Tolerance Analysis Identify each of the error sources. Determine the sensitivity of each performance parameter to changes in each error source assuming.

Slides:



Advertisements
Similar presentations
Chapter 12: Inference for Proportions BY: Lindsey Van Cleave.
Advertisements

Modeling of Data. Basic Bayes theorem Bayes theorem relates the conditional probabilities of two events A, and B: A might be a hypothesis and B might.
Chapter 6 Confidence Intervals.
CHAPTER 1: INTRODUCTION TO OPERATIONAL AMPLIFIERS
Chapter 8 Estimating Single Population Parameters
Lecture 91 Loop Analysis (3.2) Circuits with Op-Amps (3.3) Prof. Phillips February 19, 2003.
Op Amps Lecture 30.
Position Error in Assemblies and Mechanisms Statistical and Deterministic Methods By: Jon Wittwer.
Mathematical Modeling of Assembly Coordinate frames –each part has a base coordinate frame Relationships between parts are expressed as 4x4 matrix transforms.
6.1 Confidence Intervals for the Mean (Large Samples)
Principles of Physics.  More than one resistor in multiple paths  Electrons may go through any path  More electrons will go through path with less.
Lecture Sources 2.2 Ohm’s Law 2.4 Kirchhoff’s Laws.
Standard error of estimate & Confidence interval.
Lesson Objectives To know and understand what break even means. To know how to draw and label a break even chart. To understand what break even shows and.
Electronic Devices Ninth Edition Floyd Chapter 13.
“Op-Amp” Operational Amplifier Non Inverting Amplifier Inverting Amplifier Adder –(and Subtractor using an Inverter) Differential Amplifier Integrator.
ECE 340 ELECTRONICS I OPERATIONAL AMPLIFIERS. OPERATIONAL AMPLIFIER THEORY OF OPERATION CHARACTERISTICS CONFIGURATIONS.
Confidence Intervals Chapter 6. § 6.1 Confidence Intervals for the Mean (Large Samples)
Chapter 6 Confidence Intervals.
Confidence Intervals Chapter 6. § 6.1 Confidence Intervals for the Mean (Large Samples)
Confidence Intervals for the Mean (σ known) (Large Samples)
Electronics Fundamentals 8 th edition Floyd/Buchla © 2010 Pearson Education, Upper Saddle River, NJ All Rights Reserved. chapter 18 electronics.
1 Passive components and circuits - CCP Lecture 4.
ECE 352 Electronics II Winter 2003 Ch. 8 Feedback 1 Feedback *What is feedback?Taking a portion of the signal arriving at the load and feeding it back.
1 ECE 3144 Lecture 22 Dr. Rose Q. Hu Electrical and Computer Engineering Department Mississippi State University.
The signal conditioner -- changes the voltage Amplify Attenuate Filter.
CHAPTER SIX Confidence Intervals.
Power Transfer Superposition Principle. Maximum Power Transfer Choose an RL in order to maximize power delivered to RL.
ANALOG ELECTRONIC CIRCUITS 1
Break-even L:\BUSINESS\GCE\Unit 2\Break even point.xls.
Goal Seek and Solver. Goal seeking helps you n Find a specific value for a target cell by adjusting the value of one other cell whose value is allowed.
Estimation Chapter 8. Estimating µ When σ Is Known.
1Date 2004 Strictly Confidential Remote Sense (extracted from a presentation by Robert Kollman)
1 LECTURE 7. Contents 5.Sources of errors 5.1.Impedance matching Non-energetic matching Energetic matching Non-reflective matching To.
CHAPTER SIX Confidence Intervals.
Designing for Predictable Amplifier Gain Gain is hard to control Varies with operating point Non-constant gain causes distortion Gain varies from one transistor.
EE 230: Optical Fiber Communication Lecture 12
Lab I Recap Lab II Preliminary Dr. Len Trombetta 1 ECE 2100.
Noise characteristics Reference: [4] The signal-to-noise ratio is the measure for the extent to which a signal can be distinguished from the background.
Confidence Intervals Chapter 6. § 6.1 Confidence Intervals for the Mean (Large Samples)
REAL OP-AMP LIMITATIONS
Uncertainty and Reliability Analysis D Nagesh Kumar, IISc Water Resources Planning and Management: M6L2 Stochastic Optimization.
Noise characteristics Reference: [4] The signal-to-noise ratio is the measure for the extent to which a signal can be distinguished from the background.
Chapter 8 Estimation ©. Estimator and Estimate estimator estimate An estimator of a population parameter is a random variable that depends on the sample.
The Birthday Problem. The Problem In a group of 50 students, what is the probability that at least two students share the same birthday?
Amplifier An amplifier increases the strength of an electrical signal. Symbol: Type:analogue process device Amplifiers are used in: 1.radios and TV’s 2.intercoms.
Section 6-1 – Confidence Intervals for the Mean (Large Samples) Estimating Population Parameters.
Margin of Error S-IC.4 Use data from a sample survey to estimate a population mean or proportion; develop a margin of error through the use of simulation.
Chapter Confidence Intervals 1 of 31 6  2012 Pearson Education, Inc. All rights reserved.
Section 6.1 Confidence Intervals for the Mean (Large Samples) © 2012 Pearson Education, Inc. All rights reserved. 1 of 83.
Example 4.10 Finding the Thevenin equivalent of a circuit with a dependent source.
ANALOGUE ELECTRONICS CIRCUITS I EKT 204 Frequency Response of FET Amplifiers 1.
Audio Power Amplifier Detailed Design
Basics of Multivariate Probability
10 Ω 2.75 Ω 3.75 R2 R1 R3 6 Ω 6 Ω 80 V 2.5 Ω 2 R6 3 Ω R5 4.5 R7 2 Ω R4 3 Ω R8 4 Ω 5 Ω R9 R RT = = 10 Ω.
PUSAT PENGAJIAN KEJURUTERAAN KOMPUTER & PERHUBUNGAN
Quiz: Determining a SAR ADC’s Linear Range when using Operational Amplifiers TIPL 4101 TI Precision Labs – ADCs Created by Art Kay.
Quiz: Driving a SAR ADC with a Fully Differential Amplifier TIPL 4103 TI Precision Labs – ADCs Created by Art Kay.
Link Budget.
Inference: Conclusion with Confidence
Starter What’s the story? Title: Break-Even.
The resistance of a thermistor changes from 30k to 12k when the temperature changes from 20C to 70 C Calculate the sensitivity if resistance is taken.
تحليل الحساسية Sensitive Analysis.
Mathematical Modeling of Assembly
Mathematical Modeling of Assembly
Measurement errors and uncertainties
Confidence Intervals for the Mean (Large Samples)
What kinds of graphs would be useful in calculating work and energy?
Types of Errors And Error Analysis.
ECE 352 Electronics II Winter 2003 Ch. 8 Feedback 1 Feedback *What is feedback?Taking a portion of the signal arriving at the load and feeding it back.
Presentation transcript:

Tolerance Analysis Identify each of the error sources. Determine the sensitivity of each performance parameter to changes in each error source assuming all other sources are error free. Assuming all error sources are independent of each other, calculate the maximum probable error in each performance parameter. Add a safety margin before using the results in any specification.

R1R R2 ViVi VoVo Tolerance Analysis (Error Accumulation) Looking at contribution of R 1 Or (% change) in gain equals – (% change) in R 1

Now, looking at contribution of R 2 Or (% change) in gain equals (% change) in R 2

Assuming the errors in R 1 and R 2 are independent of each other: The maximum worst case error in gain will be: But sometimes the independent errors may tend to cancel each other, so the maximum probable error will be:

Example of application: We need to supply an amplifier with a gain of –5 with a max probable error of 2%. To build in a 20% safety margin, we should target for a gain error of: And if we specify the same tolerances for both resistors: