CN211528986U

CN211528986U - Cloud computing system for advanced process control

Info

Publication number: CN211528986U
Application number: CN201922238685.4U
Authority: CN
Inventors: 谢东平; 陈德基
Original assignee: Shanghai Puao Data Technology Co ltd
Current assignee: Shanghai Puao Data Technology Co ltd
Priority date: 2019-12-13
Filing date: 2019-12-13
Publication date: 2020-09-18
Anticipated expiration: 2029-12-13

Abstract

The utility model provides a cloud computing system for advanced process control, which comprises a communication module, a virtual machine, a data identification and storage module and a predictive algorithm module; the virtual machine, the data identification and storage module and the predictive algorithm module are all arranged at the cloud end; the communication module is used for reading field data from the field sensor and transmitting data output after APC operation in the virtual machine to a field DCS; the virtual machine is used for setting the internal parameters of the APC algorithm to realize the input, calculation and output of data; the data identification and storage module is used for identifying whether the field data obtained by the communication module is timely and storing data which is temporarily not needed to participate in calculation, and inputting the timely data required by the APC operation into the APC for operation. The utility model discloses an APC setting is at the high in the clouds, and the user uses high in the clouds APC from the scene, and the help user has practiced thrift the cost of installing APC locally and has helped the customer to have solved the restriction that DCS system and APC bound.

Description

Cloud computing system for advanced process control

Technical Field

The utility model belongs to the technical field of industrial control, concretely relates to cloud computing system for advanced process control.

Background

With the continuous development of the automation degree of the process industry, people pay attention to the method, and the method is shifted from automatic production to optimized production; the advanced control algorithm saves raw materials, improves production conditions, reduces energy consumption, improves yield and the like. Such advanced control algorithms are called Advanced Process Control (APC) algorithms in the Process industry. Examples of APC algorithms are MPC, Fuzzy Logic, neuro-network, etc. An APC algorithm typically has one to more field input data and one to more field output data. The APC is part of the distributed Control systems dcs (distributed Control systems) and generally runs in the controller. Several APCs are typically supported by commercially available advanced DCS systems. Mature APC algorithms are found in many DCS; however, typically, APC is very expensive and users want to reduce the cost of DCS while still using APC.

A control algorithm in the DCS comprises the APC, a period is configured during operation, the control algorithm is operated once in each period, and each operation process is divided into a plurality of steps: and reading the input parameters, performing algorithm calculation, and outputting the calculation result to the output parameters.

Many DCS systems provide a tool called Tuning that helps set the internal parameters of the APC. The tuning process includes running the APC algorithm in the field for a period of time. During this time the APC internal parameters are set to different values, resulting in the reaction characteristics of the process under different internal parameters. Based on these response characteristics, we can find the best internal parameter settings.

On the other hand, as the industrial internet matures, the production site and the upper layers and even the internet are interconnected. It is also becoming increasingly possible to run APCs on servers that are far from the site, on the cloud. Unlike field loop control algorithms, APC typically does not require continuous low latency field data. The APC output data also does not necessarily need to be fed back quickly to the control site. And the APC is operated on the cloud, and APC data is transmitted through remote communication, so that the aim of production optimization can be achieved.

CN106575282A discloses a cloud computing system and method for advanced process control. The system comprises the APC control computer arranged at the local and the APC management computer arranged at the cloud, so that the local APC can be managed at the cloud. Then, the technical scheme disclosed by the application still needs to be provided with an APC control computer locally.

Different from locally running the APC, the APC cannot be directly set by the local DCS because it is not locally running. Meanwhile, running APC on the cloud still faces the problem of unstable network communication. When the network is not stable, the data transmitted from the site may not arrive at the APC in time, and even data loss may occur. However, APC requires strict time-dependent data calculation; meanwhile, the output parameters of the APC should also be transmitted to the control object in time. The network generally has a relatively slow uplink speed, so that uploaded data cannot arrive in time and are lost particularly obviously. In addition, when some field data arrives at the cloud, the APC does not need to be input immediately, but is input when the APC needs to be input (because the APC needs to operate on the data strictly according to time). Meanwhile, some APC output data needs to be fed back to the control site after a certain time interval. At this time, these input and output data need to be stored separately.

SUMMERY OF THE UTILITY MODEL

The to-be-solved technical problem of the utility model is to provide a cloud computing system for advanced process control to it needs to set up APC control computer, cloud on locally among the solution prior art and run APC and face the unstable arrival APC that causes data can not be timely, the part temporarily need not use data storage scheduling problem to the network communication.

In order to solve the above technical problem, an embodiment of the present invention provides a cloud computing system for advanced process control, which is characterized in that the cloud computing system comprises a communication module, a virtual machine, a data recognition and storage module, and a predictive algorithm module; the virtual machine, the data identification and storage module and the predictive algorithm module are all arranged at the cloud end;

the communication module is used for reading field data from the field sensor and transmitting data output after APC operation in the virtual machine to a field DCS;

the virtual machine automatically configures the same operating system according to the field DCS system, is provided with software required by APC operation, and is completely copied with an interface for data connection with APC; the virtual machine is used for setting the internal parameters of the APC algorithm to realize the input, calculation and output of data;

the data identification and storage module is used for identifying whether the field data obtained by the communication module is timely and storing data which is temporarily not required to participate in calculation, and inputting the timely data required by APC operation into APC for operation;

the predictive algorithm module is used for predicting the field data when the data identification and storage module detects that the network data is not transmitted timely or the data is lost, giving a predicted value of the field data, and inputting the predicted value of the field data into the APC (automatic Power control) for operation. The utility model discloses in, the virtual machine has realized providing a same execution environment with the system of field installation in the high in the clouds according to the same operating system of on-the-spot DCS system automatic configuration, and is preferred, and this execution environment is Microsoft window or Linux.

Further, communication module includes data interface, the communication line who reads data from the site sensor the utility model provides a communication module's the main effect of setting is through the site sensor reading site data, with the data transmission to the DCS on-the-spot of APC output.

Further, the data identification and storage module is used for periodically detecting whether the communication module has field data input and time information on a timestamp of the input data; if the time in the input data is consistent with the APC software setting, inputting the data uploaded from the site into the APC software for operation; if no field data is input in an operation period, the predictive algorithm module performs predictive calculation according to the previous input data by using the predictive model to obtain a predicted value of the field data, and inputs the predicted value into the APC to perform operation, thereby obtaining the output data of the APC.

Further, the data identification and storage module is configured to store data that is not temporarily required to participate in the calculation: when some data do not need to be operated by the APC immediately, if the time in the input data is earlier than the operation time set in the APC, the data can be stored in the data identification and storage module; when the predetermined time is reached, the stored data is input to the APC to be operated.

Furthermore, the cloud computing system further comprises a virtual firewall, wherein the virtual firewall is used for guaranteeing the safety of the cloud and is arranged in front of the virtual machine, the data recognition and storage module and the predictive algorithm module.

The utility model discloses an above-mentioned technical scheme's beneficial effect as follows:

the utility model discloses a set up APC in the high in the clouds, the user uses the high in the clouds APC from the scene, and the help user has practiced thrift the cost at local installation APC to can help the customer to remove the restriction that DCS system and APC bound (that is the DCS supplier of the on-the-spot actual use of user can be the supplier that is different from the APC of high in the clouds operation).

The utility model discloses a cloud computing system, including data identification and storage module, predictive algorithm module; the data identification and storage module identifies whether field data are provided in time, and when the field data in the operation period do not exist, the predictive algorithm module gives a field predicted value, so that the problem that data transmission is not in time when the APC is arranged at the cloud end is solved; meanwhile, the data identification and storage module can also be used for storing data which does not need to be subjected to APC operation immediately, and inputting APC to carry out operation when the operation is needed.

The utility model discloses in because APC sets up in the high in the clouds, can conveniently realize the quick update and the optimization of the algorithm in the APC.

Drawings

Fig. 1 is a block diagram of an example cloud computing system in communication with a number of users in accordance with an embodiment of the present invention.

Fig. 2 is a flowchart illustrating steps in a method for operating a cloud computing system for advanced process control according to the present invention.

Fig. 3 is a block diagram of the communication between the cloud computing system and the user in the embodiment of the present invention.

Description of reference numerals:

100. a cloud end; 101. a virtual machine; 102. a data identification and storage module; 103. a predictive algorithm module; 110. a communication module; 120. a first user; 121. a liquid level sensor; 122. a weighing sensor; 123. an infrared sensor; 124. a field DCS system; 125. a water valve; 126. a drug addition valve; 127. an alarm; 130. a second user; 140. a third user; 150. the internet.

Detailed Description

The disclosed embodiments are described with reference to the drawings, wherein like reference numerals are used to refer to similar or equivalent elements throughout the drawings. The drawings are not drawn to scale and they are provided merely to illustrate certain disclosed aspects. Several disclosed aspects are described below with reference to example applications for illustration. It should be understood that numerous specific details, relationships, and methods are set forth to provide a full understanding of the disclosed embodiments.

One of ordinary skill in the relevant art, however, will readily recognize that the subject matter disclosed herein can be practiced without one or more of the specific details or with other methods. In other instances, well-known structures or operations are not shown in detail to avoid obscuring certain aspects. The present disclosure is not limited by the illustrated ordering of acts or events, as some acts may occur in different orders and/or concurrently with other acts or events. Moreover, not all illustrated acts or events are required to implement a methodology in accordance with the embodiments disclosed herein.

In the description of the present invention, it is to be noted that, unless otherwise explicitly specified or limited, the terms "mounted", "connected" and "connected" are to be interpreted broadly, and may be, for example, fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meaning of the above terms in the present invention can be understood in specific cases to those skilled in the art.

The embodiment of the utility model provides a cloud computing system for advanced process control, including communication module 110, virtual machine 101, data identification and storage module 102, predictive algorithm module 103; the virtual machine 101, the data recognition and storage module 102 and the predictive algorithm module 103 are all arranged at the cloud 100; the communication module 110 is configured to read field data from a field sensor and transmit data output after APC in the virtual machine 101 is run to a DCS on site; the virtual machine 101 automatically configures the same operating system according to the field DCS system, is provided with software required by APC operation, and is completely copied with an interface for data connection with APC; the virtual machine 101 is used for setting the internal parameters of the APC algorithm to realize the input, calculation and output of data; the data identification and storage module 102 is used for identifying whether the field data obtained by the communication module 110 is timely and storing data which is temporarily not needed to participate in calculation, and inputting timely data required by APC operation into APC for operation; the predictive algorithm module 103 is configured to perform field data prediction when the data identification and storage module 102 detects that network data transmission is not in time or data packet is lost, give a field data prediction value, and input the field data prediction value into the APC for operation.

FIG. 1 illustrates a block diagram of an example cloud computing system with several users including user one 120, user two 130, and user three 140. Each user may be a separate company or entity that produces goods or services; every user's scene has the DCS system, and the DCS system on scene can contain Advanced Process Control (APC), according to or not containing Advanced Process Control (APC), the DCS supplier of user present site actual use can be different from the utility model discloses well high in the clouds operation's the supplier of APC. As shown in fig. 1, the cloud computing system includes a communication module 110, a virtual machine 101, a data recognition and storage module 102, a predictive algorithm module 103; the communication module 110 is connected with a user field DCS system and a field sensor through a data interface and a communication line, and the communication module 110 is used for data transmission with a cloud end through the Internet.

As shown in fig. 3, an embodiment of the present invention further provides an operation method of a cloud computing system for advanced process control, including the following processes:

(1) and a user installs and operates the DCS on site.

(2) Virtual machine 101 for building cloud, data identification and storage module 102 and predictive algorithm module

103; and connects the cloud with the data of the field through the communication module 110.

(3) According to the scene, the inner parameters of the APC are acquired.

(4) And (4) automatically configuring a corresponding operating system according to the field DCS by the cloud virtual machine 101, installing adaptive APC software, and configuring internal parameters according to the APC internal parameters obtained in the step (3).

(5) The data recognition and storage module 102 recognizes, stores and transmits data inputted by the communication module 110.

The process of processing the data input by the communication module by the data identification and storage module 102 specifically includes the following steps:

(5-1) identification procedure of the data identification and storage Module 102

(5-1-1) in the operating process of the APC software, the data recognition and storage module 102 periodically detects whether the communication module 110 has field data input and time information on a timestamp of the input data;

(5-1-2) if the time in the input data is consistent with the APC software setting, inputting the data uploaded from the site into the APC software for operation;

(5-1-3) if no field data is input in an operation period, the predictive algorithm module 103 performs predictive calculation according to the previous input data by using a predictive model to obtain a predicted value of the field data, and inputs the predicted value into the APC for operation, thereby obtaining output data of the APC; in the present invention, the predictive algorithm in the predictive algorithm module 103 may adopt the existing conventional algorithm, such as continuously using the latest field data, using the preset value, or adding the mathematical formula according to a plurality of pre-sequence values for estimation. Predictive algorithms may also be written according to the specific application scenario.

(5-2) storage procedure of the data recognition and storage Module 102

(5-2-1) when some data do not need to be immediately operated by the APC, if the time in the inputted data is earlier than the operation time set in the APC, the data is stored in the data recognition and storage module 102;

(5-2-2) when the predetermined time is reached, inputting the stored data to the APC to perform an operation.

(6) And running the APC algorithm at the cloud end, and returning the operation result to the DCS of the user field to realize the advanced process control on the cloud.

Fig. 3 illustrates the use of the cloud computing system for advanced process control in user one 120. In the present embodiment, the first user 120 is a water treatment enterprise having on-site sensors such as a level sensor 121 for detecting an amount of sewage, a load cell 122 for measuring a weight of an additive for water treatment, and an infrared sensor 123 for monitoring whether a person approaches a sewage treatment tank, and the like, the water treatment enterprise is equipped with a DCS system 124, and the water treatment enterprise is equipped with a water valve 125, a drug addition valve 126, and an alarm 127 connected to the DCS system 124. In the use the utility model discloses a during cloud computing system, the virtual machine 101, data identification and storage module 102, predictive algorithm module 103 of user one are found at present high in the clouds, with the level sensor 121, the weighing sensor 122, the monitoring that a user's scene possessed the detection sewage volume whether someone is close to site sensors such as infrared sensor 123 in sewage treatment pond, on-the-spot DCS system 124 and communication module 110 are connected, communication module 110 is connected with high in the clouds 100 through internet 150. Setting (acquiring APC internal parameters) according to the situation of a field, automatically configuring a corresponding operating system in a virtual machine 101 of a user I constructed by the cloud 100 according to a field DCS (distributed control system) 124, installing adaptive APC software, and configuring the APC internal parameters; the cloud APC is operated, the data identification and storage module 102 identifies the data input by the communication module 110, and if the time in the input data is consistent with the APC software setting, the data uploaded from the field is input into the APC software for operation; if no field data is input in one operation period; the predictive algorithm module 103 obtains a predicted value according to the data input in the previous stage, inputs the predicted value into the APC for operation, the APC outputs the result after operation to the DCS system 124 of the user on site through the communication module, and the DCS system 124 controls the water valve 125, the drug adding valve 126 and the alarm 127 on site according to the received result data.

The foregoing is a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, a plurality of improvements and decorations can be made without departing from the principle of the present invention, and these improvements and decorations should also be regarded as the protection scope of the present invention.

Claims

1. A cloud computing system for advanced process control comprises a communication module, a virtual machine, a data identification and storage module and a predictive algorithm module; the virtual machine, the data identification and storage module and the predictive algorithm module are all arranged at the cloud end;

the predictive algorithm module is used for predicting the field data when the data identification and storage module detects that the network data is not transmitted timely or the data is lost, giving a predicted value of the field data, and inputting the predicted value of the field data into the APC (automatic Power control) for operation.

2. The cloud computing system of claim 1, wherein said communication module comprises a data interface to read data from field sensors, a communication line.

3. The cloud computing system for apc of claim 1, wherein the data recognition and storage module is configured to periodically detect whether the communication module has field data input and time information on a timestamp of the input data; if the time in the input data is consistent with the APC software setting, inputting the data uploaded from the site into the APC software for operation; if no field data is input in an operation period, the predictive algorithm module performs predictive calculation according to the previous input data by using the predictive model to obtain a predicted value of the field data, and inputs the predicted value into the APC to perform operation, thereby obtaining the output data of the APC.

4. The cloud computing system for apc of claim 1, wherein said data recognition and storage module is configured to store data that is not temporarily needed to participate in computing: when some data do not need to be operated by the APC immediately, if the time in the input data is earlier than the operation time set in the APC, the data can be stored in the data identification and storage module; when the predetermined time is reached, the stored data is input to the APC to be operated.

5. The cloud computing system of claim 1, further comprising a virtual firewall configured to secure the cloud, the virtual firewall being pre-configured with a virtual machine, a data recognition and storage module, and a predictive algorithm module.