CN108146738B - Intelligent identification method for running state of photon packet loss detection equipment - Google Patents
Intelligent identification method for running state of photon packet loss detection equipment Download PDFInfo
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- CN108146738B CN108146738B CN201711477645.4A CN201711477645A CN108146738B CN 108146738 B CN108146738 B CN 108146738B CN 201711477645 A CN201711477645 A CN 201711477645A CN 108146738 B CN108146738 B CN 108146738B
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
- B65B—MACHINES, APPARATUS OR DEVICES FOR, OR METHODS OF, PACKAGING ARTICLES OR MATERIALS; UNPACKING
- B65B57/00—Automatic control, checking, warning, or safety devices
- B65B57/10—Automatic control, checking, warning, or safety devices responsive to absence, presence, abnormal feed, or misplacement of articles or materials to be packaged
Abstract
The invention relates to an intelligent identification method for the running state of photon packet missing detection equipment in the cigarette production process. The method collects real-time signal data generated by a sensor of the photon packet missing detection equipment and operation data of associated equipment, and intelligently identifies whether the operation state of the photon packet missing detection equipment normally operates or not by establishing a dynamic mathematical model and utilizing a large data flow type calculation technology.
Description
Technical Field
The invention relates to an intelligent identification method for the running state of photon packet missing detection equipment in the cigarette production process.
Background
Photon packet missing detection equipment is equipment for detecting whether a cigarette carton product has packet missing or not in the cigarette production process. In order to produce each cigarette packet with high quality, the packet missing detection is carried out on each cigarette packet in the cigarette production process, and if the photon packet missing detection equipment is abnormally operated, the packet missing quality accident of the cigarette packet can be caused, so that the core competitiveness of an enterprise is reduced.
In the actual production process, two conditions mainly exist to cause the photon packet missing detection equipment to work abnormally, and firstly, the photon packet missing detection equipment does not work normally because the photon packet missing detection equipment is not electrified normally in the production process; and secondly, the packet missing detection function of the photon packet missing detection equipment cannot be normally performed due to the performance attenuation of related parts after the photon packet missing detection equipment is operated for a long time.
At present, whether photon bag-lack detection equipment normally operates is judged mainly by a specially-assigned person to regularly inspect on site, whether a cigarette sample (bag-lack) test equipment is normal is detected, and due to the fact that the production site is large in area and multiple in equipment, the manual inspection mode has the problems that the inspection process is complicated, the workload is large, and the equipment cannot be found in time when faults occur, and quality accidents are prone to occurring.
Disclosure of Invention
In order to solve the above technical problems, an object of the present invention is to provide an intelligent method for identifying an operating state of a photon packet loss detection device, the method collects real-time signal data generated by a sensor of the photon packet loss detection device and operating data of associated devices, and intelligently identifies whether the operating state of the photon packet loss detection device is operating normally or not by establishing a dynamic mathematical model and using a large data flow type calculation technology.
In order to achieve the purpose, the invention adopts the following technical scheme:
an intelligent identification method for the operation state of photon packet loss detection equipment comprises the following steps:
firstly, the system is connected through the PLC with lifting machine equipment, gathers the signal data of lifting machine equipment in real time, the collection of lifting machine signal data, and the data item mainly includes: run rate, throughput and run time; the acquisition frequency is once every 2 seconds;
the acquired data is transmitted to a streaming computing platform through a network, wherein the streaming computing platform adopts a streaming computing technology in a big data ecology based on HADOOP to establish a distributed computing environment to efficiently process a big data stream in real time or near real time, so that the required information and result can be obtained in near real time; the streaming computing platform processes and computes input data on a plurality of server nodes of the platform by utilizing distributed computing power, wherein a computing formula is that Y is vt, v is the running speed of a hoister and t is the running time, and through the computing formula, yield values are accumulated along with the time;
the flow type computing platform computes the slope of the increase of the yield in real time, then computes the slope of a time window, and if the slope is a monotonous rising function, the conclusion is that the elevator normally runs;
therefore, when the elevator works normally, the photon packet missing detection equipment as a product quality guarantee means must be in a normal working state, and the conclusion is taken as a sufficient necessary condition for intelligently identifying whether the photon packet missing detection equipment should be started or not in the next step;
secondly, the system is connected with the photon packet-missing detection equipment through the Ethernet, and collects the signal data of the photon packet-missing detection equipment in real time, and the collection data item of the signal data of the photon packet-missing detection equipment mainly comprises: high voltage value (V), current value (. about.10 μ a), threshold value (V), total count (bar), 0 point (V), photo 1(V), photo 2(V), sync (V), and shaft encoder (V); the acquisition frequency is once every 2 seconds;
the acquired data are transmitted to a streaming computing platform through a network, the streaming computing platform processes and computes input data on a plurality of server nodes of the platform by utilizing distributed computing capability, a computing formula is Z ═ kx, wherein k is a sensor information amplitude value of photon packet loss detection equipment, the value is 0.45, x is a sensor working state, the value is (0, 1), the streaming computing platform computes incoming sample data every 2 seconds in real time, and the working state of the photon packet loss detection equipment is considered to be normally started by identifying that the slope of the sample data is greater than 0;
thirdly, when the photon packet missing detection equipment is normally started, whether the working state is normal or not needs to be identified in real time in the production process; the system collects the output data of the elevator in real time, and transmits the collected output data to the streaming computing platform, the streaming computing platform takes the received first data as a time starting point, and calculates the time period of continuously lifting 100 cigarettes, and in the process, the streaming computing platform needs to accurately identify whether the elevator is an event behavior of continuously lifting 100 cigarettes, if the elevator stops in each 100 cigarette period, the batch of sample data needs to be identified as abnormal data;
meanwhile, the system collects signal data of photon packet loss detection equipment, one sample data is obtained every 2 seconds, and all the collected data are transmitted to a streaming computing platform, wherein for three data of a high voltage value (V), a current value (. about.10 muA) and a threshold value (V), whether the operation of the three data is in a normal range is judged by adopting an upper and lower limit standard method, the value ranges of the three data are shown in the following table 1, and the table 1 is as follows:
| serial number | Name (R) | Numerical value | Unit of | Data acquisition value format | Threshold range |
| 1 | High pressure value | 15 | KV | 1471 | 1400-1800 |
| 2 | Current value | 10 | *10μA | 1088 | 900-1200 |
| 3 | Threshold value | 1 | V | 9893 | 7000-13000 |
If the operation values of the three data exceed the threshold range in the table 1, the system immediately pushes abnormal information to a maintainer, and the maintainer arrives at the site to maintain the photon packet missing detection equipment;
furthermore, the streaming computing platform performs computation and processing in strict time series for the received data listed in table 2, where table 2 is as follows:
and the data is forcibly sequenced, the time period of every 100 cigarettes of the elevator calculated by the preorder is 90 seconds, the streaming calculation platform calculates whether each data point in the table 2 meets at least 20 changed data samples, if the condition is met, the working and the function of the photon packet missing detection equipment are judged to be normal, if the condition is not met, the function of the photon packet missing detection equipment is judged to be abnormal, abnormal information is immediately pushed to a maintainer, and the maintainer arrives at the site to maintain the photon packet missing detection equipment.
The invention adopts the following technical scheme that the method collects real-time signal data generated by a sensor of the photon packet missing detection equipment and operation data of associated equipment, and intelligently identifies whether the operation state of the photon packet missing detection equipment normally operates or not by establishing a dynamic mathematical model and utilizing a large data flow type calculation technology.
Drawings
Fig. 1 and fig. 2 are schematic diagrams of an intelligent method for identifying an operating state of a photon packet loss detection device according to the present invention.
Detailed Description
As shown in fig. 1 and fig. 2, the method for intelligently identifying the operating state of a photon packet loss detection device includes the following steps:
1. the method comprises the steps of collecting data such as the running speed, the yield and the running time of a hoist, collecting the data with the collection frequency of 2 seconds by one sample, and transmitting the data to a streaming computing platform through a network.
2. The streaming computing platform processes input data on a plurality of server nodes of the platform by utilizing distributed computing capability of the streaming computing platform, firstly judges the running time of the hoister, judges the speed of the hoister if the running time of the hoister is greater than 0, and indicates that the hoister is normally started and is in a running state if the running time of the hoister is greater than 0.
3. And the flow type calculation platform calculates the yield data by using a calculation formula Y-vt (wherein v is the operation speed of the elevator, and t is the operation time) to obtain the slope of the yield, and if the slope is greater than 0, the elevator is indicated to normally convey the cigarette carton products.
4. Data such as a high voltage value (V), a current value (10 muA), a threshold value (V), a total count (bar), a 0 point (V), a photoelectric 1(V), a photoelectric 2(V), a synchronization (V), a shaft encoder (V) and the like of the photon packet missing detection device are collected and transmitted to a streaming computation platform through a network.
5. The method comprises the steps that a streaming computing platform processes input data on a plurality of server nodes of the platform by utilizing distributed computing capacity of the streaming computing platform, the streaming computing platform sorts and arranges the received data according to time according to a system, the received data are sorted and arranged according to a computing formula Y, the computing formula Y is kx (wherein k is a sensor information amplitude value of photon packet missing detection equipment and is taken as 0.45, and x is a sensor working state and is taken as a value of [ 0, 1 ]), the streaming computing platform computes sample data of every 2 seconds in real time, and the working state of the photon packet missing detection equipment is considered to be normally started by identifying that the slope of the sample data is greater than 0.
6. The system collects the yield data of the elevator in real time, the collected yield data is transmitted to the streaming type calculation platform, the streaming type calculation platform takes the received first data as a time starting point, and calculates the time period (the period is about 90 seconds) for continuously lifting 100 cigarettes, in the process, the streaming type calculation platform needs to accurately identify whether the elevator is an event behavior for continuously lifting 100 cigarettes, if the elevator stops in each 100 cigarette periods, the sample data needs to be identified as abnormal data, and the real-time calculation processing is repeated in the next time window period.
7. The system collects signal data (one sample data every 2 seconds) of photon packet loss detection equipment, and transmits all the collected data to a streaming computing platform, wherein for three data such as a high voltage value (V), a current value (. mu.A), a threshold value (V) and the like, whether the operation of the system is in a normal range is judged by adopting an upper and lower limit standard method (the value ranges of the three data are shown in table 1), if the operation values of the three data exceed the threshold value range in table 1, the system immediately pushes abnormal information to a maintainer, and the maintainer arrives at the site to maintain the photon packet loss detection equipment.
8. The flow type computing platform calculates and processes the received data strictly according to the time sequence, and performs forced sequencing on the received data, the flow type computing platform computes whether each data point in the table 2 meets at least 20 changed data samples or not by using the time period of every 100 cigarettes of the elevator calculated in the preorder, if the condition is met, the photon packet missing detection equipment is judged to work and function normally, if the condition is not met, the photon packet missing detection equipment is judged to function abnormally, abnormal information is immediately pushed to a maintainer, and the maintainer arrives at the site to maintain the photon packet missing detection equipment.
Claims (1)
1. An intelligent identification method for the operation state of photon packet loss detection equipment is characterized by comprising the following steps:
1) firstly, the system is connected through the PLC with lifting machine equipment, gathers the signal data of lifting machine equipment in real time, the collection of lifting machine signal data, and the data item mainly includes: run rate, throughput and run time; the acquisition frequency is once every 2 seconds;
the acquired data is transmitted to a streaming computing platform through a network, wherein the streaming computing platform adopts a streaming computing technology in a big data ecology based on HADOOP to establish a distributed computing environment to efficiently process a big data stream in real time or near real time, so that the required information and result can be obtained in near real time; the streaming computing platform processes and computes input data on a plurality of server nodes of the platform by utilizing distributed computing power, wherein a computing formula is that Y is vt, v is the running speed of a hoister and t is the running time, and through the computing formula, yield values are accumulated along with the time;
the flow type computing platform computes the slope of the increase of the yield in real time, then computes the slope of a time window, and if the slope is a monotonous rising function, the conclusion is that the elevator normally runs;
therefore, when the elevator works normally, the photon packet missing detection equipment as a product quality guarantee means must be in a normal working state, and the conclusion is taken as a sufficient necessary condition for intelligently identifying whether the photon packet missing detection equipment should be started or not in the next step;
2) secondly, the system is connected with the photon packet-missing detection equipment through the Ethernet, and collects the signal data of the photon packet-missing detection equipment in real time, and the collection data item of the signal data of the photon packet-missing detection equipment mainly comprises: high voltage value (V), current value (. about.10 μ a), threshold value (V), total count (bar), 0 point (V), photo 1(V), photo 2(V), sync (V), and shaft encoder (V); the acquisition frequency is once every 2 seconds;
the acquired data are transmitted to a streaming computing platform through a network, the streaming computing platform processes and computes input data on a plurality of server nodes of the platform by utilizing distributed computing capability, a computing formula is Z ═ kx, wherein k is a sensor information amplitude value of photon packet loss detection equipment, the value is 0.45, x is a sensor working state and is (0, 1), the streaming computing platform computes incoming sample data every 2 seconds in real time, and the working state of the photon packet loss detection equipment is considered to be normally started by identifying that the slope of the sample data is greater than 0;
3) thirdly, when the photon packet missing detection equipment is normally started, whether the working state is normal or not needs to be identified in real time in the production process; the system collects the output data of the elevator in real time, and transmits the collected output data to the streaming computing platform, the streaming computing platform takes the received first data as a time starting point, and calculates the time period of continuously lifting 100 cigarettes, and in the process, the streaming computing platform needs to accurately identify whether the elevator is an event behavior of continuously lifting 100 cigarettes, if the elevator stops in each 100 cigarette period, the batch of sample data needs to be identified as abnormal data;
meanwhile, the system collects signal data of the photon packet loss detection equipment, one sample data is obtained every 2 seconds, and all the collected data is transmitted to the streaming computing platform, wherein for three data, namely a high voltage value (V), a current value (. about.10 muA) and a threshold value (V), whether the operation of the three data is in a normal range or not is judged by adopting an upper and lower limit standard method, if the operation values of the three data exceed the threshold value range, the system immediately pushes abnormal information to a maintenance worker, and the maintenance worker arrives at the site to maintain the photon packet loss detection equipment;
and aiming at the received data, the streaming calculation platform calculates and processes the data according to a time sequence strictly, and performs forced sequencing on the data, the time period of every 100 cigarettes of the elevator is calculated by using a preamble and is 90 seconds, the streaming calculation platform calculates whether each received data point meets at least 20 changed data samples, if the condition is met, the photon packet missing detection equipment works and functions normally, if the condition is not met, the photon packet missing detection equipment functions abnormally, abnormal information is immediately pushed to a maintainer, and the maintainer arrives at a site to maintain the photon packet missing detection equipment.
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| CN104528061B (en) * | 2014-12-31 | 2016-09-28 | 中国电子科技集团公司第四十一研究所 | A kind of carton box cigarette based on machine vision technique lacks package detection device |
| CN206231714U (en) * | 2016-12-06 | 2017-06-09 | 中国电子科技集团公司第四十一研究所 | A kind of image collecting device for lacking bag detection for carton box cigarette |
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