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16 pages, 46 figures. ; In this paper, a new methodology to build compact local maps in real time for outdoor robot navigation is presented. The environment information is obtained from a 3-D scanner laser. The navigation model, which is called traversable region model, is based on a Voronoi diagram technique, but adapted to large outdoor environments. The model obtained with this methodology allows a definition of safe trajectories that depend on the robot's capabilities and the terrain properties, and it will represent, in a topogeometric way, the environment as local and global maps. The application presented is validated in real outdoor environments with the robot called GOLIAT. ; This work was supported by the Spanish Government through the MICYT project DPI2003-01170. ; Publicado

Wavelet transform (WT) has been used in the diagnosis of cracked rotors since the 1990s. At present, WT is one of the most commonly used tools to treat signals in several fields. Understandably, this has been an area of extensive scientific research, which is why this paper aims to summarize briefly the major advances in the field since 2008. The present review considers advances in the use and application of WT, the selection of the parameters used, and the key achievements in using WT for crack diagnosis. ; The authors would like to thank the Spanish government for financing through the CDTI project RANKINE21 IDI-20101560.

Maintenance is essential to prevent catastrophic failures in rotating machinery. A crack can cause a failure with costly processes of reparation, especially in a rotating shaft. In this study, the Wavelet Packets transform energy combined with Artificial Neural Networks with Radial Basis Function architecture (RBF-ANN) are applied to vibration signals to detect cracks in a rotating shaft. Data were obtained from a rig where the shaft rotates under its own weight, at steady state at different crack conditions. Nine defect conditions were induced in the shaft (with depths from 4% to 50% of the shaft diameter). The parameters for Wavelet Packets transform and RBF-ANN are selected to optimize its success rates results. Moreover, 'Probability of Detection' curves were calculated showing probabilities of detection close to 100% of the cases tested from the smallest crack size with a 1.77% of false alarms. ; The authors would like to thank the Spanish Government for financing through the CDTI project RANKINE21 IDI-20101560.

The fourth industrial revolution is changing the way industries face their problems, including maintenance. The railway industry is moving to adopt this new industry model. The new trains are designed, manufactured, and maintained following an Industry 4.0 methodology, but most of the current trains in operation were not designed with this technological philosophy, so they must be adapted to it. In this paper, a new methodology for adapting a high-speed train to Industry 4.0 is proposed. That way, a train manufactured before this new paradigm can seize the advantages of Maintenance 4.0. This methodology is based on four stages (physical system, digital twin, information and communication technology infrastructure, and diagnosis) that comprise the required processes to digitalize a railway vehicle and that share information between them. The characteristics that the data acquisition and communication systems must fulfil are described, as well as the original signal processing techniques developed for analysing vibration signals. These techniques allow processing experimental data both in real time and deferred, according to actual maintenance requirements. The methodology is applied to determine the operating condition of a high-speed bogie by combining the signal processing of actual vibration measurements taken during the normal train operation and the data obtained from simulations of the digital twin. The combination of both (experimental data and simulations) allows establishing characteristic indicators that correspond to the normal running of the train and indicators that would correspond to anomalies in the behaviour of the train. ; The research work described in this paper was supported by the Spanish Government through the MM-IA4.0 PID2020-116984RB-C21 and RMS4.0 PID2020-116984RB-C22 projects.

In this article, a study of characteristic vibrations of marine oils separation system is presented. Vibrations analysis allows for the extraction of representative features that could be related to the lifetime of their pieces. Actual measurements were carried out on these systems on Ro-Pax vessels to transport passengers and freight. The vibrations obtained were processed in the frequency domain and following this, they were used in a Genetic Neuro-Fuzzy System in order to design new predictive maintenance strategies. The obtained results show that these techniques as a promising strategy can be utilized to determine incipient faults. ; This work has been supported by the Spanish Government [MAQ-STATUS DPI2015-69325-C2] and [DPI2015-69 1808271602] of Ministerio de Economía y Competitividad and with European Funds of Regional Development (FEDER).

In the present work, an introduction to the contact phenomena in multibody systems is made. The different existing approaches are described, together with their most distinctive features. Then, the term of coefficient of restitution is emphasized as a tool to characterize impact events and the algorithm for calculating the relative indentation between two convex-shaped bodies is developed. Subsequently, the main penalty contact models developed in the last decades are presented and developed, analysing their advantages and drawbacks, as well as their respective applications. Furthermore, some models with specific peculiarities that could be useful to the reader are included. The aim of this work is to provide a resource to the novice researcher in the field to facilitate the choice of the appropriate contact model for their work. ; This work was financially supported by the Spanish Government through the MCYT project "RETOS2015: sistema de monitorización integral de conjuntos mecánicos críticos para la mejora del mantenimiento en el transporte-MAQSTATUS".

High-speed rail is a key player in people's mobility thanks to its speed and high safety standards. These high safety standards are supported by extensive maintenance (of both rolling stock and track) that applies the latest nondestructive and monitoring techniques. In that context, this work presents the enhanced graphical representation of state configurations (EGRSC) and enhanced chromogram of bands of frequency (ECBF) methods, which are the evolution of the graphical representation of State configurations and chromogram of bands of frequency techniques. A clearer nomenclature is defined for the configuration states of the EGRSC. The ECBF introduces a new variable threshold that allows discarding frequency regions with small power variations and a new color palette. These methods are used in the vibratory study of an in-service high-speed train to identify the operating condition of the train. To conduct that task, a set of accelerometers is installed on the axle box of a trailer axle of the train. Accelerometers are oriented into the three space directions: longitudinal, lateral, and vertical. Vibration signals are taken during the normal operation of the train and transmitted to and stored on a remote database. Vibration measures are collected before and after a major maintenance operation. The application of EGRSC and ECBF allows collecting information from thousands of vibration signals and to display that information intuitively and understandably. The analysis of EGRSC and ECBF results allows identifying several frequency regions with significant spectral power variations that are common to the three vibration directions studied. These patterns should be taken as a reference for future maintenance actions. Any unexpected behavior of these frequency regions would indicate the presence of a fault. ; The research work described in this paper was supported by the Spanish Government through the MAQ-STATUS DPI2015-69325-C2-1-R project and by the UNED through UNED 2021-MEC-25 project.

An efficient maintenance is a key consideration in systems of railway transport, especially in high-speed trains, in order to avoid accidents with catastrophic consequences. In this sense, having a method that allows for the early detection of defects in critical elements, such as the bogie mechanical components, is a crucial for increasing the availability of rolling stock and reducing maintenance costs. The main contribution of this work is the proposal of a methodology that, based on classical signal processing techniques, provides a set of parameters for the fast identification of the operating state of a critical mechanical system. With this methodology, the vibratory behaviour of a very complex mechanical system is characterised, through variable inputs, which will allow for the detection of possible changes in the mechanical elements. This methodology is applied to a real high-speed train in commercial service, with the aim of studying the vibratory behaviour of the train (specifically, the bogie) before and after a maintenance operation. The results obtained with this methodology demonstrated the usefulness of the new procedure and allowed for the disclosure of reductions between 15% and 45% in the spectral power of selected Intrinsic Mode Functions (IMFs) after the maintenance operation. ; The research work described in this paper was supported by the Spanish Government through the MAQ-STATUS DPI2015-69325-C2-1-R project. Authors would also thank the support provided by the participating companies (Renfe, Alstom Spain, SKF Spain, and Dano-Rail-Danobatgroup Railway) in this project.

Railway axles are critical to the safety of railway vehicles. However, railway axlemaintenance is currently based on scheduled preventive maintenance using Nondestructive Testing.The use of condition monitoring techniques would provide information about the status of the axlebetween periodical inspections, and it would be very valuable in the prevention of catastrophicfailures. Nevertheless, in the literature, there are not many studies focusing on this area and thereis a lack of experimental data. In this work, a reliable real-time condition-monitoring technique forrailway axles is proposed. The technique was validated using vibration measurements obtained atthe axle boxes of a full bogie installed on a rig, where four different cracked railway axles were tested.The technique is based on vibration analysis by means of the Wavelet Packet Transform (WPT) energy,combined with a Support Vector Machine (SVM) diagnosis model. In all cases, it was observed thatthe WPT energy of the vibration signals at the first natural frequency of the axle when the wheelset isfirst installed (the healthy condition) increases when a crack is artificially created. An SVM diagnosismodel based on the WPT energy at this frequency demonstrates good reliability, with a false alarmrate of lower than 10% and defect detection for damage occurring in more than 6.5% of the section inmore than 90% of the cases. The minimum number of wheelsets required to build a general model toavoid mounting effects, among others things, is also discussed. ; This research was funded by the Spanish Government through the project MAQSTATUS with grant number DPI2015-69325-C2-1-R.

Railway axles are critical to the safety of railway vehicles. However, railway axle maintenance is currently based on scheduled preventive maintenance using Nondestructive Testing. The use of condition monitoring techniques would provide information about the status of the axle between periodical inspections, and it would be very valuable in the prevention of catastrophic failures. Nevertheless, in the literature, there are not many studies focusing on this area and there is a lack of experimental data. In this work, a reliable real-time condition-monitoring technique for railway axles is proposed. The technique was validated using vibration measurements obtained at the axle boxes of a full bogie installed on a rig, where four different cracked railway axles were tested. The technique is based on vibration analysis by means of the Wavelet Packet Transform (WPT) energy, combined with a Support Vector Machine (SVM) diagnosis model. In all cases, it was observed that the WPT energy of the vibration signals at the first natural frequency of the axle when the wheelset is first installed (the healthy condition) increases when a crack is artificially created. An SVM diagnosis model based on the WPT energy at this frequency demonstrates good reliability, with a false alarm rate of lower than 10% and defect detection for damage occurring in more than 6.5% of the section in more than 90% of the cases. The minimum number of wheelsets required to build a general model to avoid mounting effects, among others things, is also discussed. ; This research was funded by the Spanish Government through the project MAQSTATUS with grantnumber DPI2015-69325-C2-1-R.

Crack detection for railway axles is key to avoiding catastrophic accidents. Currently, non-destructive testing is used for that purpose. The present work applies vibration signal analysis to diagnose cracks in real railway axles installed on a real Y21 bogie working on a rig. Vibration signals were obtained from two wheelsets with cracks at the middle section of the axle with depths from 5.7 to 15 mm, at several conditions of load and speed. Vibration signals were processed by means of wavelet packet transform energy. Energies obtained were used to train an artificial neural network, with reliable diagnosis results. The success rate of 5.7 mm defects was 96.27%, and the reliability in detecting larger defects reached almost 100%, with a false alarm ratio lower than 5.5%. ; The research work described in this paper was supported by the Spanish Government through the MAQ-STATUS DPI2015-69325-C2-1-R project. Authors would also thank the support provided by the participating companies (Renfe, Alstom Spain, SKF Spain, and Danobat Railway Systems) in this project.

The aim of condition monitoring is to detect faults before a catastrophic failure occurs. Cracks in rotating shafts are especially critical. The present work studies vibration signals obtained from a rotating shaft under different crack depths and locations. Tests were performed in a rig called Rotokit at a steady state at different rotation speeds. Signals obtained are analyzed by means of energy using the Wavelet theory, specifically the Wavelet Packets Transform. Nine crack depths in the shafts were tested, from 4% to 50% of the shaft diameter. Previous related work showed good reliability for crack diagnosis using 3 x energy for cracks in the middle section. In the present work, previous results are compared to the obtained for a crack in a change of section at one side. In both crack locations, large changes in energy are observed at 3 x at high speeds. Energy levels at this harmonic were used for the inverse process of crack detection, and probability of detection curves were calculated by thresholding. Cracks with depths above 12% can be detected with reliability in the locations tested using this method. ; The authors would like to thankthe Spanish Government for financing through the projects RANKINE21 IDI-20101560 and MAQ-STATUS DPI2015-69325-C2-1-R.

This article belongs to the Topic Dynamical Systems: Theory and Applications. ; In the present work, different algorithms for contact detection in multibody systems based on smooth contact modelling approaches are presented. Beginning with the simplest ones, some difficult interactions are subsequently introduced. In addition, a brief overview on the different kinds of contact/impact modelling is provided and an underlining of the advantages and the drawbacks of each of them is determined. Finally, some practical examples of each interaction are presented and analyzed and an outline of the issues arisen during the design process and how they have been solved in order to obtain stable and accurate results is given. The main goal of this paper is to provide a resource for the early-stage researchers in the field that serves as an introduction to the modelling of simple contact/impact events in the context of multibody system dynamics. ; The authors would like to acknowledge the Spanish Government through the MCYT Project "RETOS2015: sistema de monitorización integral de conjuntos mecánicos críticos para la mejora del mantenimiento en el transporte-maqstatus". The authors would also like to acknowledge the financial support received by the Community of Madrid through its multi-year agreement with University Carlos III focused on its policy "Excelencia para el Profesorado Universitario".

This article belongs to the Special Issue Optimization of Motion Planning and Control for Automatic Machines, Robots and Multibody Systems. ; This work presents and discusses a general approach for the dynamic modeling and analysis of a passive biped walking robot, with a particular focus on the feet-ground contact interaction. The main purpose of this investigation is to address the supporting foot slippage and viscoelastic dissipative contact forces of the biped robot-walking model and to develop its dynamics equations for simple and double support phases. For this investigation, special attention has been given to the detection of the contact/impact between the legs of the biped and the ground. The results have been obtained with multibody system dynamics applying forward dynamics. This study aims at examining and comparing several force models dealing with different approaches in the context of multibody system dynamics. The normal contact forces developed during the dynamic walking of the robot are evaluated using several models: Hertz, Kelvin-Voight, Hunt and Crossley, Lankarani and Nikravesh, and Flores. Thanks to this comparison, it was shown that the normal force that works best for this model is the dissipative Nonlinear Flores Contact Force Model (hysteresis damping parameter - energy dissipation). Likewise, the friction contact/impact problem is solved using the Bengisu equations. The numerical results reveal that the stable periodic solutions are robust. Integrators and resolution methods are also purchased, in order to obtain the most efficient ones for this model. ; This work was financially supported by the Spanish Government through the MCYT project "RETOS2015: sistema de monitorización integral de conjuntos mecánicos críticos para la mejora del mantenimiento en el transporte-maqstatus"

The wheel re-profiling is an important part of railway wheelset maintenance. Researchers and railway operators have been very concerned about how to minimize the loss of time during wheel re-profiling without decreasing safety. Avoiding wheelset disassembly means considerable time savings, while reducing wheel damage during operation. Underfloor wheel lathes are the most appropriate tool to achieve this double objective, and therefore the most used nowadays. Multi-cut tool lathes have the disadvantage of being extremely expensive. On the other hand, with single tool lathes, re-profiling is not smooth or safe enough when current convex profile support rollers are used. It is well known by the companies that during reprofiling the wheel suffers impacts/damaged. In this article, a methodology to optimize the profile of the support rollers used in underfloor single tool lathes for railway wheel re-profiling is proposed. This novel profile design will minimize damage and increase the safety of such lathes, since it proposes a greater smoothness in the process. Simulations of re-profiling process have been carried out by the finite element method showing that the designed roller profile reduces drastically the impact/damage during the operation. The impact generated between the re-profiling wheel and the rollers is avoided. Profile-optimized support rollers have been used in a real underfloor wheel lathe, showing good results. ; This work was financially supported by the Spanish Government through the MCYT project 395 "RETOS2015: sistema de monitorización integral de conjuntos mecánicos críticos para la mejora del mantenimiento en el transporte-maqstatus."