Reliability Of Measurement System Research Articles

On the determination of the standing oblique detonation wave in an engine combustor using laser absorption spectroscopy of hydroxyl radical

Freejet experiments were conducted in the hypersonic flight-duplicated shock tunnel (JF-12) to understand the detonation combustion mode in the combustor of a standing oblique detonation ramjet (Sodramjet) engine prototype. Besides the traditional schlieren imaging to capture the oblique shock positions in the combustor, we implemented laser absorption spectroscopy of hydroxyl (OH) radical with three laser beams around the shock front. The Sodramjet engine combustor provides an ideal condition to measure OH because its molar fraction within the detonation front is estimated to exceed 0.03, which is much higher than other combustors. However, the harsh environment of freejet shock tunnel test poses a great challenge to the reliability of measurement systems. In this work, near-infrared tunable laser diode sensors centered at 1528 nm were chosen to measure the line-of-sight average of OH partial pressure. Continuous absorption measurements were conducted near the shock front, indicating a thin OH region after shock compression that could only be achieved by detonation combustion. The time-varied OH partial pressure was well predicted by the computational fluid dynamics (CFD) prediction. Our measurement results verified the detonation combustion of Sodramjet engine prototype and showed that in situ, real-time detonation diagnostics based on laser absorption spectroscopy is possible in freejet experiments of shock tunnel.

Testing Rogowski Coils with Merging Units for Smart Grids

As smart grids incorporate renewable energy sources and advanced power electronics, ensuring accurate measurement systems becomes paramount due to the increased complexity and potential sources of disturbances. This article focuses on the laboratory calibration of Rogowski coils (RCs) and merging units (MUs), which are fundamental for measuring, controlling, and monitoring digital power systems. A comprehensive digital calibration system is introduced, utilizing precise, commercially available components such as a fluxgate current transducer and a National Instrument. The system assesses magnitude and phase displacement errors under various operating conditions, including abnormal scenarios. Additionally, the impact of uncertainty sources on the measurement chain analysis is discussed, with test results conforming to established standards. This research contributes to enhancing the accuracy and reliability of measurement systems in the context of evolving smart grids.

Predictions for Bending Strain at the Tower Bottom of Offshore Wind Turbine Based on the LSTM Model

In recent years, the demand and requirement for renewable energy have significantly increased due to concerns regarding energy security and the climate crisis. This has led to a significant focus on wind power generation. As the deployment of wind turbines continues to rise, there is a growing need to assess their lifespan and improve their stability. Access to accurate load data is crucial for enhancing safety and conducting remaining life assessments of wind turbines. However, maintaining and ensuring the reliability of measurement systems for long-term load data accumulation, stability assessments, and residual life evaluations can be challenging. As a result, numerous studies have been conducted on load prediction for wind turbines. However, existing load prediction models based on 10 min statistical data cannot adequately capture the short-term load variations experienced by wind turbines. Therefore, it is essential to develop models capable of predicting load with a high temporal resolution to enhance reliability, especially with the increasing scale and development of floating wind turbines. In this paper, we developed prediction models with a 50 Hz resolution for the bending strain at the tower bottom of offshore wind turbines by combining SCADA data and acceleration data using machine learning techniques and analyzed the results. The load prediction models demonstrated high accuracy, with a mean absolute percentage error below 4%.

A stochastic linear programming model for maximizing generation and firm output at a reliability in long-term hydropower reservoir operation

The firm output, usually determined in the design stage of a hydroplant to serve as a threshold to measure system reliability, can be regarded as an unknown parameter to be explored to its maximum in long-term hydropower reservoir operation (LHRO). An unknown firm output to be ensured at certain reliability, however, will make the problem much more nonlinear and then complicate the modeling. This work presents a stochastic linear programming (SLP-1) model that can explicitly incorporate reliability in ensuring an unknown firm output to be maximized by using a probability variable to represent a decision at a state and introducing binary variables to decide whether the decision will ensure the unknown firm output. The present SLP-1 is improved on 1) another previous SLP model (SLP-0) that must have a firm output prespecified at certain reliability, and compared with 2) the stochastic dynamic programming (SDP) model that can only manage to estimate the firm output at a reliability with trial and error. Case studies show the superiority of the present SLP to the SDP that can hardly make the reliability any closer to what the SLP can achieve, especially in ensuring a high firm output, with gaps to desired reliability ranging up to 42.33% for Xiaowan and 31.8% for Nuozhadu. Indeed, the SLP-1 will encounter the dimensional difficulty that needs further efforts to overcome when applied to cascaded reservoirs.

Improving the Accuracy of Wheeled Vehicle Acceleration Estimation During Testing

The study considers the influence of installation errors during the installation of linear acceleration sensors on the accuracy of measurements during testing of wheeled vehicles, including the dynamic stability of the position. The possibility of automatic correction of these errors to improve measurement accuracy is considered. The work includes establishing the dependence of linear acceleration components on the angular deviations of the axes of the wheeled vehicle coordinate system and developing a method of automatic correction in real time to ensure high quality measurements and maintain the reliability of measurement systems.

Mechanotendography: description and evaluation of a novel method for investigating the physiological mechanical oscillations of tendons using a piezo-based measurement system.

The mechanotendography (MTG) is a method for analyzing the mechanical oscillations of tendons during muscular actions. The aim of this investigation was to evaluate the technical reliability of a piezo-based measurement system used for MTG. The reliability measurements were performed by using audio samples played by a subwoofer. The thereby generated pressure waves were recorded by a piezo-based measurement system. An audio of 40 Hz sine oscillations and four different formerly in vivo recorded MTG-signals were converted into audio files and were used as test signals. Five trials with each audio were performed and one audio was used for repetition trials on another day. The signals’ correlation was estimated by Spearman (MCC) and intraclass correlation coefficients (ICC(3,1)), Cronbach’s alpha (CA) and by mean distances (MD). All parameters were compared between repetition and randomized matched signals. The repetition trials show high correlations (MCC: 0.86 ± 0.13, ICC: 0.89 ± 0.12, CA: 0.98 ± 0.03), low MD (0.03 ± 0.03V) and differ significantly from the randomized matched signals (MCC: 0.15 ± 0.10, ICC: 0.17 ± 0.09, CA: 0.37 ± 0.16, MD: 0.19 ± 0.01V) (p = 0.001 – 0.043). This speaks for an excellent reliability of the measurement system. Presuming the skin above superficial tendons oscillates adequately, we estimate this tool as valid for the application in musculoskeletal system.

Mechanotendography: description and evaluation of a novel method for investigating the physiological mechanical oscillations of tendons using a piezo-based measurement system

The mechanotendography (MTG) is a method for analyzing the mechanical oscillations of tendons during muscular actions. The aim of this investigation was to evaluate the technical reliability of a piezo-based measurement system used for MTG. The reliability measurements were performed by using audio samples played by a subwoofer. The thereby generated pressure waves were recorded by a piezo-based measurement system. An audio of 40 Hz sine oscillations and four different formerly in vivo recorded MTG-signals were converted into audio files and were used as test signals. Five trials with each audio were performed and one audio was used for repetition trials on another day. The signals’ correlation was estimated by Spearman (MCC) and intraclass correlation coefficients (ICC(3,1)), Cronbach’s alpha (CA) and by mean distances (MD). All parameters were compared between repetition and randomized matched signals. The repetition trials show high correlations (MCC: 0.86 ± 0.13, ICC: 0.89 ± 0.12, CA: 0.98 ± 0.03), low MD (0.03 ± 0.03V) and differ significantly from the randomized matched signals (MCC: 0.15 ± 0.10, ICC: 0.17 ± 0.09, CA: 0.37 ± 0.16, MD: 0.19 ± 0.01V) (p = 0.001 – 0.043). This speaks for an excellent reliability of the measurement system. Presuming the skin above superficial tendons oscillates adequately, we estimate this tool as valid for the application in musculoskeletal system.

Measurement comparisons: A tool to guarantee the reliability of measurement systems and of high-tech industry

Measurement comparisons or inter-laboratory comparisons (ILCs) are the main tool to establish the measurements' compatibility between different laboratories or different measurement methods. Therefore, they are a mean to establish the equivalence of national standards maintained at the National Measurement Institutes (NMI), the correctness of the measurement traceability transfer from NMIs to secondary calibration laboratories, of their accreditation processes and the suitability of their operators' competence and equipment. ILCs' role is then of strategic importance as the NMIs and the secondary calibration laboratories lay at the top of a chain representing the measurement system of each modern industrialized country. Each step of this chain has to be under control to assure that final products (or product parts) could eventually assembled with other parts made in other countries. At the level of NMI, high-level key comparisons are carried out to compare national standards while at the national level, ILCs between NMIs and secondary laboratories are useful to verify the capabilities of these laboratories. Secondary laboratories calibrate standards and instruments of lower level and industrial laboratories. As these last ones support directly the industrial and manufacturing sectors, it can be concluded that ILCs are the main tool to assure the reliability of measurement systems and thus a strategic support for high-tech modern industry.

Continuous and High Flow Gauging System for Surface and Underground Liquid Fuel Storage Tanks in Colombia

Objectives: In this paper, the aim is to show how to generate a gauging table with the continuous use of electrical, hydraulic and mechanical devices that aim to provide reliability, purity and industrial safety, by not directly manipulating the fuel and actions that may vary final product or induce accidents. In addition, by making a custom gauging table for the arbitrary conditions of the tank, the uncertainty about the quantity of the liquid is reduced and, therefore, it does not discriminate on the type, shape or physical characteristics of these, because the characteristic of the tank it is carried out in the place and under the operating conditions. Methods/Analysis: The model was developed in five stages, a saber: Analysis and specification, Design and construction, Evaluation, Modification and Testing. Findings: Through the implementation of this measure system reliability, safety, and decreased operating time thanks to a methodology of continuous high flow samples and offers. Improvements: The developed model can evolve to a system with greater automation, using level and flow sensors with the same or better resolution, which does not have its own interface for reading but can be added to the communication card and flow control, needing a single USB communication port for mobile phones, with the aim of developing the application on mobile phones. Keywords: Flow, Gauging, Storage Tank, Threats, Volumetric Filling

Measurement System Reliability Assessment

Abstract Decision-making in problem situations is based on up-to-date and reliable information. A great deal of information is subject to rapid changes, hence it may be outdated or manipulated and enforce erroneous decisions. It is crucial to have the possibility to assess the obtained information. In order to ensure its reliability it is best to obtain it with an own measurement process. In such a case, conducting assessment of measurement system reliability seems to be crucial. The article describes general approach to assessing reliability of measurement systems.

Comprehensive use of redundancy for detection of metrological failures of measurement systems

A method of using information redundancy to detect metrological failures of measurement systems without dismantling their components is proposed. In contrast with existing methods, this method provides comprehensive optimization of various sources of redundant information in order to ensure a specified level of reliability of measurement systems with hard-to-reach components.

Confidence estimation of feedback information for logicdiagnosis

This paper proposes an estimation method for the confidence level of feedback information (CLFI), namely the confidence level of reported information in computer integrated manufacturing (CIM) architecture for logic diagnosis. This confidence estimation provides a diagnosis module with precise reported information to quickly identify the origin of equipment failure. We studied the factors affecting CLFI, such as measurement system reliability, production context, position of sensors in the acquisition chains, type of products, reference metrology, preventive maintenance and corrective maintenance based on historical data and feedback information generated by production equipments. We introduced the new ‘CLFI’ concept based on the Dynamic Bayesian Network approach and Tree Augmented Naïve Bayes model. Our contribution includes an on-line confidence computation module for production equipment data, and an algorithm to compute CLFI. We suggest it to be applied to the semiconductor manufacturing industry.

The need for the complex use of redundancy to ensure a specified metrological reliability of measurement systems with almost inaccessible components

The problem of ensuring the required level of metrological reliability of measuring systems with almost inaccessible components is considered. The problem of investigations on the use of different types of redundancy to solve this problem is formalized.

Reliability of measurement systems functioning as systems for the protection of dangerous production facilities

A mathematical model for the prediction of failures of systems designed to protect dangerous industrial facilities (damage control systems) based on stochastic branching processes is proposed. A system of linear ordinary differential equations for determining the probabilistic reliability characteristics of a technical system is considered and solved by means of the apparatus of generating functions.

Re-Scheduling of Unit Commitment Based on Customers' Fuzzy Requirements for Power Reliability

The development of the electricity market enables us to provide electricity of varied quality and price in order to fulfill power consumers' needs. Such customers choices should influence the process of adjusting power generation and spinning reserve, and, as a result, change the structure of a unit commitment optimization problem (UCP). To build a unit commitment model that considers customer choices, we employ fuzzy variables in this study to better characterize customer requirements and forecasted future power loads. To measure system reliability and determine the schedule of real power generation and spinning reserve, fuzzy Value-at-Risk (VaR) is utilized in building the model, which evaluates the peak values of power demands under given confidence levels. Based on the information obtained using fuzzy VaR, we proposed a heuristic algorithm called local convergence-averse binary particle swarm optimization (LCA-PSO) to solve the UCP. The proposed model and algorithm are used to analyze several test systems. Comparisons between the proposed algorithm and the conventional approaches show that the LCA-PSO performs better in finding the optimal solutions.

Reconstructing social interactions using an unreliable wireless sensor network

In the very active field of complex networks, research advances have largely been stimulated by the availability of empirical data and the increase in computational power needed for their analysis. These works have led to the identification of similarities in the structures of such networks arising in very different fields, and to the development of a body of knowledge, tools and methods for their study. While many interesting questions remain open on the subject of static networks, challenging issues arise from the study of dynamic networks. In particular, the measurement, analysis and modeling of social interactions are first class concerns. In this article, we address the challenges of capturing physical proximity and social interaction by means of a wireless network. In particular, as a concrete case study, we exhibit the deployment of a wireless sensor network applied to the measurement of health care workers’ exposure to tuberculosis-infected patients in a service unit of the Bichat–Claude Bernard hospital in Paris, France. This network has continuously monitored the presence of all HCWs in all rooms of the service during a three month period. We both describe the measurement system that was deployed and some early analysis on the measured data. We highlight the bias introduced by the measurement system reliability and provide a reconstruction method which not only leads to a significantly more coherent and realistic dataset but also evidences phenomena a priori hidden in the raw data. By this analysis, we suggest that a processing step is required prior to any adequate exploitation of data gathered thanks to a non-fully reliable measurement architecture.

Reliability-aware scheduling strategy for heterogeneous distributed computing systems

Heterogeneous computing systems are promising computing platforms, since single parallel architecture based systems may not be sufficient to exploit the available parallelism with the running applications. In some cases, heterogeneous distributed computing (HDC) systems can achieve higher performance with lower cost than single-machine supersystems. However, in HDC systems, processors and networks are not failure free and any kind of failure may be critical to the running applications. One way of dealing with such failures is to employ a reliable scheduling algorithm. Unfortunately, most existing scheduling algorithms for precedence constrained tasks in HDC systems do not adequately consider reliability requirements of inter-dependent tasks. In this paper, we design a reliability-driven scheduling architecture that can effectively measure system reliability, based on an optimal reliability communication path search algorithm, and then we introduce reliability priority rank (RRank) to estimate the task’s priority by considering reliability overheads. Furthermore, based on directed acyclic graph (DAG) we propose a reliability-aware scheduling algorithm for precedence constrained tasks, which can achieve high quality of reliability for applications. The comparison studies, based on both randomly generated graphs and the graphs of some real applications, show that our scheduling algorithm outperforms the existing scheduling algorithms in terms of makespan, scheduling length ratio, and reliability. At the same time, the improvement gained by our algorithm increases as the data communication among tasks increases.

Optimal Allocation of Replicates for Measurement Evaluation Studies

Optimal experimental design is important for the efficient use of modern high-throughput technologies such as microarrays and proteomics. Multiple factors including the reliability of measurement system, which itself must be estimated from prior experimental work, could influence design decisions. In this study, we describe how the optimal number of replicate measures (technical replicates) for each biological sample (biological replicate) can be determined. Different allocations of biological and technical replicates were evaluated by minimizing the variance of the ratio of technical variance (measurement error) to the total variance (sum of sampling error and measurement error). We demonstrate that if the number of biological replicates and the number of technical replicates per biological sample are variable, while the total number of available measures is fixed, then the optimal allocation of replicates for measurement evaluation experiments requires two technical replicates for each biological replicate. Therefore, it is recommended to use two technical replicates for each biological replicate if the goal is to evaluate the reproducibility of measurements.