Digital signal processing of in-cylinder pressure for combustion diagnosis of internal combustion engines

In-cylinder pressure analysis is a key tool for engine research and diagnosis; however, it normally requires to process the experimental signal for providing valuable information. Usual four-step data processing consists on level correction, angle referencing, cycle averaging, and filtering. Concerning the last two issues, ad-hoc methods and experience-based algorithms are mostly used, and there is not a consensus in the scientific community about the optimal way to proceed. This paper presents a step-by-step approach to optimise the signal processing both for offline and online applications based on the characteristics of the signal.     

A methodology for combustion detection in diesel engines through in-cylinder pressure derivative signal

In-cylinder pressure measurement has historically been used for off-line combustion diagnosis, but online application for real-time combustion control has become of great interest. This work considers low computing-cost methods for analysing the instant variation of the chamber pressure, directly obtained from the electric signal provided by a traditional piezoelectric sensor. Presented methods are based on the detection of sudden changes in the chamber pressure, which are amplified by the pressure derivative, and which are due to thermodynamic phenomena within the cylinder. Signal analysis tools both in time and in time-frequency domains are used for detecting the start of combustion, the end of combustion and the heat release peak. Results are compared with classical thermodynamic analysis and validated in several turbocharged diesel engines.     

Salt stress induces physiochemical alterations in rice grain composition and quality

Salinity has drastic effects on plant growth and productivity and is one of the major factors responsible for crop yield losses throughout the agricultural soils of the world. The mechanisms of salinity tolerance in plants are regulated by a set of inherent multigenes and prevalent environmental factors, which bring about a myriad of metabolic changes in each plant part. The stress-induced metabolic changes in the rice plant have been intensively studied, but extensively in plant parts such as stem, leaf, and root. However, little information exists in the literature about such stress-induced architectural and physiological changes in rice grain, a premier staple food of a large proportion of human population. Thus, the current review comprehensively describes the effects of salinity stress on rice grain composition including changes in carbohydrate, protein, fat, and mineral contents. Elucidation of salinity induced changes in rice grain composition would help to understand whether or not a nutritious and healthy staple food is available to human population from rice grown under saline environments.     

Assessment of energy distribution losses for increasing penetration of distributed generation

High levels of penetration of distributed generation (DG) are a new challenge for traditional electric power systems. Power injections from DGs change network power flows modifying energy losses. Although it is considered that DG reduce losses, this paper shows that this is not always true. This paper presents an approach to compute annual energy losses variations when different penetration and concentration levels of DG are connected to a distribution network. In addition, the impact on losses of different DG technologies, such as combined heat and power, wind power, photovoltaic, and fuel-cells, is analyzed. Results show that energy losses variation, as a function of the DG penetration level, presents a characteristic U-shape trajectory. Moreover, when DG units are more dispersed along network feeders, higher losses reduction can be expected. Regarding DG technologies, it should be noted that wind power is the one that shows the worst behavior in losses reduction. Finally, DG units with reactive power control provide a better network voltage profile and lower losses.     

The Geodesic Distance on the Generalized Gamma Manifold for Texture Image Retrieval

Journal of Mathematical Imaging and Vision - In this paper, the similarity measurement issue, in the context of texture images comparison, is tackled from a geometrical point of view by computing...     

European Balancing Act

Wind power integration into power systems has two dimensions: an economical one related to optimization of the resources and a fair sharing of the cost, and a technical one related to security of supply. The economical dimension is first observed in the allocation and use of reserves that can incur increased costs for the power system operation. The actual impact of adding wind generation in different balancing areas can vary depending on local factors. Comparing European studies, some general aspects to reduce integration costs were identified, such as aggregating wind plant output over large geographical regions, larger balancing areas, and operating the power system closer to the delivery hour. In regard to the technical dimension, appropriate grid codes, in particular FRT and frequency control requirements, are essential to allow high wind penetration levels (>15%).     

Perturbation of multivariable linear quadratic systems with jumpparameters

Considers the problem of the perturbation of a class of linear quadratic systems where the change from one structure (for the dynamics and costs) to another is governed by a finite-state Markov process. The problem above leads to the analysis of some perturbed linearly coupled sets of Riccati equations. We show that the matrix obtained as the solution of the equations, which determines the optimal value and control, has a Taylor expansion in the perturbation parameter. We compute explicitly the terms of this expansion     

Algorithms for singularly perturbed limiting average Markov controlproblems

A singularly perturbed Markov decision process with the limiting average reward criterion is considered. It is assumed that the underlying process is composed of n separate irreducible processes, and that the small perturbation is such that it unites these processes into a single irreducible process. Two algorithms for the solution of the underlying limit Markov control problem are presented. The first of these is a linear program possessing the Wolfe-Dantzig structure inherited from the ergodic `nearly decomposable' assumption in the model. The second is an aggregation-disaggregation policy improvement algorithm     

Perturbation and stability theory for Markov control problems

A unified approach to the asymptotic analysis of a Markov decision process disturbed by an ϵ-additive perturbation is proposed. Irrespective of whether the perturbation is regular or singular, the underlying control problem that needs to be understood is the limit Markov control problem. The properties of this problem are studied