Equipment Performance Monitoring Research Articles

Online remaining useful life prognostics using an integrated particle filter

The lifetime evolution of mechanical equipment with complicated structure and the harsh operating environment cannot be accurately expressed due to the dynamics of the failure mechanism. However, the performance monitoring of equipment, with the information characterizing the failure process from the sensed data, can be used to assess the failure time and then the online remaining useful life. Because of the existence of nonlinearity and non-Gaussian for most real systems, for online assessment, unscented Kalman filter combined with particle filter is studied, instead of the standard particle filter with importance sampling, which is modified to update the states iteratively. Meanwhile, Markov chain Monte Carlo is performed after resampling to improve the prediction accuracy. In the modeling, state–space model is developed to quantify the relationship between the information from online observation and underlying degradation, and the unscented particle filter is investigated to realize the assessment of remaining useful life. In particular, the sufficient statistic method is presented to obtain a joint recursive estimation on both the system state and model parameters for those state–space model with unknown time-invariant ones. At the end of this article, the acoustic emission signals of a milling cutter are illustrated as a case study for cutter online remaining useful life estimate. The milling cutter example demonstrates the effectiveness of the proposed method for online estimate and provides useful insights regarding the necessity of online updating and the assessment.

AIUM Practice Parameter for the Performance of Ultrasound Vascular Mapping for Preoperative Planning of Dialysis Access

AIUM Practice Parameter for the Performance of Ultrasound Vascular Mapping for Preoperative Planning of Dialysis Access

AIUM Practice Parameter for the Performance of an Ultrasound Examination of the Neonatal and Infant Spine

AIUM Practice Parameter for the Performance of an Ultrasound Examination of the Neonatal and Infant Spine

AIUM Practice Parameter for the Performance of a Thyroid and Parathyroid Ultrasound Examination.

AIUM Practice Parameter for the Performance of a Thyroid and Parathyroid Ultrasound Examination.

AIUM Practice Parameter for the Performance of an Ultrasound Examination of the Neonatal and Infant Spine.

AIUM Practice Parameter for the Performance of an Ultrasound Examination of the Neonatal and Infant Spine.

A data reconciliation based framework for integrated sensor and equipment performance monitoring in power plants

Power plant on-line measured operational data are often corrupted with random and gross errors. The data reconciliation method can reduce the impact of random errors by adjusting redundant measurements to satisfy system constraints and detect gross errors together with a statistical test method. In previous studies, the data reconciliation method is mainly used to deal with measurements with random and gross errors, and its application is mainly in the data preprocessing areas. In this work, we extend the data reconciliation and gross error detection method to cover both sensor and equipment performance monitoring in power plants, through introducing equipment characteristic constraints together with characteristic parameter dominant factor models in the data reconciliation method. The validity and capability of the proposed framework are illustrated with case studies in the feed water regenerative heating system of a 1000MW ultra-supercritical coal-fired power generation unit. Case study results show that the characteristic parameter dominant factor models have relative root mean squared errors smaller than 2.3%, whilst the distribution properties of the test statistics for the integrated sensor and equipment performance monitoring are validated with simulated test statistic samples. We also illustrate that the proposed framework can efficiently detect and identify both sensor biases and equipment faults in the system. At the same time, the ability of the data reconciliation and global test method for measurement gross error detection is also improved due to the increased system redundancy under the proposed framework.

Measurement of scatter radiation from the GE Infinia Hawkeye 4 SPECT/CT system

In this study the cumulative scatter dose from a typical monthly SPECT/CT workload on a new GE Infinia Hawkeye 4 system was measured by means of a dosimeter badge survey. Doses were found to be well within regulatory limits. Scatter dose rates attributable solely to the CT component were also measured experimentally for comparison with the manufacturer's isocontour plot. The measured CT dose rate isocontours were found to be of similar magnitude and location to those quoted by the manufacturer. Data generated from this study will form a valuable baseline for the monitoring of equipment performance and for future scatter radiation measurements.

Some effective control chart procedures for reliability monitoring

Abstract Control charts are widely used for process monitoring in the manufacturing industry. Little research is available on their use to monitor the failure process of components or systems, which is important for equipment performance monitoring. Some Shewhart control charts, especially those for the number of defects, can be used for monitoring the number of failures per fixed interval; however, they are not effective especially when the failure frequency becomes small. A recent control scheme based on the cumulative quantity between observations of defects has been proposed which can be easily adopted to monitor the failure process for exponentially distributed inter-failure time. An investigation of its use for reliability monitoring is presented in this paper and the scheme can be easily extended to monitor inter-failure times that follow other distributions such as the Weibull distribution. Furthermore, the scheme is extended to the monitoring of time required to observe a fixed number of failures. The advantages of this scheme include the fact that the scheme does not require any subjective sample size, can be used for both high and low reliability items and can detect process improvement even in a high-reliability environment.

Planning and using industrial television

There are many sections in metallurgical plants difficult to observe directly or dangerous to observers where monitoring of equipment performance or activities is required for control of the production process. Automatic devices, remote control mechanisms, telecommunications, or television are often used in such places to ease working conditions and improve process control. Use of industrial television began in the USSR and abroad almost simultaneously in the ferrous metallurgy sector in the early 1950s. The first use of industrial television in our country was at the Magnitogorsk Metallurgical Combine.