發(fā)布時間：2018-04-10 05:14

  本文選題：壓鑄模具　切入點：溫度控制　出處：《沈陽理工大學》2017年碩士論文

【摘要】：近些年來,隨著壓鑄行業(yè)的不斷發(fā)展,即使在經(jīng)濟不是很景氣的情況下,因為壓鑄模具的產(chǎn)品質量、生產(chǎn)工藝、產(chǎn)品的精密程度等有所提高,使得壓鑄市場仍保持比較健康的狀態(tài)。根據(jù)市場調查顯示,壓鑄模具的產(chǎn)值每年在穩(wěn)步上升。汽車、航天等行業(yè)的迅猛發(fā)展使得對模具需求量大大提高,對我國壓鑄行業(yè)來說,機遇與挑戰(zhàn)并存。然而我國壓鑄模具的制造水平與發(fā)達國家還是有一定差距,當務之急是要自主研發(fā)并改進模具的各項指標,而不是一味的去仿造國外產(chǎn)品。壓鑄模具產(chǎn)品的好壞,很主要的一個指標就是壓鑄過程中模具的溫度,這對產(chǎn)品的質量及模具的壽命有著至關重要的影響。壓鑄模具溫度的主要特點是冷卻過程較慢,耗能大,如果得不到有效控制,嚴重時會直接影響產(chǎn)品的質量,這就要求在壓鑄過程中,溫度要保持在一定的范圍內。模具溫度具有大延時、大慣性、非線性的特點,并且沒有精確的數(shù)學模型,傳統(tǒng)的控制方法不能達到精確控制的效果。基于這個問題,本論文設計了基于模糊神經(jīng)網(wǎng)絡的多路模具溫度控制系統(tǒng)。因為壓鑄模具是由個多個模具塊組合而成的,所以對每塊模具設計了獨立的循環(huán)冷卻水回路,通過調節(jié)各回路冷卻水閥門開通時間長短,來使模具降溫,最終達到控溫目的。模糊神經(jīng)網(wǎng)絡是近些年來控制領域研究的一個熱點,模糊控制和神經(jīng)網(wǎng)絡都是基于無模型、非線性系統(tǒng),其中模糊系統(tǒng)善于表達模糊、定性知識,缺乏自適應能力和自學習,而神經(jīng)網(wǎng)絡有很好的學習能力,但不能利用基于規(guī)則的知識,結合兩者優(yōu)點設計一種基于模糊神經(jīng)網(wǎng)絡控系統(tǒng),通過MATLAB仿真,與模糊控制相比較,系統(tǒng)響應更快,精度更高,效果更好。
[Abstract]:In recent years, with the continuous development of the die casting industry, even when the economy is not very prosperous, the quality of the die casting die, the production process, the precision of the products have been improved.So that the die-casting market to maintain a relatively healthy state.According to market research, the output value of die-casting dies is rising steadily every year.With the rapid development of automobile, aerospace and other industries, the demand for dies is greatly increased, and opportunities and challenges coexist for the die casting industry in China.However, the manufacturing level of die casting dies in our country is still far from that in developed countries. The urgent task is to develop and improve the die indexes independently, instead of blindly copying foreign products.The temperature of die casting process is one of the most important indexes of die casting products, which has a vital effect on the quality of products and the life of dies.The main characteristic of die casting mold temperature is that the cooling process is slow and the energy consumption is large. If it is not effectively controlled, it will directly affect the quality of the product when it is not effectively controlled, which requires that the temperature should be kept within a certain range during the die casting process.The mold temperature has the characteristics of long delay, large inertia and nonlinear, and there is no accurate mathematical model. The traditional control method can not achieve the effect of accurate control.Based on this problem, a multi-channel mold temperature control system based on fuzzy neural network is designed in this paper.Because the die casting mould is composed of several die blocks, an independent circulating cooling water circuit is designed for each die. By adjusting the opening time of each circuit cooling water valve, the mold is cooled down and the temperature control is finally achieved.Fuzzy neural network (FNN) is a hot topic in the field of control in recent years. Both fuzzy control and neural network are based on modelless, nonlinear systems, in which fuzzy systems are good at expressing fuzzy, qualitative knowledge, lack of adaptive ability and self-learning.The neural network has good learning ability, but it can't use the rule-based knowledge to design a fuzzy neural network control system based on the advantages of both. Through MATLAB simulation, compared with the fuzzy control, the system response is faster and the accuracy is higher.It works better.
【學位授予單位】：沈陽理工大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TG241;TP273

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本文編號：1729813