Diagnosis of Multiple Faults: A Sensitivity Analysis

نویسندگان

  • David Heckerman
  • Michael Shwe
چکیده

We compare the diagnostic accuracy of three diagnostic inference models: the simple Bayes model, the multimembership Bayes model, which is isomorphic to the parallel combination function in the certainty-factor model, and a model that incorporates the noisy OR-gate interaction. The comparison is done on 20 clinicopathological conference (CPC) cases from the American Journal of Medicine—challenging cases describing actual patients often with multiple disorders. We find that the distributions produced by the noisy OR model agree most closely with the gold-standard diagnoses, although substantial differences exist between the distributions and the diagnoses. In addition, we find that the multimembership Bayes model tends to significantly overestimate the posterior probabilities of diseases, whereas the simple Bayes model tends to significantly underestimate the posterior probabilities. Our results suggest that additional work to refine the noisy OR model for internal medicine will be worthwhile.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Analysis of Magnetic Flux Linkage Distribution in Salient-Pole Synchronous Generator with Different Kinds of Inter-Turn Winding Faults

A reliable and accurate diagnosis of inter-turn short circuit faults is a challenging problem in the area of fault diagnosis of electrical machines. The purpose of this challenge is to be more efficient in fault detection and to provide a reliable method with low-cost sensors and simple numerical algorithms which not only detect the occurrence of the fault, but also locate its position in the w...

متن کامل

Using Wavelet Support Vector Machine for Fault Diagnosis of Gearboxes

Identifying fault categories, especially for compound faults, is a challenging task in mechanical fault diagnosis. For this task, this paper proposes a novel intelligent method based on wavelet packet transform (WPT) and multiple classifier fusion. An unexpected damage on the gearbox may break the whole transmission line down. It is therefore crucial for engineers and researchers to monitor the...

متن کامل

On the development of a sliding mode observer-based fault diagnosis scheme for a wind turbine benchmark model

This paper addresses the design of an observer-based fault diagnosis scheme, which is applied to some of the sensors and actuators of a wind turbine benchmark model. The methodology is based on a modified sliding mode observer (SMO) that allows accurate reconstruction of multiple sensor or actuator faults occurring simultaneously. The faults are reconstructed using the equivalent output err...

متن کامل

On the development of a sliding mode observer-based fault diagnosis scheme for a wind turbine benchmark model

This paper addresses the design of an observer-based fault diagnosis scheme, which is applied to some of the sensors and actuators of a wind turbine benchmark model. The methodology is based on a modified sliding mode observer (SMO) that allows accurate reconstruction of multiple sensor or actuator faults occurring simultaneously. The faults are reconstructed using the equivalent output err...

متن کامل

Power Auto-transformer Mechanical Faults Diagnosis ‎Using Finite Element based FRA

Frequency response analysis (FRA) is a sensitive ‎method established for testing the mechanical integrity of ‎transformers. However, interpretation of FRA signature still ‎needs expert opinions and there is no FRA interpretation code ‎generally accepted. Various mechanical faults with different ‎extents on power transformers are required to aid FRA ‎interpretation. To address this challenge, in...

متن کامل

AN INTELLIGENT FAULT DIAGNOSIS APPROACH FOR GEARS AND BEARINGS BASED ON WAVELET TRANSFORM AS A PREPROCESSOR AND ARTIFICIAL NEURAL NETWORKS

In this paper, a fault diagnosis system based on discrete wavelet transform (DWT) and artificial neural networks (ANNs) is designed to diagnose different types of fault in gears and bearings. DWT is an advanced signal-processing technique for fault detection and identification. Five features of wavelet transform RMS, crest factor, kurtosis, standard deviation and skewness of discrete wavelet co...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 1993