Condition Monitoring Parameters for Fault Diagnosis of Fixed Axis Gearbox: A Review

Condition monitoring of gearboxes which is considered as a key element of rotating machines ensures to continuously reduce and eliminate cost, unscheduled downtime and unexpected breakdowns. Although, a lot of work on condition monitoring and fault diagnosis of fixed-axis gearbox has been reported in the literature, however only a few have found their way to industrial applications. The ability of condition statistical indicators is to provide accurate and precise information about the health of various components at different levels of damage. In this paper, frequently used condition indicators are addressed domain-wise and their characteristics are stated. This paper presents the review of work to provide a wide and good reference for researchers to be utilized. The structure of a fixed-axis gearbox in addition to the unique behaviors and fault characteristics of fixed-axis gearbox has been recognized and represented. By extensively reviewing and categorizing important papers and articles, this paper is able to summarize the conditional monitoring indicators on basis of adopted methodologies. Lastly, open problems are stated and further research prospects pointed out.     

Dynamic vs. Oblivious Routing in Network Design

Consider the robust network design problem of finding a minimum cost network with enough capacity to route all traffic demand matrices in a given polytope. We investigate the impact of different routing models in this robust setting: in particular, we compare oblivious routing, where the routing between each terminal pair must be fixed in advance, to dynamic routing, where routings may depend arbitrarily on the current demand. Our main result is a construction that shows that the optimal cost of such a network based on oblivious routing (fractional or integral) may be a factor of Ω(log n) more than the cost required when using dynamic routing. This is true even in the important special case of the asymmetric hose model. This answers a question in (Chekuri, SIGACT News 38(3):106–128, 2007), and is tight up to constant factors. Our proof technique builds on a connection between expander graphs and robust design for single-sink traffic patterns (Chekuri et al., Networks 50(1):50–54, 2007).     

Designing a Controller for a Multi-Train Multi-Track System

The use of formal methods for analyzing and synthesizing a controller for a multi-train multi-track railway system is discussed. The research was motivated by a case study involving the Bay Area Rapid Transit (BART) system. The overall goal is to design a train acceleration control function that enables trains to be safely placed but also increases system throughput. The use of a modeling language for specifying safety properties and a control function is illustrated. The program transformation methodology supported in the HATS system is employed to generate an efficient implementation from a high-level specification of a controller. This implementation can then be used to simulate the controller behavior, thus further enhancing confidence in the design. Properties of optimization transformations can be verified using an rewrite-rule based induction theorem prover Rewrite Rule Laboratory (RRL).     

Dataflow Architectures for GALS

In Kahn process network (KPN), the processes (nodes) communicate by unbounded unidirectional FIFO channels (arcs), with the property of non-blocking writes and blocking reads on the channels. KPN provides a semantic model of computation, where a computation can be expressed as a set of asynchronously communicating processes. However, the unbounded FIFO based asynchrony is not realizable in practice and hence requires refinement in real hardware. In this work, we start with KPN as the model of computation for GALS, and discuss how different GALS architectures can be realized. We borrow some ideas from existing dataflow architectures for our GALS designs.     

Using an induction prover for verifying arithmetic circuits

We show that existing theorem proving technology can be used effectively for mechanically verifying a family of arithmetic circuits. A theorem prover implementing: (i) a decision procedure for quantifier-free Presburger arithmetic with uninterpreted function symbols; (ii) conditional rewriting; and (iii) heuristics for carefully selecting induction schemes from terminating recursive function definitions; and (iv) well integrated with backtracking, can automatically verify number-theoretic properties of parameterized and generic adders, multipliers and division circuits. This is illustrated using our theorem prover Rewrite Rule Laboratory (RRL). To our knowledge, this is the first such demonstration of the capabilities of a theorem prover mechanizing induction. The above features of RRL are briefly discussed using illustrations from the verification of adder, multiplier and division circuits. Extensions to the prover likely to make it even more effective for hardware verification are discussed. Furthermore, it is believed that these results are scalable, and the proposed approach is likely to be effective for other arithmetic circuits as well.     

Towards locally and globally shape-aware reverse 3D modeling

The process of re-creating CAD models from actual physical parts, formally known as digital shape reconstruction (DSR) is an integral part of product development, especially in re-design. While, the majority of current methods used in DSR are surface-based, our overarching goal is to obtain direct parameterization of 3D meshes, by avoiding the actual segmentation of the mesh into different surfaces. As a first step towards reverse modeling physical parts, we extract (1) locally prominent cross-sections (PCS) from triangular meshes, and (2) organize and cluster them into sweep components, which form the basic building blocks of the re-created CAD model. In this paper, we introduce two new algorithms derived from Locally Linear Embedding (LLE) (Roweis and Sauk, 2000 [3]) and Affinity Propagation (AP) (Frey and Dueck, 2007 [4]) for organizing and clustering PCS. The LLE algorithm analyzes the cross-sections (PCS) using their geometric properties to build a global manifold in an embedded space. The AP algorithm, then clusters the local cross sections by propagating affinities among them in the embedded space to form different sweep components. We demonstrate the robustness and efficiency of the algorithms through many examples including actual laser-scanned (point cloud) mechanical parts.     

An Efficient Data Delivery Scheme in WBAN to Deal with Shadow Effect due to Postural Mobility

The body movement and change in posture exhibit high mobility in sensor nodes which causes shadowing in the Wireless Body Area Network (WBAN). Due to this, the connectivity between the nodes in WBAN is affected which further causes failure in data delivery. This article presents a MAC protocol in WBAN to deal with the problem of data delivery due to body movement and postural mobility. It uses an Improved Initial Centroid K-means clustering technique for classification of various human body postures followed by back propagation neural network as a classifier to recognize human body posture. This article proposes a posture aware dynamic data delivery (PA-DDD) protocol to deliver data dynamically. The PA-DDD protocol can be used under varying speed walking scenario. The simulation results show that it prolongs the network lifetime and is energy efficient.