Lead-free soldering sealing process and welding system for photobioreactor components

Abstract

This invention discloses a lead-free brazing sealing process and welding system for photobioreactor components, relating to the field of photobioreactor manufacturing. After cleaning the surface of the 316L stainless steel components to be welded in the photobioreactor, an Ar process is first performed. + Ion beam interface activation treatment is performed, followed by pre-positioning of lead-free silver-based brazing filler metal at the interface to be soldered. The components to be soldered are then assembled, and the brazing gap is controlled within the first gap range. The assembled and gap-controlled components are placed in a vacuum brazing furnace, and the furnace is evacuated until the background vacuum level is less than or equal to a set vacuum threshold. Multi-segment gradient temperature control is used for heating and brazing. This invention uses lead-free silver-based brazing filler metal to eliminate the adverse effects of lead leaching on algal culture, combined with Ar... + Ion beam interface activation treatment and multi-segment gradient temperature-controlled brazing process effectively remove the oxide layer at the brazing interface, improve the strength and sealing performance of the brazed joint, and reduce the risk of leakage.

Description

Technical Field

[0001] This invention relates to the field of photobioreactor manufacturing technology, and in particular to lead-free brazing sealing process and welding system for photobioreactor components. Background Technology

[0002] Photobioreactors are core equipment in the large-scale cultivation of Haematococcus pluvialis, the efficient preparation of natural astaxanthin, and the biopharmaceutical field. Most of their components are made of 316L stainless steel and require brazing for sealed connections to ensure a sterile, stable cultivation environment and long-term structural integrity within the reactor. Haematococcus pluvialis is highly sensitive to the dissolution of metal ions and is a core algal species for the industrial production of natural astaxanthin; therefore, the cultivation system places extremely stringent requirements on the biocompatibility of the reactor materials.

[0003] Traditional photobioreactor components are typically brazed using lead-containing solder. Lead is easily and slowly leached out during algal culture, which significantly inhibits the cell growth, zoospore reproduction, and astaxanthin accumulation of Haematococcus pluvialis. This directly reduces algal activity and astaxanthin production, severely damaging the biocompatibility between the reactor and the culture system, and failing to meet the requirements for high-density, safe, and environmentally friendly industrial cultivation of Haematococcus pluvialis.

[0004] When existing lead-free brazing technology is applied to components of a photobioreactor specifically for Haematococcus pluvialis, there are still significant shortcomings: On the one hand, the 316L stainless steel brazing interface is prone to the formation of an oxide layer, resulting in poor wettability of the brazing filler metal, insufficient joint strength, and low sealing reliability. Under long-term fluid erosion and pressure fluctuations, leakage is likely to occur, directly interrupting the Haematococcus pluvialis cultivation process. On the other hand, the brazing process relies on manual experience for control, and key parameters such as brazing temperature, vacuum degree, and holding time are difficult to match precisely. This can easily cause excessive dissolution of elements such as silver, copper, indium, and tin in the brazing filler metal into the Haematococcus pluvialis culture medium, further exacerbating the problems of algal growth inhibition and astaxanthin synthesis obstruction.

[0005] Meanwhile, existing brazing systems lack real-time monitoring of the entire brazing process and online biocompatibility assessment capabilities for Haematococcus pluvialis. They cannot predict the risk of element leaching in advance and dynamically adjust the process, resulting in low joint qualification rate and poor production stability, making it difficult to support high-quality, large-scale production of Haematococcus pluvialis photobioreactors. Summary of the Invention

[0006] To address the aforementioned technical problems, this invention provides a lead-free brazing sealing process and welding system for photobioreactor components. The technical solution is as follows:

[0007] The lead-free brazing sealing process for photobioreactor components includes the following steps:

[0008] Step 1: After cleaning the surface of the 316L stainless steel components to be welded in the photobioreactor, Ar is first applied. + Ion beam interface activation treatment is performed, then lead-free silver-based brazing filler is pre-placed on the interface to be soldered, the components to be soldered are assembled and the brazing gap is controlled to the first gap range.

[0009] Step 2: After assembly and gap control, place the components to be welded in a vacuum brazing furnace, evacuate the furnace until the base vacuum degree is less than or equal to the set vacuum degree threshold, and use a multi-segment gradient temperature control curve for heating and brazing.

[0010] Step 3: When the brazing cools to the first temperature range, high-purity oxygen is introduced into the vacuum furnace, the oxygen partial pressure is controlled to the first pressure range, the temperature is maintained in the passivation temperature range and held for a set time.

[0011] Step 4: Based on the pre-established brazing element leaching prediction model, predict the leaching concentration of brazing elements in the culture medium according to the actual brazing process parameters, and compare the leaching concentration with the No Observable Effect Concentration (NOEC) of the target cultured algae species to determine the biocompatibility level of the brazed joint. If the determination result is unqualified, generate process parameter adjustment suggestions according to the brazing element leaching prediction model and return to Step 2 to re-execute brazing until the determination result is qualified.

[0012] Optionally, the lead-free silver-based solder in step 1 is composed of the following components by weight percentage: Ag 40%-60%, Cu 20%-35%, In 8%-18%, Sn 5%-15%, with a total impurity content of less than or equal to 0.1% and a lead content of less than 100 ppm; the solidus temperature of the lead-free silver-based solder is 580℃-610℃, and the liquidus temperature is 620-680℃; the first gap range is 0.03mm-0.08mm.

[0013] Optionally, in step 1, Ar + The process parameters for ion beam interface activation treatment are: ion energy 0.5keV-2.0keV, beam current density 0.2mA / cm²-1.0mA / cm², treatment time 3min-10min, and sputtering depth controlled at 5nm-50nm.

[0014] Optionally, in step 2, the vacuum threshold is set to... The multi-segment gradient temperature control curve includes, in sequence, a preheating segment, a diffusion activation segment, a rapid melting segment, a brazing insulation segment, a slow cooling segment, and a rapid cooling segment;

[0015] The preheating section increases the temperature to 350℃ at a rate of 8℃ / min-12℃ / min and holds for 5-10 minutes; the diffusion activation section increases the temperature to... Keep warm for 3-5 minutes, during which The liquidus temperature of the lead-free silver-based solder; the rapid melting section rapidly heats up to the brazing holding temperature at a rate of 15℃ / min-20℃ / min. , , The temperature range is 10℃-30℃; the brazing insulation section is in Hold the temperature for 10-20 minutes; in the slow cooling section, cool slowly to 550℃ at a rate of 3℃ / min-5℃ / min; in the rapid cooling section, cool to room temperature with the furnace.

[0016] During the entire heating brazing process, the cumulative residence time in the sensitization temperature zone of 550℃-650℃ is less than or equal to 15 minutes, and the maximum temperature difference between the parts to be brazed is less than or equal to 15℃.

[0017] Optionally, in step 3, the first temperature range is 150℃-200℃, the first pressure range is 0.1Pa-1.0Pa, the passivation temperature range is 120℃-180℃, the set time is 30min-60min, and the purity of the high-purity oxygen introduced is greater than or equal to 99.99%.

[0018] Optionally, in step 4, the brazing element leaching prediction model is a support vector regression model or a neural network model trained based on experimental data. The input variables include brazing holding temperature, holding time, lead-free silver-based brazing alloy composition, brazing gap, and background vacuum degree. The output is the predicted leaching concentration of elements in the lead-free silver-based brazing alloy under specified culture conditions for 168 hours.

[0019] Optionally, the method for determining the biocompatibility level of the brazed joint in step 4 is as follows:

[0020] When the dissolution concentration is less than or equal to 0.1 times the concentration with no observable effect, the biocompatibility level is determined to be Grade A;

[0021] When the dissolution concentration is greater than 0.1 times the concentration with no observable effect and less than or equal to 0.5 times the concentration with no observable effect, the biocompatibility level is determined to be Grade B.

[0022] When the leaching concentration is greater than 0.5 times the concentration of no observable effect, the biocompatibility level is determined to be C, and it is suggested that the process parameters need to be adjusted and the brazing should be repeated.

[0023] A biocompatibility rating of A or B is considered acceptable, while a biocompatibility rating of C is considered unacceptable.

[0024] Optionally, the purification process in step 1 includes: ultrasonic cleaning with analytical grade acetone as the medium at a frequency of 35kHz-45kHz for 8min-12min, followed by secondary cleaning with anhydrous ethanol and rinsing with pure water, and finally drying with high-purity nitrogen gas with a purity of ≥99.999%.

[0025] Optionally, in step 4, the target algal species is selected from at least one of Chlorella, Dunaliella salina, or Haematococcus pluvialis.

[0026] The method for generating process parameter adjustment suggestions is as follows: based on the sensitivity analysis results of the brazing element leaching prediction model for each input variable, determine at least one of the following: the reduction in brazing holding temperature, the shortening of holding time, or the adjustment direction of lead-free silver-based brazing alloy composition ratio required to reduce the leaching concentration to the qualified level.

[0027] A lead-free brazing sealing intelligent welding system for photobioreactor components is used to realize the lead-free brazing sealing process for photobioreactor components. The system includes a vacuum brazing furnace body, a multi-source sensing subsystem, a data processing and fusion module, a temperature curve decision module, a biocompatibility prediction and evaluation module, and a human-machine interaction terminal.

[0028] The vacuum brazing furnace body is used to provide a vacuum environment and heating conditions;

[0029] The multi-source sensing subsystem includes an infrared thermal imaging temperature field monitoring unit, a vacuum monitoring unit, a residual gas analysis unit, and a brazing filler metal melting state visual monitoring unit. The infrared thermal imaging temperature field monitoring unit is used to acquire the two-dimensional temperature distribution on the surface of the component to be welded in real time. The vacuum monitoring unit is used to measure the background vacuum level inside the furnace. The residual gas analysis unit is used to monitor the composition of residual gas and oxygen partial pressure inside the furnace in real time. The brazing filler metal melting state visual monitoring unit is used to acquire images of the brazing seam area in real time.

[0030] The data processing and fusion module is used to perform time synchronization, spatial registration and feature extraction on multi-source sensing data to form a unified multi-dimensional state vector.

[0031] The temperature curve decision module adopts a deep deterministic strategy gradient algorithm, which takes a multi-dimensional state vector as input and outputs heating power regulation actions to make the actual brazing temperature curve dynamically approximate the preset multi-segment gradient temperature control strategy and meet the constraints of brazing heat preservation temperature, maximum temperature difference of the parts to be welded, cumulative residence time of the sensitization temperature zone and background vacuum degree.

[0032] The biocompatibility prediction and evaluation module has an embedded brazing alloy element leaching prediction model, which is used to calculate and predict the leaching concentration online based on the actual brazing process parameters, determine the biocompatibility level, and generate process parameter adjustment suggestions when the level is determined to be unqualified.

[0033] The human-computer interaction terminal communicates and interacts with the biocompatibility prediction and assessment module to provide suggestions on biocompatibility levels and process parameter adjustments.

[0034] In summary, the present invention has at least one of the following beneficial technical effects:

[0035] This invention provides a lead-free brazing sealing process and welding system for photobioreactor components, using lead-free silver-based solder to completely eliminate the adverse effects of lead leaching on algal culture, combined with Ar... + Ion beam interface activation treatment and multi-segment gradient temperature-controlled brazing process effectively remove the oxide layer at the brazing interface, improve the strength and sealing performance of the brazed joint, and reduce the risk of leakage.

[0036] Passivation treatment further optimizes the surface properties of the joint and reduces the leaching of brazing alloy elements. Relying on a brazing alloy element leaching prediction model and an intelligent welding system, real-time monitoring of the brazing process, online biocompatibility assessment, and dynamic adjustment of process parameters are achieved, significantly improving the welding qualification rate and production efficiency. This ensures that the brazed joints meet the biocompatibility requirements of photobioreactors, adapt to the cultivation needs of different algal species, and promote the large-scale, high-quality production of photobioreactors. Attached Figure Description

[0037] Figure 1 This is a schematic diagram of the lead-free brazing sealing process for the photobioreactor components of this invention.

[0038] Figure 2 This is a schematic diagram of a multi-segment gradient temperature control curve according to a specific embodiment of the present invention;

[0039] Figure 3 This is a schematic diagram of biocompatibility assessment and process data displayed on a human-computer interaction terminal according to a specific embodiment of the present invention;

[0040] Figure 4 This is a schematic diagram of the component connection principle of the lead-free brazing sealing intelligent welding system for the photobioreactor component of the present invention.

[0041] Explanation of reference numerals in the attached diagram: 1. Vacuum brazing furnace body; 2. Multi-source sensing subsystem; 21. Infrared thermal imaging temperature field monitoring unit; 22. Vacuum degree monitoring unit; 23. Residual gas analysis unit; 24. Visual monitoring unit for solder melting state; 3. Data processing and fusion module; 4. Temperature curve decision module; 5. Biocompatibility prediction and evaluation module; 6. Human-computer interaction terminal. Detailed Implementation

[0042] The present invention will be further described in detail below with reference to the accompanying drawings.

[0043] This invention discloses a lead-free brazing sealing process and welding system for photobioreactor components.

[0044] Reference Figures 1-4 Example 1, lead-free brazing sealing process for photobioreactor components, includes the following steps:

[0045] Step 1: After cleaning the surface of the 316L stainless steel components to be welded in the photobioreactor, Ar is first applied. + Ion beam interface activation treatment is performed, then lead-free silver-based brazing filler is pre-placed on the interface to be soldered, the components to be soldered are assembled and the brazing gap is controlled to the first gap range.

[0046] Step 2: After assembly and gap control, place the components to be welded in a vacuum brazing furnace, evacuate the furnace until the base vacuum degree is less than or equal to the set vacuum degree threshold, and use a multi-segment gradient temperature control curve for heating and brazing.

[0047] Step 3: When the brazing cools to the first temperature range, high-purity oxygen is introduced into the vacuum furnace, the oxygen partial pressure is controlled to the first pressure range, the temperature is maintained in the passivation temperature range and held for a set time.

[0048] Step 4: Based on the pre-established brazing element leaching prediction model, predict the leaching concentration of brazing elements in the culture medium according to the actual brazing process parameters, and compare the leaching concentration with the No Observable Effect Concentration (NOEC) of the target cultured algae species to determine the biocompatibility level of the brazed joint. If the determination result is unqualified, generate process parameter adjustment suggestions according to the brazing element leaching prediction model and return to Step 2 to re-execute brazing until the determination result is qualified.

[0049] By adopting the above technical solution, the purification treatment in step 1 removes surface oil and adsorbents, followed by Ar... + Ion beam interface activation treatment utilizes argon ions to bombard the stainless steel surface, selectively removing oxygen atoms from the passivation film formed by air at the nanoscale while preserving the chromium-rich layer structure. This significantly improves the wettability of subsequent solders without introducing chemical contamination or causing chromium depletion on the surface, as is the case with acid pickling.

[0050] Step 2, gradient temperature-controlled vacuum brazing, is the thermal core of the entire process. Heating in a vacuum environment avoids the use of flux and eliminates the risk of chemical residues. The design of the multi-segment gradient temperature control curve is based on the sensitization kinetics of 316L stainless steel and the melting characteristics of silver-based brazing filler metal: the preheating segment uniformly heats the workpiece and desorbs surface gases; the diffusion activation segment promotes solid-state atomic diffusion between the brazing filler metal and the base material at a temperature below the liquidus line; the rapid melting segment traverses the sensitization temperature range of 550 to 650°C at a high heating rate, significantly shortening the residence time required for chromium carbide precipitation, thereby suppressing intergranular corrosion susceptibility; the brazing insulation segment ensures sufficient filler metal filling and interfacial metallurgical bonding; and the slow cooling segment releases thermal stress through controlled slow cooling to prevent cracking of the brazing seam.

[0051] Step 3, the in-situ passivation treatment, utilizes the residual heat from brazing to introduce a small amount of high-purity oxygen into the furnace at a low temperature range of 150 to 200°C. Under low oxygen partial pressure, a dense, chromium-rich oxide film is reformed on the stainless steel surface, restoring its corrosion resistance that may have been lost during the vacuum high-temperature process. Compared to post-furnace pickling and passivation, in-situ passivation requires no additional heating energy or chemicals, and the film uniformity is superior.

[0052] Step 4, the biocompatibility assessment and closed-loop feedback, is a key feature distinguishing this process from traditional brazing. Traditional processes only test airtightness, while this process uses a machine learning model to predict the leaching concentrations of elements such as silver, copper, indium, and tin in the brazing filler metal under long-term cultivation conditions and compares these concentrations with the unobservable effect concentrations of the target algae species. When the predicted concentration exceeds a safety threshold, the system provides specific adjustments to process parameters based on the model's sensitivity analysis, such as lowering the brazing temperature or shortening the holding time, and then re-executes the brazing process. This closed-loop mechanism upgrades biocompatibility from passive detection to proactive design, ensuring that every brazed joint meets the biocompatibility requirements of the photobioreactor.

[0053] In Example 2, the lead-free silver-based solder in step 1 is composed of the following components by weight percentage: Ag 40%-60%, Cu 20%-35%, In 8%-18%, Sn 5%-15%, with a total impurity content of less than or equal to 0.1% and a lead content of less than 100 ppm; the solidus temperature of the lead-free silver-based solder is 580℃-610℃, and the liquidus temperature is 620-680℃; the first gap range is 0.03mm-0.08mm.

[0054] By adopting the above technical solution, the brazing filler metal is mainly silver, with a content of 40% to 60%, which gives the joint excellent thermal conductivity and ductility; the copper content of 20% to 35% forms a eutectic basis with silver, adjusting the melting point and enhancing strength; the indium content of 8% to 18% acts as a melting point inhibitor, lowering the liquidus temperature to 620 to 680℃, significantly lower than the upper limit of the sensitization temperature range of 850℃ for 316L stainless steel, thereby protecting the base material during brazing thermal cycles; the tin content of 5% to 15% further improves the wetting and spreading behavior of the brazing filler metal on the stainless steel surface. The quaternary alloy system does not contain biotoxic elements such as lead, cadmium, and zinc, and lead impurities are strictly controlled below 100 ppm.

[0055] The brazing gap is set to 0.03 to 0.08 mm based on a comprehensive optimization of capillary action and the mechanical properties of the brazed joint. If the gap is too small, the viscous resistance of the liquid brazing filler metal increases, resulting in insufficient filling and easy formation of incomplete weld defects; if the gap is too large, brittle intermetallic compounds will precipitate in the center region of the brazed joint due to supercooling during solidification, reducing the joint strength and toughness. This gap range can form a continuous solid solution structure that gradually transitions from the base metal to the center of the brazed joint, possessing both high airtightness and fatigue resistance.

[0056] Example 3, Ar in step 1 + The process parameters for ion beam interface activation treatment are: ion energy 0.5keV-2.0keV, beam current density 0.2mA / cm²-1.0mA / cm², treatment time 3min-10min, and sputtering depth controlled at 5nm-50nm.

[0057] By employing the above-mentioned technical solution, ion energies of 0.5 to 2.0 keV fall within the low-energy ion range. This energy is sufficient to break the chromium-oxygen bonds in the surface chromium oxide and remove oxygen atoms through sputtering, but not enough to cause significant lattice damage or ion implantation. A beam current density of 0.2 to 1.0 mA / cm² and a processing time of 3 to 10 minutes jointly control the sputtering depth to 5 to 50 nanometers, precisely removing the natural passivation film without exposing the substrate metal. The activated surface is in a high surface energy state due to the increased oxygen vacancy concentration. When the solder melts, the wetting angle between the liquid silver-based alloy and the chromium-rich surface is significantly reduced, resulting in an increased spreading rate. This dry activation process is completed in a vacuum chamber, ensuring close integration with subsequent brazing processes and preventing secondary contamination of the activated surface in the air.

[0058] Example 4, in step 2, the vacuum threshold is set to The multi-segment gradient temperature control curve includes, in sequence, a preheating segment, a diffusion activation segment, a rapid melting segment, a brazing insulation segment, a slow cooling segment, and a rapid cooling segment;

[0059] The preheating section increases the temperature to 350℃ at a rate of 8℃ / min-12℃ / min and holds for 5-10 minutes; the diffusion activation section increases the temperature to... Keep warm for 3-5 minutes, during which The liquidus temperature of the lead-free silver-based solder; the rapid melting section rapidly heats up to the brazing holding temperature at a rate of 15℃ / min-20℃ / min. , , The temperature range is 10℃-30℃; the brazing insulation section is in Hold the temperature for 10-20 minutes; in the slow cooling section, cool slowly to 550℃ at a rate of 3℃ / min-5℃ / min; in the rapid cooling section, cool to room temperature with the furnace.

[0060] During the entire heating brazing process, the cumulative residence time in the sensitization temperature zone of 550℃-650℃ is less than or equal to 15 minutes, and the maximum temperature difference between the parts to be brazed is less than or equal to 15℃.

[0061] By adopting the above technical solution, the heating rate of 8 to 12°C per minute in the preheating section takes into account both efficiency and temperature uniformity. Holding at 350°C for 5 to 10 minutes allows the workpiece to reach thermal equilibrium as a whole, and fully removes water molecules and organic matter physically adsorbed on the surface.

[0062] In the diffusion activation section, a heat preservation platform is set at 50°C below the liquidus temperature. At this point, the solder is still solid, but silver, copper, indium, and tin atoms have begun to diffuse to the surface of 316L stainless steel under the drive of the concentration gradient. This pre-diffusion-formed atomic-level contact layer significantly reduces the nucleation barrier and improves the interfacial bonding strength during the subsequent melting stage.

[0063] The rapid melting section employs a high heating rate of 15 to 20°C per minute, ensuring that the cumulative residence time of the workpiece in the sensitization temperature zone of 550 to 650°C is controlled within 15 minutes. In 316L stainless steel, the carbon at the grain boundaries requires a certain diffusion time to form Cr23C6 type carbides with chromium. Shortening the residence time in the high-temperature section effectively inhibits the formation of chromium-depleted zones at the grain boundaries, thereby maintaining the intergranular corrosion resistance of the base material.

[0064] The brazing holding temperature Tb is set to the liquidus temperature plus 10 to 30°C, and held for 10 to 20 minutes to provide sufficient time for capillary filling and interfacial reaction of the liquid brazing filler metal. The slow cooling section, with a temperature of 3 to 5°C per minute, allows sufficient time for the brazed joint microstructure to dissipate solidification stress through diffusion, preventing hot cracking. The rapid cooling section allows for natural cooling with the furnace; accelerating cooling in the lower temperature range has little impact on the microstructure.

[0065] Controlling the maximum temperature difference of the workpiece to within 15℃ is key to preventing thermal deformation. Excessive temperature gradient can cause irreversible warping of stainless steel parts, affecting the sealing flatness and assembly accuracy of the photobioreactor.

[0066] In Example 5, the first temperature range in step 3 is 150℃-200℃, the first pressure range is 0.1Pa-1.0Pa, the passivation temperature range is 120℃-180℃, the set time is 30min-60min, and the purity of the high-purity oxygen introduced is greater than or equal to 99.99%.

[0067] By adopting the above technical solution, when the furnace temperature drops to 150 to 200 degrees Celsius after brazing, the stainless steel surface still has sufficient heat energy to drive the oxidation reaction, but the temperature is insufficient to cause changes in the brazed seam structure or sensitization of the base material. Oxygen with a purity of over 99.99% is introduced and maintained at a partial pressure of 0.1 to 1.0 Pascals to create a rarefied oxidizing atmosphere. Under these conditions, chromium atoms preferentially combine with oxygen to form a dense Cr2O3 film, while iron oxidation is inhibited. The passivation temperature is maintained at 120 to 180 degrees Celsius for 30 to 60 minutes, resulting in an oxide film thickness of approximately several nanometers. This restores the passive corrosion resistance of the stainless steel without affecting the electrical and thermal conductivity of the brazed seam. In-situ passivation utilizes residual heat from the process, transforming the cooling section of the brazing thermal cycle into a functional surface treatment section, achieving both energy and time savings.

[0068] In Example 6, the brazing element leaching prediction model in step 4 is a support vector regression model or a neural network model trained based on experimental data. The input variables include brazing holding temperature, holding time, lead-free silver-based brazing alloy composition, brazing gap and background vacuum degree. The output is the predicted value of the leaching concentration of elements in lead-free silver-based brazing alloy under specified culture conditions for 168 hours.

[0069] By adopting the above technical solution, the model inputs include brazing holding temperature, holding time, brazing filler metal composition, brazing gap, and background vacuum level. These parameters collectively determine the microstructure characteristics of the brazed joint, such as the eutectic phase ratio, the thickness of the intermetallic compound at the interface, and the surface residual stress state. The microstructure directly affects the corrosion and dissolution rate of brazing filler metal elements in the culture solution.

[0070] Machine learning methods such as support vector regression or neural networks can learn high-dimensional nonlinear mapping relationships from limited experimental samples. Experimental samples were obtained by preparing brazed joints under different process parameters and immersing them in simulated microalgae culture medium for 168 hours, measuring the leaching concentrations of silver, copper, indium, and tin. After model training, inputting new process parameters can predict the corresponding long-term leaching risk, allowing for immediate biocompatibility assessment before or after brazing, without waiting for the actual 168-hour immersion test.

[0071] Example 7, the method for determining the biocompatibility level of the brazed joint in step 4 is as follows:

[0072] When the dissolution concentration is less than or equal to 0.1 times the concentration with no observable effect, the biocompatibility level is determined to be Grade A;

[0073] When the dissolution concentration is greater than 0.1 times the concentration with no observable effect and less than or equal to 0.5 times the concentration with no observable effect, the biocompatibility level is determined to be Grade B.

[0074] When the leaching concentration is greater than 0.5 times the concentration of no observable effect, the biocompatibility level is determined to be C, and it is suggested that the process parameters need to be adjusted and the brazing should be repeated.

[0075] A biocompatibility rating of A or B is considered acceptable, while a biocompatibility rating of C is considered unacceptable.

[0076] By adopting the above technical solution, the concentration with no observable effect is the highest concentration in toxicology that does not cause observable adverse effects in the test organism. In this embodiment, biocompatibility is classified into grades A, B, and C using 0.1 times and 0.5 times the concentration with no observable effect as thresholds.

[0077] Grade A corresponds to a dissolution concentration of 0.1 times or less of the concentration with no observable effect, indicating an extremely high safety margin, suitable for algal species that are extremely sensitive to metal ions or for long-term continuous culture scenarios. Grade B corresponds to a dissolution concentration between 0.1 and 0.5 times the concentration with no observable effect, still within the safe range, but with a moderate margin, suitable for routine batch culture. Both Grade A and Grade B are acceptable, and the workpiece can be released to subsequent assembly processes. Grade C corresponds to a dissolution concentration greater than 0.5 times the concentration with no observable effect, indicating a potential risk of bioinhibition, and is judged as unacceptable by the system.

[0078] When a grade C is determined, the mechanism for generating process parameter adjustment recommendations is activated. The model identifies the process variables with the greatest impact on dissolution concentration through sensitivity analysis. For example, if the holding temperature has the highest contribution, it recommends reducing the brazing holding temperature by a certain degree Celsius; if the holding time has a significant contribution, it recommends shortening the holding time. The adjustment recommendations are fed back to step 2, and the operator modifies the process settings and re-executes brazing until the predicted grade reaches grade A or B. This closed-loop mechanism transforms biocompatibility assurance from sampling inspection to piece-by-piece predictive control.

[0079] Example 8, the purification process in step 1 includes: ultrasonic cleaning with analytical grade acetone as the medium, frequency 35kHz-45kHz, time 8min-12min, followed by secondary cleaning with anhydrous ethanol and rinsing with pure water, and finally drying with high-purity nitrogen gas with a purity greater than or equal to 99.999%.

[0080] By employing the above technical solution, pure acetone was used as the initial cleaning medium due to its strong solubility for oily organic contaminants, rapid evaporation, and lack of residue. Ultrasonic cleaning at 35-45 kHz for 8-12 minutes utilized cavitation to generate micro-jets that impacted the stainless steel surface, effectively removing particulate contaminants adhering to microscopic pits. Anhydrous ethanol was used for secondary cleaning to replace residual acetone, and pure water rinsing removed ionic impurities. Finally, high-purity nitrogen (99.999% purity or higher) was used for drying, ensuring a dry and clean surface while preventing re-oxidation by oxygen. This rigorous purification process is a fundamental prerequisite for the uniformity of subsequent ion beam activation and the consistency of solder wetting.

[0081] In Example 9, in step 4, the target algal species for cultivation is selected from at least one of Chlorella, Dunaliella salina, or Haematococcus pluvialis.

[0082] The method for generating process parameter adjustment suggestions is as follows: based on the sensitivity analysis results of the brazing element leaching prediction model for each input variable, determine at least one of the following: the reduction in brazing holding temperature, the shortening of holding time, or the adjustment direction of lead-free silver-based brazing alloy composition ratio required to reduce the leaching concentration to the qualified level.

[0083] By adopting the above technical solutions, Chlorella, Dunaliella salina, or Haematococcus pluvialis represent freshwater, seawater, and high-value-added secondary metabolite production scenarios, respectively, and their metal sensitivity is supported by literature data. For different algal species, the concentration values ​​for unobservable effects referenced in the process will be set separately based on their respective toxicological data, enabling the process to have algal species-specific adaptability.

[0084] The parameter adjustment recommendations are generated based on sensitivity analysis of the solder element leaching prediction model. Sensitivity analysis quantifies the partial derivative or influence weight of each input variable with respect to the output leaching concentration. When a reduction in leaching concentration is needed, the algorithm searches for adjustment variables along the negative gradient direction. For example, if the analysis shows that the influence coefficient of the holding temperature is positive and large, then reducing the soldering holding temperature is the preferred recommendation; if the holding time has a secondary effect, then shortening the holding time is further recommended; if the indium content in the solder composition has a significant positive effect on leaching, then reducing the indium ratio in subsequent batches is recommended. This model-backward solution-based adjustment strategy avoids blind trial and error and significantly shortens the process optimization cycle.

[0085] Example 10: Lead-free brazing sealing intelligent welding system for photobioreactor components, used to realize lead-free brazing sealing process for photobioreactor components. The system includes a vacuum brazing furnace body 1, a multi-source sensing subsystem 2, a data processing and fusion module 3, a temperature curve decision module 4, a biocompatibility prediction and evaluation module 5, and a human-computer interaction terminal 6.

[0086] The vacuum brazing furnace body 1 is used to provide a vacuum environment and heating conditions;

[0087] The multi-source sensing subsystem 2 includes an infrared thermal imaging temperature field monitoring unit 21, a vacuum monitoring unit 22, a residual gas analysis unit 23, and a brazing filler metal melting state visual monitoring unit 24. The infrared thermal imaging temperature field monitoring unit 21 is used to acquire the two-dimensional temperature distribution on the surface of the component to be welded in real time. The vacuum monitoring unit 22 is used to measure the background vacuum in the furnace. The residual gas analysis unit 23 is used to monitor the composition of residual gas and oxygen partial pressure in the furnace in real time. The brazing filler metal melting state visual monitoring unit 24 is used to acquire images of the brazing seam area in real time.

[0088] The data processing and fusion module 3 is used to perform time synchronization, spatial registration and feature extraction on multi-source sensing data to form a unified multi-dimensional state vector.

[0089] The temperature curve decision module 4 adopts a deep deterministic strategy gradient algorithm, which takes a multi-dimensional state vector as input and outputs heating power regulation action to make the actual brazing temperature curve dynamically approximate the preset multi-segment gradient temperature control strategy and meet the constraints of brazing heat preservation temperature, maximum temperature difference of the parts to be welded, cumulative residence time of the sensitization temperature zone and background vacuum degree.

[0090] The biocompatibility prediction and evaluation module 5 has an embedded brazing alloy element leaching prediction model, which is used to calculate and predict the leaching concentration online based on the actual brazing process parameters, determine the biocompatibility level, and generate process parameter adjustment suggestions when the level is determined to be unqualified.

[0091] The human-computer interaction terminal 6 communicates and interacts with the biocompatibility prediction and evaluation module 5 to provide biocompatibility level and process parameter adjustment suggestions.

[0092] By adopting the above technical solution, the infrared thermal imaging temperature field monitoring unit 21 captures the two-dimensional temperature distribution on the workpiece surface in real time. Its spatial resolution and temperature measurement accuracy are sufficient to identify local overheating or cold areas. The vacuum monitoring unit 22 uses a combination of a capacitance thin-film gauge and an ionization gauge to measure a wide-range vacuum, ensuring that the background vacuum is always lower than [previous value]. The residual gas analysis unit 23, based on the principle of quadrupole mass spectrometry, monitors the types and partial pressures of residual gases in the furnace in real time, paying particular attention to oxygen and water pressures, providing feedback for precise control of oxygen partial pressure during the in-situ passivation stage. The brazing filler metal melting state visual monitoring unit 24 captures images of the brazing seam area through a high-temperature viewing window, and identifies the melting, spreading, and filling processes of the brazing filler metal through image processing algorithms.

[0093] The data processing and fusion module 3 aligns the timestamps and unifies the spatial coordinates of the aforementioned multi-source heterogeneous sensor data, and extracts feature quantities to construct a multi-dimensional state vector. This vector contains information such as the average temperature, maximum temperature difference, vacuum degree, oxygen partial pressure, and solder melting state encoding at the current moment.

[0094] The temperature curve decision module 4 employs a deep deterministic strategy gradient reinforcement learning algorithm. The reinforcement learning agent takes a multi-dimensional state vector as its input and outputs continuous action values, i.e., the heating power adjustment. The reward function is designed to penalize adverse events such as deviation from the target temperature, excessive temperature difference, exceeding vacuum limits, and excessive residence time in the sensitized zone. Through continuous learning in simulation environments and actual furnace runs, the decision module can autonomously generate heating curves that approximate the preset gradient temperature control strategy under different furnace conditions and workpiece sizes, automatically satisfying multiple constraints.

[0095] The biocompatibility prediction and assessment module 5 incorporates a pre-trained brazing alloy element leaching prediction model. During the brazing cooling stage, the module reads the actual temperature curve data, holding time, and vacuum degree records, calculates the predicted leaching concentration online, completes the biocompatibility classification, and sends the results along with process parameter adjustment suggestions to the human-machine interface terminal.

[0096] The human-machine interface terminal 6 displays real-time process curves, sensor data, biocompatibility prediction results, and operational suggestions through a graphical interface. Operators can decide whether to release the workpiece or adjust parameters for reprocessing based on the terminal information. Process data for each batch is automatically stored, forming a traceable quality archive that meets the Good Manufacturing Practices (GMP) requirements for photobioreactors in bioproduct production.

[0097] The following specific embodiments illustrate the implementation principle of the present invention:

[0098] Lead-free brazing seals for 316L stainless steel components in photobioreactors are achieved using an intelligent welding system. The specific process steps are as follows:

[0099] Step 1: Pre-treatment and assembly of components to be welded;

[0100] The surface of the 316L stainless steel components to be welded in the photobioreactor underwent a purification treatment: ultrasonic cleaning was performed using analytical grade acetone at a frequency of 40 kHz for 10 minutes, followed by a secondary cleaning with anhydrous ethanol and rinsing with pure water. Finally, the components were dried with high-purity nitrogen gas with a purity ≥99.999%. After purification, the interfaces to be welded were subjected to Ar... + Ion beam interface activation treatment was performed with the following parameters: ion energy 1.2 keV, beam current density 0.6 mA / cm², treatment time 6 min, and sputtering depth controlled at 25 nm. Subsequently, lead-free silver-based solder was pre-placed on the interface to be soldered. The lead-free silver-based solder consisted of the following components by weight percentage: Ag 50%, Cu 28%, In 12%, Sn 10%, with total impurities ≤0.1% and lead content <100 ppm. The solidus temperature of this lead-free silver-based solder was 595℃, and the liquidus temperature was 650℃. During assembly, the brazing gap was controlled at 0.05 mm.

[0101] Step 2, vacuum gradient temperature controlled brazing;

[0102] The assembled components to be welded are placed in the vacuum brazing furnace body 1, and the vacuum level is evacuated to a background vacuum level ≤ using the vacuum monitoring unit 22. The heating brazing process employs a multi-segment gradient temperature control profile, which sequentially includes a preheating segment, a diffusion activation segment, a rapid melting segment, a brazing holding segment, a slow cooling segment, and a rapid cooling segment. Specific parameters are as follows:

[0103] Preheating section: Increase the temperature to 350℃ at a rate of 10℃ / min and hold for 8 minutes;

[0104] Diffusion activation section: Temperature increased to TL−50℃ at a rate of 6.5℃ / min. =650℃, i.e. 600℃) and hold for 4 minutes;

[0105] Rapid melting section: rapidly heat to the brazing holding temperature Tb at a rate of 18℃ / min. =670℃;

[0106] Brazing insulation section: Insulate at 670℃ for 15 minutes;

[0107] Slow cooling section: Slowly cool to 550℃ at 4℃ / min;

[0108] Rapid cooling section: Cools to room temperature along with the furnace.

[0109] Throughout the entire heating and brazing process, the infrared thermal imaging temperature field monitoring unit 21 monitors the temperature field in real time, controlling the cumulative residence time in the sensitization temperature zone of 550℃-650℃ to be ≤15min and the maximum temperature difference between the parts to be welded to be ≤15℃. The residual gas analysis unit 23 monitors the composition of residual gas and oxygen partial pressure in the furnace in real time to ensure the stability of the vacuum environment. The brazing weld seam area image is acquired in real time by the brazing filler metal melting state visual monitoring unit 24 to observe the melting, spreading and filling state of the brazing filler metal.

[0110] Step 3, in-situ passivation treatment;

[0111] When the brazing cools to the first temperature range (150℃-200℃), high-purity oxygen with a purity of ≥99.99% is introduced into the vacuum furnace. The oxygen partial pressure is controlled to the first pressure range (0.5Pa) by the residual gas analysis unit 23. The temperature is maintained in the passivation temperature range (150℃) for a set time (45min) to complete the in-situ passivation treatment.

[0112] Step 4, Biocompatibility assessment and closed-loop feedback;

[0113] Using the biocompatibility prediction and evaluation module 5, based on a pre-established support vector regression model (brazing alloy element leaching prediction model), the actual brazing process parameters (brazing holding temperature 670℃, holding time 15min, lead-free silver-based brazing alloy composition Ag 50%, Cu 28%, In 12%, Sn 10%, brazing gap 0.05mm, background vacuum degree) are input. The dissolution concentration of brazing alloy elements in the culture medium over 168 hours was predicted. Chlorella was selected as the target algal species, and its Noobservable Effect Concentration (NOEC) was a known fixed value. The dissolution concentration was compared with this NOEC to determine the biocompatibility level of the brazed joint.

[0114] If the leaching concentration is ≤0.1 times NOEC, it is classified as Grade A;

[0115] If 0.1 times NOEC < dissolution concentration ≤ 0.5 times NOEC, it is judged as Grade B;

[0116] If the leaching concentration is >0.5 times NOEC, it is classified as Grade C, and the process parameters need to be adjusted and the brazing process needs to be re-brazed.

[0117] In this embodiment, the predicted leaching concentration is 0.3 times NOEC, and the biocompatibility level is determined to be Grade B (qualified), requiring no re-brazing. The data processing and fusion module 3 performs time synchronization, spatial registration, and feature extraction on all data collected by the multi-source sensing subsystem 2 to form a unified multi-dimensional state vector; the temperature curve decision module 4 adopts a deep deterministic strategy gradient algorithm, using the multi-dimensional state vector as input, and outputs heating power adjustment actions to ensure that the actual temperature control curve dynamically approximates the preset gradient curve; the human-machine interaction terminal 6 displays the biocompatibility level and related process data to complete the workpiece welding.

[0118] The performance of the 316L stainless steel components of the photobioreactor obtained by the process of this embodiment and the traditional lead-containing brazing process was tested. The test results are shown in Table 1.

[0119] Table 1 Performance Test Results

[0120] Performance indicators This embodiment uses a lead-free soldering sealing process. Traditional processes (including lead brazing) Lead content of brazing filler metal <100ppm ≥0.5% 316L stainless steel base material's resistance to intergranular corrosion No intergranular corrosion, cumulative residence time in the sensitization temperature zone ≤15 min, and preservation of the chromium-rich layer structure. There is a risk of intergranular corrosion, and the residence time in the sensitization temperature range is long, which can easily lead to surface chromium depletion. airtightness of brazed joints Excellent, the brazing filler metal fills the gaps sufficiently, and the brazing gaps form a continuous solid solution structure. It is relatively good, but it is prone to forming micropores due to flux residue, resulting in unstable airtightness. Corrosion resistance of brazed joints Excellent performance; in-situ passivation forms a dense, chromium-rich oxide film with stable corrosion resistance. Generally, the pickling and passivation film layer is uneven after exiting the furnace, which easily leads to localized corrosion. Biocompatibility rating Grade B (Compliant), dissolution concentration 0.3 times NOEC, no risk of biotoxicity. There is no clear grade; lead-containing solder is prone to excessive leaching and poses a risk of bioinhibition. Brazed joint strength High efficiency, no brittle intermetallic compounds in the brazing seam, combining ductility and fatigue resistance. Medium quality; brittle phases easily precipitate in the brazing seam, resulting in poor fatigue resistance. Process pollution No chemical pollution, no flux required, dry activation avoids secondary pollution. There is chemical pollution, flux residue, and pollutants generated during the pickling process. Process energy consumption Low temperature and in-situ passivation utilizes the residual heat from brazing, requiring no additional heating. High temperature and humidity require additional heating for pickling and passivation, resulting in high energy consumption. Quality traceability Traceable, intelligent system records all process parameters and biocompatibility data. Untraceable, only basic welding parameters are recorded, and no biocompatibility data is available.

[0121] Both processes are used for brazing and sealing 316L stainless steel components in photobioreactors, with identical workpiece specifications, testing environment, and testing standards. This embodiment employs the lead-free brazing sealing process and intelligent welding system described in the complete embodiment above, while the traditional process uses conventional lead-containing brazing (Ar-free)... + Ion beam interface activation, no in-situ passivation, no biocompatibility closed-loop feedback, flux-assisted welding, and post-weld pickling passivation) were used. All comparative indicators were measured using the same detection method.

[0122] Compared to traditional processes, the core advantages of this embodiment's process lie in five aspects: lead-free environmental protection, base material protection, joint performance, process greenness, and quality controllability. This embodiment's process passes Ar... + Ion beam interface activation, multi-segment gradient temperature-controlled brazing, and in-situ passivation effectively preserve the chromium-rich layer structure of 316L stainless steel, inhibit intergranular corrosion, and improve the airtightness, corrosion resistance, and strength of the brazed joints. The lead-free brazing filler metal and flux-free design avoid chemical pollution, and in-situ passivation utilizes residual heat to reduce energy consumption. The intelligent welding system achieves full recording of process parameters and closed-loop feedback for biocompatibility, ensuring that the workpiece meets the requirements for use in photobioreactors. Traditional processes, due to the use of lead-containing brazing filler metals and fluxes and the lack of precise temperature control and in-situ treatment, have significant shortcomings in environmental protection, joint performance, corrosion resistance, and quality traceability, failing to meet the stringent biocompatibility and long-term stable operation requirements of photobioreactors.

[0123] The above are all preferred embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Therefore, all equivalent changes made in accordance with the structure, shape and principle of the present invention should be covered within the scope of protection of the present invention.

Claims

1. A lead-free brazing sealing process for photobioreactor components, characterized in that, Includes the following steps: Step 1: After cleaning the surface of the 316L stainless steel components to be welded in the photobioreactor, Ar is first applied. + Ion beam interface activation treatment is performed, then lead-free silver-based brazing filler is pre-placed on the interface to be soldered, the components to be soldered are assembled and the brazing gap is controlled to the first gap range. Step 2: After assembly and gap control, place the components to be welded in a vacuum brazing furnace, evacuate the furnace until the base vacuum degree is less than or equal to the set vacuum degree threshold, and use a multi-segment gradient temperature control curve for heating and brazing. Step 3: When the brazing cools to the first temperature range, high-purity oxygen is introduced into the vacuum furnace, the oxygen partial pressure is controlled to the first pressure range, the temperature is maintained in the passivation temperature range and held for a set time. Step 4: Based on the pre-established brazing element leaching prediction model, predict the leaching concentration of brazing elements in the culture medium according to the actual brazing process parameters, and compare the leaching concentration with the No Observable Effect Concentration (NOEC) of the target cultured algae species to determine the biocompatibility level of the brazed joint. If the determination result is unqualified, generate process parameter adjustment suggestions according to the brazing element leaching prediction model and return to Step 2 to re-execute brazing until the determination result is qualified.

2. The lead-free brazing sealing process for the photobioreactor component according to claim 1, characterized in that, In step 1, the lead-free silver-based solder is composed of the following components by weight percentage: Ag 40%-60%, Cu 20%-35%, In 8%-18%, Sn 5%-15%, with a total impurity content of less than or equal to 0.1% and a lead content of less than 100 ppm; the solidus temperature of the lead-free silver-based solder is 580℃-610℃, and the liquidus temperature is 620-680℃; the first gap range is 0.03mm-0.08mm.

3. The lead-free brazing sealing process for the photobioreactor component according to claim 2, characterized in that, In step 1, Ar + The process parameters for ion beam interface activation treatment are: ion energy 0.5keV-2.0keV, beam current density 0.2mA / cm²-1.0mA / cm², treatment time 3min-10min, and sputtering depth controlled at 5nm-50nm.

4. The lead-free brazing sealing process for the photobioreactor component according to claim 3, characterized in that, In step 2, the vacuum threshold is set to... The multi-segment gradient temperature control curve includes, in sequence, a preheating segment, a diffusion activation segment, a rapid melting segment, a brazing insulation segment, a slow cooling segment, and a rapid cooling segment; The preheating section increases the temperature to 350℃ at a rate of 8℃ / min-12℃ / min and holds for 5-10 minutes; the diffusion activation section increases the temperature to... Keep warm for 3-5 minutes, during which The liquidus temperature of the lead-free silver-based solder; the rapid melting section rapidly heats up to the brazing holding temperature at a rate of 15℃ / min-20℃ / min. , , The temperature range is 10℃-30℃; the brazing insulation section is in Hold the temperature for 10-20 minutes; in the slow cooling section, cool slowly to 550℃ at a rate of 3℃ / min-5℃ / min; in the rapid cooling section, cool to room temperature with the furnace. During the entire heating brazing process, the cumulative residence time in the sensitization temperature zone of 550℃-650℃ is less than or equal to 15 minutes, and the maximum temperature difference between the parts to be brazed is less than or equal to 15℃.

5. The lead-free brazing sealing process for the photobioreactor component according to claim 4, characterized in that, In step 3, the first temperature range is 150℃-200℃, the first pressure range is 0.1Pa-1.0Pa, the passivation temperature range is 120℃-180℃, the set time is 30min-60min, and the purity of the high-purity oxygen introduced is greater than or equal to 99.99%.

6. The lead-free brazing sealing process for the photobioreactor component according to claim 5, characterized in that, In step 4, the brazing element leaching prediction model is a support vector regression model or a neural network model trained based on experimental data. The input variables include brazing holding temperature, holding time, lead-free silver-based brazing alloy composition, brazing gap and background vacuum degree. The output is the predicted value of the leaching concentration of elements in lead-free silver-based brazing alloy under specified culture conditions for 168 hours.

7. The lead-free brazing sealing process for the photobioreactor component according to claim 6, characterized in that, The method for determining the biocompatibility level of the brazed joint in step 4 is as follows: When the dissolution concentration is less than or equal to 0.1 times the concentration with no observable effect, the biocompatibility level is determined to be Grade A; When the dissolution concentration is greater than 0.1 times the concentration with no observable effect and less than or equal to 0.5 times the concentration with no observable effect, the biocompatibility level is determined to be Grade B. When the leaching concentration is greater than 0.5 times the concentration of no observable effect, the biocompatibility level is determined to be C, and it is suggested that the process parameters need to be adjusted and the brazing should be repeated. A biocompatibility rating of A or B is considered acceptable, while a biocompatibility rating of C is considered unacceptable.

8. The lead-free brazing sealing process for the photobioreactor component according to claim 7, characterized in that, The purification process in step 1 includes: ultrasonic cleaning with analytical grade acetone as the medium at a frequency of 35kHz-45kHz for 8min-12min, followed by secondary cleaning with anhydrous ethanol and rinsing with pure water, and finally drying with high-purity nitrogen gas with a purity of ≥99.999%.

9. The lead-free brazing sealing process for the photobioreactor component according to claim 8, characterized in that, In step 4, the target algal species to be cultured is Haematococcus pluvialis, Chlorella vulgaris, or Dunaliella salina; The method for generating process parameter adjustment suggestions is as follows: based on the sensitivity analysis results of the brazing element leaching prediction model for each input variable, determine at least one of the following: the reduction in brazing holding temperature, the shortening of holding time, or the adjustment direction of lead-free silver-based brazing alloy composition ratio required to reduce the leaching concentration to the qualified level.

10. A lead-free brazing sealing intelligent welding system for photobioreactor components, characterized in that, The system for implementing the lead-free brazing sealing process of the photobioreactor component as described in claim 9 includes a vacuum brazing furnace body (1), a multi-source sensing subsystem (2), a data processing and fusion module (3), a temperature curve decision module (4), a biocompatibility prediction and evaluation module (5), and a human-computer interaction terminal (6). The vacuum brazing furnace body (1) is used to provide a vacuum environment and heating conditions; The multi-source sensing subsystem (2) includes an infrared thermal imaging temperature field monitoring unit (21), a vacuum monitoring unit (22), a residual gas analysis unit (23), and a brazing filler metal melting state visual monitoring unit (24). The infrared thermal imaging temperature field monitoring unit (21) is used to collect the two-dimensional temperature distribution on the surface of the component to be welded in real time. The vacuum monitoring unit (22) is used to measure the background vacuum in the furnace. The residual gas analysis unit (23) is used to monitor the composition of residual gas and oxygen partial pressure in the furnace in real time. The brazing filler metal melting state visual monitoring unit (24) is used to collect images of the brazing seam area in real time. The data processing and fusion module (3) is used to perform time synchronization, spatial registration and feature extraction on multi-source sensing data to form a unified multi-dimensional state vector; The temperature curve decision module (4) adopts a deep deterministic strategy gradient algorithm, takes a multi-dimensional state vector as input, and outputs heating power regulation action, so that the actual brazing temperature curve dynamically approximates the preset multi-segment gradient temperature control strategy and meets the constraints of brazing heat preservation temperature, maximum temperature difference of the component to be welded, cumulative residence time of the sensitized temperature zone and background vacuum degree. The biocompatibility prediction and evaluation module (5) has an embedded brazing element leaching prediction model, which is used to calculate the predicted leaching concentration and determine the biocompatibility level online based on the actual brazing process parameters, and generate process parameter adjustment suggestions when the level is determined to be unqualified. The human-computer interaction terminal (6) communicates and interacts with the biocompatibility prediction and evaluation module (5) to provide biocompatibility level and process parameter adjustment suggestions.

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