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The Math of Random Signals, Fatigue Damage, Vibration Tests

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Emanuele Pesaresi

7:15:28

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  • 1.1 Pesaresi PhD dissertation.pdf
  • 1. Introduction to the course.mp4
    05:47
  • 2. Joint Gaussian Distribution.mp4
    24:25
  • 3. Probability Distribution of the Envelope of a Gaussian Signal (Rayleigh distrib).mp4
    22:34
  • 4. Mathematical Definition of Fatigue damage.mp4
    16:50
  • 5. Formula for the Expected number of Positive Peaks.mp4
    20:58
  • 6. Power Spectral Density, Standard Deviation of a Random Process & its Derivatives.mp4
    26:07
  • 7. Relating the Fatigue Damage Spectrum to the Power Spectral Density.mp4
    27:10
  • 8. Practical Explanation on How to Calculate the Fatigue Damage Spectrum.mp4
    12:53
  • 9. Maximum Response Spectrum.mp4
    12:03
  • 1. Practical use of the theory of Fatigue Damage.mp4
    12:54
  • 2. Algorithms for the Calculation of the Power Spectral Density.mp4
    07:31
  • 3. How to Create Non-Gaussian Signals with a Prescribed Fatigue Damage Spectrum.mp4
    08:01
  • 4. Application Synthesis of Non-Gaussian Signals with a Prescribed Fatigue Damage.mp4
    05:55
  • 5. Application of the Maximum Response Spectrum.mp4
    08:22
  • 1. How the Central Limit Theorem Arises from Stochastic Processes.mp4
    05:47
  • 2. Integral of Even Powers of Sinusoids.mp4
    18:14
  • 3. Some Representations of the Bessel function of Order Zero.mp4
    09:17
  • 4. Probability Density of a Sinusoid.mp4
    12:56
  • 5. Distribution of a Sinusoid Derived Intuitively.mp4
    07:52
  • 6. Why a Random Signal with Uniformly Distributed Phases is Gaussian.mp4
    18:40
  • 1. Probability Density of the Envelope of Gaussian Noise + a Deterministic Sinusoid.mp4
    16:59
  • 2. Calculating the Damage caused by Sine on Random Signals.mp4
    11:57
  • 1. Introduction to Stochastic Processes.mp4
    03:53
  • 2. Derivation of the Properties of a Linear System.mp4
    09:35
  • 3. Properties of the Fourier Transform of a Real Time Signal.mp4
    04:39
  • 4. Fourier Series Representation of the Output of a Linear System.mp4
    11:27
  • 5. Another Useful Representation of the Fourier Series.mp4
    08:24
  • 6. Recalling the Relationship Between the Fourier Series and the Fourier Transform.mp4
    07:06
  • 1. Solution to 2nd order ODE (ordinary differential equations).mp4
    37:41
  • 1. Sterlings Formula.mp4
    10:07
  • 2. How the Binomial Distribution Converges to the Gaussian One.mp4
    29:24
  • Description


    The Math of Reliability Engineering, Fatigue Damage, and its Interesting Applications in the World of Vibration Tests.

    What You'll Learn?


    • How to define Fatigue Damage mathematically
    • How to find the probability density of the peaks of a random signal
    • The importance of the Gaussian distribution and why it often appears when dealing with random signals
    • How to find the joint probability density of two Gaussian variables
    • What the Fatigue Damage Spectrum is, and why it is important for Fatigue tests
    • How to synthesize signals with a prescribed Fatigue Damage Spectrum

    Who is this for?


  • Reliability engineers
  • Mechanical engineers
  • Mathematicians
  • Engineering or math students who are interested in the mathematical modeling of Fatigue Damage
  • Students who want to see the connections between mathematical models and practical applications
  • Students who already have a good mastery of mathematics and want to learn some of its beautiful applications to Random Processes
  • Engineering and technical managers
  • Quality Engineers
  • More details


    Description

    In the first part of this course, the mathematics of fatigue damage is addressed. The most important equations are derived, and this will serve as a guide to illustrate the main applications of the theory in the second part.

    This course is not only aimed at those students who are interested in vibration tests and reliability engineering, but also at those who want to see the beautiful mathematics applied to engineering. In this case the theory contains: stochastic processes, probability distributions (and how they arise in nature/real-life applications), as well as single-degree-of-freedom systems, the probability density of the maxima of a random process, and much more. In this regard, the mathematical theory of damage is quite advanced mathematically; for instance, we will have to make use of the Gamma and the Bessel functions. Anyway, the concepts will be developed intuitively throughout the course, and the connection with real-life applications will always be highlighted.

    Most of the results shown in this course are described in the instructor’s PhD dissertation: “Advanced Mission Synthesis Algorithms for Vibration-based Accelerated Life-testing” and the references contained therein. This work will be public as of February 2023 after a two-year “embargo”, and it will be available for consultation. If you would like to consult this dissertation and you cannot find it online, just check the attachment to the first lecture of this course, you should find the dissertation attached.

    This theory was exploited to create Graphical User Interfaces (GUI), which were the result of the collaboration between the instructor and companies interested in the PhD project. We will use these GUI in the course to shed light on how the equations can be implemented to generate vibratory signals.

    Let's briefly contextualize the theory of fatigue damage in the field of vibration tests. In real-life applications, components are often subjected to stochastic loads that might lead to a premature failure; therefore, experimental tests are needed to check the components’ resistance to environmental vibrations.

    The type of tests related to fatigue-life estimation aims to reproduce the entire fatigue damage experienced by the component during its operational life, but in a shorter amount of time. These tests are usually referred to as fatigue-life tests or durability tests, and the common practice is to tailor them to the specific application. The signals which are used during the tests have the same "damage potential" as the environmental conditions (to which the components are subjected).

    The signals are created starting from a Power Spectral Density (PSD), which is used by vibrating tables or shakers to generate a vibratory motion.

    In the course, a method of relating a PSD to the fatigue damage will be shown. This will help create a (Gaussian) signal to be used during tests.

    The Gaussian distribution appears very frequently in nature and practical applications. In this course, it was deemed necessary to shed light on the importance of this distribution, by deriving the results previously derived in another course on the Central Limit Theorem (although in a different way).

    However, since there are signals measured in real applications that show a deviation from the Gaussian distribution (due to the presence of peaks and bursts in the signals), the synthesis of non-Gaussian signals will also be discussed.

    Who this course is for:

    • Reliability engineers
    • Mechanical engineers
    • Mathematicians
    • Engineering or math students who are interested in the mathematical modeling of Fatigue Damage
    • Students who want to see the connections between mathematical models and practical applications
    • Students who already have a good mastery of mathematics and want to learn some of its beautiful applications to Random Processes
    • Engineering and technical managers
    • Quality Engineers

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    Emanuele Pesaresi
    Emanuele Pesaresi
    Instructor's Courses
    I obtained my PhD in "Mechanics and Advanced Engineering Sciences" in 2021.I attained a Bachelor of Science and Master of Science in Mechanical engineering in 2015 and 2017 respectively, with honors from the University of Bologna.I was the teaching tutor for the course of Mechanics of Machines from the academic year 2018 until the end of 2021 at the University of Bologna (branch of Forlì).My passion for mathematics, physics and teaching has motivated me to lecture high school and university students.My approach as a teacher is to prove to students that memory is less important for an engineer, mathematician, or physicist, than learning how to tackle a problem through logical reasoning. I believe that a teacher of scientific subjects should try to develop his students’ curiosity about the subject, rather than just concentrating on acquisition of knowledge, however important that may also be. Students should be encouraged to dig deeper and build on their knowledge by continually questioning it, rather than accepting everything at face value without a thorough understanding.For enquiries (e.g. about tutoring, or advice related to the subjects spanned by my courses), you can either contact me on LinkedIn, or you can post questions in my courses' message boards, or you can also contact me via email or on my website.You can also find the updated versions of my courses on my website.
    Students take courses primarily to improve job-related skills.Some courses generate credit toward technical certification. Udemy has made a special effort to attract corporate trainers seeking to create coursework for employees of their company.
    • language english
    • Training sessions 31
    • duration 7:15:28
    • Release Date 2023/03/25