INVESTIGATION OF WEAR CHARACTERISTICS OF CONICAL DELRIN THRUST BEARINGS

This study focuses on the wear rate in conical thrust bearings, which is responsible for field failures of stepper motors in optical disk drives (ODD). These bearings support the stepper motor worm shaft and consist of a steel ball supported in a polymer conical bearing cup. The tribological behaviors of polymers used in bearing application has been addressed by using Archard's wear model, a well known classical model for fretting wear in the literature. However, these studies were for planar bearing surfaces and other geometries, not for the conical geometry addressed in this study. Tests were designed and implemented to study the wear rate of the conical bearing cups at with different load levels. The tribological behavior of Delrin in conical thrust bearing applications has been characterized, by quantifying the wear factors used in the modified Archard's model. Distinct reduction of wear rate is observed due to formation of a polymer transfer film on the steel ball. The variability of the wear properties is explored through replication of the test conditions. Destructive physical analysis is conducted to gain insight into the fundamental wear mechanisms as a part of this study. The results of the wear tests are used to develop a life model of the stepper motor as a case study, to demonstrate an application of this approach. The life model is used to study the effect of variability in the initial axial bearing preload (due to manufacturing tolerances), on the wear rate and life of the stepper motor

Novel Configurations of Ionic Polymer-Metal Composites (IPMCs) As Sensors, Actuators, and Energy Harvesters

This dissertation starts with describing the IPMC and defining its chemical structure and fundamental characteristics in Chapter 1. The application of these materials in the form of actuator, sensor, and energy harvester are reported through a literature review in Chapter 2. The literature review involves some electromechanical modeling approaches toward physics of the IPMC as well as some of the experimental results and test reports. This chapter also includes a short description of the manufacturing process of the IPMC. Chapter 3 presents the mechanical modeling of IPMC in actuation. For modeling, shear deformation expected not to be significant. Hence, the Euler-Bernoulli beam theory considered to be the approach defining the shape and critical points of the proposed IPMC elements. Description of modeling of IPMC in sensing mode is in Chapter 4. Since the material undergoes large deformation, large beam deformation is considered for both actuation and sensing model. Basic configurations of IPMC as sensor and actuator are introduced in Chapter 5. These basic configurations, based on a systematic approach, generate a large number of possible configurations. Based on the presented mechanisms, some parameters can be defined, but the selection of a proper arrangement remained as an unknown parameter. This mater is addressed by introducing a decision-making algorithm. A series of design for slit cylindrical/tubular/helical IPMC actuators and sensors are introduced in chapter 5. A consideration related to twisting of IPMCs in helical formations is reported through some experiments. Combinations of these IPMC actuators and sensors can be made to make biomimetic robotic devices as some of them are discussed in this chapter and the following Chapters 6 and 7. Another set of IPMC actuator/sensor configurations are introduced as a loop sensor and actuator that are presented subsequently in Chapter 6. These configurations may serve as haptic and tactile feedback sensors, particularly for robotic surgery. Both of these configurations (loop and slit cylindrical) of IPMCs are discussed in details, and some experimental measurements and results are also carried out and reported. The model for different inputs is studied, and report of the feedback is presented. Various designs of these configurations of IPMC are also presented in chapter 7, including their extension to mechanical metamaterials and soft robots

High Speed Under-Sampling Frequency Measurements on FPGA

A Sampling rate is less than Nyquist rate in some applications because of hardware limitations. Consequently, extensive researches have been conducted on frequency detection from sub-sampled signals. Previous studies on under-sampling frequency measurements have mostly discussed under-sampling frequency detection in theory and suggested possible methods for fast under-sampling frequencies detection. This study examined few suggested methods on Field Programmable Gate Array (FPGA) for fast under-sampling frequencies measurement. Implementation of the suggested methods on FPGA has issues that make them improper for fast data processing. This study tastes and discusses different methods for frequency detection including Least Squares (LS), Direct State Space (DSS), Goertzel filter, Sliding DFT, Phase changes of Fast Furrier Transform (FFT), peak amplitude of FFT to conclude which one from these methods are suitable for fast under-sampling frequencies detection on FPGA. Moreover, our proposed approach for sub-sampling detection from real waveform has less complextity than previous approaches from complex waveform

The Prevalence of Musculoskeletal Disorders and Ergonomic Risk Factors in Repair men: a Case Study in a Steel Industry

Background: Musculoskeletal disorders are one of the most common causes of occupational injuries and disability in industrialized and developing countries. The aim of this study was to investigate the prevalence of musculoskeletal disorders and to determine the level of risk for acquiring these disorders among workers in the central workshop of a steel industry in 2015. Methods: In this descriptive-analytical study done on 72 workers, the Nordic questionnaire was used to collect data related to musculoskeletal disorders and the Quick Exposure Check (QEC) method was used to determine the level of risk of these disorders and body postures. Data were analyzed through SPSS software version 16 and using Chi-Square test and Logistic regression. Results: The highest prevalence of musculoskeletal disorders were respectively in the low back (43.1%), knees (31.9%) and wrists (30.6%). The prevalence of musculoskeletal disorders was significantly related to age, work experience, and height (P<0.05). Also, there was a significant relation between the final QEC scores and the prevalence of musculoskeletal disorders (P=0.048). Conclusion: The prevalence of musculoskeletal disorders was high among the workers and the most common musculoskeletal disorder was in the lumbar region. It is essential to identify and control the related risk factors, in order to care about the health of workers and to prevent physical injuries among them

Hurdle negative binomial regression model with right censored count data

A Poisson model typically is assumed for count data. In many cases because of many zeros in the response variable, the mean is not equal to the variance value of the dependent variable. Therefore, the Poisson model is no longer suitable for this kind of data. Thus, we suggest using a hurdle negative binomial regression model to overcome the problem of overdispersion. Furthermore, the response variable in such cases is censored for some values. In this paper, a censored hurdle negative binomial regression model is introduced on count data with many zeros. The estimation of regression parameters using maximum likelihood is discussed and the goodness-of-fit for the regression model is examined