Efficient fault diagnosis of helicopter gearboxes

Application of a diagnostic system to a helicopter gearbox is presented. The diagnostic system is a nonparametric pattern classifier that uses a multi-valued influence matrix (MVIM) as its diagnostic model and benefits from a fast learning algorithm that enables it to estimate its diagnostic model from a small number of measurement-fault data. To test this diagnostic system, vibration measurements were collected from a helicopter gearbox test stand during accelerated fatigue tests and at various fault instances. The diagnostic results indicate that the MVIM system can accurately detect and diagnose various gearbox faults so long as they are included in training

Helicopter transmission research at NASA Lewis Research Center

A joint helicopter transmission research program between NASA Lewis Research Center and the U.S. Army Aviation Systems Command has existed since 1970. Program goals are to reduce weight and noise and to increase life and reliability. Reviewed are significant advances in technology for gears and transmissions and the experimental facilities at NASA Lewis for helicopter transmission testing are described. A description of each of the rigs is presented along with some significant results from the experiments

Transmission diagnostic research at NASA Lewis Research Center

The NASA Lewis Research Center and the U.S. Army Research Laboratory are involved in a joint research program to advance the technology of aerospace transmissions. Within the last six years, a transmission diagnostics research team was formed to address current and future technology barriers in transmission diagnostics. The diagnostics team conducted a survey to determine critical needs of the diagnostics community. Survey results indicated that experimental verification of gear and bearing fault detection methods and damage magnitude assessment were considered the two most critical research areas of a highly reliable health and usage monitoring system. A plan was implemented by the diagnostics team to address these key research areas, by in-house research and university grants. A variety of transmission fault detection methods were applied to experimentally obtained fatigue data. Failure modes of the fatigue tests include a variety of gear pitting failures, tooth wear, tooth fracture, and bearing spalling failures. Accomplishments to date include verification of several specific gear diagnostic methods, verification of a new pattern recognition method to determine failure, and development of a new method to model gear tooth damage. This paper presents the results of these accomplishments in transmission diagnostics research at NASA Lewis Research Center

Machine learning for automatic prediction of the quality of electrophysiological recordings

The quality of electrophysiological recordings varies a lot due to technical and biological variability and neuroscientists inevitably have to select “good” recordings for further analyses. This procedure is time-consuming and prone to selection biases. Here, we investigate replacing human decisions by a machine learning approach. We define 16 features, such as spike height and width, select the most informative ones using a wrapper method and train a classifier to reproduce the judgement of one of our expert electrophysiologists. Generalisation performance is then assessed on unseen data, classified by the same or by another expert. We observe that the learning machine can be equally, if not more, consistent in its judgements as individual experts amongst each other. Best performance is achieved for a limited number of informative features; the optimal feature set being different from one data set to another. With 80–90% of correct judgements, the performance of the system is very promising within the data sets of each expert but judgments are less reliable when it is used across sets of recordings from different experts. We conclude that the proposed approach is relevant to the selection of electrophysiological recordings, provided parameters are adjusted to different types of experiments and to individual experimenters

The Fermat-Torricelli problem in normed planes and spaces

We investigate the Fermat-Torricelli problem in d-dimensional real normed spaces or Minkowski spaces, mainly for d=2. Our approach is to study the Fermat-Torricelli locus in a geometric way. We present many new results, as well as give an exposition of known results that are scattered in various sources, with proofs for some of them. Together, these results can be considered to be a minitheory of the Fermat-Torricelli problem in Minkowski spaces and especially in Minkowski planes. This demonstrates that substantial results about locational problems valid for all norms can be found using a geometric approach

An analysis of integrative outcomes in the Dayton peace negotiations

The nature of the negotiated outcomes of the eight issues of the Dayton Peace Agreement was studied in terms of their integrative and distributive aspects. in cases where integrative elements were Sound, further analysis was conducted by concentrating on Pruitt's five types of integrative solutions: expanding the pie, cost cutting, non-specific compensation, logrolling, and bridging. The results showed that real world international negotiations can arrive at integrative agreements even when they involve redistribution of resources tin this case the redistribution of former Yugoslavia). Another conclusion was that an agreement can consist of several distributive outcomes and several integrative outcomes produced by different kinds of mechanisms. Similarly, in single issues more than one mechanism can be used simultaneously. Some distributive bargaining was needed in order to determine how much compensation was required. Finally, each integrative formula had some distributive aspects as well

Looking for leakage or monitoring for public assurance?

Monitoring is a regulatory requirement for all carbon dioxide capture and geological storage (CCS) projects to verify containment of injected carbon dioxide (CO2) within a licensed geological storage complex. Carbon markets require CO2 storage to be verified. The public wants assurances CCS projects will not cause any harm to themselves, the environment or other natural resources. In the unlikely event that CO2 leaks from a storage complex, and into groundwater, to the surface, atmosphere or ocean, then monitoring methods will be required to locate, assess and quantify the leak, and to inform the community about the risks and impacts on health, safety and the environment. This paper considers strategies to improve the efficiency of monitoring the large surface area overlying onshore storage complexes. We provide a synthesis of findings from monitoring for CO2 leakage at geological storage sites both natural and engineered, and from monitoring controlled releases of CO2 at four shallow release facilities – ZERT (USA), Ginninderra (Australia), Ressacada (Brazil) and CO2 field lab (Norway)

Continuous wave optical parametric oscillator for quartz-enhanced photoacoustic trace gas sensing

A continuous wave optical parametric oscillator, generating up to 300 mW idler output in the 3–4 μm wavelength region, and pumped by a fiber-amplified DBR diode laser is used for trace gas detection by means of quartz-enhanced photoacoustic spectroscopy (QEPAS). Mode-hop-free tuning of the OPO output over 5.2 cm-1 and continuous spectral coverage exceeding 16.5 cm-1 were achieved via electronic pump source tuning alone. Online monitoring of the idler wavelength, with feedback to the DBR diode laser, provided an automated closed-loop control allowing arbitrary idler wavelength selection within the pump tuning range and locking of the idler wavelength with a stability of 1.7×10-3 cm-1 over at least 30 min.\ud \ud Using this approach, we locked the idler wavelength at an ethane absorption peak and obtained QEPAS data to verify the linear response of the QEPAS signal at different ethane concentrations (100 ppbv-20 ppmv) and different power levels. The detection limit for ethane was determined to be 13 ppbv (20 s averaging), corresponding to a normalized noise equivalent absorption coefficient of 4.4×10-7 cm-1  W/Hz1/2

Bilateral negotiation in a multi-agent supply chain system

A supply chain is a set of organizations directly linked by flows of services from suppliers to customers. Supply chain activities range from the ordering and receipt of raw materials to the production and distribution of finished goods. Supply chain management is the integration of key activities across a supply chain for the purposes of building competitive infrastructures, synchronizing supply with demand, and leveraging worldwide logistics. This paper addresses the challenges created by supply chain management towards improving long-term performance of companies. It presents a multi-agent supply chain system composed of multiple software agents, each responsible for one or more supply chain activities, and each interacting with other agents in the execution of their responsibilities. Additionally, this paper presents the key features of a negotiation model for software agents. The model handles bilateral multi-issue negotiation and incorporates an alternating offers protocol, a set of logrolling strategies, and a set of negotiation tactics