Efficient implementation for accurate analysis of CED circuits against multiple faults

Author(s):  
Ting An ◽  
Kaikai Liu ◽  
Hao Cai ◽  
Lirida Alves de Barros Naviner
2014 ◽  
Vol 19 (2) ◽  
pp. 11-15
Author(s):  
Steven L. Demeter

Abstract The fourth, fifth, and sixth editions of the AMA Guides to the Evaluation of Permanent Impairment (AMA Guides) use left ventricular hypertrophy (LVH) as a variable to determine impairment caused by hypertensive disease. The issue of LVH, as assessed echocardiographically, is a prime example of medical science being at odds with legal jurisprudence. Some legislatures have allowed any cause of LVH in a hypertensive individual to be an allowed manifestation of hypertensive changes. This situation has arisen because a physician can never say that no component of LVH was not caused by the hypertension, even in an individual with a cardiomyopathy or valvular disorder. This article recommends that evaluators consider three points: if the cause of the LVH is hypertension, is the examinee at maximum medical improvement; is the LVH caused by hypertension or another factor; and, if apportionment is allowed, then a careful analysis of the risk factors for other disorders associated with LVH is necessary. The left ventricular mass index should be present in the echocardiogram report and can guide the interpretation of the alleged LVH; if not present, it should be requested because it facilitates a more accurate analysis. Further, if the cause of the LVH is more likely independent of the hypertension, then careful reasoning and an explanation should be included in the impairment report. If hypertension is only a partial cause, a reasoned analysis and clear explanation of the apportionment are required.


TAPPI Journal ◽  
2014 ◽  
Vol 13 (1) ◽  
pp. 33-41
Author(s):  
YVON THARRAULT ◽  
MOULOUD AMAZOUZ

Recovery boilers play a key role in chemical pulp mills. Early detection of defects, such as water leaks, in a recovery boiler is critical to the prevention of explosions, which can occur when water reaches the molten smelt bed of the boiler. Early detection is difficult to achieve because of the complexity and the multitude of recovery boiler operating parameters. Multiple faults can occur in multiple components of the boiler simultaneously, and an efficient and robust fault isolation method is needed. In this paper, we present a new fault detection and isolation scheme for multiple faults. The proposed approach is based on principal component analysis (PCA), a popular fault detection technique. For fault detection, the Mahalanobis distance with an exponentially weighted moving average filter to reduce the false alarm rate is used. This filter is used to adapt the sensitivity of the fault detection scheme versus false alarm rate. For fault isolation, the reconstruction-based contribution is used. To avoid a combinatorial excess of faulty scenarios related to multiple faults, an iterative approach is used. This new method was validated using real data from a pulp and paper mill in Canada. The results demonstrate that the proposed method can effectively detect sensor faults and water leakage.


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