Stacker Data Acquisition and Integration System Based on Distributed Message Queue

Abstract

The present invention discloses a data collection and integration system for stackers based on distributed message queues. The main design concept of the present invention is to build a large-scale, real-time interactive, reliable distributed stacker operation data collection and integration system between each stacker and the finished product warehouse, auxiliary material warehouse, and filter rod warehouse, and between the three warehouses and the logistics central control room. By collecting various operation data of the stackers and using distributed management and buffer queue circulation mechanisms, it is ensured that the data of all stackers in the three warehouses can be smoothly collected and sent to the server for subsequent analysis. The present invention can realize timely data processing and timely warning through real-time interaction between the server, the first-level master station, the second-level master station, and the substation, thereby reducing the occurrence of faults and preventing accidents, significantly reducing the downtime of the stacker, improving the efficiency of inbound and outbound logistics, and making the maintenance and maintenance of the stacker more scientific and less costly.

Description

Technical Field

[0001] The present invention relates to the field of cigarette manufacturing, and in particular to a stacker data acquisition and integration system based on a distributed message queue. Background Art

[0002] With the continuous development and improvement of the informatization and automation process of the tobacco industry, a system for automatically transporting finished cigarette pallets by a finished product warehouse stacker based on the concept of an unmanned factory was invented, which innovatively realized highly automated operating modes such as automatic entry and exit of finished cigarette pallets and automatic return of empty pallets to the warehouse; a system for automatically transporting auxiliary material pallets to production machines by an auxiliary material warehouse stacker through AGV was invented based on the concept of an unmanned factory, which innovatively realized highly automated operating modes such as automatic entry and exit of auxiliary material pallets by AGV and automatic return of empty pallets to the warehouse; a system for automatically transporting filter rod buckets to transmitters by a filter rod warehouse stacker based on the concept of an unmanned factory was invented, which innovatively realized highly automated operating modes such as automatic entry and exit of filter rod buckets and automatic return of empty buckets to the warehouse.

[0003] The stacker crane for finished product warehouse, auxiliary material warehouse and filter rod warehouse is the abbreviation of stacking crane, which is the characteristic symbol of automated high-rise warehouse. It is responsible for picking, transporting, lifting and shipping finished cigarette pallets, auxiliary material pallets and filter rods. Therefore, the function of the stacker crane directly determines the throughput efficiency of the high-rise warehouse.

[0004] In existing technology, stackers in finished product storage, auxiliary material storage, and filter rod storage can experience various faults and even accidents during operation. Some are caused by the stacker itself, others by the aging of cigarette and auxiliary material trays, others by spare parts, and still others by program vulnerabilities. To reduce faults and prevent accidents, it is necessary to analyze the causes of these faults and collect statistics on their duration and causes. This requires collecting various data on these faults. However, currently, only individual data is collected, which is relatively fragmented and lacks unified summary and analysis. Furthermore, maintenance and component replacement also depend on data such as the operating time and wear of stacker components. Failure to promptly replace aging spare parts can pose a significant risk to stacker operation and even lead to accidents. Currently, maintenance personnel often rely on experience to determine whether a component needs replacement. Therefore, the industry urgently needs to collect wear data on key stacker components, including those that experience continuous wear due to long-term operation (such as running wheels). This data can be compiled and analyzed in a timely manner to develop a scientific and comprehensive maintenance plan, ensuring timely and effective maintenance without excessive maintenance. Summary of the Invention

[0005] In view of the above, the present invention aims to provide a stacker crane data acquisition and integration system based on a distributed message queue to solve the above-mentioned technical problems.

[0006] The technical solution adopted in the present invention is as follows:

[0007] The present invention provides a stacker crane data acquisition and integration system based on a distributed message queue, which includes:

[0008] Set up a primary master station and server in the logistics central control room;

[0009] Set up secondary master stations in the dispatch cabinets of finished product warehouse, auxiliary material warehouse and filter rod warehouse respectively;

[0010] Several substations are set up in each stacker control cabinet corresponding to the finished product warehouse, auxiliary material warehouse, and filter rod warehouse;

[0011] Each substation is provided with a front-end data acquisition module, and each secondary master station is provided with a front-end distributed message communication management module and a data integration module;

[0012] A wired network communication mode is adopted between the substation and the secondary master station, and between the primary master station and the server; a 5G CPE communication mode is adopted between the secondary master station and the primary master station;

[0013] The front-end data acquisition module is used to collect the operating data of each stacker in the three warehouses in real time;

[0014] The distributed message communication management module is used to perform cluster management and load balancing support for publishing and subscribing message queue service nodes in each stacker;

[0015] The data integration module centrally stores the operation data collected by the front-end data collection module through a buffer queue circulation mechanism.

[0016] In at least one possible implementation, the centralized warehousing processing includes: determining the occupancy ratio of data acquisition threads of stackers in different warehouses according to the busyness of the stackers, and aggregating the collected operation data based on the occupancy ratio of the data acquisition threads.

[0017] In at least one possible implementation, the method for determining the data acquisition thread occupancy ratio includes:

[0018] Determine the data acquisition weight of each stacker crane based on the total number of data collected by all stacker cranes within the preset unit time and the data collection volume per unit time of each stacker crane in each warehouse;

[0019] Based on the data acquisition weight, the preset total number of data acquisition threads and the preset stacker busy coefficient of each warehouse, the thread proportion values of each stacker in the finished product warehouse, the auxiliary material warehouse and the filter rod warehouse are obtained respectively.

[0020] In at least one possible implementation manner, the stacker crane busy coefficient is a ratio of the average daily operating time of each warehouse stacker crane to a preset total operating time.

[0021] In at least one possible implementation, the operating data includes: the degree of wear of the running wheels, lifting guide wheels, overhead rail guide wheels and lifting wire ropes on the stacker.

[0022] In at least one possible implementation, the data acquisition and integration system uses an elevator wire rope flaw detection system to monitor the degree of wear of the lifting wire rope.

[0023] In at least one possible implementation, the data acquisition and integration system uses multiple visual devices to monitor the degree of wear of the running wheels, overhead rail guide wheels, and lifting guide wheels respectively.

[0024] In at least one possible implementation, the visual device includes: industrial cameras respectively installed above the walking wheel, below the overhead rail guide wheel, and in front of the lifting guide wheel.

[0025] Compared with the existing technology, the main design concept of the present invention is to build a large-scale, real-time interactive, reliable distributed stacker operation data collection and database integration system between each stacker and the finished product warehouse, auxiliary material warehouse, and filter rod warehouse, and between the three warehouses and the logistics central control room. By collecting various operation data of the stackers and using distributed management and buffer queue circulation mechanisms, it is ensured that the data of all stackers in the three warehouses can be smoothly collected and sent to the server for subsequent analysis. Through real-time interaction between the server, the primary master station, the secondary master station, and the substation, the present invention can realize timely data processing and timely warning, thereby reducing the occurrence of faults and preventing accidents, significantly reducing the downtime of the stacker, improving the efficiency of inbound and outbound logistics, and making the maintenance and maintenance of the stacker more scientific and less costly.

[0026] In particular, the present invention proposes a data scheduling method adapted to the aforementioned system, which optimizes the configuration of the weights of the stacker data acquisition threads of each library, so that stackers with busy tasks, such as filter rod library stackers, can be assigned larger weights, so that they occupy more data entry thread resources, thereby reducing the delay jitter during data collection. In this way, the data of each stacker can be entered into the library evenly, smoothly and in real time, avoiding data congestion that causes the aforementioned server analysis work to be stuck. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to make the purpose, technical solutions and advantages of the present invention more clear, the present invention will be further described below with reference to the accompanying drawings, in which:

[0028] Figure 1 A schematic diagram of a stacker crane data acquisition and integration system based on a distributed message queue provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0029] The following describes embodiments of the present invention in detail. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended only to explain the present invention and are not to be construed as limiting the present invention.

[0030] The present invention proposes an embodiment of a stacker crane data acquisition and integration system based on a distributed message queue. Specifically, Figure 1 shown, including:

[0031] In the logistics central control room, a primary master station (electronic control level, such as PLC) and a server (information control level, operating program level) are set up respectively;

[0032] Set up secondary master stations in the dispatch cabinets of finished product warehouse, auxiliary material warehouse and filter rod warehouse respectively;

[0033] Several substations are set up in each stacker control cabinet corresponding to the finished product warehouse, auxiliary material warehouse, and filter rod warehouse;

[0034] Each substation is provided with a front-end data acquisition module, and each secondary master station is provided with a front-end distributed message communication management module and a data integration module;

[0035] A wired network communication mode is adopted between the substation and the secondary main station, as well as between the primary main station and the server; a 5G CPE communication mode is adopted between the secondary main station and the primary main station.

[0036] Specifically, the CPE mentioned here stands for Customer Premise Equipment, or "customer premises equipment." Its function is to convert mobile network signals (4G, 5G, etc.) or wired broadband signals into local signals for use by terminal devices. More specifically, 5G CPE is a type of 5G terminal device that receives 5G signals from carrier base stations and converts them into Wi-Fi or wired signals, allowing more internet-connected devices to access the network. The emphasis on CPE in this system is based on the low-cost approach of integrating data transmission with mature mobile carrier networks.

[0037] The database of the front-end data acquisition module adopts MS SQL Server database, which is used to collect the operating data of each stacker in the three warehouses in real time, including but not limited to: the departure place, departure time, destination, and arrival time of the stacker's picking and placing tasks; the stacker's X-axis walking distance, duration, speed, and acceleration; the Y-axis walking distance, duration, speed, and acceleration; the number of fork extensions on the Z-axis; the voltage, current and other operating parameters of the X-axis motor, Y-axis motor, and Z-axis motor; the number and starting position of the pallets carried by the stacker per unit time; the degree of wear of the running wheels, lifting guide wheels, overhead rail guide wheels, etc. on the stacker, and the degree of wear of the lifting wire rope.

[0038] Among them, voltage recorders and current recorders can be used to collect data on the operation status of the X, Y, and Z axis motors of the stacker. In actual operation, the voltage and current recorders can use mature electrical indicator recorders and be placed in the control cabinet of each stacker.

[0039] Preferably, multiple visual recognition monitoring devices can be used to monitor the wear of the running wheels, ceiling rail guide wheels, and hoisting guide wheels respectively, and an elevator wire rope flaw detection system can be used to monitor the wear of the hoisting wire rope. In this regard, the present invention is expanded into the following specific embodiments:

[0040] (1) Detection of wheel wear

[0041] The visual recognition monitoring device includes an industrial camera mounted on a bracket above the wheel. The camera preferably utilizes a full-frame back-illuminated CMOS sensor, employing an active-pixel solid-state image sensor (IMX536). This chip features a global shutter with a variable charge integration time. Furthermore, the chip is powered by four power supplies: analog 3.3V, analog 2.9V, digital 1.1V, and interface 1.8V, enabling high sensitivity and low dark current. Furthermore, the camera can have a pixel count of 2840 (H) × 2840 (V), representing 8.06 million pixels. The maximum frame rate in full-pixel scanning mode is 194.0 fps for 8-bit, 193.4 fps for 10-bit, and 127.2 fps for 12-bit. The aperture is 2.8f or greater (near side).

[0042] During the actual inspection process, the high-speed industrial camera can be set to take three front-facing photos of the wheel at several fixed time points every day (such as 8:00, 14:00, and 20:00). The data is collected by the front data acquisition module and then transmitted to the server in the logistics central control room via 5G CPE and wired methods. Using the existing image analysis algorithm, the degree of wear of the wheel is determined from the photos, and a decision is made whether to issue an early warning.

[0043] (2) Detection of wear on the guide wheels of the overhead rail

[0044] The visual recognition monitoring device includes: a high-speed industrial camera installed on a bracket arranged below the overhead rail guide wheel. The camera model and detection process can refer to the aforementioned camera selection and timing detection analysis method.

[0045] (3) Detection of wear of lifting guide wheel

[0046] The visual recognition monitoring device includes: a high-speed industrial camera installed on a bracket arranged in front of the lifting guide wheel. The camera model and detection process can refer to the aforementioned camera selection and timing detection analysis method.

[0047] (4) Detection of hoisting wire rope wear

[0048] The aforementioned elevator wire rope flaw detection system detects various damages that occur during the use of high-speed, large-diameter elevator wire ropes, such as broken wires, fatigue, rust, wear, crushing, and twisting. Designed and manufactured for regular, localized flaw detection of consumable and vulnerable areas of in-service wire ropes, it accurately assesses the safety status of elevator wire ropes. The data transmission process is the same as described above. Specifically, data monitored by the elevator wire rope flaw detection system is collected by a front-end data acquisition module and enters the stacker crane's substation. It is then aggregated into a secondary master station, transmitted to the primary master station via a 5G CPE, and finally sent to the server.

[0049] Continuing from the previous text, the distributed message communication management module is used to perform cluster management and load balancing support for publishing and subscribing message queue service nodes in each stacker, so as to facilitate aggregation at the server terminal;

[0050] The data integration module centrally stores the operating data collected by the front-end data collection module through a buffer queue circulation mechanism (the storage operation here, in some embodiments, can be understood to refer to the process of collecting and sending the collected data to the server).

[0051] The centralized warehousing processing includes: determining the occupancy ratio of the data acquisition threads of the stackers in different warehouses (the warehouses here refer to the three warehouses mentioned above) according to the busyness of the stackers, and aggregating the collected data based on the occupancy ratio of the data acquisition threads.

[0052] Specifically, according to the total number of data collected by all the stackers in the three warehouses within a preset unit time (obtained based on the sum of the number of stackers in each warehouse and the data collected per unit time of each stacker) and the data collected per unit time of a single stacker in each warehouse, the data collection weight of each stacker is determined (data collected per unit time of a single stacker in each warehouse / total number of data collected); based on the data collection weight, the preset total number of data collection threads and the preset busy coefficient of the stackers in each warehouse, the thread ratio values occupied by each stacker in the finished product warehouse, the auxiliary material warehouse and the filter rod warehouse are obtained respectively (taking the warehouse as the unit, the data collection weight of a single stacker in the warehouse is ratioed to the data collection weight of all stackers in the warehouse, and integrated with the busy coefficient).

[0053] For example, let the total amount of data collected per unit time (minute) by the stacker cranes in the three warehouses be S. For example, there are 8 stacker cranes in the finished product warehouse, and the amount of data collected per unit time (minute) is C. i (i=1,2,3,4,5,6,7,8); There are 3 stackers in the auxiliary material warehouse, and the amount of data collected per unit time (minute) is F i (i=1,2,3); There are 4 stackers in the filter rod warehouse, and the data collection volume per unit time (minute) is L i (i=1,2,3,4).

[0054] In addition, since the service objects of the above three warehouses are different, the business busyness is also different. Therefore, the busy coefficient of each warehouse (stacker) can be set based on the proportion of the average daily operating time of each warehouse stacker to the preset total time. Correspondingly, the busy coefficient of the finished product warehouse stacker is δ, the busy coefficient of the auxiliary material warehouse stacker is ε, and the busy coefficient of the filter rod warehouse stacker is η.

[0055] In this example, the following calculation process is used to first determine the total time data collected by the three libraries:

[0056] S=S C +S F +S L (1)

[0057]

[0058]

[0059] Next, the data collection weight assigned to each stacker crane in each warehouse can be expressed as:

[0060] or

[0061] Assume that the total number of data acquisition threads pre-configured by the system is a fixed value M, then,

[0062] The thread ratio of each stacker in the finished product warehouse (i=1,2,3……8) is:

[0063]

[0064] The thread ratio of each stacker in the auxiliary material warehouse (i=1,2,3) is:

[0065]

[0066] The thread ratio of each stacker in the filter rod storage (i=1,2,3,4) is:

[0067]

[0068] In summary, the main design concept of the present invention is to build a large-scale, real-time interactive, reliable distributed stacker operation data collection and database integration system between each stacker and the finished product warehouse, auxiliary material warehouse, and filter rod warehouse, and between the three warehouses and the logistics central control room. By collecting various operation data of the stackers and using distributed management and buffer queue circulation mechanisms, it is ensured that the data of all stackers in the three warehouses can be smoothly collected and sent to the server for subsequent analysis. The present invention can realize timely data processing and timely warnings through real-time interaction between the server, the first-level master station, the second-level master station, and the substation, thereby reducing the occurrence of faults and preventing accidents, greatly reducing the downtime of the stacker, improving the efficiency of inbound and outbound logistics, and making the maintenance and maintenance of the stacker more scientific and less costly.

[0069] In the embodiment of the present invention, "at least one" refers to one or more, and "more" refers to two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can represent the existence of A alone, the existence of A and B at the same time, and the existence of B alone. A and B can be singular or plural. The character " / " generally indicates that the previous and next 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 single or plural items. For example, at least one of a, b and c can be represented by: a, b, c, a and b, a and c, b and c, or a, b and c, where a, b, c can be single or multiple.

[0070] The above describes in detail the structure, features and effects of the present invention based on the embodiments shown in the drawings, but the above is only a preferred embodiment of the present invention. It should be noted that the technical features involved in the above embodiments and their preferred modes can be reasonably combined and matched into a variety of equivalent schemes by those skilled in the art without departing from or changing the design ideas and technical effects of the present invention; therefore, the scope of implementation of the present invention is not limited to what is shown in the drawings. Any changes made in accordance with the concept of the present invention, or modifications to equivalent embodiments with equivalent changes, which still do not exceed the spirit covered by the description and drawings, should be within the scope of protection of the present invention.

Claims

1. A stacker crane data acquisition and integration system based on distributed message queue, characterized in that: include: Set up a primary master station and server in the logistics central control room; Set up secondary master stations in the dispatch cabinets of finished product warehouse, auxiliary material warehouse and filter rod warehouse respectively; Several substations are set up in each stacker control cabinet corresponding to the finished product warehouse, auxiliary material warehouse, and filter rod warehouse; Each substation is provided with a front-end data acquisition module, and each secondary master station is provided with a front-end distributed message communication management module and a data integration module; A wired network communication mode is adopted between the substation and the secondary master station, and between the primary master station and the server; a 5G CPE communication mode is adopted between the secondary master station and the primary master station; The front-end data acquisition module is used to collect the operating data of each stacker in the three warehouses in real time; The distributed message communication management module is used to perform cluster management and load balancing support for publishing and subscribing message queue service nodes in each stacker; The data integration module centrally stores the operation data collected by the front-end data collection module through a buffer queue circulation mechanism, specifically including: determining the occupancy ratio of the data collection threads of the stackers in different warehouses according to the busyness of the stackers, and aggregating the collected operation data based on the occupancy ratio of the data collection threads; Among them, the method for determining the occupancy ratio of the data acquisition threads includes: determining the data acquisition weight of each stacker according to the total number of data acquisitions of all stackers in a preset unit time and the data collection volume per unit time of a single stacker in each warehouse; based on the data acquisition weight, the preset total number of data acquisition threads and the preset stacker busy coefficient of each warehouse, respectively obtaining the thread ratio values of each stacker in the finished product warehouse, the auxiliary material warehouse and the filter rod warehouse; the stacker busy coefficient is the ratio of the average daily operating time of the stacker in each warehouse to the preset total time.

2. The stacker crane data acquisition and integration system based on distributed message queue according to claim 1 is characterized in that: The operating data includes: the degree of wear of the running wheels, lifting guide wheels, overhead rail guide wheels and lifting wire ropes on the stacker.

3. The stacker crane data acquisition and integration system based on distributed message queue according to claim 2 is characterized in that: The data acquisition and integration system uses an elevator wire rope flaw detection system to monitor the degree of wear of the lifting wire rope.

4. The stacker crane data acquisition and integration system based on distributed message queue according to claim 2 is characterized in that: The data acquisition and integration system uses multiple visual devices to monitor the wear degree of the running wheels, overhead rail guide wheels, and lifting guide wheels respectively.

5. The stacker crane data acquisition and integration system based on distributed message queue according to claim 4 is characterized in that: The visual device includes industrial cameras respectively installed above the walking wheel, below the overhead rail guide wheel and in front of the lifting guide wheel.

Images