Clamp-Force Estimation for a Brake-by-Wire System: A Sensor-Fusion Approach

The elimination of a clamp-force sensor from brake-by-wire system designs is strongly demanded due to implementation difficulties and cost issues. In this paper, a new method is presented to estimate the clamp force based on other sensory information. This estimator fuses the outputs of two models to optimize the root-mean-square error (RMSE) of estimation. Experimental results show that the estimator can accurately track the true clamp force for high-speed cases as demanded by the antilock braking system controls. A training strategy has been used to ensure that the estimator can successfully adapt to parameter variations associated with wear. This paper is concluded with a discussion on the reliability of the developed clamp-force estimator.     

Robust Optic Flow Computation

This paper formulates the optic flow problem as a set of over-determined simultaneous linear equations. It then introduces and studies two new robust optic flow methods. The first technique is based on using the Least Median of Squares (LMedS) to detect the outliers. Then, the inlier group is solved using the least square technique. The second method employs a new robust statistical method named the Least Median of Squares Orthogonal Distances (LMSOD) to identify the outliers and then uses total least squares to solve the optic flow problem. The performance of both methods are studied by experiments on synthetic and real image sequences. These methods outperform other published methods both in accuracy and robustness.     

Finite Sample Bias of Robust Estimators in Segmentation of Closely Spaced Structures: A Comparative Study

This paper presents the design and implementation of a new comparative analytical framework for studying the usability of modern high breakdown robust estimators. The emphasis is on finding the intrinsic limits, in terms of size and relative spatial accuracy, of such techniques in solving the emerging challenges of the segmentation of fine structures. A minimum threshold for the distance between separable structures is shown to depend mainly on the scale estimation error. A scale invariant performance measure is introduced to quantify the finite sample bias of the scale estimate of a robust estimator and the measure is evaluated for some state-of-the-art high breakdown robust estimators using datasets containing at least two close but distinct structures with varying distances and inlier ratios. The results show that the new generation of density-based robust estimators (such as pbM-estimator and TSSE) have a poorer performance in problems with datasets containing only a small number of samples in each structure compared with ones based on direct processing of the residuals (such as MSSE). An important message of this paper is that an estimator that performs best in some circumstances, may not be competitive in others: particularly performance on data structures that are relatively large and/or well-separated vs closely spaced fine structures.     

Nondestructive quantitative characterisation of material phases in metal additive manufacturing using multi-energy synchrotron X-rays microtomography

The International Journal of Advanced Manufacturing Technology - Metal additive manufacturing (MAM) has found emerging application in the aerospace, biomedical and defence industries. However, the...     

Real-Time Clamp Force Measurement in Electromechanical Brake Calipers

In brake-by-wire systems, central controllers require accurate information about the clamp force between the brake pad and the disc as a function of pad displacement, which is usually denoted as the characteristic curve of the caliper. Due to aging, temperature, and other environmental variations, caliper characteristic curves vary with time. Therefore, automatic caliper calibration in real-time is vital for high-performance braking action and vehicle safety. Due to memory and processing-power limitations, the calibration technique should be memory efficient and of low computational complexity. In a typical electromechanical-braking-system design, clamp force measurement variations with actuator displacement is hysteretic. This paper introduces a simple and memory-efficient real-time calibration technique in which a clamp-force model is fitted to the data samples around each hysteresis cycle. The model includes a Maxwell-slip model for the hysteresis caused by friction. Experimental results from the data recorded in various temperatures show that the proposed technique results in clamp force measurements with less than 0.7% error over the range of clamp-force variations. It is also shown that, by using these measurements, the characteristic curve can be accurately calibrated in real-time.     

Estimating clamp force for brake-by-wire systems: Thermal considerations

The use of a stiffness curve, otherwise known as the characteristic curve, to estimate clamp force for a brake-by-wire system has been the subject of past research. The requirement to estimate clamp force arises from trying to make the conventional use of a clamp force sensor a redundant component and thereby reduce costs. Previous uses of the characteristic curve do not effectively model parameter variations in response to heating effects. This paper presents foundations for a new approach to model the changes in characteristic curve parameter values under the influence of heating. The new approach centers on predicting pad temperatures and using this data to appropriately adjust characteristic curve parameter values. Two temperature sensors are required to be employed in this new approach. These additional sensors will not have a considerable impact towards the cost savings created by omitting a clamp force sensor. Finally experimental verifications are provided as well as recommendations for further research.     

Aerial tracking of elongated objects in rural environments

In this paper, a new approach to finding and tracking various land cover boundaries such as rivers, agricultural fields, channels and roads for use in visual navigation system of an unmanned aerial vehicle is presented. We use a combination of statistical estimation and optimization techniques for extraction of dominant boundaries in noisy aerial images. A set of perceptual grouping restrictions is used to connect the acquired piecewise boundaries and to find the heading direction of the main boundary. The results are further refined by applying a set of texture and colour cues and eliminating any false hypothesis. To reduce the computation requirements, another approach based on sampled colour values of different land covers is also investigated. Colour characteristics of a set of manually selected windows are compared to select the best attributes needed for discrimination between different land covers in various (natural) lighting conditions. Each frame is then partially scanned and desired environmental features are extracted and classified. The results show that the proposed technique meets the minimum speed and accuracy requirement of aforementioned application and outperforms single-feature object tracking algorithms.

Range image segmentation using surface selection criterion.

In this paper, we address the problem of recovering the true underlying model of a surface while performing the segmentation. First, and in order to solve the model selection problem, we introduce a novel criterion, which is based on minimising strain energy of fitted surfaces. We then evaluate its performance and compare it with many other existing model selection techniques. Using this criterion, we then present a robust range data segmentation algorithm capable of segmenting complex objects with planar and curved surfaces. The presented algorithm simultaneously identifies the type (order and geometric shape) of each surface and separates all the points that are part of that surface. This paper includes the segmentation results of a large collection of range images obtained from objects with planar and curved surfaces. The resulting segmentation algorithm successfully segments various possible types of curved objects. More importantly, the new technique is capable of detecting the association between separated parts of a surface, which has the same Cartesian equation while segmenting a scene. This aspect is very useful in some industrial applications of range data analysis.