Permissible Area Analyses of Measurement Errors with Required Fault Diagnosability Performance

Jiang, Dongnian; Li, Wei

doi:10.3390/s19224880

Cited by 4 publications

(2 citation statements)

References 23 publications

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“…Jiang et al proposed a fault diagnosis system that took into account a measurement error problem [23]. They assumed that the measurement error usually follows a normal distribution.…”

Section: Application Modelmentioning

confidence: 99%

Differentially Private Mobile Crowd Sensing Considering Sensing Errors

Sei

Ohsuga

2020

Sensors

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An increasingly popular class of software known as participatory sensing, or mobile crowdsensing, is a means of collecting people’s surrounding information via mobile sensing devices. To avoid potential undesired side effects of this data analysis method, such as privacy violations, considerable research has been conducted over the last decade to develop participatory sensing that looks to preserve privacy while analyzing participants’ surrounding information. To protect privacy, each participant perturbs the sensed data in his or her device, then the perturbed data is reported to the data collector. The data collector estimates the true data distribution from the reported data. As long as the data contains no sensing errors, current methods can accurately evaluate the data distribution. However, there has so far been little analysis of data that contains sensing errors. A more precise analysis that maintains privacy levels can only be achieved when a variety of sensing errors are considered.

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“…Jiang et al proposed a fault diagnosis system that took into account a measurement error problem [23]. They assumed that the measurement error usually follows a normal distribution.…”

Section: Application Modelmentioning

confidence: 99%

Differentially Private Mobile Crowd Sensing Considering Sensing Errors

Sei

Ohsuga

2020

Sensors

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“…Aiming at the problem of sensor initial fault detection and isolation, Homi Bhabha National Institute proposed a fault detection index and fault signature based on extended Kalman filter and designed fault decision statistics using KLD [1]. To improve the accuracy of the quantitative evaluation of fault detection, a method based on KLD to design the permissible area of measurement errors is proposed [2]. According to the difference between online estimated and offline reference density functions, Bounoua et al proposed a principal component analysis method based on KLD [3].…”

Section: Introductionmentioning

confidence: 99%

Optimized KLD-Based Fault Detection Method for Complex System Under Multi-Operation Conditions

Shi

Zhou

et al. 2020

IEEE Access

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With the increasing development of industrial technology, fault detection technology has been widely applied in many complex systems. Aiming at the problems of multi-operation conditions and the data length needed for fault detection using Kullback-Leibler Divergence (KLD), a novel fault detection method for complex systems based on optimized KLD under multi-operation conditions is proposed in this paper. In the first place, based on the historical data of the system, the complex operation conditions of the system are divided into several simple mutually exclusive operation conditions, and the division standard is established. In the next place, the optimal length can be quickly determined by autocorrelation analysis and applied to various operation conditions. After the next, in the training stage, the KLD values of all training data are calculated with the benchmark that is the initial optimal data length of each operation condition. And the maximum value is taken as the threshold for fault detection. Afterward, in the test phase, it starts by judging the type of operation condition that the data belongs to, then the corresponding KLD value is calculated, which is compared with the corresponding threshold, so as to determine whether the fault occurs. Eventually, this method is applied to the suspension system of the maglev train and respectively compared with the fault detection methods based on Euclidean distance or Mahalanobis distance. The results show that the proposed method possesses a low false alarm rate and high sensitivity.

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A review of research on diagnosability of control systems

Gu,

Shi

2024

Energy Reports

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Permissible Area Analyses of Measurement Errors with Required Fault Diagnosability Performance

Cited by 4 publications

References 23 publications

Differentially Private Mobile Crowd Sensing Considering Sensing Errors

Differentially Private Mobile Crowd Sensing Considering Sensing Errors

Optimized KLD-Based Fault Detection Method for Complex System Under Multi-Operation Conditions

A review of research on diagnosability of control systems

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