Kombination von Messdaten und wissensbasierter Modellierung zur Fehlerdiagnose bei Weichen / Connecting measurement data and knowledge-based engineering for heavy rail switch fault diagnosis

Die Anwendung Künstlicher Intelligenz (KI) im Bereich Prognostics and Health Management (PHM) der Eisenbahninfrastruktur, insbesondere in der Fehlerdiagnose, wird durch hinsichtlich Umfang und/oder Labelling unzureichende Datenbestände und die Notwendigkeit der Rückverfolgbarkeit aufgrund strenger Sicherheitsvorschriften erschwert. Vielversprechende Ansätze sind Feature Engineering, unüberwachtes Lernen und wissensbasierte Systeme. Vor diesem Hintergrund wird nachfolgend erörtert, wie Stromumlaufkurven von Weichenantrieben ausgewertet und mit einem für den Menschen interpretierbaren Bayes'schen Netzmodell für Diagnosezwecke verbunden werden können. -- The application of AI methods in prognostics and health management, especially fault diagnosis, for railway infrastructure is complicated by the largely unlabelled databases and the necessity for traceability due to strict safety regulations. Promising approaches include feature engineering, unsupervised learning and knowledge-based systems. This article discusses how to treat the current curve measurements of railway point machines and connect them with a human-interpretable Bayesian network model for diagnostic purposes

Directed evolution of an enantioselective Bacillus subtilis lipase

Chiral compounds are of steadily increasing importance to the chemical industry, in particular for the production of pharmaceuticals. Where do these compounds come from? Apart from natural resources, two synthetic strategies are available: asymmetric chemical catalysis using transition metal catalysts and biocatalysis using enzymes. In the latter case, screening programs have identified a number of enzymes. However, their enantioselectivity is often not high enough for a desired reaction. This problem can be solved by applying directed evolution to create enantioselective enzymes as shown here for a lipase from Bacillus subtilis. The reaction studied was the asymmetric hydrolysis of meso-1,4-diacetoxy-2-cyclopentene with the formation of chiral alcohols which were detected by electrospray ionization mass spectrometry. Iterative cycles of random mutagenesis and screening allowed the identification of several variants with improved enantioselectivities. In parallel, we have started to use X-ray structural data to simulate the Bacillus subtilis lipase A-catalyzed substrate hydrolysis by using quantum mechanical and molecular mechanical calculations. This combined approach should finally enable us to devise more efficient strategies for the directed evolution of enantioselective enzymes

Expert system based fault diagnosis for railway point machines

To meet the increasing demands for availability at reasonable cost, operators and maintainers of railway point machines are constantly looking for innovative techniques for switch condition monitoring and prediction. This includes automated fault root cause diagnosis based on measurement data (such as motor current curves) and other information. However, large, comprehensive sets of labeled data suitable for standard machine learning are not yet available. Existing data-driven approaches focus only on the differentiation of a few major fault categories at the level of the measurement data (i.e. the "fault symptoms"). There is great potential in hybrid models that use expert knowledge in combination with multiple sources of information to automatically identify failure causes at a much more detailed level. This paper discusses a Bayesian network diagnostic model for determining the root causes of faults in point machines, based on expert knowledge and few labeled data examples from the Netherlands. Human-interpretable current curve features and other information sources (e.g. past maintenance actions) are used as evidence. The result of the model is a ranking of the most likely failure causes with associated probabilities in terms of fuzzy multi-label classification, which is directly aimed at providing decision support to maintenance engineers. The validity and limitations of the model are demonstrated by a scenario-based evaluation and a brief analysis using information theoretic measures. We present the information sources used, the detailed development process and the analysis methodology. This article is intended to be a guide to developing similar models for various complex technical assets

Protocol of a randomized, double-blind, placebo-controlled, parallel-group, multicentre study of the efficacy and safety of nicotinamide in patients with Friedreich ataxia (NICOFA)

Introduction: Currently, no treatment that delays with the progression of Friedreich ataxia is available. In the majority of patients Friedreich ataxia is caused by homozygous pathological expansion of GAA repeats in the first intron of the FXN gene. Nicotinamide acts as a histone deacetylase inhibitor. Dose escalation studies have shown, that short term treatment with dosages of up to 4 g/day increase the expression of FXN mRNA and frataxin protein up to the levels of asymptomatic heterozygous gene carriers. The long-term effects and the effects on clinical endpoints, activities of daily living and quality of life are unknown.Methods: The aim of the NICOFA study is to investigate the efficacy and safety of nicotinamide for the treatment of Friedreich ataxia over 24 months. An open-label dose adjustment wash-in period with nicotinamide (phase A: weeks 1-4) to the individually highest tolerated dose of 2-4 g nicotinamide/day will be followed by a 2 (nicotinamide group): 1 (placebo group) randomization (phase B: weeks 5-104). In the nicotinamide group, patients will continue with their individually highest tolerated dose between 2 and 4 g/d per os once daily and the placebo group patients will be receiving matching placebo. Safety assessments will consist of monitoring and recording of all adverse events and serious adverse events, regular monitoring of haematology, blood chemistry and urine values, regular measurement of vital signs and the performance of physical examinations including cardiological signs. The primary outcome is the change in the Scale for the Assessment and Rating of Ataxia (SARA) over time as compared with placebo in patients with Friedreich ataxia based on the linear mixed effect model (LMEM) model. Secondary endpoints are measures of quality of life, functional motor and cognitive measures, clinician's and patient's global impression-change scales as well as the up-regulation of the frataxin protein level, safety and survival/death.Perspective: The NICOFA study represents one of the first attempts to assess the clinical efficacy of an epigenetic therapeutic intervention for this disease and will provide evidence of possible disease modifying effects of nicotinamide treatment in patients with Friedreich ataxia

Ways to Develop Specialists in Engineering Activities: Professional Development and Retraining

This article discusses ways to develop an engineer in the form of professional development and retraining courses. The relevance of this topic is due to the lack of students' and professionals' awareness of the importance of further engineering education, the lack of interest in getting additional paid education, and the bad quality of additional education in Russia

Long-term stability of a life insurer’s balance sheet

In this paper, we devise a stochastic asset–liability management (ALM) model for a life insurance company and analyze its influence on the balance sheet within a low-interest rate environment. In particular, a flexible procedure for the generation of insurers’ compressed contract portfolios that respects the given biometric structure is presented, extending the existing literature on stochastic ALM modeling. The introduced balance sheet model is in line with the principles of double-entry bookkeeping as required in accounting. We further focus on the incorporation of new business, i.e. the addition of newly concluded contracts and thus of insured in each period. Efficient simulations are obtained by integrating new policies into existing cohorts according to contract-related criteria. We provide new results on the consistency of the balance sheet equations. In extensive simulation studies for different scenarios regarding the business form of today’s life insurers, we utilize these to analyze the long-term behavior and the stability of the components of the balance sheet for different asset–liability approaches. Finally, we investigate the robustness of two prominent investment strategies against crashes in the capital markets, which lead to extreme liquidity shocks and thus threaten the insurer’s financial health

Analysis of Local Track Discontinuities and Defects in Railway Switches Based on Track-Side Accelerations

Switches are an essential, safety-critical part of the railway infrastructure. Compared to open tracks, their complex geometry leads to increased dynamic loading on the track superstructure from passing trains, resulting in high maintenance costs. To increase efficiency, condition monitoring methods specific to railway switches are required. A common approach to track superstructure monitoring is to measure the acceleration caused by vehicle track interaction. Local interruptions in the wheel–rail contact, caused for example by local defects or track discontinuities, appear in the data as transient impact events. In this paper, such transient events are investigated in an experimental setup of a railway switch with track-side acceleration sensors, using frequency and waveform analysis. The aim is to understand if and how the origins of these impact events can be distinguished in the data of this experiment, and what the implications for condition monitoring of local track discontinuities and defects with wayside acceleration sensors are in practice. For the same experimental configuration, individual impact events are shown to be reproducible in waveform and frequency content. Nevertheless, with this track-side sensor setup, the different types of track discontinuities and defects (squats, joints, crossing) could not be clearly distinguished using characteristic frequencies or waveforms. Other factors, such as the location of impact event origin relative to the sensor, are shown to have a much stronger influence. The experimental data suggest that filtering the data to narrow frequency bands around certain natural track frequencies could be beneficial for impact event detection in practice, but differentiating between individual impact event origins requires broadband signals. A multi-sensor setup with time-synchronized acceleration sensors distributed over the switch is recommended.Validerad;2024;Nivå 2;2024-04-08 (hanlid);Full text license: CC BY 4.0</p

Modellierung und Simulation atypischer Merkmale bei Weichenstellstromkurven / Modelling and simulating the atypical features of switch engine current curves

Störungen elektromechanischer Weichen lassen sich oft anhand des zeitlichen Verlaufs der Motorstellstromaufnahmeerkennen und analysieren. Die mathematische Beschreibung der Stellstromkurven anhand geeigneter statistischer und geometrischer Merkmale ist die Basis für eine fortschreitende Digitalisierung und Automatisierung der Prozesse zur Zustandsdetektion und Fehlerdiagnose. Der vorliegende Beitrag zeigt aktuelleAnsätze und diskutiert die Chancen und Herausforderungen der synthetischen Erzeugung von Daten mittels merkmalsbasierter Modelle für normale und anormale Stellstromkurven. The current curves of point machines are a good indi cator for identifying and analysing any faults in electro-mechanical switches. The mathematical representation of current curves based on their statistical and geometrical features is therefore essential for the ongoing digitalisation and automation of processes such as condition monitoring and fault diagnosis. This contribution presents recent results with regard to current curve modelling and discusses the chances and challenges of synthetically generating data using feature-oriented models for normal and abnormal current curves