Analysis and Quality Control from ARIMA Modeling

In this paper, we use ARIMA modelling to estimate a set of characteristics of a short-term indicator (for example, the index of industrial production), as trends, seasonal variations, cyclical oscillations, unpredictability, deterministic effects (as a strike), etc. Thus for each sector and product (more than 1000), we construct a vector of values corresponding to the above-mentioned characteristics, that can be used for data editing.

Dust suppressant treatments. Quality control = Tratamientos supresores de polvo. Control de calidad

La emisión de polvo por efecto del viento desde depósitos de residuos mineros o industriales y el paso de vehículos en vías no pavimentadas, es un problema que afecta las actividades productivas; el ambiente y la salud de las personas que permanecen en el área contaminada. En Chile, en los últimos años la sensibilidad social y las exigencias ambientales han aumentado, así como la oferta de diferentes supresores y tecnologías de aplicación. Se han revisado las causas que provocan emisión de polvo y las tecnologías disponibles en Chile para la supresión de polvo, además de las metodologías y normativa para evaluar el desempeño de los materiales tratados con diferentes supresores. En algunos casos no es posible comparar propiedades de desempeño, como durabilidad, dosis a aplicar y frecuencia de las aplicaciones, entre otros aspectos. Los procedimientos descritos en la norma NCh3266-2012 permiten evaluar la erosión eólica en depósitos de residuos, sitios eriazos y caminos no pavimentados, entre otros, junto con evaluar el desempeño de diferentes tipos de supresores de polvo a partir de datos objetivos comparables. Esto permite seleccionar el supresor más adecuado, mejorar la eficiencia de los tratamientos, optimizar los costos y mejorar los procesos productivos. Palabras clave: Erosión-eólica, supresor de polvo, residuos-mineros, caminos-no pavimentados. Dust emissions by wind effect from mining deposits or industrial waste and passing vehicles on unpaved roads, is a problem that affects the productive activities; the environment and the health of those who remain in the contaminated area. The social sensitivity and environmental requirements on this issue in Chile have increased, as well as offering different suppressors and application technologies. Have been reviewed the causes of dust emission and technologies available in Chile for dust suppression, plus methodologies and standards for assessing the performance of the treated materials with different suppressors. In some cases it is not possible to compare performance properties such as durability, application dose and frequency of applications, among others aspects. The procedures described in the NCh 3266-2012 standard allows the assessment of wind erosion in waste deposits, vacant lots and unpaved roads, among others, along with evaluating the performance of different types of dust suppressants from comparable objective data. This allows selecting the most suitable suppressor, improve efficiency of treatments, optimize costs and improve production processes. Keywords: Wind-erosion, dust-suppressor, mining-waste, unpavedroads

Integration of embedded data processing algorithms inside PAMELA devices

PAMELA (Phased Array Monitoring for Enhanced Life Assessment) SHMTM System is an integrated embedded ultrasonic guided waves based system consisting of several electronic devices and one system manager controller. The data collected by all PAMELA devices in the system must be transmitted to the controller, who will be responsible for carrying out the advanced signal processing to obtain SHM maps. PAMELA devices consist of hardware based on a Virtex 5 FPGA with a PowerPC 440 running an embedded Linux distribution. Therefore, PAMELA devices, in addition to the capability of performing tests and transmitting the collected data to the controller, have the capability of perform local data processing or pre-processing (reduction, normalization, pattern recognition, feature extraction, etc.). Local data processing decreases the data traffic over the network and allows CPU load of the external computer to be reduced. Even it is possible that PAMELA devices are running autonomously performing scheduled tests, and only communicates with the controller in case of detection of structural damages or when programmed. Each PAMELA device integrates a software management application (SMA) that allows to the developer downloading his own algorithm code and adding the new data processing algorithm to the device. The development of the SMA is done in a virtual machine with an Ubuntu Linux distribution including all necessary software tools to perform the entire cycle of development. Eclipse IDE (Integrated Development Environment) is used to develop the SMA project and to write the code of each data processing algorithm. This paper presents the developed software architecture and describes the necessary steps to add new data processing algorithms to SMA in order to increase the processing capabilities of PAMELA devices.An example of basic damage index estimation using delay and sum algorithm is provided.

Algorithms hardware implementation for ultrasonic data processing in SHM system

Nowadays, devices that monitor the health of structures consume a lot of power and need a lot of time to acquire, process, and send the information about the structure to the main processing unit. To decrease this time, fast electronic devices are starting to be used to accelerate this processing. In this paper some hardware algorithms implemented in an electronic logic programming device are described. The goal of this implementation is accelerate the process and diminish the information that has to be send. By reaching this goal, the time the processor needs for treating all the information is reduced and so the power consumption is reduced too.

A set of canonical problems in sloshing. Part 0: Experimental setup and data processing

In a series of attempts to research and document relevant sloshing type phenomena, a series of experiments have been conducted. The aim of this paper is to describe the setup and data processing of such experiments. A sloshing tank is subjected to angular motion. As a result pressure registers are obtained at several locations, together with the motion data, torque and a collection of image and video information. The experimental rig and the data acquisition systems are described. Useful information for experimental sloshing research practitioners is provided. This information is related to the liquids used in the experiments, the dying techniques, tank building processes, synchronization of acquisition systems, etc. A new procedure for reconstructing experimental data, that takes into account experimental uncertainties, is presented. This procedure is based on a least squares spline approximation of the data. Based on a deterministic approach to the first sloshing wave impact event in a sloshing experiment, an uncertainty analysis procedure of the associated first pressure peak value is described.

Advanced predictive quality control strategy involving different facilities

There are many industries that use highly technological solutions to improve quality in all of their products. The steel industry is one example. Several automatic surface-inspection systems are used in the steel industry to identify various types of defects and to help operators decide whether to accept, reroute, or downgrade the material, subject to the assessment process. This paper focuses on promoting a strategy that considers all defects in an integrated fashion. It does this by managing the uncertainty about the exact position of a defect due to different process conditions by means of Gaussian additive influence functions. The relevance of the approach is in making possible consistency and reliability between surface inspection systems. The results obtained are an increase in confidence in the automatic inspection system and an ability to introduce improved prediction and advanced routing models. The prediction is provided to technical operators to help them in their decision-making process. It shows the increase in improvement gained by reducing the 40 % of coils that are downgraded at the hot strip mill because of specific defects. In addition, this technology facilitates an increase of 50 % in the accuracy of the estimate of defect survival after the cleaning facility in comparison to the former approach. The proposed technology is implemented by means of software-based, multi-agent solutions. It makes possible the independent treatment of information, presentation, quality analysis, and other relevant functions.

Data Processing Modeling in Decision Support Systems.

Due to the advancement of both, information technology in general, and databases in particular; data storage devices are becoming cheaper and data processing speed is increasing. As result of this, organizations tend to store large volumes of data holding great potential information. Decision Support Systems, DSS try to use the stored data to obtain valuable information for organizations. In this paper, we use both data models and use cases to represent the functionality of data processing in DSS following Software Engineering processes. We propose a methodology to develop DSS in the Analysis phase, respective of data processing modeling. We have used, as a starting point, a data model adapted to the semantics involved in multidimensional databases or data warehouses, DW. Also, we have taken an algorithm that provides us with all the possible ways to automatically cross check multidimensional model data. Using the aforementioned, we propose diagrams and descriptions of use cases, which can be considered as patterns representing the DSS functionality, in regard to DW data processing, DW on which DSS are based. We highlight the reusability and automation benefits that this can be achieved, and we think this study can serve as a guide in the development of DSS.

KATS: A Knowledge Acquisition Tool Based on Electronic Document Processing

This paper describes a particular knowledge acquisition tool for the construction and maintenance of the knowledge model of an intelligent system for emergency management in the field of hydrology. This tool has been developed following an innovative approach directed to end-users non familiarized in computer oriented terminology. According to this approach, the tool is conceived as a document processor specialized in a particular domain (hydrology) in such a way that the whole knowledge model is viewed by the user as an electronic document. The paper first describes the characteristics of the knowledge model of the intelligent system and summarizes the problems that we found during the development and maintenance of such type of model. Then, the paper describes the KATS tool, a software application that we have designed to help in this task to be used by users who are not experts in computer programming. Finally, the paper shows a comparison between KATS and other approaches for knowledge acquisition.

Automatic Adaptation of Airport Surface Surveillance to Sensor Quality

This paper describes a novel method to enhance current airport surveillance systems used in Advanced Surveillance Monitoring Guidance and Control Systems (A-SMGCS). The proposed method allows for the automatic calibration of measurement models and enhanced detection of nonideal situations, increasing surveillance products integrity. It is based on the definition of a set of observables from the surveillance processing chain and a rule based expert system aimed to change the data processing methods

Control estadístico de la calibración de MDP volumétricos para la transferencia de custodia de hidrocarburos líquidos

Este proyecto tiene por objeto desarrollar una sistemática de control metrológico para vigilar la exactitud de los medidores volumétricos de desplazamiento positivo que operan en las compañías logísticas de hidrocarburos para la transferencia de custodia que están en el cargadero y se ensayan in situ para obtener su meter factor. El punto de partida son las hojas primarias de las calibraciones generadas frente a sus patrones y el prover que nos facilitan las compañías. Dado el elevado número de ensayos y debido a que estos medidores no tienen gráficos de control estables, el enfoque del tratamiento ha sido un etiquetado para realizar un control de inestabilidad y calidad de los ensayos y así, determinar equipos anómalos. Para la búsqueda de equipos atípicos se ha desarrollado el filtro de Tukey para el estudio de la estadística descriptiva de los valores del meter factor. Entre los dos métodos se han obtenido una clasificación de equipos vigilables, recalibrables y sustituibles para facilitar a las compañías logísticas. ABSTRACT The aim of this project is to develop a systematic metrological control to monitor the accuracy of the positive displacement flow meters operating in oil logistics companies for custody transfer which are in the loading track facilities and it are tested in-situ to obtain the meter factor. Due to the high number of assays that meters don´t have stable graphics of control, the approach of data processing has been a labeled to perform an instability and quality control of assays for establish anomalous meters. To find outliers meters is developed the filter of Turkey to study the descriptive statistics of meter factor values. Between both analytical methods is obtained a classification of controllable, recalibrables and replaceable meters to provide to the logistic company.

Image processing methods for human brain connectivity analysis from in-vivo diffusion MRI

The structural connectivity of the brain is considered to encode species-wise and subject-wise patterns that will unlock large areas of understanding of the human brain. Currently, diffusion MRI of the living brain enables to map the microstructure of tissue, allowing to track the pathways of fiber bundles connecting the cortical regions across the brain. These bundles are summarized in a network representation called connectome that is analyzed using graph theory. The extraction of the connectome from diffusion MRI requires a large processing flow including image enhancement, reconstruction, segmentation, registration, diffusion tracking, etc. Although a concerted effort has been devoted to the definition of standard pipelines for the connectome extraction, it is still crucial to define quality assessment protocols of these workflows. The definition of quality control protocols is hindered by the complexity of the pipelines under test and the absolute lack of gold-standards for diffusion MRI data. Here we characterize the impact on structural connectivity workflows of the geometrical deformation typically shown by diffusion MRI data due to the inhomogeneity of magnetic susceptibility across the imaged object. We propose an evaluation framework to compare the existing methodologies to correct for these artifacts including whole-brain realistic phantoms. Additionally, we design and implement an image segmentation and registration method to avoid performing the correction task and to enable processing in the native space of diffusion data. We release PySDCev, an evaluation framework for the quality control of connectivity pipelines, specialized in the study of susceptibility-derived distortions. In this context, we propose Diffantom, a whole-brain phantom that provides a solution to the lack of gold-standard data. The three correction methodologies under comparison performed reasonably, and it is difficult to determine which method is more advisable. We demonstrate that susceptibility-derived correction is necessary to increase the sensitivity of connectivity pipelines, at the cost of specificity. Finally, with the registration and segmentation tool called regseg we demonstrate how the problem of susceptibility-derived distortion can be overcome allowing data to be used in their original coordinates. This is crucial to increase the sensitivity of the whole pipeline without any loss in specificity.