Vibration Signature Analysis Using Artificial Neural Networks

Damage detection by measuring and analyzing vibration signals in a machine component is an established procedure in mechanical and aerospace engineering. This paper presents vibration signature analysis of steel bridge structures in a nonconventional way using artificial neural networks (ANN). Multilayer perceptrons have been adopted using the back-propagation algorithm for network training. The training patterns in terms of vibration signature are generated analytically for a moving load traveling on a trussed bridge structure at a constant speed to simulate the inspection vehicle. Using the finite-element technique, the moving forces are converted into stationary time-dependent force functions in order to generate vibration signals in the structure and the same is used to train the network. The performance of the trained networks is examined for their capability to detect damage from unknown signatures taken independently at one, three, and five nodes. It has been observed that the prediction using the trained network with single-node signature measurement at a suitability chosen location is even better than that of three-node and five-node measurement data.

Studies on age-hardening characteristics of ceramic particle/matrix interfaces in Al-Cu-SiCp composites using ultra low-load-dynamic microhardness measurements

Ultra low-load-dynamic microhardness testing facilitates the hardness measurements in a very low volume of the material and thus is suited for characterization of the interfaces in MMC's. This paper details the studies on age-hardening behavior of the interfaces in Al-Cu-5SiC(p) composites characterized using this technique. Results of hardness studies have been further substantiated by TEM observations. In the solution-treated condition, hardness is maximum at the particle/matrix interface and decreases with increasing distance from the interface. This could be attributed to the presence of maximum dislocation density at the interface which decreases with increasing distance from the interface. In the case of composites subjected to high temperature aging, hardening at the interface is found to be faster than the bulk matrix and the aging kinetics becomes progressively slower with increasing distance from the interface. This is attributed to the dislocation density gradient at the interface, leading to enhanced nucleation and growth of precipitates at the interface compared to the bulk matrix. TEM observations reveal that the sizes of the precipitates decrease with increasing distance from the interface and thus confirms the retardation in aging kinetics with increasing distance from the interface.

Modelling electricity demand with representative load curves

Models for electricity planning require inclusion of demand. Depending on the type of planning, the demand is usually represented as an annual demand for electricity (GWh), a peak demand (MW) or in the form of annual load-duration curves. The demand for electricity varies with the seasons, economic activities, etc. Existing schemes do not capture the dynamics of demand variations that are important for planning. For this purpose, we introduce the concept of representative load curves (RLCs). Advantages of RLCs are demonstrated in a case study for the state of Karnataka in India. Multiple discriminant analysis is used to cluster the 365 daily load curves for 1993-94 into nine RLCs. Further analyses of these RLCs help to identify important factors, namely, seasonal, industrial, agricultural, and residential (water heating and air-cooling) demand variations besides rationing by the utility. (C) 1999 Elsevier Science Ltd. All rights reserved.

On Training and Training Voids for Receive Antenna Subset Selection in Time-Varying Channels

Antenna selection (AS) provides most of the benefits of multiple-antenna systems at drastically reduced hardware costs. In receive AS, the receiver connects a dynamically selected subset of N available antennas to the L available RF chains. The "best" subset to be used for data reception is determined by means of channel estimates acquired using training sequences. Due to the nature of AS, the channel estimates at different antennas are obtained from different transmissions of the pilot sequence, and are, thus, outdated by different amounts in a time-varying channel. We show that a linear weighting of the estimates is optimum for the subset selection process, where the weights are related to the temporal correlation of the channel variations. When L is not an integer divisor of N, we highlight a new issue of "training voids", in which the last pilot transmission is not fully exploited by the receiver. We present a "void-filling" method for fully exploiting these voids, which essentially provides more accurate training for some antennas, and derive the optimal subset selection rule for any void-filling method. We also derive new closed-form equations for the performance of receive AS with optimal subset selection.

Profile-Based Load Scheduling in Wireless Energy Harvesting Sensors for Data Rate Maximization

In this paper, power management algorithms for energy harvesting sensors (EHS) that operate purely based on energy harvested from the environment are proposed. To maintain energy neutrality, EHS nodes schedule their utilization of the harvested power so as to save/draw energy into/from an inefficient battery during peak/low energy harvesting periods, respectively. Under this constraint, one of the key system design goals is to transmit as much data as possible given the energy harvesting profile. For implementational simplicity, it is assumed that the EHS transmits at a constant data rate with power control, when the channel is sufficiently good. By converting the data rate maximization problem into a convex optimization problem, the optimal load scheduling (power management) algorithm that maximizes the average data rate subject to energy neutrality is derived. Also, the energy storage requirements on the battery for implementing the proposed algorithm are calculated. Further, robust schemes that account for the insufficiency of battery storage capacity, or errors in the prediction of the harvested power are proposed. The superior performance of the proposed algorithms over conventional scheduling schemes are demonstrated through computations using numerical data from solar energy harvesting databases.

Relay Load Balancing in Queued Cooperative Wireless Networks with Rateless Codes

Relay selection combined with buffering of packets of relays can substantially increase the throughput of a cooperative network that uses rateless codes. However, buffering also increases the end-to-end delays due to the additional queuing delays at the relay nodes. In this paper we propose a novel method that exploits a unique property of rateless codes that enables a receiver to decode a packet from non-contiguous and unordered portions of the received signal. In it, each relay, depending on its queue length, ignores its received coded bits with a given probability. We show that this substantially reduces the end-to-end delays while retaining almost all of the throughput gain achieved by buffering. In effect, the method increases the odds that the packet is first decoded by a relay with a smaller queue. Thus, the queuing load is balanced across the relays and traded off with transmission times. We derive explicit necessary and sufficient conditions for the stability of this system when the various channels undergo fading. Despite encountering analytically intractable G/GI/1 queues in our system, we also gain insights about the method by analyzing a similar system with a simpler model for the relay-to-destination transmission times.

Training-Embedded, Single-Symbol ML-Decodable, Distributed STBCs for Relay Networks

Recently, a special class of complex designs called Training-Embedded Complex Orthogonal Designs (TE-CODs) has been introduced to construct single-symbol Maximum Likelihood decodable (SSD) distributed space-time block codes (DSTBCs) for two-hop wireless relay networks using the amplify and forward protocol. However, to implement DSTBCs from square TE-CODs, the overhead due to the transmission of training symbols becomes prohibitively large as the number of relays increase. In this paper, we propose TE-Coordinate Interleaved Orthogonal Designs (TE-CIODs) to construct SSD DSTBCs. Exploiting the block diagonal structure of TE-CIODs, we show that the overhead due to the transmission of training symbols to implement DSTBCs from TE-CIODs is smaller than that for TE-CODs. We also show that DSTBCs from TE-CIODs offer higher rate than those from TE-CODs for identical number of relays while maintaining the SSD and full-diversity properties.

Application of an evolutionary fuzzy system for the estimation of workforce deployment and cross-training in an assembly environment

Owing to the increased customer demands for make-to-order products and smaller product life-cycles, today assembly lines are designed to ensure a quick switch-over from one product model to another for companies' survival in market place. The complexity associated with the decisions pertaining to the type of training and number of workers and their exposition to the different tasks especially in the current era of customized production is a serious problem that the managers and the HRD gurus are facing in industry. This paper aims to determine the amount of cross-training and dynamic deployment policy caused by workforce flexibility for a make-to-order assembly. The aforementioned issues have been dealt with by adopting the concept of evolutionary fuzzy system because of the linguistic nature of the attributes associated with product variety and task complexity. A fuzzy system-based methodology is proposed to determine the amount of cross-training and dynamic deployment policy. The proposed methodology is tested on 10 sample products of varying complexities and the results obtained are in line with the conclusions drawn by previous researchers.

Training and Voids in Receive Antenna Subset Selection in Time-Varying Channels

Receive antenna selection (AS) provides many benefits of multiple-antenna systems at drastically reduced hardware costs. In it, the receiver connects a dynamically selected subset of N available antennas to the L available RF chains. Due to the nature of AS, the channel estimates at different antennas, which are required to determine the best subset for data reception, are obtained from different transmissions of the pilot sequence. Consequently, they are outdated by different amounts in a time-varying channel. We show that a linear weighting of the estimates is necessary and optimum for the subset selection process, where the weights are related to the temporal correlation of the channel variations. When L is not an integer divisor of N , we highlight a new issue of ``training voids'', in which the last pilot transmission is not fully exploited by the receiver. We then present new ``void-filling'' methods that exploit these voids and greatly improve the performance of AS. The optimal subset selection rules with void-filling, in which different antennas turn out to have different numbers of estimates, are also explicitly characterized. Closed-form equations for the symbol error probability with and without void-filling are also developed.

Scheduling expression trees for delayed-load architectures

In this paper we consider the problem of scheduling expression trees on delayed-load architectures. The problem tackled here takes root from the one considered in [Proceedings of the ACM SIGPLAN '91 Conf. on Programming Language Design and Implementation, 1991. p. 256] in which the leaves of the expression trees all refer to memory locations. A generalization of this involves the situation in which the trees may contain register variables, with the registers being used only at the leaves. Solutions to this generalization are given in [ACM Trans. Prog. Lang. Syst. 17 (1995) 740, Microproc. Microprog. 40 (1994) 577]. This paper considers the most general case in which the registers are reusable. This problem is tackled in [Comput. Lang, 21 (1995) 49] which gives an approximate solution to the problem under certain assumptions about the contiguity of the evaluation order: Here we propose an optimal solution (which may involve even a non-contiguous evaluation of the tree). The schedule generated by the algorithm given in this paper is optimal in the sense that it is an interlock-free schedule which uses the minimum number of registers required. An extension to the algorithm incorporates spilling. The problem as stated in this paper is an instruction scheduling problem. However, the problem could also be rephrased as an operations research problem with a difference in terminology. (C) 2002 Elsevier Science B.V. All rights reserved.

Nonlinear Finite-Element Modeling of Batter Piles under Lateral Load

In this paper, a finite-element model is developed in which the nonlinear soil behavior is represented by a hyperbolic relation for static load condition and modified hyperbolic relation, which includes both degradation and gap for a cyclic load condition. Although batter piles are subjected to lateral load, the soil resistance is also governed by axial load, which is incorporated by considering the P-Δ moment and geometric stiffness matrix. By adopting the developed numerical model, static and cyclic load analyses are performed adopting an incremental-iterative procedure where the pile is idealized as beam elements and the soil as elastoplastic spring elements. The proposed numerical model is validated with published laboratory and field pile test results under both static and cyclic load conditions. This paper highlights the importance of the degradation factor and its influence on the soil resistance-displacement (p-y) curve, number of cycles of loading, and cyclic load response.

Starting scheme for load commutated inverter-fed wound field synchronous machine using an auxiliary low-power voltage source inverter

Conventional thyristor-based load commutated inverter (LCI)-fed wound field synchronous machine operates only above a minimum speed that is necessary to develop enough back emf to ensure commutation. The drive is started and brought up to a speed of around 10-15% by a complex `dc link current pulsing' technique. During this process, the drive have problems such as pulsating torque, insufficient average starting torque, longer starting time, etc. In this regard a simple starting and low-speed operation scheme, by employing an auxiliary low-power voltage source inverter (VSI) between the LCI and the machine terminals, is presented in this study. The drive is started and brought up to a low speed of around 15% using the VSI alone with field oriented control. The complete control is then smoothly and dynamically transferred to the conventional LCI control. After the control transfer, the VSI is turned off and physically disconnected from the main circuit. The advantages of this scheme are smooth starting, complete control of torque and flux at starting and low speeds, less starting time, stable operation, etc. The voltage rating of the required VSI is very low of the order of 10-15%, whereas the current rating is dependent on the starting torque requirement of the load. The experimental results from a 15.8 hp LCI-fed wound field synchronous machine are given to demonstrate the scheme.

Training Young Minds for Nanoscience and Technology: Issues and Challenges

This article explores issues and challenges in the field of education in nanoscience and technology with special emphasis with respect to India, where an expanding programme of research in nano science and technology is in place. The article does not concentrate on actual curricula that are needed in nano science and technology education course. Rather it focuses on the desirability of nanoscience and technology education at different levels of education and future prospect of students venturing into this within the economic and cultural milieu of India. We argue that care is needed in developing the education programme in India. However, the risk is worth taking as the education on nanoscience and technology can bridge the man power gap not only in this area of technology but also related technologies of hardware and micro electronics for which the country is a promising destination at global level. This will also unlock the demographical advantage that India will enjoy in the next five decades.

Reliability-based load and resistance factors for soil-nail walls

Existing soil nailing design methodologies are essentially based on limit equilibrium principles that together with a lumped factor of safety or a set of partial factors on the material parameters and loads account for uncertainties in design input parameter values. Recent trends in the development of design procedures for earth retaining structures are towards load and resistance factor design (LRFD). In the present study, a methodology for the use of LRFD in the context of soil-nail walls is proposed and a procedure to determine reliability-based load and resistance factors is illustrated for important strength limit states with reference to a 10 m high soil-nail wall. The need for separate partial factors for each limit state is highlighted, and the proposed factors are compared with those existing in the literature.