PCB Testing Using Infrared Thermal Signatures

Moldovan, H.; Marcu, Marius; Vlăduţiu, Mircea

doi:10.1109/imtc.2005.1604516

Cited by 9 publications

(11 citation statements)

References 7 publications

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“…PCBAs is the infrared thermal signature technique [6]. By classifying integrated circuits (IC) into a number of functional classes based on their thermal image, the PCBAs can also be classified into functional categories based on the classification of the ICs implemented on the board.…”

Section: An Alternative Inspection Technique For High Densitymentioning

confidence: 99%

New testing approach using near electromagnetic field probing intending to upgrade in-circuit testing of high density PCBAs

Alaoui

Tounsi

Boyer

et al. 2018

2018 IEEE 27th North Atlantic Test Workshop (NATW)

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With the density increase of today's printed circuit board assemblies (PCBA), the electronic test methods reached their limits, in the same time the requirements of high reliability and robustness are greater. Original equipment manufacturers are obliged to reduce the number of physical test points and to find better-adapted test methods. Current test methods must be rethought to include a large panel of physical phenomena that can be used to detect electrical defects of components, absence, wrong value, and shorts at component level on the board under test (BUT). We will present the possibility of using electromagnetic signature to diagnose faulty components contactlessly. The technique consists in using small diameter near electromagnetic field probes, which detect the field distribution over powered sensitive components. A giant magnetoresistance (GMR) sensor was used as well to detect variations in low frequency components. The loading of the BUT is specifically chosen to enhance the sensitivity of the EM measurements. Reference EM signatures are extracted from a fault-free circuit, which will be compared to those extracted from a sample PCBA in which we introduced a component level defect by removing or changing the value of critical components. As a result, we will show that the amplitude of a specific harmonic acts as a sensing parameter, which is accurately related to the variation of the component value.

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Section: An Alternative Inspection Technique For High Densitymentioning

confidence: 99%

New testing approach using near electromagnetic field probing intending to upgrade in-circuit testing of high density PCBAs

Alaoui

Tounsi

Boyer

et al. 2018

2018 IEEE 27th North Atlantic Test Workshop (NATW)

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show abstract

“…These methods are used for diagnosis and eliminate the defects and speed up weak component failures. However, problems with a short circuit, a faulty transistor, or a circuit that creates hotspot will stay invisible [2]. Therefore, the thermal testing methods are useful in the process of designing and testing of complex VLSI circuits.…”

Section: Introductionmentioning

confidence: 99%

“…The thermal testing method is one of the Non-Destructive Testing (NDT) techniques for testing and showing hot spots on operating ICs, depending on the failure conditions such as shorts, over stressed or faulty components [2]. The primary benefits of NDT are to detect the flaws and defects of materials without changing or destroying their functionality and guarantee the safe operation of the system components.…”

Section: Introductionmentioning

confidence: 99%

IC testing using thermal image based on intelligent classification methods

Al-Obaidy¹

2021

Preprint

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The goal of this thesis is to propose an algorithm which would can locate the defect IC on the PCB during their manufacturing phase based on a thermal image. A 3-dimensional PCB finite-element model is developed to estimate the temperature profile of stacked ICs. Image processing by noise removing and region of interest segmentation are applied. Two sets of feature extraction are presented; first-order histogram features and Gray Level Co-occurrence Matrix (GLCM) features. The Principle Component Analysis (PCA) method is applied to decrease the feature's extractions into smallest uncorrelated input. Three main intelligent techniques; Multilayer Perceptron (MLP), Support Vector Machine (SVM), and Adaptive Neuro-Fuzzy Inference System (ANFIS) are used to classify the thermal conditions of ICs into normal and faulty status. On validation, the proposed approach applies to do thermal testing on Arduino UNO. The experimental evaluation is performed to detect the fault condition on the real time operating PCB.

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“…In the process of testing this defect detection approach, we used the temperature evolution of capacitors mounted on a DC/DC boost converter board [4] as heat signatures. The usual way of using infrared testing is to compare an acquired IR signature with a statistical model computed from IR signatures obtained from a set of knowngood boards [5], [6]. The problem of this solution is to choose a proper threshold value and to compute and maintain the statistical model.…”

Section: Introductionmentioning

confidence: 99%

Detecting PCB Assembly Defects Using Infrared Thermal Signatures

Alaoui¹,

Tounsi²,

Boyer³

et al. 2019

2019 MIXDES - 26th International Conference "Mixed Design of Integrated Circuits and Systems"

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A Printed Circuit Board assembly (PCBA) testing approach using infrared thermal signatures is presented. The concept of thermal signature for PCBAs is introduced. Based on this concept, the testing method is able to:-detect assembly defects such as presence, polarity, value and solder (shorts and opens) and in some cases component health state-classify the components mounted on the PCB into a number of classes (e.g.-fault free(reliable), functional (less reliable), faulty). According to the thermal signature of each component on the PCBA, PCBAs can be also classified in the same number of classes. In this article a special focus is put on capacitor defects especially capacitor value defects. Therefore, they will be the main components tested. The fault detection indicator used in this proof of concept is a statistical mean squared error measure (MSE).

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PCB Testing Using Infrared Thermal Signatures

Cited by 9 publications

References 7 publications

New testing approach using near electromagnetic field probing intending to upgrade in-circuit testing of high density PCBAs

New testing approach using near electromagnetic field probing intending to upgrade in-circuit testing of high density PCBAs

IC testing using thermal image based on intelligent classification methods

Detecting PCB Assembly Defects Using Infrared Thermal Signatures

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