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Examines the trade‐off between system redundancy and acceptance sampling as alternative means to improve system reliability. We assume that components of the system follow an exponential failure law and investigate expected times to failure of systems of various levels of component redundancy which have been exposed to acceptance sampling plans of various levels of stringency. We also show the probability distributions of system reliability for outgoing lots at various levels of component redundancy and sampling stringency. The paper shows a straightforward method for calculating these trade‐offs and provides the decision maker with a previously unavailable tool of system design and testing.

Aims to use some of the sampling techniques and sampling routines, mentioned in Part 1 of the article, to perform practical tests to determine their differences in withdrawing samples. Uses two different types of systems, a hydraulic system and a gear system, together with some of the investigated sampling techniques. In order to find out the optimum sampling method for each of the two systems, uses a specification of requirements and a systematic approach, together with practical sample withdrawal from the two systems. For the hydraulic system, uses an on‐line particle counter and bottle samples from valves, and for the gear system, applies drain‐plug and vacuum pump sampling. It was found that for hydraulic systems on‐line sampling is the most appropriate, if information on the elements is not required. If information on the elements is required, bottle sampling from a valve together with flushing of the valve should be performed. For the gear system no difference was seen between the samples taken with a vacuum pump and those taken from the drain‐plug, and therefore an alternative method is suggested to improve the reliability of the sampling.

The wear of a machine element, whether it is due to fatigue or abrasive wear, will add contaminants in the form of particulates to the system. If a machine element is starting to wear out it will produce a large amount of particles and it will finally break down. Since this can be very costly, one can establish the need to monitor the system so that one can foresee failure. There are many different ways to monitor a system, e.g. measurements of the temperature, pressure, vibrations and the degree of contamination. The purpose of contamination control is to extend the life of a component and thereby save money. When monitoring a system it is very important that the monitoring control instrument should give the right output. One important factor in achieving this is the withdrawal of a representative oil sample. In this paper an investigation of where and how to take a representative sample is performed using Stokes’ law and the migration of spheres in a channel. A generalised sedimentation chart for different oils and particles is introduced. Sampling routines for proper sample withdrawal are also presented.

The purpose of this paper is to propose a novel condition-based maintenance (CBM) policy with two sampling intervals for a system subject to stochastic deterioration described by the Cox’s proportional hazards model (PHM).

In this paper, the new or renewed system is monitored using a longer sampling interval. When the estimated hazard function of the system exceeds a warning limit, the observations are taken more frequently, i.e., the sampling interval changes to a shorter one. Preventive maintenance is performed when either the hazard function exceeds a maintenance threshold or the system age exceeds a pre-determined age. A more expensive corrective maintenance is performed upon system failure. The proposed model is formulated in the semi-Markov decision process (SMDP) framework.

The optimal maintenance policy is found and a computational algorithm based on policy iteration for SMDP is developed to obtain the control thresholds as well as the sampling intervals minimizing the long-run expected average cost per unit time.

A numerical example is presented to illustrate the whole procedure. The newly proposed maintenance policy with two sampling intervals outperforms previously developed maintenance policies using PHM. The paper compares the proposed model with a single sampling interval CBM model and well-known age-based model. Formulas for the conditional reliability function and the mean residual life are also derived for the proposed model. Sensitivity analysis has been performed to study the effect of the changes in the Weibull parameters on the average cost.

The results show that considerable cost savings can be obtained by implementing the maintenance policy developed in this paper.

Unlike the previous CBM policies widely discussed in the literature which use sequential or periodic monitoring, the authors propose a new sampling strategy based on two sampling intervals. From the economic point of view, when the sampling is costly, it is advantageous to monitor the system less frequently when it is in a healthy state and more frequently when it deteriorates and enters the unhealthy state.

The purpose of this paper is to present a compressed sensing (CS)-based sampling system for ultra-wide-band (UWB) signal. By exploiting the sparsity of signal, this new sampling system can sub-Nyquist sample a multiband UWB signal, whose unknown frequency support occupies only a small portion of a wide spectrum.

A random Rademacher sequence is used to sense the signal in the frequency domain, and a matrix constructed by Hadamard basis is used to compress the signal. The probability of reconstruction is proved mathematically, and the reconstruction matrix is developed in the frequency domain.

Simulation results indicate that, with an ultra-low sampling rate, the proposed system can capture and reconstruct sparse multiband UWB signals with high probability. For sparse multiband UWB signals, the proposed system has potential to break through the Shannon theorem.

Different from the traditional sub-Nyquist techniques, the proposed sampling system not only breaks through the limitation of Shannon theorem but also avoids the barrier of input bandwidth of analog-to-digital converters (ADCs).

An effective chemical conditioning technique was successfully tested and investigated to control and minimize the chemistry-related damages within mixed metallurgy steam and water cycle of Heller dry cooled combined cycle power plants (CCPPs), in which cooling water and condensate are completely mixed in direct contact condenser. This study aims to perform a comprehensive experimental research in four mixed metallurgy steam and water cycle.

A comprehensive experimental study was carried out in four mixed metallurgy steam and water cycle fabricated with ferrous- and aluminum-based alloys which have various corrosion resistance capabilities in contact with water. Chemical conditioning was conducted using both volatile and non-volatile alkalizing agents, and, to perform chemical conditioning effectively, quality parameters (pH, conductivity, dissolved oxygen, sodium, silica, iron, aluminum and phosphate) were monitored by analyzing grab and online samples taken at eight key sampling points.

Results indicated that pH was the most critical parameter which was not mainly within the recommended ranges of widely used standards and guidelines at all key sampling points that generally increases the occurrence of chemistry-related damages. The other quality parameters were mostly satisfactory.

In this research, the development of a suitable chemical conditioning technique in mixed metallurgy steam and water cycle, fabricated with ferrous and aluminum-based alloys, was studied. The obtained results in this thorough research work was evaluated by comparison with the chemistry limits of the widely used standards and guidelines, and combined use of volatile and solid alkalizing agents was considered as a promising chemical conditioning technique for utilization in mixed metallurgy units of Heller dry cooled CCPPs.

Selects one of Hamaker′s procedures for deriving a “σ” method (i.e. known process standard deviation) double sampling plan and exploits some of its properties to develop a system of “s” method (i.e. unknown process standard deviation) double sampling plans by variables that match the system of single specification limit “s” method single sampling plans of the current edition of the international standard on sampling by variables. ISO 3951: 1989. The new system is presented in two forms, the second of which may also be used for combined double specification limits and multivariate acceptance sampling.

A table and a procedure are given for finding the single‐sampling quick switching system for which the sum of producer′s and consumer′s risks is minimum for specified Acceptable Quality Level and Limiting Quality Level.

The purpose of this paper is to improve the transient response and the inter‐sample behavior of a model reference adaptive control system by an appropriate selection of the fractional order hold (FROH) gain β and the multirate gains used in the control reconstruction signal through a fully freely chosen reference model even when the continuous plant possesses unstable zeros.

A multiestimation adaptive control scheme for linear time‐invariant continuous‐time plant with unknown parameters is presented. The set of discrete adaptive models is calculated from a different combination of the correcting gain β in a FROH and the set of gains to reconstruct the plant input under multirate sampling with fast input sampling. Then the scheme selects online the model with the best continuous‐time tracking performance which includes a measure of the inter‐sample ripple, which is improved. The estimated discrete unstable zeros are avoided through an appropriate design of the multirate gains so that the reference model might be freely chosen with no constraints on potential unstable zeros.

The scheme is able to select online the discretization model with the best continuous‐time tracking performance without an appropriate initialization.

The switching mechanism among the different models should maintain in operation the active discretization model at least for a minimum residence time in order to guarantee closed‐loop stability. The inter‐sample behavior is improved, but it is not always completely removed.

The transient response and the inter‐sample behavior are improved by using this multiestimation‐based discrete controller compared with a single estimation‐based one. The implementation of discrete controllers makes it easier and cheaper to implement and also more reliable than continuous‐time controllers.

The main innovation of the paper compared with previous background work is that the reference output is supplied by a stable continuous transfer function. Then the scheme is able to partly regulate the continuous‐time tracking error while the controller is essentially discrete‐time and operated by a FROH in general.

The purpose of this paper is to present research in the area of control method for the man‐machine systems with brain machine interface (BMI). Concrete target system is, for instance, a car cruising system and so on.

The improved receding horizon control (RHC) method for the sampled‐data systems and the adaptive digital‐to‐analog (DA) converter which has the way to switch the sampling functions according to the system status are used. The feature selection method based on the kernel support vector machines with the backward stepwise selection for the BMI signals are also used.

This paper proposes the new improved RHC method with the adaptive DA converter for the application of the BMI‐based systems. The proposed method is illustrated as useful and effective method for the systems to which switch of control laws is indispensable by the simulations.

Although the proposed method is effective for the BMI‐based systems with switching of control laws, the faster algorithm for RHC will be need to apply to the man‐machine systems with the BMI in practical use.

The basic concept or framework of the proposed method can be used for the real man‐machine systems with the BMI, for examples, car crusing systems, wheel‐chaired systems and so on.

The paper contributes to the development of the new effective control method for the BMI‐based man‐machine systems.