Marcos E. Orchard

University of Chile · Departamento de Ingeniería Eléctrica

The performance of random forest (RF) based satellite attitude control system (ACS) fault diagnosis methods is limited by uninformative features in high-dimensional data. To solve this problem, we proposed a feature-weighted random forest with Boruta (FWRFB) based fault diagnosis method is proposed for fault diagnosis of ACSs. Firstly, a Boruta fea...

Thermal effects exert a crucial influence on the electrical behavior of lithium-ion batteries, significantly impacting key parameters such as the open circuit voltage curve, internal impedance, and cell degradation rate. Furthermore, these effects may give rise to electrolyte loss, resulting in a reduction in capacity. The cycling of batteries inhe...

The rapid advancement of machine learning algorithms has significantly enhanced tools for monitoring system health, making data-driven approaches predominant in Prognostics and Health Management (PHM). In contrast, model-based approaches have seen modest progress, as they are often constrained by the need for prior knowledge of specific governing e...

Current trends in the Industrial Internet of Things (IIoT) have increased the sensorization of systems, thus increasing data availability to apply data-driven fault detection and diagnosis techniques to monitor these systems. In this work, we show the capabilities of an information-driven method for detecting and quantifying faults in a subsystem c...

In modern industrial and engineering systems, stochastic degradation models are widely used for reliability analysis and maintenance decision-making. However, due to imperfect sensors and environmental influences, it is difficult to directly observe the latent degradation states. Traditional degradation models typically assume that measurement erro...

In adaptive control, error models use system output error and adaptive laws to update controller parameters for control or identification tasks. Fractional-order calculus, involving non-integer-order derivatives and integrals, is increasingly important for modeling, estimation, and control due to its ability to generalize classical methods and offe...

This study presents a comparative analysis of classical model reference adaptive control (IO-DMRAC) and its fractional-order counterpart (FO-DMRAC), which are applied to the pitch-rate control of an F-16 aircraft longitudinal model. The research demonstrates a significant enhancement in control performance with fractional-order adaptive control. No...

: This paper presents a comparison between direct integer orders or classical model reference adaptive control (IO-DMRAC) versus its fractional orders counterpart (FO-DMRAC) applied to the F-16 aircraft longitudinal model pitch rate control. A substantial improvement is achieved when using fractional order adaptive control, since, in addition to pe...

This paper presents the design, implementation, and validation of an on-blade sensor system for remote vibration measurement for low-capacity wind turbines. The autonomous sensor system was deployed on three wind turbines, with one of them operating in harsh weather conditions in the far south of Chile. The system recorded the acceleration response...

Modal properties of dynamically tested wind turbine blades (WTBs) of a utility-scale wind turbine are identified. A comprehensive experimental program including free vibration and short- and long-term forced vibrations representing resonance and simplified fatigue conditions was carried out to investigate vibration-based features for damage diagnos...

In this paper we study the joint determination of source and background flux for point sources as observed by digital array detectors. We explicitly compute the two-dimensional Cramér–Rao absolute lower bound (CRLB) as well as the performance bounds for high-dimensional implicit estimators from a generalized Taylor expansion. This later approach al...

Multimedia video streaming, identified as the dominant internet data consumption service, brings forth challenges in consistently delivering optimal video quality. Dynamic Adaptive Streaming over HTTP (DASH), while prevalent, often encounters buffering problems, causing video pauses due to empty video buffers. This study introduces the Adaptive Sca...

The prognostic of events, and particularly of failures, is a key step towards allowing preventive decision-making, as in the case of predictive maintenance in Industry 4.0. However, the occurrence time of a future event is subject to uncertainty, and is typically modelled as a random variable. In this regard , the default procedure (benchmark) to c...

Understanding the intricate interplay between neural dynamics and metabolic constraints is crucial for unraveling the mysteries of the brain. Despite the significance of this relationship, specific details concerning the impact of metabolism on neuronal dynamics and neural network architecture remain elusive, creating a notable gap in the existing...

The prognostic of events, and particularly of failures, is a key step towards allowing preventive decision-making, as in the case of predictive maintenance in Industry 4.0, for example. However, the occurrence time of a future event is subject to uncertainty, so it is natural to think of it as a random variable. In this regard, the default procedur...

As environmental awareness grow, many organizations seek to implement Electric Vehicle (EV) fleets. Nonetheless, EVs’ low driving ranges and high recharging times, and the limited Charging Stations (CS) availability make their management more challenging than conventional vehicles. The Electric Vehicle Routing Problem (E-VRP) tackles these challeng...

This paper deals with the longitudinal movement control of an airplane (pitch angle) using fractional order adaptive controllers (FOACs). It shows the improvements achieved in the plane’s behavior, in terms of the minimization of a given performance index. At the same time, less control effort is needed to accomplish the control objectives compared...

Multimedia video streaming is the most used data consumption service on the Internet. Maintaining a data flow rate that provides the best video quality possible without overflowing the pipeline is challenging. Dynamic Adaptive Streaming over HTTP (DASH) is a commonly used protocol that sends video data in small packages called chunks. However, this...

Failure prognostic predicts the Remaining Useful Life (RUL) of machine/components, which will allow timely maintenance and repair leading to continuous reliable and safe operating conditions. In this paper, a novel hybrid RUL prediction approach is proposed for heavy-duty gas turbines. Two common failures, namely the fouling in the gas turbine comp...

The optimal instant of observation of astrophysical phenomena for objects that vary on human timescales is an important problem, as it bears on the cost-effective use of usually scarce observational facilities. In this paper, we address this problem in the case of tight visual binary systems through a Bayesian framework based on the maximum entropy...

Aircrafts are complex engineering systems composed of many interconnected subsystems with possible uncertainties in their structure. They often function for long number of flight hours under varying or harsh environments. Hence, Prognostic and Health Management (PHM) of critical subsystems or components within the overall system is crucial for main...

Prognosis of the time of first occurrence of events, particularly failures, is a problem that has been studied and analyzed from different perspectives, being referred to as the "first-hitting time" or "first-passage time" problem, among other names. Within the Prognostics and Health Management community, as well as in other disciplines, the prob-a...

The prediction of the time of occurrence of future events has been studied for decades in various scientific disciplines. Such events have historically been defined as moments where variables of interest (or indicators) hit pre-determined thresholds (i.e. the first-hitting time). Recently, semi-closed mathematical expressions were reported in the l...

This paper proposes a three-phase AC battery based on the modular multilevel converter (M2C). The AC battery concept allows plug-and-play combinatorial integration of diverse battery cells with different characteristics such as nominal voltage, state of charge (SoC), and degradation levels. The resulting modular and reconfigurable battery pack can...

This paper proposes a Bayesian framework based on particle filters for online fatigue damage diagnosis and prognosis for wind turbine blades (WTBs). The framework integrates theoretical and practical aspects with the purpose of developing a robust monitoring tool. Besides, a damage indicator based on identified modal frequencies of the WTB is defin...

The Levelized Cost of Driving (LCOD) calculates how much it costs to drive a vehicle, per kilometer, over the vehicle lifespan, and it is typically measured in USD/km. LCOD has been widely applied to assess and compare the performance of Electric Vehicles (EVs) and Internal Combustion engine Vehicles (ICVs). Unfortunately, there is no common method...

We present a Bayesian inference methodology for the estimation of orbital parameters on single-line spectroscopic binaries with astrometric data, based on the No-U-Turn sampler Markov chain Monte Carlo algorithm. Our approach is designed to provide a precise and efficient estimation of the joint posterior distribution of the orbital parameters in t...

Condition Monitoring (CM) is an essential element of securing reliable operating conditions of Wind Turbines (WT) in a wind farm. CM helps optimize maintenance by providing Remaining Useful Life (RUL) forecast. However, the expected RUL is not often reliable due to uncertainty associated with the prediction horizon. In this paper, we employ high-le...

We present a Bayesian inference methodology for the estimation of orbital parameters on single-line spectroscopic binaries with astrometric data, based on the No-U-Turn sampler Markov chain Monte Carlo algorithm. Our approach is designed to provide a precise and efficient estimation of the joint posterior distribution of the orbital parameters in t...

This work addresses testing the independence of two continuous and finite-dimensional random variables from the design of a data-driven partition. The empirical log-likelihood statistic is adopted to approximate the sufficient statistics of an oracle test against independence (that knows the two hypotheses). It is shown that approximating the suffi...

Recent developments in lithium-ion (Li-ion) storage technology have enabled a revolution in the automotive industry. Fully electric vehicles (EVs) operate under the most diverse combination of driving and environmental conditions affecting the autonomy range. In other words, an equal state-of-charge (SOC) on two same model EV does not mean the same...

This work addresses testing the independence of two continuous and finite-dimensional random variables from the design of a data-driven partition. The empirical log-likelihood statistic is adopted to approximate the sufficient statistics of an oracle test against independence (that knows the two hypotheses). It is shown that approximating the suffi...

Model-based prognostic approaches use first-principle or regression models to estimate and predict the system’s health state in order to determine the remaining useful life (RUL). Then, in order to handle the prediction results uncertainty, the Bayesian framework is usually used, in which the prior estimates are updated by infield measurements with...

State-of-Charge (SoC) is commonly defined as a ratio between the available charge and the battery capacity. Unfortunately, SoC has been misguidedly interpreted as an indicator of autonomy. Despite its widespread use, this concept has two critical flaws that affect the quality of estimates for energy availability in lithium-ion batteries: (i) SoC is...

The adoption of Electric Vehicles (EVs) has substantially increased during the last decade, creating the need for customized EV-oriented routing strategies capable of using the enormous amount of historical, and real-time, traffic data that is collected through Intelligent Transport Systems (ITSs). Existing EV routing algorithms, however, concentra...

The authors wish to make the following corrections to their paper [...]

Fault diagnosis and prognosis are some of the most crucial functionalities in complex and safety-critical engineering systems, and particularly fault diagnosis, has been a subject of intensive research in the past four decades. Such capabilities allow for detection and isolation of early developing faults as well as prediction of fault propagation...

It is widely accepted that the brain, like any other physical system, is subjected to physical constraints that restrict its operation. The brain's metabolic demands are particularly critical for proper neuronal function, but the impact of these constraints continues to remain poorly understood. Detailed single‐neuron models are recently integratin...

Under certain rather prevalent conditions (driven by dynamical orbital evolution), a hierarchical triple stellar system can be well approximated, from the standpoint of orbital parameter estimation, as two binary star systems combined. Even under this simplifying approximation, the inference of orbital elements is a challenging technical problem be...

In this article we present a Hybrid Neural Adaptive State Space Model (NASSM), the purpose of which is to solve the complex problem of accurately characterising the ever changing (non-measurable) polarising impedance multi-dimensional surface and capacity degradation of a Lithium-Ion battery. We achieve this by proposing a novel strategy and archit...

The determination of the time at which an event may take place in the future is a well-studied problem in a number of science and engineering disciplines. Indeed, for more than fifty years, researchers have tried to establish adequate methods to characterize the behaviour of dynamic systems in time and implement predictive decision-making policies....

Failure prognostic is generally conducted following two approaches, model-based or data-driven. On the one hand, model-based approaches offer better physical interpretability and may be easily embedded in the structure of Bayesian processors for uncertainty characterization purposes. However, it is challenging to identity degradation models in comp...

One of the main challenges in prognostics corresponds to the estimation of the probability density function (PDF) of the system’s time-of-failure (ToF) prior to reach a fault condition. An appropriate characterization of the ToF-PDF will let the user know about the remaining useful life of the system or component, allowing the users to prevent cat...

It is widely accepted that the brain, like any other physical system, is subjected to physical constraints restricting its operation. The brain’s metabolic demands are particularly critical for proper neuronal function, but the impact of these constraints is still poorly understood. Detailed single-neuron models are recently integrating metabolic c...

The main purpose of this article is to propose a novel definition for the remaining useful life of lithium-ion batteries based on the increase of the inefficiency related to the Joule effect due to the growth on the internal impedance of the battery as it degrades. The applied methodology consists in the cycling of a rechargeable lithium-ion cell a...

As CO2 emission regulations increase, fleet owners increasingly consider the adoption of Electric Vehicle (EV) fleets in their business. The conventional Vehicle Routing Problem (VRP) aims to find a set of routes to reduce operational costs. However, route planning of EVs poses different challenges than that of Internal Combustion Engine Vehicles (...

The implementation of particle-filtering-based algorithms for state estimation purposes often has to deal with the problem of missing observations. An efficient design requires an appropriate methodology for real-time uncertainty characterization within the estimation process, incorporating knowledge from other available sources of information. Thi...

As wind energy is becoming a significant utility source, minimizing the Operation and Maintenance (O&M) expenses has raised a crucial issue to make wind energy competitive to fossil fuels. Wind Turbines (WTs) are subject to unexpected failures due to operational and environmental conditions, aging, etc. An accurate estimation of time to failures as...

Temperature prediction of a battery plays a significant role in terms of energy efficiency and safety of electric vehicles, as well as several kinds of electric and electronic devices. In this regard, it is crucial to identify an adequate model to study the thermal behavior of a battery. This article reports a comparative study on thermal modeling...

Small unmanned aerial vehicles (UAVs) have been increasingly popular in the last years, being employed in a wide range of applications in diverse areas, including, for instance, military, medicine, and package delivery. These aerial vehicles are commonly energized by rechargeable batteries, and, as a result, their autonomy can be significantly affe...

Considering traditional model-based prognostics approaches, a previously defined model is required to estimate the system's health state and then propagate it to predict the system remaining useful life (SRUL). Following a Bayesian framework, the result of this prior estimation is updated by in-field measurements without changing the model paramete...

Gear faults contribute to a significant portion of failures in wind turbine system. As such, condition monitoring and fault detection of these components assist in maintenance scheduling; hence, preventing catastrophic failures of the gearbox. This paper introduces a new hybrid fault detection approach to detect gear faults in wind turbines. to acc...

The failure progression of Wind Turbine (WT) bearings comprises of multiple degraded health states due to applied load by Varying Operating Conditions (VOC). Therefore, determining the VOC impact on the failure dynamics severity is an essential task for bearing failure prognostics. This paper introduces a hybrid prognosis method using real-time Sup...

Modern systems, that are often constituted of different interacting components, have increasing requirements for improving availability and safety when suffering unanticipated failures. Therefore, one needs to continuously monitor them, estimate and predict their health states through the implementation of prognostics and health management processe...

In literature, a major part of the prognostic studies considers the mission profile as a static parameter when evaluating the system Remaining Useful Life (RUL). However, in practice, the way in which a system operates significantly impacts the future evolution of its degradation. Therefore, this paper aims at evaluating the impact associated with...

This article proposes a monitoring system that allows to track transitions between different stages in the berry harvesting process (berry picking, waiting for transport, transport and arrival at the packing site) solely using information from temperature and vibration sensors located in the basket. The monitoring system assumes a characterization...

Characterizing the degradation process of lithium-ion (Li-ion) batteries is still a matter of ongoing research due to the diverse operating conditions at which they are submitted. For example, different current discharge rates and asymmetrical charge/discharge cycles are critical operating conditions that affect both the performance and the lifespa...

Typically, datasheets of photovoltaic (PV) modules state that the guaranteed power production remains constant for a certain period of time and after this point, a linear reduction begins reaching an estimated 80% of the original rated power. Moreover, literature reports that the degradation of PV modules reaches less than 1% per year. In this rega...

Blades are one of the main and more costly components of wind turbines and, besides, are difficult to inspect and maintain. Due to operational conditions, wind turbine blades (WTBs) are prone to suffer structural damage, chiefly because of fatigue or extreme loading. Therefore, it is crucial to monitor the state of health (SoH) of these components...

This article proposes a monitoring system that allows to track transitions between different stages in the berry harvesting process (berry picking, waiting for transport, transport, and arrival to the packing) solely using information from temperature and vibration sensors located in the basket. The monitoring system assumes a characterization of t...

This paper presents the design and application of a multiple-input–multiple-output fractional order proportional-integral (MIMO FOPI) controller to a grinding mill circuit. The MIMO FOPI controller parameters are tuned using an off-line optimization process based on Particle Swarm Optimization (PSO). Its performance is compared to a single-input–si...

Partial measurements of relative position are a relatively common event during the observation of visual binary stars. However, these observations are typically discarded when estimating the orbit of a visual pair. In this article we present a novel framework to characterize the orbits from a Bayesian standpoint, including partial observations of r...

Duty cycling is a technique that has been implemented in medium-access-control protocols to reduce the listening time and minimize energy consumption in wireless sensor networks. This technique manages the active and sleep modes to reduce the energy consumption of the sensor nodes, sending the node to sleep mode more frequently as the energy is dra...