CN107272571A - A kind of big data plateform system and its method of work based on MHCIMS - Google Patents
A kind of big data plateform system and its method of work based on MHCIMS Download PDFInfo
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- CN107272571A CN107272571A CN201710712243.1A CN201710712243A CN107272571A CN 107272571 A CN107272571 A CN 107272571A CN 201710712243 A CN201710712243 A CN 201710712243A CN 107272571 A CN107272571 A CN 107272571A
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/04—Programme control other than numerical control, i.e. in sequence controllers or logic controllers
- G05B19/05—Programmable logic controllers, e.g. simulating logic interconnections of signals according to ladder diagrams or function charts
- G05B19/058—Safety, monitoring
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/10—Plc systems
- G05B2219/14—Plc safety
- G05B2219/14006—Safety, monitoring in general
Abstract
The invention discloses a kind of big data plateform system based on MHCIMS and its method of work, described system includes MHCIMS data acquisition modules and background service platform, and background service platform receives the data of MHCIMS data collecting module collecteds；The PLC system that MHCIMS data acquisition modules are connected to scene through Agent servers gathers the data of each sensing equipment of crane.The problem of present invention to the live crane of user by producing data are refined and analyzed, and are helped user to find problem and propose solution, are helped Field Force to improve maintenance efficiency, lift repair quality.The present invention finds out the driver personnel for maloperation driver personnel and frequent operation often occur, optimization, standard operation process, increase equipment life, reduction fault rate by the refinement and analysis to driver operation data.The present invention by can improve equipment life, reduce fault rate, to ensure that spare part is used abundant.
Description
Technical field
The present invention relates to crane monitoring field, more particularly to a kind of crane remote data collecting system and big data clothes
Business plateform system.
Background technology
Current most crane, because of special process such as its severe operational environment, frequent, the portable combined operations of operation
Feature, restricts the controlled level of crane；The bicycle manual operation mode for making it rest on mostly based on artificial operate, production
Safety and poor reliability, efficiency are low, synergic production management pattern falls behind, and is that the production and operation brings many adverse effects.
Adjoint manufacturing equipment industry product is fast-developing to maximization, networking, intellectuality, scale, automated system skill
Art services is increasingly numerous and diverse, and either after-sale service or Task of Debugging become increasingly complex and variation, traditional service mould
Formula has been difficult to meet quick, accurate, the thoughtful technical support requirement of user.If collection remote fault diagnosis, dimension can be developed
The intelligent big data service platform system that the functions such as finger shield is led, the analysis of remote assistance, big data are integrated, by all parts of the country
Manufacturing equipment remote supervisory gets up, and the various states of equipment operation are grasped in real time, so can be by all kinds of numbers of crane
According to collection, it is incorporated into a big data processing module plateform system, arrangement, the analysis integrated show that some are more reasonable
Judgement or result, instruct crane user more rationally effectively to use crane, improve production efficiency and maintenance efficiency.
But existing crane monitoring system can only be monitored to the partial data of separate unit gantry body, not to this
Factory or larger range of crane carry out data acquisition and data processing and comprehensive big data is analyzed.
The content of the invention
To solve the above mentioned problem that prior art is present, the present invention will design a kind of crane progress that can be to big region
Big data plateform system based on MHCIMS and its work side that data acquisition and data processing and comprehensive big data are analyzed
Method.
To achieve these goals, technical scheme is as follows：A kind of big data plateform system based on MHCIMS,
Including MHCIMS data acquisition modules and background service platform, described background service platform receives MHCIMS data acquisition modules
The data of collection；The PLC system that described MHCIMS data acquisition modules are connected to scene through Agent servers gathers crane
The data of each sensing equipment；
Described background service platform includes big data processing module, database, the data service module based on B/S frameworks
And terminal user, described big data processing module is bi-directionally connected with database, described big data processing module input termination
Receive the data of MHCIMS data collecting module collecteds, its output end and pass through data service module and terminal user based on B/S frameworks
Connection；
Described background service platform sets a variety of data communication interfaces, including wireless communication interface, wired communication interface
And USB interface；
Described big data processing module is responsible for reception, decoding, storage, computing and the statistics of data, generates service data,
And service data is distributed to terminal user by the data service module based on B/S frameworks.
A kind of method of work of the big data plateform system based on MHCIMS, comprises the following steps：
Step 1：The crane data of PLC system collection site sensing equipment；Described crane data are included in industry
All kinds of protection signals, crane operating status information, operation information and production in live crane facility information, crane facility
Data message；
Step 2：By the crane data feedback of collection to Agent servers；The data address that PLC system is gathered
Communication setting is carried out in Agent servers；Described address refers to crane data in the collection address of PLC registers；Described
Communication refers to PLC system and Agent servers are communicated by RS-485 or Modbus communications protocol, and in advance in Agent
The one-to-one data receiver address in collection address of server settings and PLC registers；
Step 3：Agent servers are by numeric feedback to MHCIMS data acquisition modules, MHCIMS data acquisition modules pair
The crane data of collection are handled；The processing item of described crane data includes following project：
1) type of crane, technical parameter；
2) crane master equipment list (MEL)；
3) energy consumption of crane：
4) supply voltage of crane feeder ear, electric current；
5) operational order of crane；
6) the handling load of crane；
7) the working cycles number of times of crane；
8) accumulated operating time of crane；
9) each mechanism working cycles number of times of crane；
10) crane each mechanism accumulated operating time；
11) crane visual plant service data：Including motor, brake, major control equipment and dominant touch device
Action frequency, actuation time, equipment accumulated operating time and equipment replacement information data；
12) fault alarm of crane；
Each processing item carries out the processing of data, the fault alarm processing of such as crane according to each different processing methods
Method is：
Alarm structure：Driving number-mechanism-classification-code；
Alarm sending method：Timing sends, sent in real time or self-defined transmission；
Alarm sending mode；Alarm only sends failure code when sending, or sends failure code and related data, sends
Content is every group of multiple analog quantity, sends 15 groups of data altogether, start first 2 seconds and latter 1 second of trouble point, every 200 milliseconds of collections one
Secondary data；
Step 4：In several ways crane data are transmitted to big data processing module；
Step 5：Big data processing module is analyzed the crane data received, described analysis include decoding,
Storage, computing and statistics；Analysis item includes following project：
1) operating power consumption：Average, maximum, the minimum operating power consumption of all types of cranes；
2) load energy consumption：Average, maximum, the minimum load energy consumption of all types of cranes；
3) crane productivity ratio：Average, maximum, the minimum production rate of all types of cranes；
4) the utilization grade of crane：Average, maximum, the minimum utilization grade of all types of cranes；
5) Crane Load spectral coefficient：Average, maximum, the minimum load spectral coefficient of all types of cranes；
6) crane service life：Average, maximum, the minimum service life of all types of cranes；
7) capacity utilization：The all types of various equipment of crane are average, maximum, minimum utilization rate；
8) equipment average motion number of times：The all types of various equipment of crane are average, maximum, minimum average B configuration action frequency；
9) equipment life：All kinds, average, maximum, the minimum electrical endurance of the equipment of various brands, mechanical life；
10) crane fault rate：Average, maximum, the minimum fault rate of all types of cranes, each crane manufacturer rises
Heavy-duty machine fault rate；
11) all types of failure fault rates：The all types of failures of all types of cranes are average, maximum, minimum fault rate；
Step 6：Big data processing module is by Internet network by data publication to terminal user.
Further, the various ways described in step 4 include in the following manner：Data direct copying transmission means, GPRS are passed
Defeated mode and LAN transmission means；
Described data direct copying transmission means is as follows：
For the equipment without network environment at present, immediate data copy is supported, by the industry spot crane phase collected
Close data to export as prescribed form and preserve on a storage device, storage device is linked into big data processing module by importing
Mode is stored data into big data processing module；Described prescribed form includes driving model, structure, time and numerical value；
Described GPRS transmission mode is as follows：The industry spot crane data collected are passed through into common network GPRS/
3G network is transferred directly in big data processing module；
Described local network transport mode is as follows：The industry spot crane data collected are passed by WLAN
It is defeated to arrive at least one ground monitoring center LDC；Ground monitoring center LDC receive after crane data by specialized network VPN or
Common network is by crane data transfer into big data processing module.
Compared with prior art, the invention has the advantages that：
1st, the problem of present invention to the live crane of user by producing data are refined and analyzed, and help user to find
Problem simultaneously proposes solution, helps Field Force to improve maintenance efficiency, lifts repair quality；
2nd, the present invention finds out often by the refinement and analysis to driver operation data and maloperation driver personnel and behaviour occurs
Make frequently driver personnel, optimization, standard operation process, increase equipment life, reduction fault rate；
3rd, the present invention is by the refinement and analysis to equipment life data, and optimization often damages equipment item, equipment life and expired
, equipment and spare part usage amount, improve equipment life, reduce fault rate, to ensure that spare part is used abundant.
4th, refinement and analysis of the present invention to efficiency data, finds low run-time efficiency, fault time length, to hang load overweight
Deng crane, optimization run time, fault treating procedure, hang load reasonability, make system more efficiently, safety.
5th, in summary, the present invention in remote crane mass data to gathering, while record user searches automatically
Suo Jilu and the frequency for proposing relevant issues, make the efficiency that crane is used increase.
Brief description of the drawings
Fig. 1 is flow chart of the method for the present invention.
Fig. 2 is front end data acquisition method flow diagram of the invention.
Fig. 3 sends and receives flow chart for data in step 4 of the present invention.
Fig. 4 is MHCIMS and big data processing module data interaction overall flow design drawing.
Embodiment
To make the object, technical solutions and advantages of the present invention clearer, below in conjunction with attached in the embodiment of the present invention
Figure, technical scheme is clearly and completely described, it is clear that described embodiment is that a part of the invention is real
Apply example, rather than whole embodiments.It is as described below, the only present invention preferably embodiment, but the protection of the present invention
Scope is not limited thereto, any one skilled in the art the invention discloses technical scope in, according to this
The technical scheme of invention and its inventive concept are subject to equivalent substitution or change, should all be included within the scope of the present invention.
Fig. 1 show the present invention and utilizes PLC system collection site sensing equipment data, and data are transmitted into MHCIMS systems
To handle the data on crane, and by the modes such as wired, wireless, copy by data copy into big data processing module.
Big data processing module is decoded to the data message received, stored, computing and statistics.Big data processing module passes through
Internet network is by data publication to monitor terminal.
Fig. 2 show the present invention front-end collection method connection figure, 1. be MHCIMS by call Agent library files bind
Data are connected with Agent servers, and 2. carry out binding in PLC addresses by binding data for Agent servers is connected with PLC,
3. it is connected for PLC by hardware with crane.
Data transmission flow shown in Fig. 3：Gathered data is subjected to data preparation by MHCIMS configuring conditions, then packed
And add CRC check, GPRS communication apparatus is sent data to by serial ports, GPRS communication apparatus is passed data by Ethernet
Deliver to webserver data receiving terminal.Data receiver flow：The webserver packs statistical data analysis, passes through Ethernet
GPRS communication apparatus is sent to, GPRS will be sent to MHCIMS with RS-485 agreements by serial ports again and show.
In actual work on the spot, PLC system gathered data such as Fig. 4, collection PLC data include driver operation number
According to, data, energy consumption data, the weight data such as fault data, limit switch, door switch, overspeed switch etc..
With gear data instance, MHCIMS systems will carry out following count：
The positive 1 grade of run time of statistics and number of times；
The positive 2 grades of run times of statistics and number of times；
The positive 3 grades of run times of statistics and number of times；
The positive 4 grades of run times of statistics and number of times；
Count reverse 1 grade of run time and number of times；
Count reverse 2 grades of run times and number of times；
Count reverse 3 grades of run times and number of times；
Count reverse 4 grades of run times and number of times；
Count crawl number of operations statistics；
Count violation operation number of times statistics；
Count combined operation time and number of times statistics；
Obtain after data above, data timing is sent in big data processing module.
Big data processing module is received and calculated after data above according to conditions such as the classification of crane, region, times
It is as follows that the numerical value such as maximum, minimum value, average value, intermediate value, mean square deviation, specific data acquisition and data extract content：
1st, specific gathered data content see the table below：
The basis of table 1 collection item table
| Gear gives |
| Velocity feedback |
| Trigger voltage |
| Current value |
| Failure code |
| Control panel information and version number |
| By first 2 seconds and the above-mentioned data of rear 1S (option) |
2nd, target data contents extraction is as follows：
(1) energy consumption data：
1) specific energy consumption：Energy consumption/natural time (year, month, day, when)；
2) operating power consumption：Energy consumption/accumulated operating time (summation, year, month, day)；
3) load energy consumption：Energy consumption/handling load (summation, year, month, day)；
4) single operating power consumption：Energy consumption/working cycles number of times (summation, year, month, day)；
(2) efficiency data：
1) crane productivity ratio p (handling load/natural time) (summation, year, month, day)；
2) utilization grade U0~U9 (working cycles number of times x projected lives/statistic years) of crane；
3) Crane Load spectral coefficient Kd (handling load/(rated load x working cycles number of times))；
4) crane complete machine real work rank；
5) crane remaining projected life (real work rank corresponding projected life (the year)-reality input time limit)；
6) crane work ratio：The complete machine accumulated operating time/natural time (summation, year, month, day)；
7) mechanism work ratio：Each mechanism accumulated operating time/natural time (summation, year, month, day)；
8) crane average operation number of times：Complete machine working cycles number of times/complete machine accumulated operating time (summation, year, the moon,
Day)；
9) each mechanism average operation number of times：Each mechanism working cycles number of times/each mechanism accumulated operating time (summation, year,
The moon, day)；
10) the crane single working time：The complete machine accumulated operating time/working cycles number of times (summation, year, month, day)；
11) each mechanism single working time：Each mechanism accumulated operating time/working cycles number of times (summation, year, month, day)；
12) gear work ratio：Per mechanism each gear working time/each mechanism accumulated operating time (summation, year, month, day)；
(3) device data：
1) capacity utilization：The equipment accumulated operating time/complete machine accumulated operating time (summation, year, month, day)；
2) equipment average motion number of times：Number of equipment action/complete machine working cycles number of times (summation, year, month, day)；
3) equipment electrical endurance：The equipment accumulated operating time (life cycle)；
4) the plant machinery life-span：Equipment accumulation work times (life cycle)；
(4) fault data：
1) crane fault rate：The crane number of stoppages/complete machine accumulated operating time (summation, year, month, day)；
2) crane fault rate-time (consecutive days) curve map；
3) all types of failure fault rates：The all types of number of stoppages/complete machine accumulated operating time (summation, year, the moon)；
(5) big data is extracted：
1) operating power consumption：Average, maximum, the minimum operating power consumption of all types of cranes；
2) load energy consumption：Average, maximum, the minimum load energy consumption of all types of cranes；
3) crane productivity ratio：Average, maximum, the minimum production rate of all types of cranes；
4) the utilization grade of crane：Average, maximum, the minimum utilization grade of all types of cranes；
5) Crane Load spectral coefficient：Average, maximum, the minimum load spectral coefficient of all types of cranes；
6) crane service life：Average, maximum, the minimum service life of all types of cranes；
7) other efficiency datas are extracted：Ibid；
8) capacity utilization：The all types of various equipment of crane are average, maximum, minimum utilization rate；
9) equipment average motion number of times：The all types of various equipment of crane are average, maximum, minimum average B configuration action frequency；
10) equipment life：All kinds, average, maximum, the minimum electrical endurance of the equipment of various brands, mechanical life；
11) crane fault rate：Average, maximum, the minimum fault rate of all types of cranes, each crane manufacturer rises
Heavy-duty machine fault rate；
12) all types of failure fault rates：The all types of failures of all types of cranes are average, maximum, minimum fault rate.
Claims (3)
1. a kind of big data plateform system based on MHCIMS, it is characterised in that：Including MHCIMS data acquisition modules and backstage
Service platform, described background service platform receives the data of MHCIMS data collecting module collecteds；Described MHCIMS data
The PLC system that acquisition module is connected to scene through Agent servers gathers the data of each sensing equipment of crane；
Described background service platform includes big data processing module, database, the data service module based on B/S frameworks and end
End subscriber, described big data processing module is bi-directionally connected with database, and described big data processing module input is received
The data of MHCIMS data collecting module collecteds, its output end connect through the data service module based on B/S frameworks and terminal user
Connect；
Described background service platform sets a variety of data communication interfaces, including wireless communication interface, wired communication interface and USB
Interface；
Described big data processing module is responsible for reception, decoding, storage, computing and the statistics of data, generates service data, and will
Service data is distributed to terminal user by the data service module based on B/S frameworks.
2. a kind of method of work of the big data plateform system based on MHCIMS, it is characterised in that：Comprise the following steps：
Step 1：The crane data of PLC system collection site sensing equipment；Described crane data are included in industry spot
All kinds of protection signals, crane operating status information, operation information and creation data in crane facility information, crane facility
Information；
Step 2：By the crane data feedback of collection to Agent servers；The data address that PLC system is gathered is existed
Agent servers carry out communication setting；Described address refers to crane data in the collection address of PLC registers；Described is logical
Letter refers to PLC system and Agent servers are communicated by RS-485 or Modbus communications protocol, and in advance in Agent clothes
The setting of business device and the one-to-one data receiver address in collection address of PLC registers；
Step 3：Agent servers are by numeric feedback to MHCIMS data acquisition modules, and MHCIMS data acquisition modules are to collection
Crane data handled；The processing item of described crane data includes following project：
1) type of crane, technical parameter；
2) crane master equipment list (MEL)；
3) energy consumption of crane：
4) supply voltage of crane feeder ear, electric current；
5) operational order of crane；
6) the handling load of crane；
7) the working cycles number of times of crane；
8) accumulated operating time of crane；
9) each mechanism working cycles number of times of crane；
10) crane each mechanism accumulated operating time；
11) crane visual plant service data：It is dynamic including motor, brake, major control equipment and dominant touch device
Make number of times, actuation time, equipment accumulated operating time and equipment replacement information data；
12) fault alarm of crane；
Each processing item carries out the processing of data, the fault alarm processing method of such as crane according to each different processing methods
For：
Alarm structure：Driving number-mechanism-classification-code；
Alarm sending method：Timing sends, sent in real time or self-defined transmission；
Alarm sending mode；Alarm only sends failure code when sending, or sends failure code and related data, transmission content
For every group of multiple analog quantitys, 15 groups of data are sent altogether, start first 2 seconds and latter 1 second of trouble point, number of every 200 milliseconds of collections
According to；
Step 4：In several ways crane data are transmitted to big data processing module；
Step 5：Big data processing module is analyzed the crane data received, described analysis include decoding, storage,
Computing and statistics；Analysis item includes following project：
1) operating power consumption：Average, maximum, the minimum operating power consumption of all types of cranes；
2) load energy consumption：Average, maximum, the minimum load energy consumption of all types of cranes；
3) crane productivity ratio：Average, maximum, the minimum production rate of all types of cranes；
4) the utilization grade of crane：Average, maximum, the minimum utilization grade of all types of cranes；
5) Crane Load spectral coefficient：Average, maximum, the minimum load spectral coefficient of all types of cranes；
6) crane service life：Average, maximum, the minimum service life of all types of cranes；
7) capacity utilization：The all types of various equipment of crane are average, maximum, minimum utilization rate；
8) equipment average motion number of times：The all types of various equipment of crane are average, maximum, minimum average B configuration action frequency；
9) equipment life：All kinds, average, maximum, the minimum electrical endurance of the equipment of various brands, mechanical life；
10) crane fault rate：Average, maximum, the minimum fault rate of all types of cranes, each crane manufacturer crane
Fault rate；
11) all types of failure fault rates：The all types of failures of all types of cranes are average, maximum, minimum fault rate；
Step 6：Big data processing module is by Internet network by data publication to terminal user.
3. a kind of method of work of big data plateform system based on MHCIMS according to claim 2, it is characterised in that：
Various ways described in step 4 include in the following manner：Data direct copying transmission means, GPRS transmission mode and local network transport
Mode；
Described data direct copying transmission means is as follows：
For the equipment without network environment at present, immediate data copy is supported, by the industry spot crane dependency number collected
According to exporting as prescribed form and preserving on a storage device, storage device is linked into big data processing module by lead-in mode
Store data into big data processing module；Described prescribed form includes driving model, structure, time and numerical value；
Described GPRS transmission mode is as follows：The industry spot crane data collected are passed through into common network GPRS/3G nets
Network is transferred directly in big data processing module；
Described local network transport mode is as follows：The industry spot crane data collected are transferred to by WLAN
At least one ground monitoring center LDC；Ground monitoring center LDC passes through specialized network VPN or public after receiving crane data
Network is by crane data transfer into big data processing module.
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| CN108829063A (en) * | 2018-07-02 | 2018-11-16 | 深圳市佳运通电子有限公司 | Heating furnace Integrity Management centralized control equipment |
| CN111624972A (en) * | 2019-02-27 | 2020-09-04 | 中国石油化工股份有限公司 | Method for diagnosing state of equipment of production process and machine readable storage medium |
| CN112249909A (en) * | 2020-10-20 | 2021-01-22 | 苏州大学应用技术学院 | Intelligent crane control system and control method |
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| CN107272571B (en) | 2019-07-19 |
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