Systems and methods for detecting foreign metallic particles

Patent metadata

Field	Value
Publication number	US-12590878-B2
Application number	US-202318475501-A
Country	US
Kind code	B2
Filing date	Sep 27, 2023
Priority date	Feb 28, 2023
Publication date	Mar 31, 2026
Grant date	Mar 31, 2026

Abstract

One form of a metallic particle detection system detects automatically, through analysis of image data from a first sensor, a foreign metallic particle in or on an active material layer of an electrode strip moving between a section and a subsequent section on a roll-to-roll coated electrode manufacturing line that manufactures a plate electrode. The system also determines a position of the foreign metallic particle on the electrode strip moving on the roll-to-roll coated electrode manufacturing line. The system also triggers, in response to detection of the foreign metallic particle and based on the position of the foreign metallic particle and a speed at which the electrode strip is moving, the second sensor, the second sensor generating a reflectance spectrum of the foreign metallic particle. The system also analyzes the reflectance spectrum to identify a type of metal of which the foreign metallic particle is composed.

First claim

What is claimed is:

1 . A system for detecting foreign metallic particles, the system comprising:
a first sensor and a second sensor; a processor; and a memory storing machine-readable instructions that, when executed by the processor, cause the processor to:
detect automatically, through analysis of image data from the first sensor, a foreign metallic particle in or on an active material layer of an electrode strip moving between a section and a subsequent section on a roll-to-roll coated electrode manufacturing line that manufactures a plate electrode;
determine a position of the foreign metallic particle on the electrode strip moving on the roll-to-roll coated electrode manufacturing line;
trigger, in response to detection of the foreign metallic particle and based on the position of the foreign metallic particle and a speed at which the electrode strip is moving, the second sensor, the second sensor generating a reflectance spectrum of the foreign metallic particle;
analyze the reflectance spectrum to identify a type of metal of which the foreign metallic particle is composed; and
determine automatically, based on the type of metal and associated size and morphology data, an origin, in the roll-to-roll coated electrode manufacturing line, of the detected foreign metallic particle.

2 . The system of claim 1 , wherein the first sensor is one of a line scanner and a sCMOS camera with a rolling shutter.

3 . The system of claim 1 , wherein the first sensor detects light from a monochromatic light source that is reflected from the active material layer.

4 . The system of claim 1 , wherein the second sensor is a hyperspectral imager, the hyperspectral imager detecting light from a broadband light source that is reflected from the active material layer and that passes through a spectroscopic optical element, the spectroscopic optical element operating in a wavelength-dependent manner upon the light from the broadband light source that is reflected from the active material layer.

5 . The system of claim 4 , wherein the spectroscopic optical element is one of a diffraction grating and a photonic crystal mask.

6 . The system of claim 1 , wherein the machine-readable instructions to at least one of analyze the image data from the first sensor and analyze the reflectance spectrum from the second sensor include instructions that, when executed by the processor, cause the processor to apply a machine-learning model.

7 . The system of claim 1 , wherein the type of metal is one of copper, aluminum, gold, silver, and stainless steel.

8 . The system of claim 1 , wherein the plate electrode is one of a battery plate electrode and a fuel cell plate electrode.

9 . The system of claim 1 , wherein the machine-readable instructions include further instructions that, when executed by the processor, cause the processor to remove automatically, from the roll-to-roll coated electrode manufacturing line, a segment of the electrode strip that contains the detected foreign metallic particle.

10 . The system of claim 1 , further comprising a reference sensor that improves accuracy of absolute reflectance measurements by accounting for fluctuations in a light source associated with the second sensor.

11 . A non-transitory computer-readable medium for detecting foreign metallic particles and storing instructions that, when executed by a processor, cause the processor to:
detect automatically, through analysis of image data from a first sensor, a foreign metallic particle in or on an active material layer of an electrode strip moving between a section and a subsequent section on a roll-to-roll coated electrode manufacturing line that manufactures a plate electrode; determine a position of the foreign metallic particle on the electrode strip moving on the roll-to-roll coated electrode manufacturing line; trigger, in response to detection of the foreign metallic particle and based on the position of the foreign metallic particle and a speed at which the electrode strip is moving, a second sensor that generates a reflectance spectrum of the foreign metallic particle; analyze the reflectance spectrum to identify a type of metal of which the foreign metallic particle is composed; and determine automatically, based on the type of metal and associated size and morphology data, an origin, in the roll-to-roll coated electrode manufacturing line, of the detected foreign metallic particle.

12 . The non-transitory computer-readable medium of claim 11 , wherein the instructions include further instructions that, when executed by the processor, cause the processor to remove automatically, from the roll-to-roll coated electrode manufacturing line, a segment of the electrode strip that contains the detected foreign metallic particle.

13 . The non-transitory computer-readable medium of claim 11 , wherein the instructions to at least one of analyze the image data from the first sensor and analyze the reflectance spectrum from the second sensor include instructions that, when executed by the processor, cause the processor to apply a machine-learning model.

14 . A method, comprising:
detecting automatically, through analysis of image data from a first sensor, a foreign metallic particle in or on an active material layer of an electrode strip moving between a section and a subsequent section on a roll-to-roll coated electrode manufacturing line that manufactures a plate electrode; determining a position of the foreign metallic particle on the electrode strip moving on the roll-to-roll coated electrode manufacturing line; triggering, in response to detection of the foreign metallic particle and based on the position of the foreign metallic particle and a speed at which the electrode strip is moving, a second sensor that generates a reflectance spectrum of the foreign metallic particle; analyzing the reflectance spectrum to identify a type of metal of which the foreign metallic particle is composed; and determining automatically, based on the type of metal and associated size and morphology data, an origin, in the roll-to-roll coated electrode manufacturing line, of the detected foreign metallic particle.

15 . The method of claim 14 , wherein at least one of analyzing the image data from the first sensor and analyzing the reflectance spectrum from the second sensor is performed using a machine-learning model.

16 . The method of claim 14 , further comprising removing automatically, from the roll-to-roll coated electrode manufacturing line, a segment of the electrode strip that contains the detected foreign metallic particle.

17 . The method of claim 14 , further comprising using a reference sensor to improve accuracy of absolute reflectance measurements by accounting for fluctuations in a light source associated with the second sensor.

Assignees

• Toyota Res Inst Inc
• Toyota Motor Co Ltd

Inventors

• Gordon Matthew P

Classifications

• Y02E60/10

  Energy storage using batteries · CPC title

• G01N21/95

  characterised by the material or shape of the object to be examined (G01N21/89 - G01N21/91, G01N21/94 take precedence) · CPC title

• G01N2021/8909

  Scan signal processing specially adapted for inspection of running sheets · CPC title

• G01N2021/8861

  Determining coordinates of flaws · CPC title

• G01N21/94

  Investigating contamination, e.g. dust (G01N21/85 takes precedence) · CPC title