Method for detecting elements in molten iron

Abstract

The invention discloses a method for detecting elements in molten iron. The method comprises the following steps: S1, sampling and preparing a sample; and S2, detecting by using spark discharge atomic emission spectrometry, wherein the parameter setting comprises argon flushing time of 2-7 seconds, pre-combustion time of 8-12 seconds and exposure time of 9-13 seconds. By means of the method, rapid analysis of ultralow sulfur with the mass fraction smaller than 0.0050% in the molten iron and simultaneous analysis of elements such as carbon, silicon, manganese, phosphorus, nickel, chromium, copper, arsenic, tin, vanadium and titanium can be achieved, and the method has wide application prospects in the iron smelting industry.

Description

Technical Field

[0001] This invention belongs to the field of molten iron detection and analysis, specifically relating to a method for detecting elements in molten iron. Background Technology

[0002] Elemental analysis of molten iron is a crucial step in the steelmaking process. Its purpose is to monitor the reaction status within the furnace in real time, ensuring that the steel composition meets standards. By accurately determining the content of elements such as carbon, silicon, manganese, phosphorus, and sulfur in the molten iron, the appropriate amounts of slagging agents, coolants, and alloying agents can be precisely calculated, reducing production costs. Desulfurization of molten iron is also a step in the steelmaking process; accurately and efficiently detecting the residual sulfur content in the molten iron is essential for the quality control of the finished steel.

[0003] The analytical range for sulfur in GB / T24234-2009, "Determination of Multi-Element Content in Cast Iron by Spark Discharge Atomic Emission Spectrometry (Conventional Method)," is 0.005% to 0.2% by mass. Analytical results for sulfur content below 0.005% are inaccurate. The determination of sulfur content in molten iron typically employs the method disclosed in GB / T20123-2006, "Determination of Total Carbon and Sulfur Content in Iron and Steel by Infrared Absorption Method After Combustion in a High-Frequency Induction Furnace." However, this method requires the sample to be processed into chips or granules with a diameter of not less than 0.4 mm. The Brinell hardness (HB) of molten iron samples is typically in the range of 150 to 250, indicating high hardness and brittleness, making it difficult to obtain chip or granular samples. Furthermore, the high carbon and silicon content of molten iron samples easily leads to fragmentation during cutting, making it difficult to form continuous chips. Additionally, tool wear is rapid, and the analysis time is long. Summary of the Invention

[0004] The purpose of this invention is to provide a method for detecting elements in molten iron, so as to solve the problem of rapid analysis of ultra-low sulfur content below 0.0050% in molten iron, and simultaneous analysis of elements such as carbon, silicon, manganese, phosphorus, nickel, chromium, copper, arsenic, tin, vanadium, and titanium.

[0005] To achieve the above objectives, the present invention provides the following technical solution: A method for detecting elements in molten iron, comprising the following steps: S1. Sampling and sample preparation; S2. Detection is performed using spark discharge atomic emission spectrometry, with parameter settings including: argon rinsing time 2~7s; And / or, pre-ignition time 8~12s; And / or, exposure time 9~13s.

[0006] As a further embodiment of the present invention: in step S1, a fully automatic milling machine is used for sample preparation, and the grinding depth is 0.7~1.0 mm, preferably 0.8 mm.

[0007] As a further embodiment of the present invention: the elements detected in step S2 include carbon, silicon, manganese, phosphorus, sulfur, nickel, chromium, copper, arsenic, tin, vanadium and titanium.

[0008] As a further embodiment of the present invention: the sulfur content detected in step S2 is 0.0006%~0.2% by mass, preferably 0.0006%~0.005% by mass.

[0009] As a further embodiment of the present invention, the parameter settings for step S2 include: argon purging time 2~3s, pre-ignition time 8~10s, and exposure time 9~11s.

[0010] As a further aspect of the present invention: the detector used in step S2 includes at least one of a CCD detector and a PMT detector, preferably a CCD detector. The CCD detector has low dark current, which can effectively capture the weak signals of sulfur characteristic spectral lines, improve the signal-to-noise ratio (SNR), simultaneously cover the entire spectrum, and acquire sulfur spectral lines and adjacent interfering spectral lines in real time. Combined with algorithms to subtract background interference, it ensures accurate resolution of the sulfur signal. Furthermore, it supports high-sensitivity modes and strong signal suppression, avoiding saturation of strong spectral lines of matrix elements (such as Fe), while accurately quantifying the weak signals of trace sulfur, ensuring the quantitative reliability of sulfur in complex samples.

[0011] As a further embodiment of the present invention: the detection wavelength used in step S2 is 145~322nm, wherein the detection wavelength for carbon is preferably 191~195nm, more preferably 193.1nm; the detection wavelength for silicon is preferably 285~290nm, more preferably 288.2nm; the detection wavelength for manganese is preferably 285~290nm, more preferably 293.3nm; the detection wavelength for phosphorus is preferably 175~180nm, more preferably 178.3nm; the detection wavelength for sulfur is preferably 178~182nm, more preferably 180.7nm; and the detection wavelength for nickel is preferably 230nm. The detection wavelength for chromium is preferably 310-315 nm, more preferably 313.2 nm; the detection wavelength for copper is preferably 210-215 nm, more preferably 212.3 nm; the detection wavelength for arsenic is preferably 185-190 nm, more preferably 189 nm; the detection wavelength for tin is preferably 145-150 nm, more preferably 147.5 nm; the detection wavelength for vanadium is preferably 308-312 nm, more preferably 310.2 nm; and the detection wavelength for titanium is preferably 305-310 nm, more preferably 308.8 nm.

[0012] As a further embodiment of the present invention: the pre-burning frequency used in step S2 is 450~550Hz, and / or the exposure frequency is 350~450Hz.

[0013] As a further embodiment of the present invention, step S2 further includes at least one of signal acquisition, discrete spark intensity removal, working curve plotting, and data reading.

[0014] As a further embodiment of the present invention: the signal acquisition start time is 300~500us, and the initial energy current is 50~150A.

[0015] As a further embodiment of the present invention: the working curve is a sulfur element working curve, and the equation of the sulfur element working curve is y=0.00000000116x-0.000005.

[0016] This invention has at least the following technical effects: Spark discharge atomic emission spectrometry (SFAES) is used to analyze and detect the content of carbon, silicon, manganese, phosphorus, sulfur, nickel, chromium, copper, arsenic, tin, vanadium, and titanium in molten iron. The detection limit for sulfur content can reach 0.0006% by mass, expanding the lower limit of existing analytical techniques with high precision and accuracy. Compared with other detection methods, the analysis time for a single molten iron sample is reduced from 300 seconds to within 180 seconds. The operation process is simple, avoiding lengthy preparation work such as crucible preparation, saving on flux and crucible material costs, and reducing labor intensity. It has broad application prospects in the iron and steel industry. Attached Figure Description

[0017] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings.

[0018] Figure 1 This is a schematic diagram of the sampling mold in Embodiment 1 of the present invention; Figure 2 This is a time-based data acquisition trend chart from Embodiment 1 of the present invention. Figure 3 This is a schematic diagram of intensity filtration in Embodiment 1 of the present invention; Figure 4 This is a working curve diagram of sulfur element in Embodiment 1 of the present invention. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only for explaining the invention and are not intended to limit the invention; that is, the described embodiments are merely some embodiments of the invention, and not all embodiments.

[0020] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0021] Example 1 Sampler: Provided by Mingda Keji Technology (Shanghai) Co., Ltd.

[0022] Testing and processing instruments: German SPECTROLAB M10 direct-reading spectrometer, Shanghai Minuofu MLF-MILL-D dual-station milling machine, Sichuan Pury CZA-4F argon purifier.

[0023] Standard samples: BSCC-14, YSBS11080-2003, GSB03-2482-2008-1, GBW01144a, YSBS451049-11(K146), GSB03-1462-2014(T017-1), CZ 20034 17C, CTIF F012, CZ 2003415C, and CTIF FPA 1 were all purchased from the market.

[0024] 1. Sampling and Sample Preparation Quickly and steadily scoop an appropriate amount of molten iron from the ladle using a preheated ladle. Pour the molten iron from the ladle into the sampler and let it stand for a moment to solidify naturally. Then, use a hammer to open the sampler. Place the sample in running water for rapid cooling for about 60 seconds. The sample should be full and free of obvious slag inclusions. A schematic diagram of the sampling mold is shown below. Figure 1 As shown. After complete white cast iron formation, a fully automatic milling machine was used to prepare the sample, with a grinding depth of 0.8 mm, to obtain a molten iron sample for testing.

[0025] 2. Detection using spark discharge atomic emission spectrometry. (1) Setting of detection conditions A German SPECTROLAB M10 direct-reading spectrometer was used, with a CCD detector selected. The light source conditions are shown in Table 1. Iron reference was used as an internal standard, and the detection wavelengths of each element and the iron reference are shown in Table 2.

[0026] Table 1 Light source conditions

[0027] Table 2 Detection Wavelengths

[0028] (2) Signal acquisition Time-based acquisition is performed within an extremely short time window synchronized with a single spark. The optimized start and duration of this window allow for the acquisition of relevant signals when the adverse effects of unrelated signals (such as noise, high background radiation, or spectral interference) are minimized, thereby achieving a low detection limit and good accuracy. Taking sulfur as an example... Figure 2 As shown, during the detection process, it was found that when the signal acquisition time was 400 μs and the initial energy current was 100 A, the optimal BEC / DL (extremely low background noise (low BEC), extremely high signal response (low DL), ensuring extremely high sensitivity and accuracy of detection at ultra-low concentrations) could be achieved, and spectral interference could be reduced.

[0029] (3) Discrete spark intensity removal The signal acquisition window integrates the most stable discharge signal for each element, removes discrete spark signals, and processes the optimal single spark intensity subset from each element channel by discarding abnormal low-intensity signals, thereby collecting the most stable signal data and improving accuracy. A schematic diagram of the intensity filtering for sulfur during detection is shown below. Figure 3 As shown.

[0030] (4) Drawing working curves After cleaning the spectrometer lens, regenerating the argon purifier, and performing comprehensive maintenance on the spark stand, the data was observed to be stable and the excitation spots were normal. Then, a trace was created to establish the correspondence between the pixel positions on the spectrometer detector and the actual wavelengths, eliminating wavelength shifts. A new working curve was then created. The total amount and balance of elements in the standard materials were calculated, and the standard values ​​of the elements to be added were entered as shown in Tables 3-1 and 3-2. The relative intensities of each standard material were measured sequentially, and a working curve for sulfur was plotted using the average relative intensity of the analytical line and the element content. A linear regression with a correlation coefficient R0 was selected. 2 =0.9985. During the inspection, it was found that the discrete points of the curve were concentrated in samples with high manganese levels, suggesting that manganese may interfere with sulfur levels. After excluding the interference of manganese, the correlation coefficient R... 2 =0.9999, the sulfur element working curve is as follows Figure 4 As shown.

[0031] Table 3-1 Standard substance content (ω / %)

[0032] Table 3-2 Standard substance content (ω / %)

[0033] The calculation process for sulfur content in standard materials is shown in Table 4. When testing unknown samples, the standard curve y = 0.00000000116x - 0.000005 is used. The measured sulfur spectral line intensity x is substituted into the standard curve equation to calculate y. The initial iron-based content is substituted as 100%. According to the formula sulfur content (%) = iron-based content * y, the calculated sulfur content in the unknown sample is calculated. For the calculation of other element contents, the working curves for the corresponding elements are established according to the above method. Then, the content of each element in the unknown sample is calculated according to the standard curve of the element. The remainder is obtained by subtraction, which is the actual iron-based content in the unknown sample. Iterative calculation is performed, and the actual content of each element is obtained according to the formula element actual content (%) = element calculated content * iron-based actual content.

[0034] Table 4 shows the calculation process for the sulfur content in the standard reference material.

[0035] Accuracy experiment: Ten standard substances were used as samples, and each sample was analyzed three times. The average value of the sulfur content was calculated to obtain the measured value. The measured value was compared with the reference value of the standard substances, and the results are shown in Table 5. The data show that the measured value of sulfur content obtained by the detection method of this invention is in good agreement with the reference value, indicating that the detection method of this invention has high accuracy.

[0036] Table 5. Accuracy experiment of sulfur content determination in standard substances (ω / %)

[0037] Precision experiment: Four standard substances, BSCC-14, YSBS11080-2003, GSB03-2482-2008-1 and GBW01144a, were used as samples. Six consecutive analyses were performed on the sulfur elemental working curve. The standard deviation (SD), 3SD, and reproducibility limit (r) in the standard GB / T 20123-2006 "Determination of Total Carbon and Sulfur Content in Iron and Steel - Infrared Absorption Method After Combustion in High-Frequency Induction Furnace (Conventional Method)" were compared. The calculation method for the reproducibility limit (r) is as shown in Appendix D of the standard GB / T 20123-2006 "Determination of Total Carbon and Sulfur Content in Iron and Steel - Infrared Absorption Method After Combustion in High-Frequency Induction Furnace (Conventional Method)" (Figure D.2 Sulfur Content (w)). B ) and reproducibility (r) and repeatability (R) W The logarithmic relationship between R and R is shown in the graph, and the precision results are shown in Table 6. The data indicate that the precision of sulfur elemental analysis meets the standard requirements.

[0038] Table 6. Precision test of sulfur element in standard materials (ω / %)

[0039] Four molten iron samples, numbered A1 to A4 respectively, were analyzed six times consecutively on the sulfur element working curve. The standard deviation (SD), 3SD, and reproducibility limit (r) in the standard GB / T 20123-2006 "Determination of Total Carbon and Sulfur Content in Iron and Steel - Infrared Absorption Method after Combustion in High-Frequency Induction Furnace (Conventional Method)" were compared. The precision results are shown in Table 7. The data indicate that the precision of the sulfur element content detection and analysis in the molten iron samples meets the standard requirements.

[0040] Table 7. Precision test of sulfur element in molten iron samples (ω / %)

[0041] Example 2 Eight molten iron samples were taken and their sulfur content was tested according to the detection method in Example 1 and the infrared absorption method.

[0042] Infrared absorption method detection procedure: Refer to the detection method in GB / T 20123-2006 Determination of total carbon and sulfur content in steel by infrared absorption method after combustion in high frequency induction furnace (conventional method)

[0043] Principle: Sulfur is converted into sulfur dioxide by combustion in an oxygen stream, and the infrared absorption spectrum of sulfur dioxide in the oxygen stream is used for measurement.

[0044] Crucible preparation: Carbon and sulfur contaminants can usually be removed by burning the crucible in an electric furnace in air for at least 40 minutes at 1000°C or at least 15 minutes at 1350°C. Afterward, remove the crucible and place it in a clean, heat-resistant dish to cool for 2-3 minutes. Finally, store the crucible in a desiccator. If organic contaminants are suspected in the oxygen, purify the oxygen by heating the oxidation catalyst (copper oxide or platinum oxide) tube connected to the carbon dioxide and water absorbent at the rear end to 600°C before the oxygen enters the instrument's gas path system.

[0045] Add flux and sample: Weigh 500mg±20mg of sample, and then add about 1.5g of high-purity tungsten-tin flux. The flux can reduce the combustion temperature and improve the melting state.

[0046] Instrument calibration: The instrument is calibrated using known calibration standards, the values ​​of which are similar to the content of the sample to be tested.

[0047] Testing: Place the crucible stably and upright on the instrument's crucible holder, and the instrument will automatically analyze the data to obtain the test results.

[0048] Table 8 shows the comparison data between the method of Example 1 and the infrared absorption method detection results. The data shows that the sulfur content detection results obtained by the detection method of the present invention are consistent with the infrared absorption method detection results.

[0049] Table 8 Comparison of sulfur element detection results using different analytical methods (ω / %)

[0050] Example 3 Five molten iron samples were taken and numbered C1 to C5 respectively, and different methods were used to detect different elements and their contents.

[0051] Spark discharge atomic emission spectrometry (SES-AES) was used to detect and analyze the content of carbon, silicon, manganese, phosphorus, sulfur, nickel, chromium, copper, arsenic, tin, vanadium, and titanium according to the detection method in Example 1.

[0052] Other detection methods: Carbon and sulfur elements were detected by infrared absorption method according to "GB / T20123-2006 Determination of total carbon and sulfur content in steel - Infrared absorption method after combustion in high frequency induction furnace (conventional method)" (refer to Example 2). Silicon, manganese, phosphorus, nickel, chromium, copper, arsenic, tin, vanadium and titanium elements were detected by XRF method according to "GBT223.79-2007 Determination of multi-element content in steel - X-ray fluorescence spectrometry (conventional method)".

[0053] XRF detection steps: Principle: When primary X-rays generated by an X-ray tube irradiate a smooth, clean sample surface, the resulting characteristic X-rays are dispersed by a crystal. The detector measures the X-ray fluorescence intensity at the 2θ angle corresponding to the selected characteristic wavelength. Based on the calibration curve and the measured X-ray fluorescence intensity, the mass fractions of silicon, manganese, phosphorus, sulfur, copper, aluminum, nickel, chromium, molybdenum, vanadium, titanium, tungsten, and niobium in the sample are calculated.

[0054] Sample preparation: The equipment used to polish the sample surface was a belt abrasive mill, and the abrasive used was alumina with a belt particle size of less than 0.5 mm.

[0055] Curve preparation: Under selected operating conditions, a series of certified standard samples / reference materials with similar smelting processes and chemical compositions to the sample are measured using an X-ray fluorescence spectrometer. Each sample is measured twice. Using the instrument's software, the calibration curve parameters, the overall absorption correction factor (or α-factor), and the spectral overlap interference correction factor are calculated based on the element content value in the certified standard sample / reference material and the average measured fluorescence intensity.

[0056] Sample analysis: The fluorescence intensity of the analyte in the unknown sample was measured using an X-ray fluorescence spectrometer. Each sample was measured twice, and the average value was taken.

[0057] The comparison data of the test results are shown in Tables 9-1 and 9-2. The calculation method of the reproducibility limit R is as shown in Appendix D of the standard GB / T 20123-2006 Determination of Total Carbon and Sulfur Content in Iron and Steel by Infrared Absorption Method after Combustion in High-Frequency Induction Furnace (Conventional Method), "Figure D.2 Sulfur Content (w)". B ) and reproducibility (r) and repeatability (R) W The logarithmic relationship between R and (R) is shown in the graph. The results show that the carbon and sulfur content detection results obtained using the method of Example 1 are consistent with the results obtained by infrared absorption spectroscopy, while the content detection results for silicon, manganese, phosphorus, nickel, chromium, copper, arsenic, tin, vanadium, and titanium are consistent with the results obtained by XRF spectroscopy. This indicates that the detection method of this invention can simultaneously detect multiple elements in molten iron with high accuracy.

[0058] Table 9-1 Comparison of different analytical methods for different element contents in molten iron samples (ω / %)

[0059] Table 9-2 Comparison of different analytical methods for different element contents in molten iron samples (ω / %)

[0060] Comparative Examples 1-3 Four standard substances were used as samples. The detection conditions or parameters were changed as shown below, and the remaining steps were the same as in Example 1. The sulfur element was detected and the relative standard deviation (RSD) was calculated. Comparative Example 1: The detector is a CCD detector, and the iron reference detection wavelength is 172.2 nm; Comparative Example 2: The detector is a CCD detector, and the iron reference detection wavelength is 217.8 nm; Comparative Example 3: The detector is a PMT detector, and the iron reference detection wavelength is 187.7 nm.

[0061] The detection results are shown in Table 10. The results show that when selecting a CCD detector and using an iron reference with a detection wavelength of 172.2 nm to detect sulfur, the RSD is minimized.

[0062] Table 10 Comparison of relative standard deviations for different detectors and reference intensities.

[0063] Comparative Example 4 Using standard substance BSCC-14 as the sample, the rinsing time in Example 1 was replaced with 1s, 2s, 3s, 4s, 5s, 6s, 7s, and 8s respectively. The remaining steps and parameters were the same as in Example 1. The contents of carbon, silicon, manganese, phosphorus, and sulfur in the sample were detected. Five measurements were taken under each rinsing time parameter condition, and the relative standard deviation of the sulfur spectral intensity was statistically analyzed. The results are shown in Table 11.

[0064] The results showed that too short a rinsing time led to higher detection results for carbon and silicon content and lower detection results for phosphorus and sulfur content. It also resulted in sample residue and caused significant deviations. Extending the rinsing time could improve accuracy, but excessively long rinsing times would increase argon gas consumption and prolong the analysis time. Therefore, it is necessary to optimize the rinsing time to improve accuracy and precision while ensuring efficiency.

[0065] Table 11. Effects of rinsing time variation on element detection in molten iron.

[0066] Comparative Example 5 Using standard substance BSCC-14 as the sample, the pre-burning time in Example 1 was replaced with 2s, 4s, 6s, 8s, 10s, 12s, 14s, and 16s, respectively. The remaining steps and parameters were the same as in Example 1. The contents of carbon, silicon, manganese, phosphorus, and sulfur in the sample were detected. Five measurements were taken under each pre-burning time parameter condition, and the relative standard deviation of the sulfur spectral intensity was statistically analyzed. The detection results are shown in Table 12.

[0067] Table 12 Effect of pre-combustion time on element detection in molten iron

[0068] Comparative Example 6 Using standard material BSCC-14 as the sample, the pre-burning time in Example 1 was replaced with 3s, 5s, 7s, 9s, 11s, 13s, 15s, and 17s respectively. The remaining steps and parameters were the same as in Example 1. The contents of carbon, silicon, manganese, phosphorus, and sulfur in the sample were detected. Five measurements were taken under each exposure time parameter condition, and the relative standard deviation of the sulfur spectral intensity was calculated. The detection results are shown in Table 13.

[0069] Table 13. Effect of Exposure Time on Element Detection in Molten Iron

[0070] The results showed that the length of pre-burning time and exposure time had a significant impact on the detection results of element content, and comprehensive control of detection conditions was needed to improve the accuracy and reliability of the detection.

[0071] Comparative Example 7 Compared with other processing methods, using a fully automatic milling machine to process molten iron samples has advantages such as low labor intensity, high sample processing quality, consistent surface texture, smooth and flat surface, automatic sample purging during processing to prevent overheating, and minimal human interference. Therefore, this embodiment of the invention preferably uses a fully automatic milling machine to process molten iron samples. However, the grinding depth when using a fully automatic milling machine has a significant impact on the detection and analysis results of the molten iron samples: if the grinding depth is insufficient, the oxide layer on the sample surface will not be completely removed; if the grinding depth is too deep, the white iron layer will be lost due to its thinness, affecting the analysis results.

[0072] Three molten iron samples were taken. During sample preparation, a fully automatic milling machine was used to grind the sample to a depth of 0.4 mm. Then, the depth of each sample was increased by 0.1 mm, resulting in depths of 0.5 mm, 0.6 mm, 0.7 mm, 0.8 mm, 0.9 mm, 1.0 mm, 1.1 mm, 1.2 mm, 1.3 mm, 1.4 mm, and 1.5 mm. Sulfur content was measured at each depth according to the method in Example 1. Then, molten iron chips were collected and the sulfur content was measured according to the method in GB / T 20123-2006 "Determination of Total Carbon and Sulfur Content in Iron and Steel - Infrared Absorption Method After Combustion in a High-Frequency Induction Furnace (Conventional Method)" (refer to Example 2). The results are shown in Table 14. The results show that when the sample was ground to a depth of 0.8 mm on the fully automatic milling machine, the analytical data and the results of the infrared absorption method were highly consistent.

[0073] Table 14. Effects of different grinding depths on sulfur content on fully automatic milling machines.

[0074] The above description is merely an example and illustration of the structure of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described, or use similar methods to replace them, as long as they do not deviate from the structure of the invention or exceed the scope defined in the claims, all of which should fall within the protection scope of the present invention.

Claims

1. A method for detecting elements in molten iron, characterized in that, Includes the following steps: S1. Sampling and sample preparation; S2. Detection is performed using spark discharge atomic emission spectrometry, with parameter settings including: argon rinsing time 2~7s; And / or, pre-ignition time 8~12s; And / or, exposure time 9~13s.

2. The detection method according to claim 1, characterized in that, The elements detected in step S2 include carbon, silicon, manganese, phosphorus, sulfur, nickel, chromium, copper, arsenic, tin, vanadium, and titanium.

3. The detection method according to claim 2, characterized in that, The sulfur content in step S2 is 0.0006%~0.2% by mass.

4. The detection method according to claim 1, characterized in that, The parameter settings in step S2 include: argon purging time 2~3s, pre-burning time 8~10s, and exposure time 9~11s.

5. The detection method according to claim 1, characterized in that, The detector used in step S2 includes at least one of a CCD detector and a PMT detector.

6. The detection method according to claim 1, characterized in that, The detection wavelength used in step S2 is 145~322nm.

7. The detection method according to claim 1, characterized in that, The pre-burning frequency used in step S2 is 450~550Hz, and / or the exposure frequency is 350~450Hz.

8. The detection method according to claim 1, characterized in that, Step S2 also includes at least one of signal acquisition, discrete spark intensity removal, working curve plotting, and data reading.

9. The detection method according to claim 8, characterized in that, The signal acquisition start time is 300~500us, and the initial energy current is 50~150A.

10. The detection method according to claim 8, characterized in that, The equation for the working curve is y = 0.00000000116x - 0.000005.

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