Page 58 - 《橡塑技术与装备》英文版2026年1月

HINA R&P TECHNOLOGY AND EQUIPMENT

1.3.2 Mathematical model
Utilizing the timing trigger function of the network
server, not only is the timing collection of data achieved,
but also real-time analysis of data can be conducted. The
true value of equipment informatization lies in data-driven
services and decision-making. The way to achieve services
and decision-making is to establish mathematical models
based on data. After the informatization upgrade of the current
extrusion laboratory experimental equipment, various targeted
Figure 2 On-site real-time monitoring system mathematical models have been developed based on data

such as current and temperature during equipment operation,
1.3 Data management including system operation energy consumption analysis,
1.3.1 Data storage
Second-level data storage can be achieved through the heating and cooling system fault analysis, host machine fault
warning analysis, feeding system adjustment warning, and
on-site network. Relying on this data, edge computing can
pelletizer anti-blocking rotation analysis.
be utilized to achieve rapid fault analysis and early warning
response. Considering the operation and maintenance costs 1.4 Application and management
of data storage, data storage servers will not be established in 1.4.1 On/off guidance system
From the perspective of the characteristics of laboratory
the laboratory. Therefore, the amount of data stored through
the on-site network will only be based on the data required for operating personnel, the majority of those operating
experimental equipment are students. Although students have
short-cycle data analysis mathematical models.
acquired certain professional theoretical knowledge before
Through the external network, not only is the equipment
operation data connected to the IoT cloud platform, but it is entering the laboratory, there is still a significant deficiency in
their proficiency in equipment operation. In order to enhance
also stored in the cloud server database. These data will not
students' active participation in the experimental process
only be used for analysis models with longer cycles but also
and ensure the safe and reliable operation of equipment, a
serve as the basis for tracing the operation management process
of laboratory equipment. Considering factors such as data startup and shutdown guidance system for the extrusion unit
has been developed based on the digital twin system of the
synchronization lag and data transmission stability limitations,
extrusion unit that we have developed. During the operation
the interval between data being connected to the IoT cloud
platform and stored in the cloud server database is calculated of this system, the prompts for startup and shutdown steps
are provided based on the real-time status of the equipment.
as 20 seconds.
During the startup process, the system divides the startup
Although connecting data to the IoT cloud platform and
storing it in the cloud server database incurs certain operational process into 10 steps. If any previous step is not executed
properly, the system will not provide prompts for the
costs, this approach avoids the expenses and maintenance
subsequent steps. For example, if the real-time temperature
costs associated with setting up servers in the laboratory. In
fact, this model is of great help to small and medium-sized of the barrel is lower than the set temperature, the system
will not proceed to the heat preservation stage; if the heat
enterprises in achieving equipment information management.
preservation time is shorter than the specified time, the system
The related technology upgrade costs can be concentrated
will disable the host machine startup function. In this way,
on the information upgrade of in-house equipment, greatly
avoiding the need to set up private servers. At the same time, after conducting necessary safety checks on the unit according
to the startup system prompts, operators can follow the on-
adopting cloud services can also greatly reduce the labor and
screen prompts to perform the startup steps in order. During
maintenance costs at the data level.
the shutdown process, following the system prompts and based

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