Abstract
Flexible photoelectric film is an anisotropic material. The slight change of equipment performance during processing is prone to cause deformation of the material. Therefore, it is important to predict the degradation of processing equipment performance. Since the performance degradation of flexible photoelectric film material Roll-to-Roll (R2R) processing equipment is a nonlinear process, this paper introduces an adaptive fuzzy clustering method to construct a fuzzy membership function model for calculating the performance degradation index of R2R processing equipment and studies the parameter solving method such as the AFCM division of the roller vibration data, the category center value of the fuzzy membership function, and the input data division area width. Finally, the performance degradation index calculation algorithm is designed. The roller shaft accelerated life test was carried out using self-made equipment. The test data were 1000 sets. The results showed that the root mean square eigenvalues and the kurtosis eigenvalues of the roller vibration data are sensitive to the performance degradation. The equipment performance curve described by the first and second types of performance degradation indicators was very stable in the early stage. After the 800th group, the curve continued to decrease, and the change was more severe, indicating that the performance degradation of the equipment is more serious. In the 980th group, the longer-lasting roller shaft was damaged, and the performance index value was about zero, which proved the correctness of the performance degradation prediction method proposed in this paper in calculating the performance degradation value of the equipment.
Highlights
In recent years, breakthroughs have been made in the research of wearable sensors, OLEDs, and film solar cells using flexible photoelectric films as substrate materials, and the demand for industrialization and large-scale production has been put on the agenda
Since the performance degradation of flexible photoelectric film material Roll-to-Roll (R2R) processing equipment is a nonlinear process, this paper introduces an adaptive fuzzy clustering method to construct a fuzzy membership function model for calculating the performance degradation index of R2R processing equipment and studies the parameter solving method such as the Adaptive Fuzzy Clustering Method (AFCM) division of the roller vibration data, the category center value of the fuzzy membership function, and the input data division area width
The results showed that the root mean square eigenvalues and the kurtosis eigenvalues of the roller vibration data are sensitive to the performance degradation
Summary
Breakthroughs have been made in the research of wearable sensors, OLEDs, and film solar cells using flexible photoelectric films as substrate materials, and the demand for industrialization and large-scale production has been put on the agenda. The AFCM is used to fuzzy divide the data of the normal operation state of the equipment, and the fuzzy prototypes of various characteristic parameters of the roller shaft vibration data are obtained. The clustering center vi of the characteristic parameters and the partitioning area width σj are solved, and the membership function of the device performance degradation is derived. The adaptive fuzzy clustering method (AFCM) and the Mahalanobis distance are combined, and the Mahalanobis distance is used to represent the measurement of the distance of the roller vibration data of the processing equipment. The fuzzy partition matrix and the category center of characteristic parameter xt can be obtained by solving the minimum value of the objective function (formula (1)) of the c fuzzy partitions of the various parameters of the roller vibration data [7, 8]. When the value of the membership function is close to 0, it indicates that the performance of the roller shaft is seriously degraded
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