Granted Patent B2

US 12,480,984 · App. 18/017,336 · Granted Nov 25, 2025

Inventors: Lackis Eleftheriadis (Valbo, SE); Athanasios Karapantelakis (Solna, SE); Konstantinos Vandikas (Solna, SE); Aneta Vulgarakis Feljan (Stockholm, SE); Yifei Jin (Solna, SE)

Assignee: TELEFONAKTIEBOLAGET LM ERICSSON (PUBL)

G01R31/2801

Abstract

Claims (74)

1 . A method for testing a Printed Circuit Board (PCB), the method being executed at a testing system comprising a Radio Frequency (RF) test analyzer, a RF energy source, and one or more RF probes, the method comprising:

performing a first level scanning of a first set of components in the PCB;

identifying a first anomaly based on information obtained as a result of performing the first level scanning;

identifying a second set of components in the PCB different from the first set of components in the PCB based on the first anomaly that was identified based on the information obtained as a result of performing the first level scanning of the first set of components in the PCB;

performing a second level scanning of the second set of components in the PCB; and

determining a root cause of the first anomaly based on information obtained as a result of performing the second level scanning of the second set of components.

2 . The method of claim 1 , further comprising:

training a RF testing data model using machine learning techniques in the RF test analyzer;

analyzing the information obtained as a result of performing the first level scanning with the trained RF testing data model in the RF test analyzer;

analyzing information obtained as a result of performing the second level scanning with the trained RF testing data model in the RF test analyzer; and

retraining the RF testing data model based on identified associated new learnings using machine learning techniques in the RF test analyzer.

3 . The method of claim 2 , wherein performing the first level scanning further comprises:

identifying the first set of components in the PCB and associated set of scanning conditions for each component of the first set of components in the PCB using the RF test analyzer;

deducing a RF signature for each component of a general set of components in the PCB based on a general associated set of scanning conditions by the RF test analyzer, wherein the general set of components in the PCB corresponds to the first set of components in the PCB and the general associated set of scanning conditions corresponds to the associated set of scanning conditions;

identifying the first anomaly based on verifying the deduced RF signature for each component of the first set of components using the trained RF testing data model in the RF test analyzer; and

providing the information obtained as a result of performing the first level scanning.

4 . The method of claim 2 , wherein performing the second level scanning further comprises:

determining the second set of components in the PCB and associated set of scanning conditions for each component of the second set of components in the RF test analyzer;

deducing a RF signature for each component of a general set of components in the PCB based on a general associated set of scanning conditions by the RF test analyzer, wherein the general set of components in the PCB corresponds to the second set of components in the PCB and the general associated set of scanning conditions corresponds to the associated set of scanning conditions; and

performing next level scanning based on verifying the deduced RF signature for each component of the second set of components using the trained RF testing data model in the RF test analyzer.

5 . The method of claim 2 , wherein performing the second level scanning further comprises:

determining the root cause of the first anomaly using the RF test analyzer; and

correlating the root cause and a second root cause for identifying the associated new learnings using the RF test analyzer.

6 . The method of claim 5 , wherein determining the root cause of the identified first anomaly comprising:

analyzing the identified first anomaly using machine learning techniques for identifying the root cause in the RF test analyzer.

7 . A non-transitory computer readable storage medium storing a computer program comprising computer-executable instruction for causing a testing system to perform the method of claim 1 .

8 . The method of claim 1 , wherein

the first set of components comprises a first component located in a first layer of the PCB,

determining, based on the first anomaly, that an anomaly exists in the first layer of the PCB, and

identifying the second set of components in the PCB based on the first anomaly comprises:

as a result of determining that an anomaly exists in the first layer of the PCB, a) selecting a component that i) was not scanned during the first level scanning and ii) is located in the first layer of the PCB and b) adding the identified component to the second set of components.

9 . A testing system configured for testing a Printed Circuit Board (PCB), comprising:

a Radio Frequency (RF) test analyzer;

a RF energy source;

one or more RFprobes;

a memory; and

a processor circuitry configured to:

perform a first level scanning of a first set of components in the PCB;

identify a first anomaly based on information obtained as a result of performing the first level scanning;

identify a second set of components in the PCB different from the first set of components in the PCB based on the first anomaly that was identified based on the information obtained as a result of performing the first level scanning of the first set of components in the PCB;

perform a second level scanning of the second set of components in the PCB; and

determine a root cause of the first anomaly based on information obtained as a result of performing the second level scanning of the second set of components.

10 . The testing system of claim 9 , further configured to:

train a RF testing data model using machine learning techniques in the RF test analyzer;

analyze the information obtained as a result of performing the first level scanning with the trained RF testing data model in the RF test analyzer;

analyze information obtained as a result of performing the second level scanning with the trained RF testing data model in the RF test analyzer; and

retrain the RF testing data model based on identified associated new learnings using machine learning techniques in the RF test analyzer.

11 . The testing system of claim 10 , wherein to perform the first level scanning comprises to:

identify the first set of components in the PCB and associated set of scanning conditions for each component of the first set of components in the PCB using the RF test analyzer;

deduce a RF signature for each component of a general set of components in the PCB based on a general associated set of scanning conditions by the RF test analyzer, wherein the general set of components in the PCB corresponds to the first set of components in the PCB and the general associated set of scanning conditions corresponds to the associated set of scanning conditions;

identify the first anomaly based on verifying the deduced RF signature for each component of the first set of components using the trained RF testing data model in the RF test analyzer; and

provide the information obtained as a result of performing the first level scanning.

12 . The testing system of claim 11 , wherein to deduce the RF signature for each component of the general set of components in the PCB comprises to:

activate each component of the general set of components in the PCB by applying a set of electromagnetic signals generated using the RF energy source based on the general associated set of scanning conditions for each component of the general set of components;

capture RF signals generated by each activated component of the general set of components based on the applied set of electromagnetic signals using the RF probes; and

deduce the RF signature by the RF test analyzer for each component of the general set of components based on analyzing the captured RF signals for each component of the general set of components provided to the RF test analyzer by the RF probes.

13 . The testing system of claim 11 , wherein the scanning conditions are based on: functionalities of a component to be verified, different positions of testing, and/or depth level of the component in the PCB.

14 . The testing system of claim 10 , wherein to perform the second level scanning comprises to:

determine the second set of components in the PCB and associated set of scanning conditions for each component of the second set of components in the RF test analyzer;

deduce a RF signature for each component of a general set of components in the PCB based on a general associated set of scanning conditions by the RF test analyzer, wherein the general set of components in the PCB corresponds to the second set of components in the PCB and the general associated set of scanning conditions corresponds to the associated set of scanning conditions; and

perform next level scanning based on verifying the deduced RF signature for each component of the second set of components using the trained RF testing data model in the RF test analyzer.

15 . The testing system of claim 14 , wherein to determine the second set of components in the PCB and associated set of scanning conditions for each component of the second set of components comprises to:

identify the second set of components in the PCB and associated set of scanning conditions for each component of the second set of components based on the first anomaly using the trained RF testing data model in the RF test analyzer.

16 . The testing system of claim 14 , wherein to perform next level scanning comprises to:

determine a third set of components in the PCB and associated set of scanning conditions for each component of the third set of components in the RF test analyzer.

17 . The testing system of claim 10 , wherein to perform the second level scanning comprises to:

determine the root cause of the first anomaly using the RF test analyzer; and

correlate the root cause and a second root cause for identifying the associated new learnings using the RF test analyzer.

18 . The testing system of claim 17 , wherein to determine the root cause of the first anomaly comprises to:

analyze the identified first anomaly using machine learning techniques for identifying the root cause in the RF test analyzer.

19 . The testing system of claim 17 , wherein to correlate the root cause and the second root cause for identifying the associated new learnings comprises to:

identify the associated new learnings by correlating the root cause and the second root cause using machine learning techniques in the RF test analyzer.

20 . The testing system of claim 9 , wherein the first level scanning is a high-level scanning performed on a minimal number of components and associated set of scanning conditions.

21 . The testing system of claim 9 , wherein the second level scanning is a detailed level scanning performed for the second set of components and associated set of scanning conditions identified based on the first anomaly.

Assignments (1)

Continuity (1)

References Cited (17)