We reported a compact, stable 12-picosecond Innoslab amplifier. A mode-locked seed laser with an initial power of 4.5W was amplified using a discrete beam path (DBP) configuration. The 1064nm Nd:YAG slab amplifier showed the high average output power of 165W at 1MHz of pulse repetition rate. The amplifier exhibited 16.6% of optical conversion efficiency. The long-term power stability of the laser system was calculated for one hour and the fluctuation was found to be 0.27%.
In this paper we proposed a method of monitoring industrial robot reducer online cloud platform. Based on the theory of cyber physical model, a cloud state monitoring system is designed due to the problems of complex objects, massive failure information, high stable demand and poor real-time control ability in the modern industrial robot maintain. It includes intelligent sensor and edge computing to network cloud technology. With data model, the system uses deep learning and over-limit learning algorithm on the cloud management center server. The deep learning method trains and predicts the collected fault data, and can predict the malfunction of vector reducer. Further, the intelligent optimization scheduling algorithm is used in the cloud to obtain real-time fault in industrial robot reducer. The problem of distribution and the dynamic running performance of cloud system is monitored and improved.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.