Method for modifying application of low cyclic silicone oil in high toughness cable jacketing material

Abstract

The application discloses a modified application method of low-cyclic silicone oil in a high-toughness cable sheath material, and belongs to the field of cable material modification. The low-cyclic silicone oil is grafted and modified to serve as a toughening modifier, is compounded with a base resin, a reinforcing filler and a functional additive, and the modification process parameters and material ratios are optimized through multi-algorithm collaborative optimization such as toughening efficiency optimization and response surface optimization, so that the technical problems of poor compatibility of traditional low-cyclic silicone oil with a sheath material base and rough modification process regulation are solved. In the application, the silicone oil modification stirring rate is regulated through a viscosity collaborative algorithm, the component uniform dispersion is ensured through temperature gradient mixing and a torque feedback algorithm, the extrusion parameters are optimized through a BP neural network algorithm, and the sheath material comprehensive performance is quantitatively evaluated by relying on an entropy weight-TOPSIS coupling algorithm. The process has strong controllability and accurate parameter optimization, can be widely applied to the preparation of cable sheaths in fields such as rail transit, new energy and outdoor laying, and has good industrial application prospect.

Description

Technical Field

[0001] This invention belongs to the field of cable material modification technology, specifically involving a method for modifying and applying low-cyclic silicone oil in high-toughness cable sheath materials. In particular, it involves a method for synergistically improving the toughness, weather resistance, and processability of cable sheath materials by using multi-algorithm collaborative optimization of modification processes and material ratios. Background Technology

[0002] As the cable industry develops towards high-end and multi-functional applications, the performance requirements for cable sheath materials in applications such as rail transit, new energy, and outdoor laying are becoming increasingly stringent. These materials not only need excellent toughness and tensile strength but also must meet multiple requirements including low-temperature flexibility, weather resistance, and processing fluidity. Traditional cable sheath materials often use plasticizers and rubber elastomers as toughening agents, but these have problems such as easy migration, poor temperature resistance, and poor compatibility with the matrix resin. This leads to a decrease in toughness and an increased risk of low-temperature embrittlement after long-term use, making it difficult to meet the needs of high-end applications.

[0003] Low-cyclic silicone oils are characterized by short molecular chains, good fluidity, and low surface energy. The active groups in their molecular structure can interact with the polymer matrix, making them a promising new and efficient toughening modifier for cable sheathing materials. However, unmodified low-cyclic silicone oils have poor compatibility with the matrix resin of the sheathing material, and direct addition easily leads to phase separation, resulting in a decrease in the mechanical properties of the sheathing material. Furthermore, current technologies for modifying low-cyclic silicone oils often rely on empirical methods to determine process parameters and addition amounts, lacking systematic algorithmic support. This makes it impossible to precisely control the modification effect and the overall performance of the sheathing material, resulting in poor performance stability and significant batch-to-batch variations in the modified sheathing material.

[0004] Currently, patents such as CN114716807A, which discloses a special flexible cable sheath material and its preparation method, rely on the modification of traditional nitrile rubber (NBR) elastomers. Without optimizing the compatibility of the modifier, there is a risk of uneven dispersion, making it impossible to achieve molecular-level toughening. The upper limit of toughness improvement is lower than that of low-cyclic silicone oil grafting modification technology. Another example is patent CN113681749B, which discloses a high-softness, high-toughness, crack-resistant sheath material and its preparation method. This patent relies on the physical morphology regulation of polyolefin elastic fibers for toughening, requiring additional specialized equipment such as fiber winding machines and electron accelerators. The process is complex and energy-intensive, resulting in higher production costs compared to chemical modification with low-cyclic silicone oil (addition amount only 1-8%). Using methylphenyl silicone oil as a lubricant without optimizing the functional additive ratio through analytic hierarchy process, the synergy between processing fluidity and weather resistance is insufficient. Compared to the precise compounding of multiple additives in low-cyclic silicone oil modification, the overall processing performance is worse.

[0005] Therefore, developing a dedicated modification process for low-cyclic silicone oil, and using multi-algorithm collaborative optimization of modification parameters and material ratios to achieve efficient application of low-cyclic silicone oil in high-toughness cable sheath materials, and solving the problems of performance shortcomings of traditional sheath materials and extensive control of modification processes, has become a key technology that urgently needs to be solved in this field. Summary of the Invention

[0006] The purpose of this invention is to overcome the shortcomings of existing technologies, such as poor compatibility between low-cyclic silicone oil and cable sheath material matrix, rough control of modification process, and difficulty in simultaneously achieving both toughness and weather resistance / processability of sheath material. This invention provides a method for modifying and applying low-cyclic silicone oil in high-toughness cable sheath material. By grafting and modifying the low-cyclic silicone oil, and combining multiple algorithms to collaboratively optimize modification process parameters and material ratios, the invention achieves a synergistic improvement in the toughness, weather resistance, and processability of the sheath material by the low-cyclic silicone oil. Simultaneously, it enhances the controllability and precision of the modification process, ensuring the performance stability of the modified sheath material.

[0007] To achieve the above objectives, the present invention adopts the following technical solution:

[0008] A method for modifying and applying low-cyclic silicone oil in high-toughness cable sheath materials involves introducing modified low-cyclic silicone oil as a toughening modifier into the cable sheath material system. This modified silicone oil is then compounded with the sheath material matrix resin, reinforcing fillers, and functional additives. Through multi-algorithm collaborative optimization of modification process parameters and material ratios, the toughness, weather resistance, and processability of the sheath material are synergistically improved. The modified cable sheath material meets the following requirements: elongation at break ≥600%, tensile strength ≥18MPa, low-temperature embrittlement temperature ≤-40℃, and tensile strength retention rate ≥85% and elongation at break retention rate ≥80% after thermal aging.

[0009] Furthermore, the low-cyclic silicone oil is at least one of hydrogen-containing low-cyclic silicone oil and hydroxyl-terminated low-cyclic silicone oil, with a number-average molecular weight of 500-2000 g / mol and a cyclic content ≥98%. Its addition amount in the sheathing material system is determined by a toughening efficiency optimization algorithm, the algorithm expression of which is:

[0010] ;

[0011] Where: Y_T is the toughening efficiency score of the sheath material (full score of 100 points, evaluation indicators include elongation at break, low temperature embrittlement temperature, and tensile strength, with weights of 0.5, 0.3, and 0.2 respectively), and X_S is the mass ratio of low cyclic silicone oil (based on the total mass of the sheath material). These are the fitting coefficients (obtained by fitting experimental data). Values ​​range from 8.5 to 9.5. The value is 0.4-0.6), ε_T is the error term of the algorithm model (≤±2), the optimization objective is Y_T≥90 points, and the amount of low-cyclic silicone oil added is 1-8% of the total mass of the sheath material.

[0012] The cyclic content of low-cyclic silicone oil is ≥98% to ensure its purity and toughening effect, while the number average molecular weight is controlled at 500-2000 g / mol to balance its flowability and compatibility with the matrix. The toughening efficiency optimization algorithm quantifies the nonlinear relationship between the amount of low-cyclic silicone oil added and the toughening efficiency, avoiding the problems of insufficient toughening effect due to too little addition and decreased tensile strength of the sheath material due to too much addition, thus achieving precise control of the addition amount.

[0013] Furthermore, the low-cyclic silicone oil was grafted and modified. The optimal process parameters were determined using a response surface methodology algorithm, and a quadratic regression model was established.

[0014]

[0015] Where: Y_G is the grafting rate of low-cyclic silicone oil (%), A is the modification reaction temperature (°C), B is the modification reaction time (h), and C is the amount of grafted monomer (based on the mass of low-cyclic silicone oil, %). For constant terms, The regression coefficients for the corresponding independent variables and their interaction terms and quadratic terms (obtained by fitting experimental data) are optimized to achieve a grafting rate ≥85%.

[0016] The grafted monomer is at least one of maleic anhydride and acrylate monomers. The modification reaction uses azobisisobutyronitrile as the initiator, and the amount of initiator is 0.5-2% of the total mass of the low-cyclic silicone oil and the grafted monomer. The stirring rate of the modification reaction is controlled by a viscosity-coordinated algorithm. Where: V_S is the stirring rate (r / min), and μ is the real-time viscosity of the reaction system. k is the viscosity coefficient (values ​​range from 0 to 10) (Adjustments may be made based on the type of grafted monomer) to ensure that the viscosity uniformity of the reaction system is ≥92%.

[0017] Grafting modification can introduce active groups compatible with the matrix resin onto the low-cyclic silicone oil molecular chain, solving the phase separation problem between the resin and the matrix. Response surface methodology can comprehensively consider the effects of modification reaction temperature, time, graft monomer dosage, and their interactions on the grafting rate, and can more accurately determine the optimal process parameters compared to single-factor experiments. Viscosity synergy algorithm matches the viscosity changes of the reaction system by real-time control of the stirring rate, ensuring uniform mixing of the reaction system and improving the grafting rate and grafting uniformity.

[0018] Furthermore, the matrix resin of the sheath material is a blend of at least two of polyvinyl chloride, polyolefin elastomer, and chlorinated polyethylene. The blending ratio of the matrix resin is determined by a multiple linear regression algorithm, the expression of which is:

[0019] ;

[0020] Where: Y_P is the comprehensive performance score of the matrix resin (full score 100 points, evaluation indicators include compatibility, processing fluidity and mechanical properties, with weights of 0.4, 0.3 and 0.3 respectively). This represents the mass percentage of polyvinyl chloride. This represents the mass percentage of polyolefin elastomers. This represents the mass percentage of chlorinated polyethylene. The regression coefficients for the corresponding resins (obtained by fitting experimental data) The value ranges from 0.25 to 0.35. The value ranges from 0.35 to 0.45. The value is 0.25-0.35), ε_P is the error term of the algorithm model (≤±2), and the optimization objective is Y_P≥88 points.

[0021] Polyvinyl chloride (PVC) has excellent electrical insulation and chemical corrosion resistance. Polyolefin elastomers can improve the low-temperature flexibility of the sheath material, and chlorinated polyethylene can enhance the tensile strength and weather resistance of the sheath material. The combination of the three can optimize the comprehensive performance of the matrix resin. The multiple linear regression algorithm accurately determines the optimal compounding ratio by fitting the linear relationship between the ratio of each resin and the comprehensive performance, laying the foundation for the comprehensive performance of the sheath material.

[0022] Furthermore, the reinforcing filler is at least one of nano-calcium carbonate, silica, and talc, and the surface activation degree of the filler is evaluated using an activation efficiency algorithm.

[0023] ;

[0024] Where: η_A is the surface activation degree of the filler (%). The specific surface area (m² / g) of the activated filler. The specific surface area (m² / g) of the filler before activation is optimized to achieve a surface activation degree ≥75%, and the amount of reinforcing filler added is 10-30% of the total mass of the matrix resin.

[0025] After surface activation treatment with stearic acid and silane coupling agent, the compatibility of the filler with the matrix resin is greatly improved, which can effectively play a reinforcing role and avoid filler agglomeration leading to a decrease in the toughness of the sheath material. The activation efficiency algorithm can quantitatively evaluate the activation effect of the filler, ensuring that the activated filler can effectively improve the tensile strength and toughness of the sheath material without affecting the processing fluidity.

[0026] Furthermore, the functional additives include antioxidants (preferably a combination of antioxidant 1010 and antioxidant 168), light stabilizers (preferably hindered amine light stabilizer 944), and lubricants (preferably a combination of calcium stearate and polyethylene wax). The proportions and weights of each additive are determined using the analytic hierarchy process (AHP) to construct a weight vector. Where: W is the weight vector of functional additive proportions, The ratio weight of antioxidants is 0.35-0.45. The proportion of light stabilizer is 0.30-0.40. The weighting ratio of the lubricant is (0.20-0.30), and The total amount of functional additives added is 2-6% of the total mass of the sheath material.

[0027] The Analytic Hierarchy Process (AHP) constructs a hierarchical structure consisting of a target layer (comprehensive effect of functional additives), a criterion layer (thermal stability, light stability, and processing fluidity), and a scheme layer (each functional additive). This structure scientifically determines the proportion and weight of each additive, avoids performance defects caused by excessive or insufficient amounts of a single additive, and ensures a synergistic improvement in the weather resistance and processability of the sheath material.

[0028] Furthermore, the mixing process of the modified low-cyclic silicone oil and each component of the sheathing material is controlled by a temperature gradient mixing algorithm, with the mixing temperature set according to... Gradient heating, where: The initial mixing temperature is 80-90℃. This refers to the intermediate mixing temperature (100-110℃). The final mixing temperature is 120-130℃, with a heating rate of 5-8℃ / min. The mixing time is determined by a torque feedback algorithm: when the real-time torque M_t of the mixer is equal to the equilibrium torque... Mixing should be stopped when the deviation rate δ_M ≤ 5%. The formula for calculating the deviation rate is:

[0029] ;

[0030] To balance the torque of the mixing system ( The value was determined through preliminary experiments. ).

[0031] The temperature gradient mixing algorithm can avoid resin degradation and low-cyclic silicone oil volatilization caused by instantaneous high temperature, ensuring that each component melts gradually and mixes evenly; the torque feedback algorithm can accurately determine the mixing endpoint by monitoring the torque change of the mixer in real time, avoiding uneven component dispersion caused by insufficient mixing or reduced toughness of the sheath material caused by over-mixing.

[0032] Furthermore, the mixed material is extruded and granulated by a twin-screw extruder to obtain sheath material particles. The extrusion parameters are optimized by a BP neural network algorithm. The model takes the extrusion temperature T (130-150℃), screw speed N (100-200r / min), and feed rate F (20-50kg / h) as input parameters and the particle size uniformity U (%) as output parameter. After optimization, the particle size uniformity is ≥95%, and the model prediction error ε_N≤3%, where: ε_N=|U_predicted-U_actual| / U_actual×100%, U_predicted is the particle size uniformity predicted by the model, and U_actual is the actual detected particle size uniformity.

[0033] The training process of the BP neural network model is as follows: 1) Collect 60-80 sets of particle size uniformity sample data corresponding to different extrusion parameters; 2) Normalize the sample data and map it to the [0,1] interval; 3) Construct the network structure with 3 neurons in the input layer, 12-16 neurons in the hidden layer, and 1 neuron in the output layer, and use the Sigmoid function as the activation function; 4) Optimize the network weights using the gradient descent method, with a learning rate of 0.01-0.05 and 1500-2000 training iterations until the model prediction error is ≤3%; 5) Use the trained model to adjust the extrusion parameters in real time to ensure uniform particle size.

[0034] Furthermore, the comprehensive performance of the modified cable sheath material was evaluated using the entropy weight-TOPSIS coupled algorithm. The weights of each performance index were calculated as w_i=(1-e_i) / Σ(1-e_i), where: e_i is the information entropy of the i-th performance index, e_i=-kΣ(p_ijlnp_ij), k=1 / lnn (n is the number of detected samples), and p_ij is the normalized value of the i-th index corresponding to the j-th sample; the comprehensive evaluation closeness C_i=(d_i^-) / (d_i^++d_i^-), where: d_i^+ is the Euclidean distance between the i-th sample and the positive ideal solution, and d_i^- is the Euclidean distance between the i-th sample and the negative ideal solution. The optimization objective is C_i≥0.85.

[0035] Evaluation indicators include elongation at break, tensile strength, low-temperature embrittlement temperature, tensile strength retention rate after thermal aging, and elongation at break retention rate after thermal aging. The entropy weight-TOPSIS coupled algorithm can objectively determine the weight of each indicator through the entropy weight method, avoiding the bias of subjective assignment. Then, the TOPSIS method is used to realize the quantitative evaluation of the comprehensive performance of the sheath material, ensuring the objectivity and accuracy of the evaluation results.

[0036] Compared with the prior art, the present invention has the following beneficial effects:

[0037] This invention addresses the technical problems of poor compatibility and easy phase separation between unmodified low-cyclic silicone oil and the matrix by grafting and modifying low-cyclic silicone oil to introduce active groups compatible with the sheathing material matrix into its molecular chain. The modified low-cyclic silicone oil can be uniformly dispersed in the sheathing material system, giving full play to its toughening effect. The modified sheathing material has an elongation at break of ≥600%, a low-temperature embrittlement temperature of ≤-40℃, and significantly improved toughness and low-temperature flexibility.

[0038] This invention employs a combination of algorithms, including toughening efficiency optimization, response surface methodology, and multiple linear regression, to collaboratively optimize modification process parameters and material ratios, replacing traditional empirical methods. This achieves precise control over the amount of low-cyclic silicone oil added, modification process parameters, and matrix resin compounding ratio, avoiding performance fluctuations caused by coarse parameter settings. The batch-to-batch performance difference of the modified sheath material is ≤5%, significantly improving performance stability.

[0039] This invention uses a temperature gradient mixing algorithm and a torque feedback algorithm to ensure uniform dispersion of the modified low-cyclic silicone oil and the components of the sheathing material. Combined with a BP neural network algorithm to optimize extrusion parameters, it improves the processability and particle uniformity of the sheathing material, solves the problem of poor processing flowability of traditional toughened modified sheathing materials, and achieves a synergistic improvement in the toughness and processability of the sheathing material.

[0040] The modification and application method of this invention has strong process controllability, and the parameters of each step can be precisely controlled by algorithms. Moreover, the amount of low-cyclic silicone oil added is small (1-8%), resulting in low production costs. No toxic or harmful gases are generated during the modification process, which meets environmental protection requirements. The modified sheath material has excellent toughness, tensile strength, low-temperature flexibility and weather resistance. After heat aging, the tensile strength retention rate is ≥85% and the elongation at break retention rate is ≥80%. It can be widely used in the preparation of cable sheaths for high-end application scenarios such as rail transit, new energy, and outdoor laying, and has good prospects for industrial application. Detailed Implementation

[0041] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0042] Example 1

[0043] A method for modifying and applying low-cyclic silicone oil in high-toughness cable sheathing materials, comprising the following steps:

[0044] Low-cyclic silicone oil modification: Hydroxyl-terminated low-cyclic silicone oil (number average molecular weight 1000 g / mol, cyclic content 99%) was selected, maleic anhydride was used as the grafting monomer, and azobisisobutyronitrile (1% of the total mass of low-cyclic silicone oil and maleic anhydride) was used as the initiator. The modification process parameters were determined using response surface methodology: reaction temperature A = 85℃, reaction time B = 2 h, grafting monomer dosage C = 15%, and grafting rate Y_G = 88%. During the modification process, the stirring rate was controlled using a viscosity-coordinated algorithm, and the real-time viscosity of the reaction system was monitored. viscosity coefficient stirring rate The viscosity uniformity of the reaction system is 94%.

[0045] Material proportioning determination: The amount of modified low-cyclic silicone oil added was determined to be 4% of the total mass of the sheath material using a toughening efficiency optimization algorithm. The algorithm fitting coefficient was... The toughening efficiency score Y_T = 92 points; the matrix resin is polyvinyl chloride + polyolefin elastomer (mass ratio 7:3), and the comprehensive performance score Y_P = 90 points was determined by multiple linear regression algorithm; the reinforcing filler is activated nano calcium carbonate (surface activation degree η_A = 80%), and the addition amount is 20% of the total mass of the matrix resin; the functional additives are antioxidant 1010 + 168 (compound ratio 1:1), light stabilizer 944, and calcium stearate, and the weight vector W = (0.4, 0.35, 0.25) was determined by analytic hierarchy process, and the total addition amount is 4% of the total mass of the sheath material.

[0046] Mixing process: Modified low-cyclic silicone oil, matrix resin, activated nano-calcium carbonate, and functional additives are added to an internal mixer, and a temperature gradient mixing algorithm is used, according to... Gradient heating at a rate of 6℃ / min; preliminary experiments determined the equilibrium torque. When real-time torque When the deviation rate δ_M = 4% ≤ 5%, stop mixing and the mixing time is 15 min.

[0047] Extrusion granulation: The mixed material is fed into a twin-screw extruder, and the extrusion parameters are optimized by a BP neural network algorithm: extrusion temperature T=140℃, screw speed N=150r / min, feeding speed F=35kg / h, particle size uniformity U=96%, and model prediction error ε_N=2.2%.

[0048] Performance testing and evaluation: The modified sheath material was tested and found to have an elongation at break of 650%, a tensile strength of 20 MPa, a low-temperature embrittlement temperature of -45℃, and a tensile strength retention rate of 89% and an elongation at break retention rate of 85% after 168 hours of heat aging at 100℃. Evaluation was conducted using the entropy-weighted TOPSIS coupled algorithm. Ten samples were selected, with the information entropy e_i of each performance index ranging from 0.02 to 0.08, and the weight w_i ranging from 0.18 to 0.22. The overall evaluation closeness C_i = 0.90 ≥ 0.85, indicating excellent performance.

[0049] Example 2

[0050] A method for modifying and applying low-cyclic silicone oil in high-toughness cable sheathing materials, comprising the following steps:

[0051] Low-cyclic silicone oil modification: Hydrogen-containing low-cyclic silicone oil (number average molecular weight 800 g / mol, cyclic content 98.5%) was selected, butyl acrylate was used as the grafting monomer, and azobisisobutyronitrile (0.8% of the total mass of low-cyclic silicone oil and butyl acrylate) was used as the initiator. The modification process parameters were determined using response surface methodology: modification reaction temperature A = 80℃, reaction time B = 2.5 h, grafting monomer dosage C = 12%, grafting rate Y_G = 86%. The real-time viscosity of the reaction system during the modification process was also measured. viscosity coefficient stirring rate The viscosity uniformity of the reaction system is 93%.

[0052] Material proportioning determination: The amount of modified low-cyclic silicone oil added was determined to be 3% of the total mass of the sheath material using a toughening efficiency optimization algorithm. The algorithm fitting coefficient was... The toughening efficiency score Y_T = 91 points; the matrix resin is polyvinyl chloride + chlorinated polyethylene (mass ratio 6:4), and the comprehensive performance score Y_P = 89 points was determined by multiple linear regression algorithm; the reinforcing filler is activated silica (surface activation degree η_A = 78%), and the addition amount is 15% of the total mass of the matrix resin; the functional additive weight vector W = (0.38, 0.37, 0.25), and the total addition amount is 3.5% of the total mass of the sheath material.

[0053] Mixing process: Temperature gradient of internal mixer is Heating rate 5℃ / min; Balance torque Real-time torque Deviation rate δ_M = 4.5% ≤ 5%, mixing time 16 min.

[0054] Extrusion granulation: BP neural network algorithm optimizes extrusion parameters: extrusion temperature T=135℃, screw speed N=140r / min, feeding speed F=30kg / h, particle size uniformity U=95%, model prediction error ε_N=2.8%.

[0055] Performance testing and evaluation: The modified sheath material has an elongation at break of 620%, a tensile strength of 19 MPa, a low-temperature embrittlement temperature of -42℃, and a tensile strength retention rate of 87% and an elongation at break retention rate of 82% after heat aging at 100℃ for 168 hours. The entropy weight-TOPSIS coupled algorithm provides a closeness C_i of 0.88 ≥ 0.85, indicating excellent performance.

[0056] Example 3

[0057] A method for modifying and applying low-cyclic silicone oil in high-toughness cable sheathing materials, comprising the following steps:

[0058] Low-cyclic silicone oil modification: Hydrogen-containing low-cyclic silicone oil + hydroxyl-terminated low-cyclic silicone oil (mixture ratio 1:1, number average molecular weight 1500 g / mol, cyclic content 98%) were selected. The grafting monomers were maleic anhydride + ethyl acrylate (mixture ratio 1:2), and the initiator dosage was 1.5% of the total mass. The modification process parameters were determined using response surface methodology: A = 90℃, B = 1.5 h, C = 18%, grafting rate Y_G = 89%. The real-time viscosity of the reaction system was... viscosity coefficient stirring rate Viscosity uniformity is 95%.

[0059] Material proportions determined as follows: the amount of low-cyclic silicone oil added is 6% of the total mass of the sheath material, with a toughening efficiency score Y_T=93; the matrix resin is polyvinyl chloride + polyolefin elastomer + chlorinated polyethylene (mass ratio 5:3:2), with a comprehensive performance score Y_P=91; the reinforcing filler is nano-calcium carbonate + talc (compound ratio 2:1, surface activation 79%), with an addition amount of 25% of the total mass of the matrix resin; the total amount of functional additives added is 5% of the total mass of the sheath material, with a weight vector W=(0.42,0.33,0.25).

[0060] Mixing process: temperature gradient is Heating rate: 8℃ / min; Balance torque Real-time torque M_t= Deviation rate δ_M = 3.6% ≤ 5%, mixing time 14 min.

[0061] Extrusion granulation: Extrusion parameters are T=145℃, N=160r / min, F=40kg / h, particle size uniformity U=97%, and model prediction error ε_N=2.0%.

[0062] Performance testing and evaluation: The modified sheath material has an elongation at break of 680%, a tensile strength of 21 MPa, a low-temperature embrittlement temperature of -48℃, and a tensile strength retention rate of 90% and an elongation at break retention rate of 86% after heat aging at 100℃ for 168 hours. The overall evaluation closeness Ci=0.92≥0.85 indicates excellent performance.

[0063] Comparative Example 1

[0064] The low-cyclic silicone oil was not modified. The hydroxyl-terminated low-cyclic silicone oil (the same as in Example 1) was directly introduced into the sheath material system at an addition amount of 4%. The remaining material ratios and process parameters were the same as in Example 1.

[0065] Test results: The sheath material has an elongation at break of 350%, a tensile strength of 15 MPa, a low-temperature embrittlement temperature of -20℃, and a tensile strength retention rate of 70% and an elongation at break retention rate of 65% after thermal aging. The overall evaluation closeness C_i=0.62<0.85. Due to the poor compatibility between the low-cyclic silicone oil and the matrix, the phase separation is severe, and the performance of the sheath material is greatly reduced.

[0066] Comparative Example 2

[0067] The process parameters and addition amount of low-cyclic silicone oil were determined using an empirical method. The modification reaction temperature was 70℃, the time was 1h, the grafted monomer dosage was 10%, the low-cyclic silicone oil addition amount was 10%, and the rest were the same as in Example 1.

[0068] Test results: Low cyclic silicone oil grafting rate 65%, sheath material elongation at break 420%, tensile strength 12MPa, low temperature embrittlement temperature -25℃, performance retention rate after thermal aging 75%; comprehensive evaluation closeness C_i=0.68<0.85, due to unreasonable modification process parameters and addition amount, the toughness improvement of sheath material is limited, and the tensile strength is significantly reduced.

[0069] The above embodiments and comparative examples show that, by grafting and modifying low-cyclic silicone oil and combining multiple algorithms to collaboratively optimize the modification process parameters and material ratios, the present invention can achieve a synergistic improvement in the toughness, weather resistance, and processability of cable sheath materials by low-cyclic silicone oil. The overall performance of the modified sheath material is significantly better than that of the unmodified sheath material controlled by empirical methods, which fully demonstrates the effectiveness and superiority of the technical solution of the present invention.

[0070] Industrial applicability

[0071] The method for modifying and applying low-cyclic silicone oil in high-toughness cable sheathing materials according to this invention has clear process steps. All process parameters and material ratios can be precisely controlled through algorithms. The equipment used is conventional equipment in the cable material production field (internal mixer, twin-screw extruder, etc.), requiring no additional equipment and resulting in low modification costs. It can be directly applied to existing industrial production lines for cable sheathing materials. The modified sheathing material exhibits excellent comprehensive performance, meeting the needs of high-end applications such as rail transit, new energy, and outdoor laying, and has broad industrial application prospects.

Claims

1. A method for modifying and applying low-cyclic silicone oil in high-toughness cable sheath materials, characterized in that, Low-cyclic silicone oil was modified and introduced into the cable sheath material system as a toughening modifier. It was compounded with the sheath material matrix resin, reinforcing filler, and functional additives. Through multi-algorithm collaborative optimization of modification process parameters and material ratio, the toughness, weather resistance, and processability of the sheath material were synergistically improved. The modified cable sheath material meets the following requirements: elongation at break ≥600%, tensile strength ≥18MPa, low-temperature embrittlement temperature ≤-40℃, tensile strength retention rate ≥85% and elongation at break retention rate ≥80% after heat aging.

2. The modified application method according to claim 1, characterized in that, The low-cyclic silicone oil is at least one of hydrogen-containing low-cyclic silicone oil and hydroxyl-terminated low-cyclic silicone oil, with a number-average molecular weight of 500-2000 g / mol and a cyclic content ≥98%. Its addition amount in the sheathing material system is determined by a toughening efficiency optimization algorithm, the algorithm expression of which is: ； Where: Y_T is the toughening efficiency score of the sheath material, and X_S is the mass percentage of low-cyclic silicone oil (based on the total mass of the sheath material). ε_T is the fitting coefficient, and Y_T is the algorithm model error term. The optimization objective is Y_T≥90 points (out of 100 points). The amount of low-cyclic silicone oil added is 1-8% of the total mass of the sheath material.

3. The modified application method according to claim 1, characterized in that, Graft modification was performed on low-cyclic silicone oil. The optimal process parameters were determined using response surface methodology, and a quadratic regression model was established. ； Where: Y_G is the grafting rate of low-cyclic silicone oil (%), A is the modification reaction temperature (°C), B is the modification reaction time (h), and C is the amount of grafted monomer (based on the mass of low-cyclic silicone oil, %). For constant terms, These are the regression coefficients of the corresponding independent variables and their interaction terms and quadratic terms, respectively, with an optimized grafting rate ≥85%.

4. The modified application method according to claim 3, characterized in that, The grafted monomer is at least one of maleic anhydride and acrylate monomers. The modification reaction uses azobisisobutyronitrile as the initiator, and the amount of initiator is 0.5-2% of the total mass of the low-cyclic silicone oil and the grafted monomer. The stirring rate of the modification reaction is controlled by a viscosity-coordinated algorithm. ； Where: V_S is the stirring rate (r / min), and μ is the real-time viscosity of the reaction system. k is the viscosity coefficient (values ​​range from 0 to 10) This ensures that the viscosity uniformity of the reaction system is ≥92%.

5. The modified application method according to claim 1, characterized in that, The sheath material matrix resin is a blend of at least two of polyvinyl chloride, polyolefin elastomer, and chlorinated polyethylene. The blending ratio of the matrix resin is determined by a multiple linear regression algorithm, the expression of which is: ； Where: Y_P is the comprehensive performance score of the matrix resin. This represents the mass percentage of polyvinyl chloride. This represents the mass percentage of polyolefin elastomers. This represents the mass percentage of chlorinated polyethylene. The regression coefficients for the corresponding resins are given, ε_P is the error term of the algorithm model, and the optimization objective is Y_P≥88 points (out of 100).

6. The modified application method according to claim 5, characterized in that, The reinforcing filler is at least one of nano-calcium carbonate, silica, and talc. The surface activation degree of the filler is evaluated using an activation efficiency algorithm. ； Where: η_A is the surface activation degree of the filler (%). The specific surface area of ​​the activated packing ( ), The specific surface area of ​​the packing before activation ( After optimization, the surface activation degree of the filler is ≥75%, and the amount of reinforcing filler added is 10-30% of the total mass of the matrix resin.

7. The modified application method according to claim 1, characterized in that, The functional additives include antioxidants, light stabilizers, and lubricants. The weighting ratios of each additive are determined using the analytic hierarchy process (AHP), constructing a weight vector W=( ), where: W is the weight vector of functional additive proportions, The weighting of antioxidants in the formulation. The weight ratio of light stabilizers. The weighting of the lubricant is given, and The total amount of functional additives added is 2-6% of the total mass of the sheath material.

8. The modified application method according to claim 1, characterized in that, The mixing process of the modified low-cyclic silicone oil and each component of the sheathing material was controlled by a temperature gradient mixing algorithm, with the mixing temperature set according to... Gradient heating, where: The initial mixing temperature is 80-90℃. This refers to the intermediate mixing temperature (100-110℃). The final mixing temperature is 120-130℃, and the mixing time is determined by a torque feedback algorithm: when the real-time torque M_t of the mixer is equal to the equilibrium torque... Mixing should be stopped when the deviation rate δ_M ≤ 5%. The formula for calculating the deviation rate is: , To balance the torque of the mixing system .

9. The modified application method according to claim 8, characterized in that, The mixed material is extruded and granulated to obtain sheath material granules. The extrusion parameters are optimized by a BP neural network algorithm. The model takes the extrusion temperature T, screw speed N, and feeding speed F as input parameters and the particle size uniformity U as output parameter. After optimization, the particle size uniformity is ≥95%, and the model prediction error ε_N≤3%, where: ε_N=|U_predicted-U_actual| / U_actual×100%, U_predicted is the particle size uniformity predicted by the model, and U_actual is the actual detected particle size uniformity.

10. The modified application method according to claim 1, characterized in that, The comprehensive performance of the modified cable sheath material was evaluated using the entropy weight-TOPSIS coupled algorithm. The weight of each performance index was calculated as w_i=(1-e_i) / Σ(1-e_i), where: e_i is the information entropy of the i-th performance index, and Σ(1-e_i) is the sum of (1-e_i) of all performance indices. The comprehensive evaluation closeness C_i=(d_i^-) / (d_i^++d_i^-) where: d_i^+ is the Euclidean distance between the i-th sample and the positive ideal solution, and d_i^- is the Euclidean distance between the i-th sample and the negative ideal solution. The optimization objective was C_i≥0.85.

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