661 research outputs found

    Analysis of the visually detectable wear progress on ball screws

    Get PDF
    The actual progression of pitting on ball screw drive spindles is not well known since previous studies have only relied on the investigation of indirect wear effects (e. g. temperature, motor current, structure-borne noise). Using images from a camera system for ball screw drives, this paper elaborates on the visual analysis of pitting itself. Due to its direct, condition-based assessment of the wear state, an image-based approach offers several advantages, such as: Good interpretability, low influence of environmental conditions, and high spatial resolution. The study presented in this paper is based on a dataset containing the entire wear progression from original condition to component failure of ten ball screw drive spindles. The dataset is being analyzed regarding the following parameters: Axial length, tangential length, and surface area of each pit, the total number of pits, and the time of initial visual appearance of each pit. The results provide evidence that wear development can be quantified based on visual wear characteristics. In addition, using the dedicated camera system, the actual course of the growth curve of individual pits can be captured during machine operation. Using the findings of the analysis, the authors propose a formula for standards-based wear quantification based on geometric wear characteristics

    Analysis of the Visually Detectable Wear Progress on Ball Screws

    Get PDF
    The actual progression of pitting on ball screw drive spindles is not well known since previous studies have only relied on the investigation of indirect wear effects (e. g. temperature, motor current, structure-borne noise). Using images from a camera system for ball screw drives, this paper elaborates on the visual analysis of pitting itself. Due to its direct, condition-based assessment of the wear state, an image-based approach offers several advantages, such as: Good interpretability, low influence of environmental conditions, and high spatial resolution. The study presented in this paper is based on a dataset containing the entire wear progression from original condition to component failure of ten ball screw drive spindles. The dataset is being analyzed regarding the following parameters: Axial length, tangential length, and surface area of each pit, the total number of pits, and the time of initial visual appearance of each pit. The results provide evidence that wear development can be quantified based on visual wear characteristics. In addition, using the dedicated camera system, the actual course of the growth curve of individual pits can be captured during machine operation. Using the findings of the analysis, the authors propose a formula for standards-based wear quantification based on geometric wear characteristics

    ПРОГНОЗ КАЧЕСТВА ИЗГОТАВЛИВАЕМЫХ ДЕТАЛЕЙ ПЕРЕДАЧ НА ОСНОВЕ ВЕРОЯТНОСТНОЙ МОДЕЛИ ФУНКЦИОНИРОВАНИЯ ТЕХНОЛОГИЧЕСКИХ СИСТЕМ

    Get PDF
    The method of probabilistic estimation of the kinematic error of transmissions with excessive connections depending on the quality of manufacturing of their parts is considered. The method is based on the results of the analysis of the technological accuracy of the equipment involved in the production of gear parts, followed by the synthesis of a model of gear accuracy. The geometric accuracy of the technological system is the expected errors of the finished product. Its connection with technological accuracy is probabilistic in nature. To open this connection, a separation of systematic and random errors characterizing the technological process was made. On the basis of well-known works on the accuracy of technological processes, a technique for separating systematic and random errors has been developed. The basic formulas of this technique are given.As an example, a method for synthesizing a probabilistic model of the output accuracy of ball screw gears is considered. This method, with minor modifications, can also be used to calculate the kinematic accuracy of roller screw, worm, and spiral-pinion gears. The effectiveness of the developed algorithm for calculating accuracy has been proven in practice. Increasing the efficiency of the method of synthesis of a probabilistic model of the output accuracy of ball screw gears is possible if the influence of elastic properties of transmission parts on its output accuracy is taken into account in the mathematical model.1) clarified the features of the technological environment in which the production of the main transmission elements with excessive connections is carried out;2) a method for the synthesis of a probabilistic model of the output accuracy of gears with redundant connections has been developed, which allows taking into account the basic errors of technological systems;3) the developed probabilistic model is verified based on the hypothesis of normal distribution of manufacturing errors.Рассмотрен метод вероятностной оценки кинематической погрешности передач и трансмиссий с избыточными связями в зависимости от качества изготовления их деталей. Метод основан на результатах анализа технологической точности оборудования, задействованного при производстве деталей передач, с последующим синтезом модели точности передач. Геометрическая точность технологической системы это ожидаемые погрешности готовых изделий. Её связь с точностью технологической среды носит вероятностный характер. Для вскрытия этой связи произвели разделение систематических и случайных погрешностей, характеризующих технологический процесс изготовления деталей сложного контура. На основе известных работ по точности технологических процессов разработана методика разделения систематических и случайных погрешностей. Приведены основные формулы этой методики.В качестве примера рассмотрен метод синтеза вероятностной модели выходной точности шариковых винтовых передач. Данный метод, с небольшими модификациями, можно использовать также для расчёта кинематической точности роликовых винтовых, червячно- и спирально-реечных передач. Эффективность разработанного алгоритма расчёта точности доказана на практике. Повышение эффективности метода синтеза вероятностной модели выходной точности шариковых винтовых передач возможно при учёте в математической модели влияния упругих свойств деталей передачи на её выходную точность.Основные задачи, решённые в ходе исследования:1) выяснены особенности технологической среды, при которых осуществляют производство основных элементов передач с избыточными связями;  2) разработан метод синтеза вероятностной модели выходной точности передач с избыточными связями, позволяющий учитывать основные погрешности технологических систем;3) осуществлена проверка разработанной вероятностной модели, основываясь на гипотезе нормального распределения погрешностей изготовления

    Correlation between Machining Monitoring Signals, Cutting Tool Wear and Surface Integrity on High Strength Titanium Alloys.

    Get PDF
    It is widely accepted that tool wear has a direct impact on a machining process, playing a key part in surface integrity, part quality, and therefore, process efficiency. By establishing the state of a tool during a machining process, it should be possible to estimate both the surface properties and the optimal process parameters, while allowing intelligent predictions about the future state of the process to be made; thus ultimately reducing unexpected component damage. This thesis intends to address the problem of tool wear prediction during machining where wear rates vary between components; for instance, due to the relatively large size of the component forging and, therefore, inherent material variations when compared to existing research. In this case, the industrial partner, Safran Landing Systems, is interested in the ability to predict tool wear during the finish milling of large, curved, titanium components, despite differing material properties and, therefore, tool wear rates. This thesis is split into four key parts, the first of which describes in detail the formulation and implementation of an experimental procedure, intended to provide a working set of industrially representative monitoring data that can be used throughout the remainder of the thesis. This part includes development of a relevant machining strategy, material specimen extraction, sensor selection and placement, and 3D tool geometry measurement, all of which have been completed at industrial partners facilities. It finishes with a preliminary investigation into the data collected during the machining process from the tools, material specimens, and sensors placed in close proximity to the cutting zone. The second, third, and fourth parts follow logically from one-another, beginning with a state classification problem, and ending with a full dynamic model prediction of wear during the machining of large landing gear components; this method, however, is applicable to many other machining scenarios using the new technique applied in this thesis. The state classification chapter is a necessary first step in developing a predictive model as is aims to prove the data is indeed separable based upon the generating wear state. Once confirmed, given the sequential nature of tool wear, the order of observations can be included in the modelling, in an attempt to improve classification accuracy. This forms the basis of the state tracking chapter, and leads naturally into the full dynamic model prediction in the final part. This is a promising result for the machining community, as process monitoring often relies on operator expertise to detect wear rate fluctuations and, in turn, results in over-conservative tool usage limits, adding time and expense to many complex machining processes. It also presents the opportunity to predict part quality through pre-existing relationships between the acquired signals and material surface finish - correlations which are explored and presented as part of this thesis. The solution to predicting a varying wear rate within a harsh machining environment introduced in this thesis is based around the application of a Gaussian process (GP) NARX (Nonlinear Auto-Regressive with eXogenous inputs) model borrowed from the machine learning prediction and, more recently, structural health monitoring (SHM) communities. The GP-NARX approach is found to be well suited to the application of wear prediction during machining, and forms a promising contribution to the development of autonomous manufacturing processes

    Hidden Markov Model-based Methods In Condition Monitoring of Machinery Systems

    Get PDF
    Ph.DDOCTOR OF PHILOSOPH

    SIMULATING CONSUMABLE ORDER FULFILLMENT VIA ADDITIVE MANUFACTURING TECHNOLOGIES

    Get PDF
    Operational availability of naval aircraft through material readiness is critical to ensuring combat power. Supportability of aircraft is a crucial aspect of readiness, influenced by several factors including access to 9B Cognizance Code (COG) aviation consumable repair parts at various supply echelons. Rapidly evolving additive manufacturing (AM) technologies are transforming supply chain dynamics and the traditional aircraft supportability construct. As of June 2022, there are 595 AM assets within the Navy’s inventory—all for research and development purposes. This report simulates 9B COG aviation consumable fulfillment strategies within the U.S. Indo-Pacific sustainment network for a three-year span, inclusive of traditional supply support avenues and a developed set of user-variable capability inputs. Simulated probabilistic demand configurations are modeled from historical trends that exploit a heuristic methodology to assign a “printability” score to each 9B COG requirement, accounting for uncertainty, machine failure rates, and other continuous characteristics of the simulated orders. The results measure simulated lead time across diverse planning horizons in both current and varied operationalized AM sustainment network configurations. This research indicates a measurable lead time reduction of approximately 10% across all 9B order lead times when AM is employed as an order fulfillment source for only 0.5% of orders.NPS Naval Research ProgramThis project was funded in part by the NPS Naval Research Program.Lieutenant Commander, United States NavyApproved for public release. Distribution is unlimited

    Proceedings of the Post-Graduate Conference on Robotics and Development of Cognition, 10-12 September 2012, Lausanne, Switzerland

    Get PDF
    The aim of the Postgraduate Conference on Robotics and Development of Cognition (RobotDoC-PhD) is to bring together young scientists working on developmental cognitive robotics and its core disciplines. The conference aims to provide both feedback and greater visibility to their research as lively and stimulating discussion can be held amongst participating PhD students and senior researchers. The conference is open to all PhD students and post-doctoral researchers in the field. RobotDoC-PhD conference is an initiative as a part of Marie-Curie Actions ITN RobotDoC and will be organized as a satellite event of the 22nd International Conference on Artificial Neural Networks ICANN 2012

    Proceedings of the Post-Graduate Conference on Robotics and Development of Cognition, 10-12 September 2012, Lausanne, Switzerland

    Get PDF
    The aim of the Postgraduate Conference on Robotics and Development of Cognition (RobotDoC-PhD) is to bring together young scientists working on developmental cognitive robotics and its core disciplines. The conference aims to provide both feedback and greater visibility to their research as lively and stimulating discussion can be held amongst participating PhD students and senior researchers. The conference is open to all PhD students and post-doctoral researchers in the field. RobotDoC-PhD conference is an initiative as a part of Marie-Curie Actions ITN RobotDoC and will be organized as a satellite event of the 22nd International Conference on Artificial Neural Networks ICANN 2012
    corecore