Method and system for testing a printed circuit board

Patent metadata

Field	Value
Publication number	US-12480984-B2
Application number	US-202018017336-A
Country	US
Kind code	B2
Filing date	Jul 22, 2020
Priority date	Jul 22, 2020
Publication date	Nov 25, 2025
Grant date	Nov 25, 2025

Abstract

A testing system and method for testing a Printed Circuit Boards (PCBs) is provided. The method is being executed at a testing system which comprises a RF test analyzer; a RF energy source; and one or more RF probes. The method includes performing a first level scanning of a first set of components in the PCB. The method further includes performing a second level scanning of another set of components in the PCB, which differs from the first set of components in the PCB; the second level scanning is performed only if anomalies are identified which is based on analyzing the results of the performed first level scanning. The method further includes determining detailed root causes of the identified anomalies which is based on analyzing results of the performed second level scanning.

First claim

The invention claimed is:

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; an

Assignees

• Ericsson Telefon Ab L M

Inventors

• Eleftheriadis Lackis
• Karapantelakis Athanasios
• Vandikas Konstantinos
• Vulgarakis Feljan Aneta
• Jin Yifei

Classifications

• G01R31/2812

  Checking for open circuits or shorts, e.g. solder bridges; Testing conductivity, resistivity or impedance (of connections G01R31/66) · CPC title

• G01R31/2801 Primary

  Testing of printed circuits, backplanes, motherboards, hybrid circuits or carriers for multichip packages [MCP] (G01R31/318508 takes precedence; contactless testing G01R31/302; testing contacts or connections G01R31/66) · CPC title

• G01R31/2813 Primary

  Checking the presence, location, orientation or value, e.g. resistance, of components or conductors (orientation of the DUT with respect to the test fixture G01R1/06705) · CPC title