Methodologies for System-State Interrogation for Prognostication of Electronics Under Thermo-Mechanical Loads

2007 ◽  
Author(s):  
Pradeep Lall ◽  
Madhura Hande ◽  
Chandan Bhat ◽  
Jeff Suhling
Keyword(s):  
Health Monitoring ◽  
Least Squares Method ◽  
Residual Life ◽  
Electronic System ◽  
Minimal Risk ◽  
Leading Indicators ◽  
System State ◽  
Electronic Warfare ◽  
Mechanical Loads ◽  
Marquardt Algorithm

Methodologies for prognostication and health monitoring can significantly impact electronic reliability for applications in which even minimal risk of failure may be unbearable. Presently, health monitoring approaches such as the built-in self-test (BIST) are based on reactive failure diagnostics and unable to determine residual-life or estimate residual-reliability [Allen 2003, Drees 2004, Gao 2002, Rosenthal 1990]. Prognostics health-monitoring (PHM) approach presented in this paper is different from state-of-art diagnostics and resides in the pre-failure-space of the electronic-system, in which no macro-indicators such as cracks or delamination exist. Applications for the presented PHM framework include, consumer applications such as automotive safety systems including front and rear impact protection system, chassis-control systems, x-by-wire systems; and defense applications such as avionics systems, naval electronic warfare systems. The presented PHM methodologies enable the estimation of prior damage in deployed electronics by interrogation of the system state. The presented methodologies will trigger repair or replacement, significantly prior to failure. The approach involves the use of condition monitoring devices which can be interrogated for damage proxies at finite time-intervals. The system’s residual life is computed based on residual-life computation algorithms. Previously, Lall, et. al. [2004, 2005, 2006] have developed several leading indicators of failure. In this paper a mathematical approach has been presented to calculate the prior damage in electronics subjected to cyclic and isothermal thermomechanical loads. Electronic components operating in a harsh environment may be subjected to both temperature variations in addition to thermal aging during use-life. Data has been collected for leading indicators of failure for 95.5Sn4Ag0.5Cu first-level interconnects under both single and sequential application of cyclic and isothermal thermo-mechanical loads. Methodology for the determination of prior damage history has been presented using non-linear least-squares method based interrogation techniques. The methodology presented used the Levenberg-Marquardt Algorithm. Test vehicle includes various area-array packaging architectures soldered on Immersion Ag finish, subjected to thermal cycling in the range of −40°C to 125°C and isothermal aging at 125°C.

Leading Prognostic Indicators for Health Management of Electronics Under Thermo-Mechanical Stresses

2007 ◽  
Author(s):  
Pradeep Lall ◽  
Madhura Hande ◽  
Chandan Bhat ◽  
Jeff Suhling
Keyword(s):  
Health Monitoring ◽  
Least Squares Method ◽  
Health Management ◽  
Residual Life ◽  
Electronic System ◽  
Prognostic Indicators ◽  
Minimal Risk ◽  
Leading Indicators ◽  
Mechanical Loads ◽  
Marquardt Algorithm

Methodologies for prognostication and health monitoring can significantly impact electronic reliability for applications in which even minimal risk of failure may be unbearable. Presently, health monitoring approaches such as the built-in self-test (BIST) are based on reactive failure diagnostics and unable to determine residual-life or estimate residual-reliability [Allen 2003, Drees 2004, Gao 2002, Rosenthal 1990]. Prognostics health-monitoring (PHM) approach presented in this paper is different from state-of-art diagnostics and resides in the pre-failure-space of the electronic-system, in which no macro-indicators such as cracks or delamination exist. Applications for the presented PHM framework include, consumer applications such as automotive safety systems including front and rear impact protection system, chassis-control systems, x-by-wire systems; and defense applications such as avionics systems, naval electronic warfare systems. The presented PHM methodologies enable the estimation of prior damage in deployed electronics by interrogation of the system state. The presented methodologies will trigger repair or replacement, significantly prior to failure. The approach involves the use of condition monitoring devices which can be interrogated for damage proxies at finite time-intervals. The system’s residual life is computed based on residual-life computation algorithms. Previously, Lall, et. al. [2004, 2005, 2006] have developed several leading indicators of failure. In this paper a mathematical approach has been presented to calculate the prior damage in electronics subjected to cyclic and isothermal thermo-mechanical loads. Electronic components operating in a harsh environment may be subjected to both temperature variations in addition to thermal aging during use-life. Data has been collected for leading indicators of failure for 95.5Sn4Ag0.5Cu first-level interconnects under both single and sequential application of cyclic and isothermal thermo-mechanical loads. Methodology for the determination of prior damage history has been presented using non-linear least-squares method based interrogation techniques. The methodology presented used the Levenberg-Marquardt Algorithm. Test vehicle includes various area-array packaging architectures soldered on Immersion Ag finish, subjected to thermal cycling in the range of −40°C to 125°C and isothermal aging at 125°C.

Prognostication of system-state in lead-free electronics equipment under cyclic and steady-state thermo-mechanical loads

2009 ◽  
Vol 49 (8) ◽  
pp. 825-838 ◽  
Author(s):  
Pradeep Lall ◽  
Madhura Hande ◽  
Chandan Bhat ◽  
Vikrant More ◽  
Rahul Vaidya
Keyword(s):  
Steady State ◽  
Lead Free ◽  
System State ◽  
Mechanical Loads

scholarly journals A Robust and Adaptive Complementary Kalman Filter Based on Mahalanobis Distance for Ultra Wideband/Inertial Measurement Unit Fusion Positioning

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3435 ◽  
Author(s):  
Xin Li ◽  
Yan Wang ◽  
Kourosh Khoshelham
Keyword(s):  
Kalman Filter ◽  
Mahalanobis Distance ◽  
Inertial Measurement Unit ◽  
Least Squares Method ◽  
Ultra Wideband ◽  
Measurement Unit ◽  
Observation Error ◽  
System State ◽  
Inertial Measurement ◽  
The Impact

Ultra wideband (UWB) has been a popular technology for indoor positioning due to its high accuracy. However, in many indoor application scenarios UWB measurements are influenced by outliers under non-line of sight (NLOS) conditions. To detect and eliminate outlying UWB observations, we propose a UWB/Inertial Measurement Unit (UWB/IMU) fusion filter based on a Complementary Kalman Filter to track the errors of position, velocity and direction. By using the least squares method, the positioning residual of the UWB observation is calculated, the robustness factor of the observation is determined, and an observation weight is dynamically set. When the robustness factor does not exceed a pre-defined threshold, the observed value is considered trusted, and adaptive filtering is used to track the system state, while the abnormity of system state, which might be caused by IMU data exceptions or unreasonable noise settings, is detected by using Mahalanobis distance from the observation to the prior distribution. When the robustness factor exceeds the threshold, the observed value is considered abnormal, and robust filtering is used, whereby the impact of UWB data exceptions on the positioning results is reduced by exploiting Mahalanobis distance. Experimental results show that the observation error can be effectively estimated, and the proposed algorithm can achieve an improved positioning accuracy when affected by outlying system states of different quantity as well as outlying observations of different proportion.

scholarly journals Audit of physical health monitoring during initiation and ongoing treatment with antipsychotic medication in a tier 3 outpatient CAMHS service, Belfast

BJPsych Open ◽  
2021 ◽  
Vol 7 (S1) ◽  
pp. S323-S324
Author(s):  
Pam Hamlyn ◽  
Aaron McMenamin ◽  
Hilary Boyd ◽  
Lara Patton
Keyword(s):  
Young People ◽  
Physical Health ◽  
Antipsychotic Medication ◽  
Health Monitoring ◽  
Care Pathway ◽  
Electronic System ◽  
Clinical Notes ◽  
Medication Monitoring ◽  
Tier 3 ◽  
Health Parameters

AimsTo evidence that physical health monitoring during antipsychotic initiation and continued treatment within the Child and Family Clinic is current, as per the agreed Antipsychotic Medication Monitoring Schedule for Belfast Trust CAMHS (2015), supporting Quality Network for Community CAMHS(QNCC) accreditation.BackgroundThe Antipsychotic Medication Monitoring Schedule CAMHS(2015) was agreed by a working group of consultant psychiatrists and pharmacists, based on evidence from The Canadian Alliance for Monitoring Effectiveness and Safety of Antipsychotics in Children (CAMSEA), NICE Guidelines CG 185(2014), CG155(2013) and Maudsley Guidelines, and was to be located on the electronic system (PARIS).MethodIn January 2019, a list of all children/young people on antipsychotic medication was collated (n = 12). Presence of the monitoring schedule in the clinical notes or PARIS was recorded. The Electronic Care Record was reviewed for blood results and PARIS letters for documentation of physical health parameters (heart rate, blood pressure, height, weight, BMI, extrapyramidal side effects, ECG) and to identify documentation of risk/benefit review where monitoring was declined. Re-audit January 2020 (n = 9). Criteria:All patients commenced on antipsychotic medication will have baseline blood investigations and other physical health parameters documented as per the monitoring schedule. If monitoring was declined, the reason for this and indications for prescribing must be documented as a risk/benefit analysis.All patients on antipsychotic medication will be current with their physical health Monitoring Schedule.All patients will have their Monitoring Schedule completed in clinical notes or on PARIS.ResultFirst cycle results (n = 12):Baseline bloods (or documented declined) = 92%, Baseline ECG (or documented declined) = 75%Complete monitoring bloods = 33%, Physical health monitoring parameters complete = 42%Monitoring schedule present in the notes and current = 42% (0% on PARIS).Initial Recommendations: Standardised recording of monitoring using PARIS clinic letters and the schedule in front of clinical notes; Baseline ECG mandatorySecond cycle results (n = 9):Baseline bloods (or declined) = 89%, Baseline ECG (or declined) = 67%Complete monitoring bloods = 44%, Physical health monitoring parameters complete = 56%Monitoring schedule present in notes and current = 38%, Present, not current = 50% (0% on PARIS).ConclusionLower numbers at re-audit limit interpretation.Further recommendations: Antipsychotic initiation checklist; Central bloods diary for clinicians; Antipsychotic care-pathway booklet, co-produced with young people, incorporating the monitoring schedule.

Leading Indicators of Damage for Prognostication of Leadfree Electronics Subjected to Multiple Thermo-Mechanical Environments

2009 ◽  
Author(s):  
Pradeep Lall ◽  
Rahul Vaidya ◽  
Vikrant More ◽  
Jeff Suhling ◽  
Kai Goebel
Keyword(s):  
Residual Life ◽  
Thermal Environment ◽  
High Reliability ◽  
Damage State ◽  
Core System ◽  
Thermal Environments ◽  
Marquardt Algorithm ◽  
Tools And Techniques ◽  
Deployed Systems ◽  
Electronic Assemblies

Electronic assemblies deployed in harsh environments may be subjected to multiple thermal environments during the use-life of the equipment. Often the equipment may not have any macro-indicators of damage such as cracks or delamination. Quantification of thermal environments during use-life is often not feasible because of the data-capture and storage requirements, and the overhead on core-system functionality. There is need for tools and techniques to quantify damage in deployed systems in absence of macro-indicators of damage without knowledge of prior stress history. The presented PHM framework is targeted towards high reliability applications such as avionic and space systems. In this paper, Sn3.0Ag0.5Cu alloy packages have been subjected to multiple thermal cycling environments including −55 to 125C and 0 to 100C. Assemblies investigated include area-array packages soldered on FR4 printed circuit cards. The methodology involves the use of condition monitoring devices, for gathering data on damage pre-cursors at periodic intervals. Damage-state interrogation technique has been developed based on the Levenberg-Marquardt Algorithm in conjunction with the microstructural damage evolution proxies. The presented technique is applicable to electronic assemblies which have been deployed on one thermal environment, then withdrawn from service and targeted for redeployment in a different thermal environment. Test cases have been presented to demonstrate the viability of the technique for assessment of prior damage, operational readiness and residual life for assemblies exposed to multiple thermo-mechanical environments. Prognosticated prior damage and the residual life show good correlation with experimental data, demonstrating the validity of the presented technique for multiple thermo-mechanical environments.

Remaining Useful-Life Based on Damage Pre-Cursors for Leadfree Electronics Subjected to Multiple Thermal-Environments

2009 ◽  
Author(s):  
Pradeep Lall ◽  
Rahul Vaidya ◽  
Vikrant More ◽  
Jeff Suhling ◽  
Kai Goebel
Keyword(s):  
Residual Life ◽  
Thermal Environment ◽  
High Reliability ◽  
Remaining Useful Life ◽  
Damage State ◽  
Core System ◽  
Thermal Environments ◽  
Marquardt Algorithm ◽  
Tools And Techniques ◽  
Electronic Assemblies

Electronic assemblies deployed in harsh environments may be subjected to multiple thermal environments during the use-life of the equipment. Often the equipment may not have any macro-indicators of damage such as cracks or delamination. Quantification of thermal environments during use-life is often not feasible because of the data-capture and storage requirements, and the overhead on core-system functionality. There is need for tools and techniques to quantify damage in deployed systems in absence of macro-indicators of damage without knowledge of prior stress history. The presented PHM framework is targeted towards high reliability applications such as avionic and space systems. In this paper, Sn3.0Ag0.5Cu alloy packages have been subjected to multiple thermal cycling environments including −55 to 125C and 0 to 100C. Assemblies investigated include area-array packages soldered on FR4 printed circuit cards. The methodology involves the use of condition monitoring devices, for gathering data on damage pre-cursors at periodic intervals. Damage-state interrogation technique has been developed based on the Levenberg-Marquardt Algorithm in conjunction with the microstructural damage evolution proxies. The presented technique is applicable to electronic assemblies which have been deployed on one thermal environment, then withdrawn from service and targeted for redeployment in a different thermal environment. Test cases have been presented to demonstrate the viability of the technique for assessment of prior damage, operational readiness and residual life for assemblies exposed to multiple thermo-mechanical environments. Prognosticated prior damage and the residual life show good correlation with experimental data, demonstrating the validity of the presented technique for multiple thermo-mechanical environments.

Nondestructive health monitoring techniques for composite materials: A review

2020 ◽  
pp. 096739112092170
Author(s):  
M Senthilkumar ◽  
TG Sreekanth ◽  
S Manikanta Reddy
Keyword(s):  
Health Monitoring ◽  
Composite Structures ◽  
Residual Life ◽  
Present Condition ◽  
Nondestructive Technique ◽  
Technical Data ◽  
Monitoring Techniques ◽  
Low Weight ◽  
Marine Applications ◽  
The Impact

Structural health monitoring is the process of acquisition and analyzing technical data obtained from structures to determine the present condition of the structure and residual life. Composites have been widely in use because of their low weight and better mechanical properties compared to conventional metals. They are more prone to damage during cyclic loading and the impact of foreign objects. So, usage of the nondestructive techniques is important to detect such damage in composites at the beginning stage itself, which further helps to avoid catastrophic failure. Many review articles are discussing a single nondestructive technique to monitor the health of the structure, but a single technique is not sufficient in most of the cases. This review is focused on the most commonly used nondestructive health monitoring techniques such as acoustic emission, vibration testing, ultrasonic testing, infrared thermography, and shearography to detect and characterize the damage in composite structures used in aerospace, automotive, and marine applications. The comparison among the techniques also has been presented in this review.

scholarly journals Method to generate growth and degrowth models obtained from differential equations applied to agrarian sciences

2018 ◽  
Vol 39 (6) ◽  
pp. 2659 ◽  
Author(s):  
André Luiz Pinto dos Santos ◽  
Guilherme Rocha Moreira ◽  
Cicero Carlos Ramos de Brito ◽  
Frank Gomes-Silva ◽  
Maria Lindomárcia Leonardo da Costa ◽  
...  
Keyword(s):  
Differential Equations ◽  
Goodness Of Fit ◽  
Least Squares Method ◽  
Growth Curves ◽  
Information Criterion ◽  
Coefficient Of Determination ◽  
Absolute Deviation ◽  
Marquardt Algorithm ◽  
Maturation Rate ◽  
Biological Interpretation

This study aims to propose a method to generate growth and degrowth models using differential equations as well as to present a model based on the method proposed, compare it with the classic linear mathematical models Logistic, Von Bertalanffy, Brody, Gompertz, and Richards, and identify the one that best represents the mean growth curve. To that end, data on Undefined Breed (UB) goats and Santa Inês sheep from the works of Cavalcante et al. (2013) and Sarmento et al. (2006a), respectively, were used. Goodness-of-fit was measured using residual mean squares (RMS), Akaike information criterion (AIC), Bayesian information criterion (BIC), mean absolute deviation (MAD), and adjusted coefficient of determination . The models’ parameters (?, weight at adulthood; ?, an integration constant; ?, shape parameter with no biological interpretation; k, maturation rate; and m, inflection point) were estimated by the least squares method using Levenberg-Marquardt algorithm on the software IBM SPSS Statistics 1.0. It was observed that the proposed model was superior to the others to study the growth curves of goats and sheep according to the methodology and conditions under which the present study was carried out.

Sign in / Sign up

Export Citation Format

Share Document