CN113903099B - Equipment monitoring method and system based on scada - Google Patents
Equipment monitoring method and system based on scada Download PDFInfo
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- CN113903099B CN113903099B CN202111003387.2A CN202111003387A CN113903099B CN 113903099 B CN113903099 B CN 113903099B CN 202111003387 A CN202111003387 A CN 202111003387A CN 113903099 B CN113903099 B CN 113903099B
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- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C3/00—Registering or indicating the condition or the working of machines or other apparatus, other than vehicles
- G07C3/005—Registering or indicating the condition or the working of machines or other apparatus, other than vehicles during manufacturing process
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- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C3/00—Registering or indicating the condition or the working of machines or other apparatus, other than vehicles
- G07C3/08—Registering or indicating the production of the machine either with or without registering working or idle time
Abstract
The invention relates to the technical field of electric power monitoring, and discloses a scada-based equipment monitoring method and system, wherein the method comprises the following steps: s1: acquiring actual workload information of current equipment within a preset time period; s2: analyzing the relation coordinates of the actual workload of the current equipment and the expected workload in a preset time period according to a preset judging flow; s3: predicting whether the current equipment reaches the expected yield in a preset time period according to the relation coordinates; and analyzing and recording a preset time period when the equipment is abnormal according to the relation coordinates. The method can monitor and record the running condition of the equipment in the whole shift in real time. Whether the target workload can be completed according to the current production progress can be timely predicted. The reason for the slow production can be analyzed on the basis of the recorded information whether a short shut down or a malfunction of the equipment is caused.
Description
Technical Field
The invention relates to the technical field of power monitoring, in particular to a scada-based equipment monitoring method and system.
Background
SCADA (Supervisory Control And Data Acquisition), a data acquisition and monitoring control system. SCADA is a computer-based DCS and power automation monitoring system; the method has wide application fields, and can be applied to various fields such as data acquisition and monitoring control, process control and the like in the fields of electric power, metallurgy, petroleum, chemical industry, fuel gas, railways and the like.
In the power system, SCADA is most widely applied and the technical development is most mature. The remote control system plays an important role in a remote control system, and can monitor and control on-site operation equipment to realize various functions such as data acquisition, equipment control, measurement, parameter adjustment, various signal alarms and the like, namely a four-remote function. RTU (remote terminal unit), FTU (feeder terminal unit) is an important component thereof.
In the equipment management of a factory, the current work task of the equipment on the same day can be known only after the production is finished, or the work task is not achieved, and the completion result of the work task of the equipment cannot be predicted in the equipment production process. And the failure to accurately locate which time period caused the abnormality leads to the failure of the work plan of the equipment, and the objective statistics and prediction of the throughput of the field equipment are not possible.
Disclosure of Invention
Aiming at the current state of the art, the technical problem to be solved by the invention is to provide a scada-based equipment monitoring method and system, which are used for monitoring and recording the running condition of equipment in the whole shift in real time. Whether the target workload can be completed according to the current production progress can be timely predicted. The reason for the slow production can be analyzed on the basis of the recorded information whether a short shut down or a malfunction of the equipment is caused.
The invention discloses a device monitoring method and a system based on scada, which concretely comprise the following technical scheme:
a scada-based device monitoring method comprising the steps of:
s1: acquiring actual workload information of current equipment within a preset time period;
s2: analyzing the relation coordinates of the actual workload of the current equipment and the expected workload in a preset time period according to a preset judging flow;
s3: predicting whether the current equipment reaches the expected yield in a preset time period according to the relation coordinates; and analyzing and recording a preset time period when the equipment is abnormal according to the relation coordinates.
Further, the preset time period includes a shift time period and a shutdown time period.
Further, the step S1 includes:
s11: and acquiring the actual workload information of the current equipment in the shift time period.
Further, the step S2 includes:
s21: comparing the actual workload of the current device within the shift time period with the expected workload;
when the actual workload is greater than or equal to the expected workload, judging that the current equipment is in a normal production state;
when the actual workload is smaller than the expected workload, judging that the current equipment is in an abnormal production state;
s22: acquiring actual working time used for producing actual workload in an abnormal production state, and comparing the actual working time with expected working time;
when the actual working hour time is less than or equal to the expected working hour time, judging that the current equipment is in a short-time shutdown state;
when the actual working time is longer than the expected working time, judging that the current equipment is in a fault state;
s23: uploading the corresponding shift time period information when the current equipment is in the fault state to a background server, and generating relation coordinates of the actual workload of the current equipment and the expected workload in the preset time period according to the shift time period, the actual workload and the expected workload.
Further, the step S3 includes:
s31: predicting whether the current equipment reaches the expected yield within a preset time period according to the relation coordinates in the step S23;
s32: if yes, marking the current equipment as normal production equipment;
s33: if not, marking the current equipment as abnormal production equipment, stopping the equipment, judging the equipment according to the step S22, and if the equipment is judged to be in a short-time stopping state, starting the equipment to continue to operate; if the fault state is judged, the shutdown state is maintained and maintenance is carried out.
Further, the expected yield is expressed as:
wherein L represents the expected yield, X t Representing the shift time period, K, of the current equipment operation t A shift time period representing the start of the current device, S t Representing a downtime period, T representing an expected man-hour time.
A scada-based device monitoring system comprising:
the acquisition module is used for: the method comprises the steps of acquiring actual workload information of current equipment in a preset time period;
and an analysis module: analyzing the relation coordinates of the actual workload of the current equipment and the expected workload in a preset time period according to a preset judging flow;
and a prediction module: predicting whether the current equipment reaches the expected yield in a preset time period according to the relation coordinates; analyzing and recording a preset time period when the equipment is abnormal according to the relation coordinates;
the preset time period includes a shift time period and a downtime period.
Further, the acquisition module includes:
a workload information acquisition unit: for obtaining actual workload information of the current device during the shift time period.
Further, the analysis module includes:
a first comparison unit: for comparing the actual workload of the current device during the shift time period with the expected workload;
when the actual workload is greater than or equal to the expected workload, judging that the current equipment is in a normal production state;
when the actual workload is smaller than the expected workload, judging that the current equipment is in an abnormal production state;
a second comparing unit: the method comprises the steps of obtaining actual working hour time used for producing actual workload under abnormal production conditions, and comparing the actual working hour time with expected working hour time;
when the actual working hour time is less than or equal to the expected working hour time, judging that the current equipment is in a short-time shutdown state;
when the actual working time is longer than the expected working time, judging that the current equipment is in a fault state;
a relation coordinate generating unit: uploading the corresponding shift time period information when the current equipment is in the fault state to a background server, and generating relation coordinates of the actual workload of the current equipment and the expected workload in the preset time period according to the shift time period, the actual workload and the expected workload.
Further, the prediction module includes:
prediction unit: predicting whether the current equipment reaches the expected yield within a preset time period according to the relation coordinates in the relation coordinate generating unit;
a first marking unit: if yes, marking the current equipment as normal production equipment;
a second marking unit: if not, marking the current equipment as abnormal production equipment, stopping the equipment to judge the equipment according to the second comparison unit, and if judging to be in a short-time stopping state, starting the equipment to continue to operate; if the fault state is judged, the shutdown state is maintained and maintenance is carried out.
The technical scheme adopted by the invention at least comprises the following beneficial effects:
the method can monitor the production efficiency of the equipment in the current shift or the historical shift, display the current production progress, predict whether the equipment can complete the task on time, record the current working state type and the actual workload of the equipment according to the preset time period, and monitor the running condition of the equipment in the whole shift in real time. It is predicted in the process whether the target workload can be achieved according to the current operation condition. And the reasons for slow production and abnormal shutdown of the equipment can be analyzed according to the recorded working state type and the actual workload.
Drawings
FIG. 1 is a flowchart of a method for monitoring a scada-based device according to a first embodiment of the present invention;
FIG. 2 is a flowchart of a second method for monitoring a scada-based device according to a first embodiment of the present invention;
fig. 3 is a first block diagram of a scada-based device monitoring system according to a second embodiment of the present invention;
fig. 4 is a second block diagram of a device monitoring system based on scada according to a second embodiment of the present invention.
Detailed Description
The following are specific embodiments of the present invention and the technical solutions of the present invention will be further described with reference to the accompanying drawings, but the present invention is not limited to these embodiments.
Example 1
The embodiment provides a device monitoring method based on scada, as shown in fig. 1 and fig. 2, the method includes the steps of:
s1: acquiring actual workload information of current equipment within a preset time period;
s2: analyzing the relation coordinates of the actual workload of the current equipment and the expected workload in a preset time period according to a preset judging flow;
s3: predicting whether the current equipment reaches the expected yield in a preset time period according to the relation coordinates; and analyzing and recording a preset time period when the equipment is abnormal according to the relation coordinates.
Specifically, the shift time period may be defined according to a processing time period of each normal equipment, for example, 8:00 to 17:00. Planned downtime: the plant shut down rest period may be defined as 12:00 to 13:00. Expected man-hour time: the time taken to process a product, for example, 120 seconds, means that it takes 120 seconds or less to process a product to produce normally.
Processing time exceeding 20% is abnormal shutdown: if the processing of a product takes more than 144 (120+120×20%) seconds as abnormal shutdown based on the expected working hours, the production is slow from more than 120 seconds to less than or equal to 144 seconds.
Expected yield: the calculation formula is equal to (shift period of operation of the former equipment-shift period of start of the current equipment-downtime period)/expected man-hour time. For example, the current time is 10:00, the expected yield is equal to (10:00-8:00)/120=60
Actual yield: the actual production quantity obtained from the device counter is collected once at a device collection frequency of 60 seconds.
Wherein the preset time period comprises a shift time period and a shutdown time period.
Wherein, step S1 includes: s11: and acquiring the actual workload information of the current equipment in the shift time period.
Wherein, step S2 includes:
s21: comparing the actual workload of the current device within the shift time period with the expected workload;
when the actual workload is greater than or equal to the expected workload, judging that the current equipment is in a normal production state;
when the actual workload is smaller than the expected workload, judging that the current equipment is in an abnormal production state;
s22: acquiring actual working time used for producing actual workload in an abnormal production state, and comparing the actual working time with expected working time;
when the actual working hour time is less than or equal to the expected working hour time, judging that the current equipment is in a short-time shutdown state;
when the actual working time is longer than the expected working time, judging that the current equipment is in a fault state;
s23: uploading the corresponding shift time period information when the current equipment is in the fault state to a background server, and generating relation coordinates of the actual workload of the current equipment and the expected workload in the preset time period according to the shift time period, the actual workload and the expected workload.
Wherein, step S3 includes:
s31: predicting whether the current equipment reaches the expected yield within a preset time period according to the relation coordinates in the step S23;
s32: if yes, marking the current equipment as normal production equipment;
s33: if not, marking the current equipment as abnormal production equipment, stopping the equipment, judging the equipment according to the step S22, and if the equipment is judged to be in a short-time stopping state, starting the equipment to continue to operate; if the fault state is judged, the shutdown state is maintained and maintenance is carried out.
Wherein the expected yield is expressed as:
wherein L represents the expected yield, X t Representing the shift time period, K, of the current equipment operation t A shift time period representing the start of the current device, S t Representing a downtime period, T representing an expected man-hour time.
The method can monitor the production efficiency of the equipment in the current shift or the historical shift, display the current production progress, predict whether the equipment can complete the task on time, record the current working state type and the actual workload of the equipment according to the preset time period, and monitor the running condition of the equipment in the whole shift in real time. It is predicted in the process whether the target workload can be achieved according to the current operation condition. And the reasons for slow production and abnormal shutdown of the equipment can be analyzed according to the recorded working state type and the actual workload.
Example two
The embodiment provides a device monitoring system based on scada, as shown in fig. 3 and fig. 4, the system includes:
the acquisition module is used for: the method comprises the steps of acquiring actual workload information of current equipment in a preset time period;
and an analysis module: analyzing the relation coordinates of the actual workload of the current equipment and the expected workload in a preset time period according to a preset judging flow;
and a prediction module: predicting whether the current equipment reaches the expected yield in a preset time period according to the relation coordinates; analyzing and recording a preset time period when the equipment is abnormal according to the relation coordinates;
the preset time period includes a shift time period and a downtime period.
Wherein, the acquisition module includes:
a workload information acquisition unit: for obtaining actual workload information of the current device during the shift time period.
Wherein the analysis module comprises:
a first comparison unit: for comparing the actual workload of the current device during the shift time period with the expected workload;
when the actual workload is greater than or equal to the expected workload, judging that the current equipment is in a normal production state;
when the actual workload is smaller than the expected workload, judging that the current equipment is in an abnormal production state;
a second comparing unit: the method comprises the steps of obtaining actual working hour time used for producing actual workload under abnormal production conditions, and comparing the actual working hour time with expected working hour time;
when the actual working hour time is less than or equal to the expected working hour time, judging that the current equipment is in a short-time shutdown state;
when the actual working time is longer than the expected working time, judging that the current equipment is in a fault state;
a relation coordinate generating unit: uploading the corresponding shift time period information when the current equipment is in the fault state to a background server, and generating relation coordinates of the actual workload of the current equipment and the expected workload in the preset time period according to the shift time period, the actual workload and the expected workload.
Wherein the prediction module comprises:
prediction unit: predicting whether the current equipment reaches the expected yield within a preset time period according to the relation coordinates in the relation coordinate generating unit;
a first marking unit: if yes, marking the current equipment as normal production equipment;
a second marking unit: if not, marking the current equipment as abnormal production equipment, stopping the equipment to judge the equipment according to the second comparison unit, and if judging to be in a short-time stopping state, starting the equipment to continue to operate; if the fault state is judged, the shutdown state is maintained and maintenance is carried out.
The system can monitor the production efficiency of the equipment in the current shift or the historical shift, display the current production progress, predict whether the equipment can complete tasks on time, record the current working state type and the actual workload of the equipment according to the preset time period, and monitor the running condition of the equipment in the whole shift in real time. It is predicted in the process whether the target workload can be achieved according to the current operation condition. And the reasons for slow production and abnormal shutdown of the equipment can be analyzed according to the recorded working state type and the actual workload.
The specific embodiments described herein are offered by way of example only to illustrate the spirit of the invention. Those skilled in the art may make various modifications or additions to the described embodiments or substitutions thereof without departing from the spirit of the invention or exceeding the scope of the invention as defined in the accompanying claims.
Claims (2)
1. A scada-based device monitoring method, comprising the steps of:
s1: acquiring actual workload information of current equipment within a preset time period;
s2: analyzing the relation coordinates of the actual workload of the current equipment and the expected workload in a preset time period according to a preset judging flow;
s3: predicting whether the current equipment reaches the expected yield in a preset time period according to the relation coordinates; analyzing and recording a preset time period when the equipment is abnormal according to the relation coordinates;
the preset time period comprises a shift time period and a shutdown time period;
the step S1 includes:
s11: acquiring actual workload information of current equipment in a shift time period;
the step S2 includes:
s21: comparing the actual workload of the current device within the shift time period with the expected workload;
when the actual workload is greater than or equal to the expected workload, judging that the current equipment is in a normal production state;
when the actual workload is smaller than the expected workload, judging that the current equipment is in an abnormal production state;
s22: acquiring actual working time used for producing actual workload in an abnormal production state, and comparing the actual working time with expected working time;
when the actual working hour time is less than or equal to the expected working hour time, judging that the current equipment is in a short-time shutdown state;
when the actual working time is longer than the expected working time, judging that the current equipment is in a fault state;
s23: uploading the corresponding shift time period information when the current equipment is in a fault state to a background server, and generating a relation coordinate of the actual workload of the current equipment and the expected workload in a preset time period according to the shift time period, the actual workload and the expected workload;
the step S3 includes:
s31: predicting whether the current equipment reaches the expected yield within a preset time period according to the relation coordinates in the step S23;
s32: if yes, marking the current equipment as normal production equipment;
s33: if not, marking the current equipment as abnormal production equipment, stopping the equipment, judging the equipment according to the step S22, and if the equipment is judged to be in a short-time stopping state, starting the equipment to continue to operate; if the fault state is judged, maintaining the shutdown state and maintaining;
the expected yield is expressed as:
wherein L represents the expected yield, X t Representing the shift time period, K, of the current equipment operation t A shift time period representing the start of the current device, S t Representing a downtime period, T representing an expected man-hour time.
2. A scada-based device monitoring system, comprising:
the acquisition module is used for: the method comprises the steps of acquiring actual workload information of current equipment in a preset time period;
and an analysis module: analyzing the relation coordinates of the actual workload of the current equipment and the expected workload in a preset time period according to a preset judging flow;
and a prediction module: predicting whether the current equipment reaches the expected yield in a preset time period according to the relation coordinates; analyzing and recording a preset time period when the equipment is abnormal according to the relation coordinates;
the preset time period comprises a shift time period and a shutdown time period;
the acquisition module comprises:
a workload information acquisition unit: the method comprises the steps of acquiring actual workload information of current equipment in a shift time period;
the analysis module comprises:
a first comparison unit: for comparing the actual workload of the current device during the shift time period with the expected workload;
when the actual workload is greater than or equal to the expected workload, judging that the current equipment is in a normal production state;
when the actual workload is smaller than the expected workload, judging that the current equipment is in an abnormal production state;
a second comparing unit: the method comprises the steps of obtaining actual working hour time used for producing actual workload under abnormal production conditions, and comparing the actual working hour time with expected working hour time;
when the actual working hour time is less than or equal to the expected working hour time, judging that the current equipment is in a short-time shutdown state;
when the actual working time is longer than the expected working time, judging that the current equipment is in a fault state;
a relation coordinate generating unit: uploading the corresponding shift time period information when the current equipment is in a fault state to a background server, and generating a relation coordinate of the actual workload of the current equipment and the expected workload in a preset time period according to the shift time period, the actual workload and the expected workload;
the prediction module includes:
prediction unit: predicting whether the current equipment reaches the expected yield within a preset time period according to the relation coordinates in the relation coordinate generating unit;
a first marking unit: if yes, marking the current equipment as normal production equipment;
a second marking unit: if not, marking the current equipment as abnormal production equipment, stopping the equipment to judge the equipment according to the second comparison unit, and if judging to be in a short-time stopping state, starting the equipment to continue to operate; if the fault state is judged, the shutdown state is maintained and maintenance is carried out.
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