View source for Boe technology group co., ltd. (20240185115). METHOD AND APPARATUS FOR EARLY WARNING OF DRY PUMP SHUTDOWN, ELECTRONIC DEVICE, STORAGE MEDIUM AND PROGRAM simplified abstract

=METHOD AND APPARATUS FOR EARLY WARNING OF DRY PUMP SHUTDOWN, ELECTRONIC DEVICE, STORAGE MEDIUM AND PROGRAM=


==Organization Name==

[[:Category:boe technology group co., ltd.|boe technology group co., ltd.]]


[[Category:boe technology group co., ltd.]]

==Inventor(s)==

[[:Category:Qing Zhang of Beijing (CN)|Qing Zhang of Beijing (CN)]][[Category:Qing Zhang of Beijing (CN)]]

[[:Category:Quanguo Zhou of Beijing (CN)|Quanguo Zhou of Beijing (CN)]][[Category:Quanguo Zhou of Beijing (CN)]]

[[:Category:Lijia Zhou of Beijing (CN)|Lijia Zhou of Beijing (CN)]][[Category:Lijia Zhou of Beijing (CN)]]

[[:Category:Jiuyang Cheng of Beijing (CN)|Jiuyang Cheng of Beijing (CN)]][[Category:Jiuyang Cheng of Beijing (CN)]]

[[:Category:Zhidong Wang of Beijing (CN)|Zhidong Wang of Beijing (CN)]][[Category:Zhidong Wang of Beijing (CN)]]

[[:Category:Ruwang Guo of Beijing (CN)|Ruwang Guo of Beijing (CN)]][[Category:Ruwang Guo of Beijing (CN)]]

[[:Category:Lirong Xu of Beijing (CN)|Lirong Xu of Beijing (CN)]][[Category:Lirong Xu of Beijing (CN)]]

[[:Category:Junrui Zhang of Beijing (CN)|Junrui Zhang of Beijing (CN)]][[Category:Junrui Zhang of Beijing (CN)]]

[[:Category:Xuehui Zhu of Beijing (CN)|Xuehui Zhu of Beijing (CN)]][[Category:Xuehui Zhu of Beijing (CN)]]

[[:Category:Meng Guo of Beijing (CN)|Meng Guo of Beijing (CN)]][[Category:Meng Guo of Beijing (CN)]]

==METHOD AND APPARATUS FOR EARLY WARNING OF DRY PUMP SHUTDOWN, ELECTRONIC DEVICE, STORAGE MEDIUM AND PROGRAM - A simplified explanation of the abstract==


This abstract first appeared for US patent application 20240185115 titled 'METHOD AND APPARATUS FOR EARLY WARNING OF DRY PUMP SHUTDOWN, ELECTRONIC DEVICE, STORAGE MEDIUM AND PROGRAM

==Simplified Explanation==

The disclosure provides a method and apparatus for early warning of dry pump shutdown, an electronic device, a storage medium and a program, and belongs to the technical field of automatic control. The method comprises: obtaining historical operating data of a dry pump; building a Kalman filter model by using the historical operating data; predicting predicted operating data of the dry pump through the Kalman filter model; training a shutdown prediction model by using the historical operating data and the predicted operating data; and inputting current operating data of the dry pump into the trained shutdown prediction model to obtain shutdown early warning information of the dry pump.

* Obtaining historical operating data of a dry pump
* Building a Kalman filter model using the historical operating data
* Predicting future operating data of the dry pump through the Kalman filter model
* Training a shutdown prediction model using historical and predicted data
* Inputting current operating data into the trained model for early warning of shutdown

== Potential Applications ==
The technology can be applied in industrial settings where dry pumps are used, such as semiconductor manufacturing, chemical processing, and vacuum systems.

== Problems Solved ==
This technology addresses the issue of unexpected dry pump shutdowns, which can lead to production delays, equipment damage, and increased maintenance costs.

== Benefits ==
The early warning system allows for proactive maintenance and troubleshooting of dry pumps, reducing downtime and improving overall efficiency in industrial operations.

== Potential Commercial Applications ==
Potential commercial applications include selling the early warning system as a standalone product or integrating it into existing dry pump systems for enhanced monitoring and control.

== Possible Prior Art ==
Prior art may include similar predictive maintenance systems for industrial equipment, but the specific application to dry pump shutdown prediction may be novel.

=== Unanswered Questions ===

=== How does the Kalman filter model improve the accuracy of shutdown predictions compared to other methods? ===
The Kalman filter model is known for its ability to estimate the state of a system based on noisy measurements, but it is not clear how this specifically benefits the early warning system for dry pump shutdowns.

=== What are the limitations of the shutdown prediction model in terms of accuracy and reliability? ===
While the technology provides early warning information, it is important to understand the potential limitations of the shutdown prediction model in real-world scenarios, such as varying operating conditions and system complexities.


==Original Abstract Submitted==

the disclosure provides a method and apparatus for early warning of dry pump shutdown, an electronic device, a storage medium and a program, and belongs to the technical field of automatic control. the method comprises: obtaining historical operating data of a dry pump; building a kalman filter model by using the historical operating data; predicting predicted operating data of the dry pump through the kalman filter model; training a shutdown prediction model by using the historical operating data and the predicted operating data; and inputting current operating data of the dry pump into the trained shutdown prediction model to obtain shutdown early warning information of the dry pump.



[[Category:G06N20/00]]
[[Category:G06N5/022]]