Soft measurement method of quality index data in rubber mixing process of internal mixer
A quality index, rubber mixing technology, applied in the direction of electrical program control, comprehensive factory control, comprehensive factory control, etc., can solve the lack of soft measurement modeling method of mixing process, high computational complexity, and inability to effectively track rubber online Problems such as the time-varying characteristics of the mixing process
A quality index, rubber mixing technology, applied in the direction of electrical program control, comprehensive factory control, comprehensive factory control, etc., can solve the lack of soft measurement modeling method of mixing process, high computational complexity, and inability to effectively track rubber online Problems such as the time-varying characteristics of the mixing process
CN101893884AInactive Publication Date: 2010-11-24ZHEJIANG UNIV
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[0078] The present invention will be described in detail below in conjunction with the embodiments and accompanying drawings, but the present invention is not limited thereto.
[0079] There are a lot of production process data in the rubber mixing process, including mixing time, temperature, energy consumption, pressure, rubber hardness, mixing process, formula, etc. Reasonable and effective selection of these features to form the input sample feature space is of great significance for modeling. On the one hand, introducing too many features will increase the collection of industrial production data, increase the calculation intensity and make the model more complex, and when some features can be linearly represented by other features, this calculation is redundant; on the other hand On the one hand, when some important features are not selected, it will lead to inaccurate model establishment. In response to the above problems, when performing feature selection, we use the Ke...
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The invention discloses a soft measurement method of quality index data in the rubber mixing process of an internal mixer. The method is characterized by establishing a mixing process off-line model based on the historical data of the rubber mixing process, then acquiring the production data and the quality index data of the current mixing process as the current samples and projecting the current samples to high dimensional feature space, computing the linear relationship between the samples in the high dimensional feature space by the Kernel function, correcting the parameters and the samples of the model according to the linear similarity of the samples, eliminating the data samples with least contribution when the sample number in the model exceeds the set value, updating the mixing processing model on line and outputting the predicated value of the quality index of the mixed rubber in real time when the current production data are input, thus realizing soft measurement in the rubber mixing process. The method realizes effective online tracking of the rubber mixing process, is low in computation complexity, good in stability and accurate and reliable in measurement and has quite important practical value in pre-detection and system optimization control in the rubber mixing production process.
Description
technical field [0001] The invention belongs to the field of industrial control, relates to detection and automatic control technology in the field of rubber manufacturing, and in particular to an online real-time soft measurement method for quality index data in the rubber mixing process of an internal mixer. Background technique [0002] Rubber mixing is the first main process of rubber processing, which has a great influence on the processing performance of subsequent processes and the quality of finished products. Therefore, the control of the mixing process plays an important role in improving the overall quality of rubber products. The rubber mixing process is a typical fast batch process, which is generally carried out in a transitional state without a stable working point. Its dynamic and nonlinear characteristics are more significant than those of a continuous process. Many important variables are usually unable to be measured online, and there is no accurate Mechan...
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Patent Timeline
24 Nov 2010
Publication
CN101893884A
- IPC
- G05B19/418; G01N33/44
- CPC
- Y02P90/02
- Inventors
- 纪俊; 朱可辉