Order tracking for discrete-random separation in variable speed conditions

The transmission path from the excitation to the measured vibration on the surface of a mechanical system introduces a distortion both in amplitude and in phase. Moreover, in variable speed conditions, the amplification/attenuation and the phase shift, due to the transfer function of the mechanical system, varies in time. This phenomenon reduces the effectiveness of the traditionally tachometer based order tracking, compromising the results of a discrete-random separation performed by a synchronous averaging. In this paper, for the first time, the extent of the distortion is identified both in the time domain and in the order spectrum of the signal, highlighting the consequences for the diagnostics of rotating machinery. A particular focus is given to gears, providing some indications on how to take advantage of the quantification of the disturbance to better tune the techniques developed for the compensation of the distortion. The full theoretical analysis is presented and the results are applied to an experimental case.

Diagnostic of Rolling Element Bearings with Envelope Analysis in Non-Stationary Conditions

In the field of rolling element bearing diagnostics, envelope analysis has gained in the last years a leading role among the different digital signal processing techniques. The original constraint of constant operating speed has been relaxed thanks to the combination of this technique with the computed order tracking, able to resample signals at constant angular increments. In this way, the field of application of this technique has been extended to cases in which small speed fluctuations occur, maintaining high effectiveness and efficiency. In order to make this algorithm suitable to all industrial applications, the constraint on speed has to be removed completely. In fact, in many applications, the coincidence of high bearing loads, and therefore high diagnostic capability, with acceleration-deceleration phases represents a further incentive in this direction. This chapter presents a procedure for the application of envelope analysis to speed transients. The effect of load variation on the proposed technique will be also qualitatively addressed.

A coordinated voltage control approach for coordination of OLTC, voltage regulator and DG to regulate voltage in a distribution feeder

Integration of small-scale electricity generators, known as Distributed Generation (DG), into the distribution networks has become increasingly popular at the present. This tendency together with the falling price of synchronous-type generator has potential to give the DG a better chance in participating in the voltage regulation process together with other devices already available in the system. The voltage control issue turns out to be a very challenging problem for the distribution engineers since existing control coordination schemes would need to be reconsidered to take into account the DG operation. In this paper, we propose a control coordination technique, which is able to utilize the ability of the DG as a voltage regulator, and at the same time minimizes interaction with other active devices, such as On-load Tap Changing Transformer (OLTC) and voltage regulator. The technique has been developed based on the concept of control zone, Line Drop Compensation (LDC), as well as the choice of controller's parameters. Simulations carried out on an Australian system show that the technique is suitable and flexible for any system with multiple regulating devices including DG.

Electrochemical and photochemical routes to semiconducting transition metal-tetracyanoquinodimethane coordination polymers

TCNQ·− radical anions (TCNQ = 7,7,8,8,-tetracyanoquinodimethane) form a wide range of semiconducting coordination polymers when coordinated to transition metals. Some such as CuTCNQ and AgTCNQ exhibit molecular switching and memory storage properties; others have intriguing magnetic properties and for example may behave as molecular magnets at low temperature. In this review, the electro- and photo-chemical synthesis and characterization of this important class of material is reviewed. In particular, the electrochemistry and the redox properties of TCNQ derivatives of coordination polymers based on Cu, Ag, Mn, Fe, Co, Ni, Zn and Cd transition metals are surveyed, with an emphasis on the mechanistic aspects of their electrochemical formation via nucleation–growth processes. Given that TCNQ is an extremely good electron acceptor, readily forming TCNQ•− and TCNQ2-, electrochemical reduction of TCNQ in the presence of a transition metal ion provides an ideal method for synthesis of metal-TCNQ materials by electrocrystallization from organic solvents and ionic liquids or solid-solid transformation using TCNQ modified electrodes from aqueous media containing transition metal electrolytes. The significance of the reversible formal potential (E0f) in these studies is discussed. The coupling of electrocrystallisation on electrode surfaces and microscopic characterization of the electrodeposited materials reveals a wide range of morphologies and phases which strongly influence their properties and applications. Since TCNQ also can be photo-reduced in the presence of suitable electron donors, analogous photochemical approaches to the synthesis of TCNQ-transition metal derivatives are available. The advantages of electrochemical and photochemical methods of synthesis relative to chemical synthesis are outlined.

Selective combination of visual and thermal imaging for resilient localization in adverse conditions : day and night, smoke and fire

Long-term autonomy in robotics requires perception systems that are resilient to unusual but realistic conditions that will eventually occur during extended missions. For example, unmanned ground vehicles (UGVs) need to be capable of operating safely in adverse and low-visibility conditions, such as at night or in the presence of smoke. The key to a resilient UGV perception system lies in the use of multiple sensor modalities, e.g., operating at different frequencies of the electromagnetic spectrum, to compensate for the limitations of a single sensor type. In this paper, visual and infrared imaging are combined in a Visual-SLAM algorithm to achieve localization. We propose to evaluate the quality of data provided by each sensor modality prior to data combination. This evaluation is used to discard low-quality data, i.e., data most likely to induce large localization errors. In this way, perceptual failures are anticipated and mitigated. An extensive experimental evaluation is conducted on data sets collected with a UGV in a range of environments and adverse conditions, including the presence of smoke (obstructing the visual camera), fire, extreme heat (saturating the infrared camera), low-light conditions (dusk), and at night with sudden variations of artificial light. A total of 240 trajectory estimates are obtained using five different variations of data sources and data combination strategies in the localization method. In particular, the proposed approach for selective data combination is compared to methods using a single sensor type or combining both modalities without preselection. We show that the proposed framework allows for camera-based localization resilient to a large range of low-visibility conditions.

Laser-to-radar sensing redundancy for resilient perception in adverse environmental conditions

This paper presents an approach to promote the integrity of perception systems for outdoor unmanned ground vehicles (UGV) operating in challenging environmental conditions (presence of dust or smoke). The proposed technique automatically evaluates the consistency of the data provided by two sensing modalities: a 2D laser range finder and a millimetre-wave radar, allowing for perceptual failure mitigation. Experimental results, obtained with a UGV operating in rural environments, and an error analysis validate the approach.

Perception Quality Evaluation with Visual and Infrared Cameras in Challenging Environmental Conditions

This work aims to contribute to the reliability and integrity of perceptual systems of unmanned ground vehicles (UGV). A method is proposed to evaluate the quality of sensor data prior to its use in a perception system by utilising a quality metric applied to heterogeneous sensor data such as visual and infrared camera images. The concept is illustrated specifically with sensor data that is evaluated prior to the use of the data in a standard SIFT feature extraction and matching technique. The method is then evaluated using various experimental data sets that were collected from a UGV in challenging environmental conditions, represented by the presence of airborne dust and smoke. In the first series of experiments, a motionless vehicle is observing a ’reference’ scene, then the method is extended to the case of a moving vehicle by compensating for its motion. This paper shows that it is possible to anticipate degradation of a perception algorithm by evaluating the input data prior to any actual execution of the algorithm.

Towards discrimination of challenging conditions for UGVs with visual and infrared sensors

This work aims to contribute to reliability and integrity in perceptual systems of autonomous ground vehicles. Information theoretic based metrics to evaluate the quality of sensor data are proposed and applied to visual and infrared camera images. The contribution of the proposed metrics to the discrimination of challenging conditions is discussed and illustrated with the presence of airborne dust and smoke.

Datasets for the evaluation of multi-sensor perception in natural environments with challenging conditions

This paper presents large, accurately calibrated and time-synchronised datasets, gathered outdoors in controlled environmental conditions, using an unmanned ground vehicle (UGV), equipped with a wide variety of sensors. It discusses how the data collection process was designed, the conditions in which these datasets have been gathered, and some possible outcomes of their exploitation, in particular for the evaluation of performance of sensors and perception algorithms for UGVs.

The Marulan data sets: multi-sensor perception in a natural environment with challenging conditions

In this paper we present large, accurately calibrated and time-synchronized data sets, gathered outdoors in controlled and variable environmental conditions, using an unmanned ground vehicle (UGV), equipped with a wide variety of sensors. These include four 2D laser scanners, a radar scanner, a color camera and an infrared camera. It provides a full description of the system used for data collection and the types of environments and conditions in which these data sets have been gathered, which include the presence of airborne dust, smoke and rain.

Towards reliable perception for unmanned ground vehicles in challenging conditions

This work aims to promote reliability and integrity in autonomous perceptual systems, with a focus on outdoor unmanned ground vehicle (UGV) autonomy. For this purpose, a comprehensive UGV system, comprising many different exteroceptive and proprioceptive sensors has been built. The first contribution of this work is a large, accurately calibrated and synchronised, multi-modal data-set, gathered in controlled environmental conditions, including the presence of dust, smoke and rain. The data have then been used to analyse the effects of such challenging conditions on perception and to identify common perceptual failures. The second contribution is a presentation of methods for mitigating these failures to promote perceptual integrity in adverse environmental conditions.

A nation’s role in addressing base erosion and profit shifting : balancing sovereignty with international collaboration and coordination

The notion of sovereignty is central to any international tax issue. While a nation is free to design its tax laws as it sees fit and raise revenue in accordance with the needs of its citizens, it is not possible to undertake such a task in isolation. In a world of cross-border investments and business transactions, all tax regimes impact on one another. Tax interactions between sovereign states cannot be avoided. Ultimately, the interactions mean that a nation must decide whether to engage in both collaboration and coordination with other nations and supranational bodies alike or maintain an individualised stance in relation to its tax policy. Whatever the decision, there is arguably an exercise in national sovereignty in some form. In the context of an international tax regime, whether that regime is interpreted broadly as meaning international norms generally adopted by nations around the world or domestic regimes legislating for cross-border transactions, rhetoric around national fiscal sovereignty takes on many different forms. At one end of the spectrum it is relied upon by financial secrecy jurisdictions (tax havens) as a defence to their position on the basis that ‘other’ nations cannot interfere with the fiscal sovereignty of a jurisdiction. At the other end of the spectrum, it is argued that profit shifting and international tax avoidance if not stopped is, in and of itself, a threat to a nation’s fiscal sovereignty on the basis that it threatens the ability to tax and raise the revenue needed. This paper considers a modern conceptualisation of sovereignty along with its role within international tax coordination and collaboration to argue that a move towards a more unified approach to addressing international base erosion and profit shifting may be the ultimate exercise of national fiscal sovereignty. By using the current transfer pricing regime as a case study, this paper posits that it is not merely enough to have international agreement on allocation rules to be applied, but that the ultimate exercise of national sovereignty is political agreement with other states to ensure that it is governments which determine the allocational basis of worldwide profits to be taxed. In doing so, it is demonstrated that the arm’s length pricing requirement of the current transfer pricing regime, rather than providing governments with the ability to determine the location of profits, is providing multinational entities with the ultimate power to determine that location. If left unchecked, this will eventually erode a nation’s ability to capture the required tax revenue and, as a consequence, may be deemed a failure by nation states to exercise their fiscal sovereignty.

Mesenchymal stem cell therapies for bone and tendon conditions

Bone, tendon, and cartilage are highly specialized musculoskeletal connective tissues that are subject to injury and degeneration. These tissues have relatively poor healing capabilities, and coupled with their variable response to established medical treatments, produce significant morbidity. Mesenchymal stem cells (MSCs) are capable of regenerating skeletal tissues and therefore offer great promise in the treatment of connective tissue pathologies. Adult MSCs are multipotent cells that possess the properties of proliferation and differentiation into all connective tissues. Furthermore, they can be gene modified to secrete growth factors and utilized in connective tissue engineering. Potential MSC-based therapies for bone and tendon conditions are reviewed in this chapter.

Exact series solutions of reactive transport models with general initial conditions

Exact solutions of partial differential equation models describing the transport and decay of single and coupled multispecies problems can provide insight into the fate and transport of solutes in saturated aquifers. Most previous analytical solutions are based on integral transform techniques, meaning that the initial condition is restricted in the sense that the choice of initial condition has an important impact on whether or not the inverse transform can be calculated exactly. In this work we describe and implement a technique that produces exact solutions for single and multispecies reactive transport problems with more general, smooth initial conditions. We achieve this by using a different method to invert a Laplace transform which produces a power series solution. To demonstrate the utility of this technique, we apply it to two example problems with initial conditions that cannot be solved exactly using traditional transform techniques.