CN113505043A - Cigarette equipment state monitoring method based on real-time data collection - Google Patents
Cigarette equipment state monitoring method based on real-time data collection Download PDFInfo
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- CN113505043A CN113505043A CN202110904331.8A CN202110904331A CN113505043A CN 113505043 A CN113505043 A CN 113505043A CN 202110904331 A CN202110904331 A CN 202110904331A CN 113505043 A CN113505043 A CN 113505043A
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- 235000019504 cigarettes Nutrition 0.000 title claims abstract description 37
- 238000012544 monitoring process Methods 0.000 title claims abstract description 19
- 238000000034 method Methods 0.000 title claims abstract description 13
- 238000013480 data collection Methods 0.000 title abstract description 6
- 238000012423 maintenance Methods 0.000 claims abstract description 9
- 230000005856 abnormality Effects 0.000 claims abstract description 8
- 230000002159 abnormal effect Effects 0.000 claims description 14
- 238000007619 statistical method Methods 0.000 claims description 8
- 238000004886 process control Methods 0.000 claims description 6
- 230000001174 ascending effect Effects 0.000 claims description 3
- 230000003247 decreasing effect Effects 0.000 claims description 3
- 238000005065 mining Methods 0.000 claims description 2
- 238000004519 manufacturing process Methods 0.000 claims 1
- 230000002427 irreversible effect Effects 0.000 abstract description 4
- 230000000694 effects Effects 0.000 description 4
- 238000013461 design Methods 0.000 description 3
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- 230000006866 deterioration Effects 0.000 description 2
- 241000208125 Nicotiana Species 0.000 description 1
- 235000002637 Nicotiana tabacum Nutrition 0.000 description 1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/3065—Monitoring arrangements determined by the means or processing involved in reporting the monitored data
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- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
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Abstract
The invention discloses a cigarette equipment state monitoring method based on real-time data collection. The invention solves the problem that the current equipment state monitoring is in the condition of post management and control, can quickly reflect the actual state of the cigarette equipment, is convenient for carrying out measures such as spare part purchasing, centralized maintenance, maintenance and the like aiming at the cigarette equipment, and avoids the loss caused by irreversible abnormality of the state of the cigarette equipment.
Description
Technical Field
The invention relates to the field of tobacco industry, in particular to a cigarette equipment state monitoring method based on real-time data acquisition.
Background
With the further integration of cigarette industrialization and informatization, the cigarette equipment state monitoring is mainly embodied by indexes such as equipment effective operation rate, equipment comprehensive efficiency (OEE) and the like at present, wherein the equipment effective operation rate is equipment effective time divided by equipment running total time; the equipment comprehensive efficiency OEE is the quality yield × time actuation rate × performance actuation rate × 100%. Even though the above-mentioned methods have established the association between the equipment state and the equipment processing effect, the above-mentioned detection methods are all in the state of post management and control, that is, when a problem is found, irreversible damage may have been already caused to the equipment, so that the equipment state is converted from the "natural deterioration" state to the "forced deterioration" state.
Specifically, the existing cigarette equipment abnormity detection mechanism mainly establishes an evaluation index system aiming at the effective operation rate of equipment and the comprehensive efficiency OEE of the equipment, detects the equipment state in an off-line mode, and fails to fully reflect the equipment abnormity in real time. This leads to the fact that the device management mode is often in a post-management state, and further causes two drawbacks of post-management: one is to avoid the abnormal condition of the equipment, an excessive amount of parts are purchased in advance for replacement, however, if the equipment has no abnormal problem, many parts can exceed the quality guarantee period and cannot be used continuously, which causes the waste of cost; another is lack of spare part preparation, and once the equipment is in trouble, temporary parts need to be purchased, so that on-site downtime is caused, which not only affects the construction period, but also can bring other more serious and associated effects.
Disclosure of Invention
In view of the above, the present invention aims to provide a method for monitoring the state of cigarette equipment based on real-time data collection, so as to solve the problem that the existing detection mode causes the equipment to be in a post-management state.
The technical scheme adopted by the invention is as follows:
a cigarette equipment state monitoring method based on real-time data comprises the following steps:
acquiring process control parameters of the cigarette equipment through a real-time data acquisition system, and collecting and storing the process control parameters;
carrying out judgment and analysis on the control parameters acquired in real time by using a big data statistical analysis strategy; wherein the discriminant analysis comprises: judging whether the real-time collected data accords with a plurality of data abnormal indications predetermined by utilizing the stored data through statistical analysis;
when the real-time data accords with any data abnormal indication, a multiple regression tracing analysis mechanism is adopted to correlate maintenance information, overhaul information and spare part information of the cigarette equipment corresponding to the abnormal real-time data, and determine the correlation influence weight of the state of the cigarette equipment and each factor;
and outputting a state monitoring conclusion corresponding to the cigarette equipment and carrying out early warning based on the abnormal real-time data acquisition data and the associated influence weight.
In at least one possible implementation, the data anomaly indicators include one or more of:
at least one data point acquired in real time is more than a preset upper limit value or a preset lower limit value from the central line;
at least a first preset number of continuous data points are linearly distributed on one side of the data mean value;
at least a preset second number of continuous data points are continuously increased or decreased according to a preset slope;
at least a preset third number of continuous data points are distributed in an alternate ascending or descending way;
at least two thirds of the data points in a plurality of consecutive data points on the same side of the data mean exceed twice the established standard deviation;
at least four fifths of the data points in a plurality of continuous data points on the same side of the data mean value exceed one time of the set standard deviation;
at least a preset fourth number of consecutive data points fluctuating within one time of a predetermined standard deviation;
at least a fifth predetermined number of consecutive data points, each exceeding one time the predetermined standard deviation on both sides of the data mean.
In at least one possible implementation manner, the upper limit value is the data mean plus three times the established standard deviation; the lower limit is the standard deviation of the data mean reduced by three times.
The design concept of the invention is that real-time state monitoring is carried out on cigarette equipment by using a big data statistical analysis algorithm and combining real-time data acquisition, the data acquisition data for detecting abnormity is automatically associated to corresponding equipment, and abnormity feedback of the corresponding equipment is given in time. The invention solves the problem that the current equipment state monitoring is in the condition of post management and control, can quickly reflect the actual state of the cigarette equipment, is convenient for carrying out measures such as spare part purchasing, centralized maintenance, maintenance and the like aiming at the cigarette equipment, and avoids the loss caused by irreversible abnormality of the state of the cigarette equipment.
Drawings
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be further described with reference to the accompanying drawings, in which:
fig. 1 is a flowchart of a method for monitoring the state of a cigarette making apparatus based on real-time data collection according to an embodiment of the present invention;
fig. 2 to 9 are schematic diagrams of eight data abnormality indications provided by the embodiment of the present invention.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are illustrative only and should not be construed as limiting the invention.
The invention provides an embodiment of a cigarette equipment state monitoring method based on real-time data collection, and specifically, as shown in fig. 1, the method may include:
s1, acquiring process control parameters of the cigarette equipment through the real-time coal mining system, and collecting and storing the process control parameters;
step S2, carrying out judgment and analysis on the control parameters acquired in real time by using a big data statistical analysis strategy; wherein the discriminant analysis comprises: judging whether the real-time collected data accords with a plurality of data abnormal indications predetermined by utilizing the stored data through statistical analysis;
step S3, when the real-time data accords with any data abnormal indication, a multiple regression retroactive analysis mechanism is adopted to correlate the maintenance information, the overhaul information and the spare part information of the cigarette equipment corresponding to the abnormal real-time data, and determine the correlation influence weight of the state of the cigarette equipment and each factor;
and S4, outputting a state monitoring conclusion corresponding to the cigarette equipment and giving an early warning based on the abnormal real-time data acquisition data and the associated influence weight.
Further, the data abnormality indications include one or more of:
at least one data point acquired in real time is more than a preset upper limit value or a preset lower limit value from the central line;
at least a first preset number of continuous data points are linearly distributed on one side of the data mean value;
at least a preset second number of continuous data points are continuously increased or decreased according to a preset slope;
at least a preset third number of continuous data points are distributed in an alternate ascending or descending way;
at least two thirds of the data points in a plurality of consecutive data points on the same side of the data mean exceed twice the established standard deviation;
at least four fifths of the data points in a plurality of continuous data points on the same side of the data mean value exceed one time of the set standard deviation;
at least a preset fourth number of consecutive data points fluctuating within one time of a predetermined standard deviation;
at least a fifth predetermined number of consecutive data points, each exceeding one time the predetermined standard deviation on both sides of the data mean.
Further, the upper limit value is the data mean plus three times the established standard deviation; the lower limit is the standard deviation of the data Mean reduced by three times, such as UCL Mean +3 σ, LCL Mean-3 σ; the UCL is an upper limit value, the LCL is a lower limit value, Mean is a Mean value of all data acquisition data of the unified data acquisition point, and sigma is a preset standard deviation.
With reference to fig. 2-9, the present invention provides eight examples of data anomaly indicators as follows:
(1) as shown in fig. 2: one point is more than 3 sigma from the center line.
(2) As shown in fig. 3: the 9 dots are arranged in a continuous line on one side of the center line.
(3) As shown in fig. 4: the 6 dots are lined up and continue to increase or decrease regularly.
(4) As shown in fig. 5: the 14 dots are arranged in a continuous line and alternately rise or fall.
(5) As shown in fig. 6: two of the 3 points consecutively arranged on the same side are more than 2 σ away from the center.
(6) As shown in fig. 7: four of the 5 points consecutively arranged on the same side are more than 1 σ from the center.
(7) As shown in fig. 8: the 15 points in the series are all located within 1 σ from the center line.
(8) As shown in fig. 9: the 8 points consecutively arranged on both sides of the center line are more than 1 sigma away from the center line.
In summary, the design concept of the present invention is to monitor the real-time status of the cigarette equipment by using a big data statistical analysis algorithm and combining real-time data acquisition, automatically associate the data acquisition data for detecting the abnormality to the corresponding equipment, and timely give the abnormality feedback of the corresponding equipment. The invention solves the problem that the current equipment state monitoring is in the condition of post management and control, can quickly reflect the actual state of the cigarette equipment, is convenient for carrying out measures such as spare part purchasing, centralized maintenance, maintenance and the like aiming at the cigarette equipment, and avoids the loss caused by irreversible abnormality of the state of the cigarette equipment.
In the embodiments of the present invention, "at least one" means one or more, "a plurality" means two or more. "and/or" describes the association relationship of the associated objects, and means that there may be three relationships, for example, a and/or B, and may mean that a exists alone, a and B exist simultaneously, and B exists alone. Wherein A and B can be singular or plural. The character "/" generally indicates that the former and latter associated objects are in an "or" relationship. "at least one of the following" and similar expressions refer to any combination of these items, including any combination of singular or plural items. For example, at least one of a, b, and c may represent: a, b, c, a and b, a and c, b and c or a and b and c, wherein a, b and c can be single or multiple.
The structure, features and effects of the present invention have been described in detail with reference to the embodiments shown in the drawings, but the above embodiments are merely preferred embodiments of the present invention, and it should be understood that technical features related to the above embodiments and preferred modes thereof can be reasonably combined and configured into various equivalent schemes by those skilled in the art without departing from and changing the design idea and technical effects of the present invention; therefore, the invention is not limited to the embodiments shown in the drawings, and all the modifications and equivalent embodiments that can be made according to the idea of the invention are within the scope of the invention as long as they are not beyond the spirit of the description and the drawings.
Claims (3)
1. A cigarette equipment state monitoring method based on real-time data is characterized by comprising the following steps:
acquiring process control parameters of the cigarette equipment through a real-time data acquisition system, and collecting and storing the process control parameters;
carrying out judgment and analysis on the control parameters acquired in real time by using a big data statistical analysis strategy; wherein the discriminant analysis comprises: judging whether the real-time collected data accords with a plurality of data abnormal indications predetermined by utilizing the stored data through statistical analysis;
when the real-time data accords with any data abnormal indication, a multiple regression tracing analysis mechanism is adopted to correlate maintenance information, overhaul information and spare part information of the cigarette equipment corresponding to the abnormal real-time data, and determine the correlation influence weight of the state of the cigarette equipment and each factor;
and outputting a state monitoring conclusion corresponding to the cigarette equipment and carrying out early warning based on the abnormal real-time data acquisition data and the associated influence weight.
2. The method for monitoring the condition of cigarette equipment based on real-time production data according to claim 1, wherein the data abnormality indication comprises one or more of:
at least one data point acquired in real time is more than a preset upper limit value or a preset lower limit value from the central line;
at least a first preset number of continuous data points are linearly distributed on one side of the data mean value;
at least a preset second number of continuous data points are continuously increased or decreased according to a preset slope;
at least a preset third number of continuous data points are distributed in an alternate ascending or descending way;
at least two thirds of the data points in a plurality of consecutive data points on the same side of the data mean exceed twice the established standard deviation;
at least four fifths of the data points in a plurality of continuous data points on the same side of the data mean value exceed one time of the set standard deviation;
at least a preset fourth number of consecutive data points fluctuating within one time of a predetermined standard deviation;
at least a fifth predetermined number of consecutive data points, each exceeding one time the predetermined standard deviation on both sides of the data mean.
3. The method for monitoring the condition of cigarette equipment based on real-time mining data according to claim 2, wherein the upper limit value is the data mean plus three times the established standard deviation; the lower limit is the standard deviation of the data mean reduced by three times.
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| Application Number | Priority Date | Filing Date | Title |
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| CN202110904331.8A CN113505043A (en) | 2021-08-06 | 2021-08-06 | Cigarette equipment state monitoring method based on real-time data collection |
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| CN202110904331.8A CN113505043A (en) | 2021-08-06 | 2021-08-06 | Cigarette equipment state monitoring method based on real-time data collection |
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| US20190012553A1 (en) * | 2017-07-07 | 2019-01-10 | Kabushiki Kaisha Toshiba | Diagnostic device, diagnosis method and computer program |
| CN111241482A (en) * | 2020-01-10 | 2020-06-05 | 合肥工业大学 | Method and system for detecting abnormal working state of multi-parameter system |
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2021
- 2021-08-06 CN CN202110904331.8A patent/CN113505043A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20170249200A1 (en) * | 2016-02-29 | 2017-08-31 | International Business Machines Corporation | Analyzing computing system logs to predict events with the computing system |
| CN108875964A (en) * | 2017-05-12 | 2018-11-23 | 深圳烟草工业有限责任公司 | A kind of cigarette manufacturing equipment point inspection analysis method and system |
| US20190012553A1 (en) * | 2017-07-07 | 2019-01-10 | Kabushiki Kaisha Toshiba | Diagnostic device, diagnosis method and computer program |
| CN111241482A (en) * | 2020-01-10 | 2020-06-05 | 合肥工业大学 | Method and system for detecting abnormal working state of multi-parameter system |
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