activities can be found in the concluding chapter.

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In the recent years, vibration-based structural damage identification has been subject of significant research in structural engineering. The basic idea of vibration-based methods is that damage induces mechanical properties changes that cause anomalies in the dynamic response of the structure, which measures allow to localize damage and its extension. Vibration measured data, such as frequencies and mode shapes, can be used in the Finite Element Model Updating in order to adjust structural parameters sensible at damage (e.g. Young’s Modulus). The novel aspect of this thesis is the introduction into the objective function of accurate measures of strains mode shapes, evaluated through FBG sensors. After a review of the relevant literature, the case of study, i.e. an irregular prestressed concrete beam destined for roofing of industrial structures, will be presented. The mathematical model was built through FE models, studying static and dynamic behaviour of the element. Another analytical model was developed, based on the ‘Ritz method’, in order to investigate the possible interaction between the RC beam and the steel supporting table used for testing. Experimental data, recorded through the contemporary use of different measurement techniques (optical fibers, accelerometers, LVDTs) were compared whit theoretical data, allowing to detect the best model, for which have been outlined the settings for the updating procedure.

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Physical exercise programmes are routinely prescribed in clinical practice to treat impairments, improve activity and participation in daily life because of their known physiological, health and psychological benefits (RCP, 2009). Progressive resistance exercise is a type of exercise prescribed specifically to improve skeletal muscle strength (Latham et al., 2004). The effectiveness of progressive resistance exercise varies considerably between studies and populations. This thesis focuses on how training parameters influence the delivery of progressive resistance exercise. In order to appropriately evaluate the influence of training parameters, this thesis argues the need to record training performance and the total work completed by participants as prescribed by training protocols. In the first study, participants were taken through a series of protocols differentiated by the intensity and volume of training. Training intensity was defined as a proportion of the mean peak torque achieved during maximal voluntary contractions and was set at 80% and 40% respectively of the MVC mean peak torque. Training volume was defined as the total external work achieved over the training period. Measures of training performance were developed to accurately report the intensity, repetitions and work completed during the training period. A second study evaluated training performance of the training protocols over repeated sessions. These protocols were then applied to 3 stroke survivors. Study 1 found sedentary participants could achieve a differentiated training intensity. Participants completing the high and low intensity protocols trained at 80% and 40% respectively of the MVC mean peak torque. The total work achieved in the high intensity low repetition protocol was lower than the total work achieved in the low intensity high repetition protocol. With repeated practice, study 2 found participants were able to improve in their ability to perform manoeuvres as shown by a reduction in the variation of the mean training intensity achieving total work as specified by the protocol to a lower margin of error. When these protocols were applied to 3 stroke survivors, they were able to achieve the specified training intensity but they were not able to achieve the total work as expected for the protocol. This is likely to be due to an inability in achieving a consistent force throughout the contraction. These results demonstrate evaluation of training characteristics and support the need to record and report training performance characteristics during progressive resistance exercise, including the total work achieved, in order to elucidate the influence of training parameters on progressive resistance exercise. The lack of accurate training performance may partly explain the inconsistencies between studies on optimal training parameters for progressive resistance exercise.

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We develop the a posteriori error estimation of interior penalty discontinuous Galerkin discretizations for H(curl)-elliptic problems that arise in eddy current models. Computable upper and lower bounds on the error measured in terms of a natural (mesh-dependent) energy norm are derived. The proposed a posteriori error estimator is validated by numerical experiments, illustrating its reliability and efficiency for a range of test problems.

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Over the past few years, the number of wireless networks users has been increasing. Until now, Radio-Frequency (RF) used to be the dominant technology. However, the electromagnetic spectrum in these region is being saturated, demanding for alternative wireless technologies. Recently, with the growing market of LED lighting, the Visible Light Communications has been drawing attentions from the research community. First, it is an eficient device for illumination. Second, because of its easy modulation and high bandwidth. Finally, it can combine illumination and communication in the same device, in other words, it allows to implement highly eficient wireless communication systems. One of the most important aspects in a communication system is its reliability when working in noisy channels. In these scenarios, the received data can be afected by errors. In order to proper system working, it is usually employed a Channel Encoder in the system. Its function is to code the data to be transmitted in order to increase system performance. It commonly uses ECC, which appends redundant information to the original data. At the receiver side, the redundant information is used to recover the erroneous data. This dissertation presents the implementation steps of a Channel Encoder for VLC. It was consider several techniques such as Reed-Solomon and Convolutional codes, Block and Convolutional Interleaving, CRC and Puncturing. A detailed analysis of each technique characteristics was made in order to choose the most appropriate ones. Simulink models were created in order to simulate how diferent codes behave in diferent scenarios. Later, the models were implemented in a FPGA and simulations were performed. Hardware co-simulations were also implemented to faster simulation results. At the end, diferent techniques were combined to create a complete Channel Encoder capable of detect and correct random and burst errors, due to the usage of a RS(255,213) code with a Block Interleaver. Furthermore, after the decoding process, the proposed system can identify uncorrectable errors in the decoded data due to the CRC-32 algorithm.