scholarly journals New Multifeature Information Health Index (MIHI) Based on a Quasi-Orthogonal Sparse Algorithm for Bearing Degradation Monitoring

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Xiao Zhang ◽  
Tengyi Peng ◽  
Shilong Sun ◽  
Yu Zhou
Keyword(s):  
Health Management ◽  
Maintenance Cost ◽  
Health Index ◽  
Equipment Operation ◽  
Degradation Data ◽  
Fault Type ◽  
Current State ◽  
Degradation Monitoring ◽  
Straight Lines

Data-driven intelligent prognostic health management (PHM) systems have been widely investigated in the area of defective bearing signals. These systems can provide precise information on condition monitoring and diagnosis. However, existing PHM systems cannot identify the accurate degradation trend and the current fault types simultaneously. Given that different fault types have various effects on the mechanical system, the corresponding maintenance strategies also vary. Then, choosing the appropriate maintenance strategy according to the future fault type can reduce the maintenance cost of the equipment operation. Therefore, a multifeature information health index (MIHI) must be developed to trace various bearing degradation trends with various types of faults simultaneously. This paper reports a new quasi-orthogonal sparse project algorithm that can mutually convert the degraded processing feature vector sets (such as spectrum) for each type of fault to orthogonal approximate spatial straight lines. The algorithm builds a MIHI through the spectrum of current state measured points. The MIHI is then transformed by a quasi-orthogonal sparse project algorithm to trace the various bearing degradation trends and recognize the fault type simultaneously. The case study of bearing degradation data demonstrates that this approach is effective in assessing the various degradation trends of different fault types.

scholarly journals Residual Lifetime Prediction with Multistage Stochastic Degradation for Equipment

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Zhan Gao ◽  
Qi-guo Hu ◽  
Xiang-yang Xu
Keyword(s):  
Real Time ◽  
Health Management ◽  
Residual Life ◽  
Performance Degradation ◽  
Monitoring Data ◽  
Estimation Accuracy ◽  
Residual Lifetime ◽  
Practical Case ◽  
Degradation Data ◽  
Degradation Monitoring

Residual useful lifetime (RUL) prediction plays a key role of failure prediction and health management (PHM) in equipment. Aiming at the problems of residual life prediction without comprehensively considering multistage and individual differences in equipment performance degradation at present, we explore a prediction model that can fit the multistage random performance degradation. Degradation modeling is based on the random Wiener process. Moreover, according to the degradation monitoring data of the same batch of equipment, we apply the expectation maximization (EM) algorithm to estimate the prior distribution of the model. The real-time remaining life distribution of the equipment is acquired by merging prior information of real-time degradation data and historical degradation monitoring data. The accuracy of the proposed model is demonstrated by analyzing a practical case of metalized film capacitors, and the result shows that a better RUL estimation accuracy can be provided by our model compared with existing models.

scholarly journals Extending Geodemographics Using Data Primitives: A Review and a Methodological Proposal

2021 ◽  
Vol 10 (6) ◽  
pp. 386
Author(s):  
Jennie Gray ◽  
Lisa Buckner ◽  
Alexis Comber
Keyword(s):  
Social Dynamics ◽  
Feature Space ◽  
Social Processes ◽  
Multiple Time ◽  
Current State ◽  
Cluster Label ◽  
Static Data ◽  
The Social ◽  
Using Data

This paper reviews geodemographic classifications and developments in contemporary classifications. It develops a critique of current approaches and identifiea a number of key limitations. These include the problems associated with the geodemographic cluster label (few cluster members are typical or have the same properties as the cluster centre) and the failure of the static label to describe anything about the underlying neighbourhood processes and dynamics. To address these limitations, this paper proposed a data primitives approach. Data primitives are the fundamental dimensions or measurements that capture the processes of interest. They can be used to describe the current state of an area in a multivariate feature space, and states can be compared over multiple time periods for which data are available, through for example a change vector approach. In this way, emergent social processes, which may be too weak to result in a change in a cluster label, but are nonetheless important signals, can be captured. As states are updated (for example, as new data become available), inferences about different social processes can be made, as well as classification updates if required. State changes can also be used to determine neighbourhood trajectories and to predict or infer future states. A list of data primitives was suggested from a review of the mechanisms driving a number of neighbourhood-level social processes, with the aim of improving the wider understanding of the interaction of complex neighbourhood processes and their effects. A small case study was provided to illustrate the approach. In this way, the methods outlined in this paper suggest a more nuanced approach to geodemographic research, away from a focus on classifications and static data, towards approaches that capture the social dynamics experienced by neighbourhoods.

scholarly journals Evaluating the effectiveness of machine acquisitions and design by the impact on maintenance cost – a case study

2020 ◽  
Vol 53 (3) ◽  
pp. 25-30
Author(s):  
M. Hane Hagström ◽  
K. Gandhi ◽  
D. Bergsjö ◽  
A. Skoogh
Keyword(s):  
Maintenance Cost ◽  
The Impact

scholarly journals Defining and Quantifying Intermittency in the Power Sector

Energies ◽  
2020 ◽  
Vol 13 (13) ◽  
pp. 3366
Author(s):  
Daniel Suchet ◽  
Adrien Jeantet ◽  
Thomas Elghozi ◽  
Zacharie Jehl
Keyword(s):  
Power Source ◽  
Production Data ◽  
Power Sector ◽  
Predictive Capacity ◽  
The Public ◽  
Current State ◽  
Definition Of ◽  
Quantitative Definition ◽  
The Impact

The lack of a systematic definition of intermittency in the power sector blurs the use of this term in the public debate: the same power source can be described as stable or intermittent, depending on the standpoint of the authors. This work tackles a quantitative definition of intermittency adapted to the power sector, linked to the nature of the source, and not to the current state of the energy mix or the production predictive capacity. A quantitative indicator is devised, discussed and graphically depicted. A case study is illustrated by the analysis of the 2018 production data in France and then developed further to evaluate the impact of two methods often considered to reduce intermittency: aggregation and complementarity between wind and solar productions.

The Role of Constraints and Human Interaction in Evolving MEMS Designs: Microresonator Case Study

2004 ◽  
Author(s):  
Raffi Kamalian ◽  
Alice M. Agogino ◽  
Hideyuki Takagi
Keyword(s):  
Genetic Algorithms ◽  
Geometric Constraints ◽  
Human Interaction ◽  
Design System ◽  
Current State ◽  
Mems Resonator ◽  
Computer Aided ◽  
Generative Methods

In this paper we review the current state of automated MEMS synthesis with a focus on generative methods. We use the design of a MEMS resonator as a case study and explore the role that geometric constraints and human interaction play in a computer-aided MEMS design system based on genetic algorithms.

Multisensor Degradation Data Fusion and Remaining Life Prediction

2017 ◽  
Author(s):  
Changxi Wang ◽  
E. A. Elsayed ◽  
Kang Li ◽  
Javier Cabrera
Keyword(s):  
Data Fusion ◽  
Prediction Accuracy ◽  
Life Prediction ◽  
Clustering Algorithm ◽  
Partial Information ◽  
Degradation Process ◽  
Sensor Data ◽  
Multiple Sensors ◽  
Degradation Data ◽  
Degradation Monitoring

Multiple sensors are commonly used for degradation monitoring. Since different sensors may be sensitive at different stages of the degradation process and each sensor data contain only partial information of the degraded unit, data fusion approaches that integrate degradation data from multiple sensors can effectively improve degradation modeling and life prediction accuracy. We present a non-parametric approach that assigns weights to each sensor based on dynamic clustering of the sensors observations. A case study that involves a fatigue-crack-growth dataset is implemented in order evaluate the prognostic performance of the unit. Results show that the fused path obtained with the proposed approach outperforms any individual sensor data and other paths obtained with an adaptive threshold clustering algorithm in terms of life prediction accuracy.

Ressourceneffizienz durch Digitalisierung*/Resource efficiency through digitisation. Potentials for SMEs in the manufacturing industry

2018 ◽  
Vol 108 (05) ◽  
pp. 319-324
Author(s):  
I. Bogdanov ◽  
A. Nuffer ◽  
A. Sauer
Keyword(s):  
Manufacturing Industry ◽  
State Of The Art ◽  
Manufacturing Sector ◽  
Resource Efficiency ◽  
Digitale Transformation ◽  
Case Study Analysis ◽  
Current State ◽  
Stand Der Technik ◽  
A Current

Der vorliegende Beitrag behandelt den Themenkomplex Ressourcen-effizienz und digitale Transformation im verarbeitenden Gewerbe sowie die dabei entstehenden Wechselwirkungen. Neben dem aktuellen Stand der Technik werden die im Rahmen einer aktuellen Studie durchgeführte Fallbeispielanalyse und die entwickelte Methodik zur Ermittlung der Ressourceneffizienzpotenziale vorgestellt. Diese Potenziale und die eingesetzten digitalen Maßnahmen sind zentrale Bausteine des vorliegenden Beitrags.   This article deals with the topic complex of resource efficiency and digital transformation in the manufacturing sector as well as the resulting interactions. In addition to the current state of the art and perspectives, the case study analysis carried out as part of a current study, as well as the developed method for establishing the resource efficiency potentials will be presented. The resultant potential and the digital measures are central components of this article.

Non-directive play therapy with autistic adolescents: a qualitative study of therapists’ interactional practices

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Eliza Maciejewska
Keyword(s):  
Autism Spectrum Disorder ◽  
Conversation Analysis ◽  
Play Therapy ◽  
Autism Spectrum ◽  
Current State ◽  
Local Functions ◽  
Play Therapists ◽  
Practical Implications ◽  
Detailed Picture

Abstract This case study identifies and examines interactional practices of non-directive play therapists during their therapeutic sessions with autistic adolescents. The study involved two therapists and two adolescents (siblings) on the autism spectrum. The video-recorded sessions took place at participants’ home and were conducted in Polish. Employing insights and tools from discourse-analytic approaches, in particular conversation analysis (CA), the findings show how clients and therapists are both involved in co-constructing therapeutic interactions by orienting to each other’s utterances. CA is presented in this article as a useful tool for recognizing and describing the therapists’ interactional contributions and their local functions. The therapeutic practices identified in the analysis (talk-in-practice) – e.g. mirroring, meaning expansion, recast and scaffolding – are further juxtaposed with theories concerning interactional practices in non-directive therapies (talk-in-theory) in order to provide a more detailed picture of these practices as well as complete them. The findings from this study expand the current state of knowledge of non-directive play therapies of autism spectrum disorder (ASD) and carry practical implications for specialists involved in ASD treatment.

A methodology for resiliency assessment of existing bridges – a study on a bridge from 1930

2021 ◽  
Author(s):  
Guy L. Larose ◽  
Pierre-Olivier Dallaire ◽  
Theresa Erskine ◽  
Chiara Pozzuoli ◽  
Emanuele Mattiello
Keyword(s):  
Hazard Assessment ◽  
Health Monitoring ◽  
Ad Hoc ◽  
Rehabilitation Program ◽  
Wind Loading ◽  
Close Collaboration ◽  
Current State ◽  
Design Life ◽  
Existing Bridges

<p>This paper introduces the methodology RWDI has developed, tested and consolidated over the years working in close collaboration with bridge designers, owners and operators, for the multi-hazard assessment of existing bridges and the ad hoc development of a structural health monitoring programme leading to enhanced resiliency. The work is highlighted through the presentation of a case study for a 2,725 m long cantilever bridge built in 1930. The dynamics of the structure in its current state were characterised and its capacity to today and future wind loading was assessed fully following the proposed methodology prior to the initiation of a structural rehabilitation program to extend the design life of the bridge beyond its 150th anniversary.</p>

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