# US 2004/0069754 A1 · Laser weld Monitor > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2004/0069754 A1 - Document ID: US20040069754A1 - Status: Published application - Kind: A1 - Application number: 10/673,828 - Filed: 2003-09-29 - Published: 2004-04-15 - Earliest claimed: 2002-07-31 - Assignees: Miyachi Unitek Corporation; Miyachi Technos Corporation - Inventors: Gregory Bates; Girish Kelkar - Web page: https://patentgrep.com/patent/US20040069754A1 ## CPC - B23K 26/032: {using optical means} - B23K 26/03: Observing, e.g. monitoring, the workpiece - B23K 26/034: {Observing the temperature of the workpiece} - B23K 26/22: Spot welding - B23K 26/242: Fillet welding, i.e. involving a weld of substantially triangular cross section joining two parts - B23K 26/244: Overlap seam welding - B23K 31/125: {Weld quality monitoring} - G01N 3/08: by applying steady tensile or compressive forces (G01N3/28 takes precedence) - G01N 2203/0694: Temperature - B23K: SOLDERING OR UNSOLDERING; WELDING; CLADDING OR PLATING BY SOLDERING OR WELDING; CUTTING BY APPLYING HEAT LOCALLY, e.g. FLAME CUTTING; WORKING BY LASER BEAM - G01N: INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES (measuring or testing apparatus or processes other than immunoassay, involving enzymes or microorganisms C12M, C12Q) ## Abstract A laser weld monitoring system capable of assessing a weld quality of welding using a pulsed laser is provided. The system includes at least one sensor capable of capturing a weld characteristic of welding using said pulsed laser. The weld characteristic has multiple attributes. The system also includes data acquisition and processing equipment adapted for storing and analyzing the weld characteristic. A user first performs multiple welds to capture at least one weld characteristic for each weld. The user then determines the weld quality of each weld, and runs at least one of a library of algorithms associated with the attributes on said at least one weld characteristic for each weld to generate a single value output for the associated attribute. The user selects an attribute indicative of the weld quality by correlating the single value outputs of said at least one algorithm with the weld qualities of the welds. ## Claims ### Claim 1 A laser weld monitoring system capable of assessing a weld quality of welding using a laser, said system comprising: at least one sensor capable of capturing a weld characteristic of welding using said laser, said weld characteristic having a plurality of attributes; and data acquisition and processing equipment adapted for storing and analyzing said weld characteristic, wherein a user performs a plurality of welds to capture at least one weld characteristic for each weld, determines the weld quality of each weld, runs at least one of a library of algorithms associated with the attributes on said at least one weld characteristic for each weld to generate a single value output for the associated attribute, and selects an attribute indicative of the weld quality by correlating the single value outputs of said at least one algorithm with the weld qualities of the welds. ### Claim 2 (depends on 1) The laser weld monitoring system according to claim 1, wherein the user performs the welds at different weld conditions to correlate a variation in the weld quality with the variation in the single value output for said at least one algorithm as the weld conditions change. ### Claim 3 (depends on 1) The laser weld monitoring system according to claim 1, wherein the user determines the weld quality of each weld by performing a physical testing. ### Claim 4 (depends on 1) The laser weld monitoring system according to claim 1, wherein the user determines the weld quality of each weld by performing a visual inspection. ### Claim 5 (depends on 1) The laser weld monitoring system according to claim 1, wherein said at least one sensor includes at least one selected from a group consisting of a photodiode, a microphone, a monitor sensor, a plasma sensor and a machine vision sensor. ### Claim 6 (depends on 1) The laser weld monitoring system according to claim 1, wherein said weld characteristic includes at least one selected from a group consisting of a reflection signal, an IR signal and an acoustic signal. ### Claim 7 (depends on 1) The laser weld monitoring system according to claim 1, wherein said attributes include at least one selected from a group consisting of a maximum, a minimum, a slope, an integration, at least one algebraic function and at least one calculus function. ### Claim 8 (depends on 1) The laser weld monitoring system according to claim 1, wherein said laser is selected from a group consisting of a feedback laser, a non-feedback laser, an Nd:YAG laser, a C02 laser and a green laser. ### Claim 9 (depends on 1) The laser weld monitoring system according to claim 1, further comprising a CCTV camera capable of capturing images of welding parts. ### Claim 10 (depends on 1) The laser weld monitoring system according to claim 1, wherein the data acquisition and processing equipment comprises a digitizer for processing said weld characteristic, wherein said digitizer comprises at least one selected from a group consisting of an oscilloscope, a digital oscilloscope, a DSP board, a DAQ board and custom electronics. ### Claim 11 (depends on 1) The laser weld monitoring system according to claim 1, wherein the library of algorithms associated with the attributes have been predetermined by a developer of said laser weld monitoring system. ### Claim 12 (depends on 1) The laser weld monitoring system according to claim 1, wherein the library of algorithms associated with the attributes are developed by the user. ### Claim 13 (depends on 1) The laser weld monitoring system according to claim 1, wherein the system can be used for both process development and process control. ### Claim 14 A method of monitoring a weld quality of a laser, said method comprising: performing a plurality of test welds; capturing at least one weld characteristic of each test weld, said at least one weld characteristic having a plurality of attributes; determining the weld quality of each test weld; running at least one of a library of algorithms associated with the attributes on said at least one weld characteristic for each weld to generate a single value output for the associated attribute; and selecting an attribute indicative of the weld quality by correlating the single value outputs of said at least one algorithm with the weld qualities of the test welds. ### Claim 15 (depends on 14) The method according to claim 14, wherein performing the plurality of test welds comprises performing the testing welds at different weld conditions to correlate a variation in the weld quality with the variation in the single value output for said at least one algorithm as the weld conditions change. ### Claim 16 (depends on 14) The method according to claim 14, wherein running at least one of a library of algorithms comprises generating the single value output for at least one attribute selected from a group consisting of a maximum, a minimum, a slope, an integration, at least one algebraic function and at least one calculus function. ### Claim 17 (depends on 14) The method according to claim 14, wherein determining the weld quality comprises performing a weld strength test. ### Claim 18 (depends on 14) The method according to claim 14, wherein determining the weld quality comprises performing a weld interface area test. ### Claim 19 (depends on 14) The method according to claim 14, further comprising defining good and bad welds based on the single value output of the algorithm associated with the selected attribute. ### Claim 20 (depends on 19) The method according to claim 19, further comprising: performing a weld; capturing the weld characteristic of the weld; and running the algorithm associated with the selected attribute on the weld characteristic for the weld to generate the single value output. ### Claim 21 (depends on 20) The method according to claim 20, further comprising determining the weld to be either a good weld or a bad weld by comparing the single value output for the weld with the definition of good and bad welds. ### Claim 22 A method of adjusting a focus height of a laser, said method comprising: performing a plurality of test welds, each test weld being performed at a different focus height about a predetermined initial focus height; capturing a temperature characteristic of each test weld; and determining the focus height that results in a maximum rising slope in the temperature characteristic as a correct focus height.