Grease deterioration detecting method and lubricant deterioration detecting method
US-2024310354-A1 · Sep 19, 2024 · US
US2024201103A1 · US · A1
| Field | Value |
|---|---|
| Publication number | US-2024201103-A1 |
| Application number | US-202318220985-A |
| Country | US |
| Kind code | A1 |
| Filing date | Jul 12, 2023 |
| Priority date | Aug 29, 2022 |
| Publication date | Jun 20, 2024 |
| Grant date | — |
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An inspection method includes extracting a first similarity by comparing first data of a first optical signal with reference data of a reference optical signal, generating a first normal distribution of the first similarity, extracting a second similarity by comparing second data of a second optical signal with the reference data of the reference optical signal, generating a second normal distribution of the second similarity, and comparing the first normal distribution with the second normal distribution. The extracting of the first similarity includes deriving the first data of the first optical signal.
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What is claimed is: 1 . A substrate processing method comprising: extracting a first similarity by comparing first data of a first optical signal with reference data of a reference optical signal; generating a first normal distribution of the first similarity; extracting a second similarity by comparing second data of a second optical signal with the reference data; generating a second normal distribution of the second similarity; and comparing the first normal distribution with the second normal distribution, wherein the extracting the first similarity by comparing the first data of the first optical signal with the reference data of the reference optical signal comprises deriving the first data of the first optical signal, wherein the deriving the first data of the first optical signal comprises: collecting spectrum data of the first optical signal in a chamber by using optical emission spectrometry; selecting data of a first section and data of a second section, which have a first section size, from the spectrum data; scaling each of the data of the first section and the data of the second section to a value greater than or equal to 0 and less than or equal to 1; converting the scaled data by using a fitting function f(x)=Ae −ω|x n | +c, where n is a rational number greater than or equal to 1, and less than or equal to 5; determining a peak probability of each of the data of the first section and the data of the second section by using the fitting function; based on the peak probability of each of the data of the first section and the data of the second section being less than a reference point, converting the peak probability into 0; and based on the peak probability of each of the data of the first section and the data of the second section being equal to or greater than the reference point, converting the peak probability into 1, and wherein the reference data and the second data are derived using a method that is the same as that of the first data. 2 . The substrate processing method of claim 1 , wherein the deriving the first data further comprises determining a stable time section of the spectrum data, and wherein the first section and the second section are from the stable time section. 3 . The substrate processing method of claim 1 , wherein the extracting the first similarity further comprises: extracting the first similarity in a first time; and extracting the first similarity in a second time, wherein the extracting of the first similarity in the first time comprises comparing the first data in the first time with the reference data in a third time, wherein the extracting of the first similarity in the second time further comprises comparing the first data in the second time with the reference data in a fourth time, and wherein the generating of the first normal distribution of the first similarity further comprises generating distributions of the first similarity in the first time and the first similarity in the second time. 4 . The substrate processing method of claim 3 , wherein the deriving the first data further comprises determining a stable time section of the spectrum data, and wherein the first time and the second time are from the stable time section. 5 . The substrate processing method of claim 1 , wherein the collecting the spectrum data is performed in a visible light wavelength region. 6 . The substrate processing method of claim 1 , wherein the first optical signal is a first comparison group, wherein the second optical signal is a second comparison group, wherein the reference optical signal is a control group, and wherein the substrate processing method further comprises comparing optical signals of the first comparison group and the second comparison group to the control group. 7 . The substrate processing method of claim 1 , wherein the reference data and the second data are derived by selecting data of a plurality of sections having the first section size. 8 . The substrate processing method of claim 1 , wherein the determining the peak probability further comprises representing the peak probability as a value greater than or equal to 0 and less than or equal to 1. 9 . The substrate processing method of claim 1 , wherein the extracting the first similarity further comprises comparing data of the first data with data of the reference data in identical wavelength sections. 10 . A substrate processing method comprising: performing an inspection method for identifying a condition in a chamber; and based on the condition in the chamber being identified as a normal state, performing a plasma processing operation of processing a substrate in the chamber using plasma, wherein the inspection method comprises: collecting spectrum data of a first optical signal in the chamber by using optical emission spectrometry; selecting data of a first section and data of a second section, which have a first section size, from the spectrum data; scaling each of the data of the first section and the data of the second section to a value greater than or equal to 0 and less than or equal to 1; converting the scaled data by using a fitting function f(x)=Ae −ω|x n | +c, where n is a rational number greater than or equal to 1, and less than or equal to 5; determining a peak probability of each of the data of the first section and the data of the second section by using the fitting function; based on the peak probability of each of the data of the first section and the data of the second section being less than a reference point, converting the peak probability into 0; based on the peak probability of each of the data of the first section and the data of the second section being equal to or greater than the reference point, the peak probability into 1; deriving first data of the first optical signal; and extracting a first similarity by comparing the first data with reference data of a reference optical signal, and wherein the reference data and the first data are derived using a same method. 11 . The substrate processing method of claim 10 , further comprising: extracting a second similarity by comparing second data of a second optical signal with the reference data; and comparing the first similarity with the second similarity, wherein the second similarity and the first similarity are extracted using a same method. 12 . The substrate processing method of claim 11 , further comprising: generating a first normal distribution of the first similarity; generating a second normal distribution of the second similarity; and comparing the first normal distribution with the second normal distribution. 13 . The substrate processing method of claim 10 , wherein the deriving the first data further comprises determining a stable time section of the spectrum data, and wherein the first section and the second section are from the stable time section. 14 . The substrate processing method of claim 10 , wherein the extracting the first similarity further comprises: extracting the first similarity from a first time; and extracting the first similarity from a second time, wherein the extracting the first similarity from the first time comprises comparing the first data from the first time with the reference data from a third time, and wherein the extracting the first similarity from the second time further comprises comparing the first data from the second time with the reference data from a fourth time. 15 . The substrate processing method of claim 12 , wherein the extracting the first similarity further co
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