Surveillance system and method having an adaptive sequential probability fault detection test

System and method providing surveillance of an asset such as a process and/or apparatus by providing training and surveillance procedures that numerically fit a probability density function to an observed residual error signal distribution that is correlative to normal asset operation and then utilizes the fitted probability density function in a dynamic statistical hypothesis test for providing improved asset surveillance

Automated Monitoring with a BSP Fault-Detection Test

The figure schematically illustrates a method and procedure for automated monitoring of an asset, as well as a hardware- and-software system that implements the method and procedure. As used here, asset could signify an industrial process, power plant, medical instrument, aircraft, or any of a variety of other systems that generate electronic signals (e.g., sensor outputs). In automated monitoring, the signals are digitized and then processed in order to detect faults and otherwise monitor operational status and integrity of the monitored asset. The major distinguishing feature of the present method is that the fault-detection function is implemented by use of a Bayesian sequential probability (BSP) technique. This technique is superior to other techniques for automated monitoring because it affords sensitivity, not only to disturbances in the mean values, but also to very subtle changes in the statistical characteristics (variance, skewness, and bias) of the monitored signals

Automated Monitoring with a BCP Fault-Decision Test

The Bayesian conditional probability (BCP) technique is a statistical fault-decision technique that is suitable as the mathematical basis of the fault-manager module in the automated-monitoring system and method described in the immediately preceding article. Within the automated-monitoring system, the fault-manager module operates in conjunction with the fault-detector module, which can be based on any one of several fault-detection techniques; examples include a threshold-limit-comparison technique or the BSP or SPRT technique mentioned in the preceding article. The present BCP technique is used to evaluate a series of one or more fault-detection events for the purpose of filtering out occasional false alarms produced by many types of statistical fault-detection procedures. The BCP technique increases the probability that an automated monitoring system produces a correct decision regarding the presence or absence of a fault. Because occasional false alarms are an inevitable consequence of the SPRT, BSP, or any other statistically based fault-detection test, there is a need for a logical procedure to distinguish between true and false alarms. Heretofore, it has been common practice to make a fault decision on an ad hoc basis for example by following a multiple-observation voting strategy in which a signal is declared to be indicative of a fault if m of the last n observations produced a fault-detection alarm. The BCP technique was developed to obtain results more reliable than those afforded by a voting strategy. The BCP technique involves a test in which one applies Bayesian inference techniques to a series of one or more single-observation alarms produced by a fault-detection test. One considers the last n decisions generated by a fault-detection test in order to evaluate the conditional probability that a failure is indicated (see figure). Each new decision reached by a fault-detection test is treated as a new piece of evidence about the state of the monitored asset, and the conditional probability of failure for the system is updated on the basis of this new evidence. The conditional probability of failure is compared with a predefined limit. For a probability below the limit, the asset is declared to be healthy. For a probability above the limit, the asset is declared to be faulty

Finite element model for vibration and buckling of functionally graded sandwich beams based on a refined shear deformation theory

Finite element model for vibration and buckling of functionally graded sandwich beams based on a refined shear deformation theory is presented. The core of sandwich beam is fully metal or ceramic and skins are composed of a functionally graded material across the depth. Governing equations of motion and boundary conditions are derived from the Hamilton’s principle. Effects of power-law index, span-to-height ratio, core thickness and boundary conditions on the natural frequencies, critical buckling loads and load–frequency curves of sandwich beams are discussed. Numerical results show that the above-mentioned effects play very important role on the vibration and buckling analysis of functionally graded sandwich beams

Senior Inquiry: Diversity of the Human Experience

This collaboratively created poster summarizes, in graphic form, the Senior Inquiry students\u27 year-long course of study

Intraspecific and biogeographical variation in foliar fungal communities and pathogen damage of native and invasive Phragmites australis

AimRecent research has highlighted that the relationship between species interactions and latitude can differ between native and invasive plant taxa, generating biogeographical heterogeneity in community resistance to plant invasions. In the first study with foliar pathogens, we tested whether co‐occurring native and invasive lineages of common reed (Phragmites australis) exhibit non‐parallel latitudinal gradients in foliar fungal communities, pathogen susceptibility and damage, and whether these biogeographical patterns can influence the success of invasion.LocationNorth America.Time period2015–2017.Major taxa studiedPerennial grass P. australis.MethodsWe surveyed 35 P. australis field populations, spanning 17° latitude and comprising four phylogeographical lineages, including one endemic to North America and one invasive from Europe. For each population, we quantified the percentage of leaf pathogen damage and cultured fungi from diseased leaves, which we identified using molecular tools. To assess whether latitudinal gradients in pathogen damage had a genetic basis, we inoculated plants from 73 populations with four putative pathogens in a complementary common garden experiment and measured P. australis susceptibility (i.e., diseased leaf area).ResultsWe isolated 84 foliar fungal taxa. Phragmites australis lineage influenced fungal community composition but not diversity. Despite the invasive European P. australis lineage being the least susceptible to three of the four pathogens tested in the common garden experiment, pathogen damage in the field was similar between native and invasive lineages, providing no evidence that release from foliar pathogens contributes to the success of invasion. Genetically based latitudinal gradients in pathogen susceptibility observed in the common garden were isolate specific and obscured by local environmental conditions in the field, where pathogen damage was threefold higher for northern compared with southern populations, regardless of lineage.Main conclusionsOur results highlight that host plant lineage and genetically based biogeographical gradients strongly influence foliar fungal communities and pathogen susceptibility, but do not translate to patterns of pathogen damage observed in the field.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/155999/1/geb13097.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/155999/2/geb13097_am.pd