CN105967063A - Failure analyzing and handling system and method of maintenance platform - Google Patents

Failure analyzing and handling system and method of maintenance platform Download PDF

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Publication number
CN105967063A
CN105967063A CN201610323520.5A CN201610323520A CN105967063A CN 105967063 A CN105967063 A CN 105967063A CN 201610323520 A CN201610323520 A CN 201610323520A CN 105967063 A CN105967063 A CN 105967063A
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China
Prior art keywords
fault
signal
field
failure
type
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CN201610323520.5A
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Chinese (zh)
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CN105967063B (en
Inventor
余丹炯
杨仁民
王晓海
汤斌斌
樊岳标
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SHANGHAI ZPMC ELECTRIC Co Ltd
Shanghai Zhenghua Heavy Industries Co Ltd
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SHANGHAI ZPMC ELECTRIC Co Ltd
Shanghai Zhenghua Heavy Industries Co Ltd
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Priority to CN201610323520.5A priority Critical patent/CN105967063B/en
Publication of CN105967063A publication Critical patent/CN105967063A/en
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    • BPERFORMING OPERATIONS; TRANSPORTING
    • B66HOISTING; LIFTING; HAULING
    • B66CCRANES; LOAD-ENGAGING ELEMENTS OR DEVICES FOR CRANES, CAPSTANS, WINCHES, OR TACKLES
    • B66C13/00Other constructional features or details
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B66HOISTING; LIFTING; HAULING
    • B66CCRANES; LOAD-ENGAGING ELEMENTS OR DEVICES FOR CRANES, CAPSTANS, WINCHES, OR TACKLES
    • B66C15/00Safety gear

Abstract

The invention discloses a failure analyzing and handling system and method of a maintenance platform. The system comprises a failure distribution module, a failure analyzing module, a failure handling module and a field data interface. The field data interface receives a failure signal, recognizes the type of the failure signal according to the signal features of the failure signal and writes the type into the failure signal. The failure distribution module is connected with the field data interface, receives the failure signal with the type written, adds distribution fields to the failure signal, and then sends the processed failure signal to the failure analyzing module or the failure handling module according to the distribution fields and the failure type. The failure analyzing and handling system and method of the maintenance platform can conduct diagnosis and maintenance effectively and accurately in time within a short period of time, equipment failures are handled for users, and the shutdown duration of a crane is shortened.

Description

Repair and maintenance platform fault analysis process system and method
Technical field
The present invention relates to crane gear repair and maintenance platform fault solve system and method, more specifically, Relate to a kind of repair and maintenance platform fault analysis process system and method.
Background technology
At present, domestic and international science and technology new technique (such as artificial intelligence, cybernetics and theory of information etc.) and existing For the fast development of network technology, the fault diagnosis of remote equipment, maintenance technology and function obtain constantly Ground enriches and perfect.Its application develops into aviation, sea from single Mechanical device diagnosis The ocean complication system such as boats and ships and hydraulic and electric engineering.The most remotely diagnosis maintenance platform is of a great variety, Various Functions, but currently available technology does not also have the fault diagnosis for harbour lifting equipment with long-range Maintenance platform.
Constantly expand along with whole world crane facility spreads all over scope, and the complexity of each region port environment Property and multiformity, will realize carrying out each wharf crane parts remote supervisory and have the biggest technology and choose War, but also there is the strongest realistic meaning.For manufacturer, will be big by remote supervisory Big reduce service engineer to time at scene and expense, becoming of manpower and material resources can not only be saved in a large number This, the most also can provide long-distance Maintenance Service in the shortest time to on-the-spot wharf crane fault, reduce Harbour user loses.
Summary of the invention
For the above-mentioned problems in the prior art, it is an object of the invention to provide a kind of repair and maintenance platform Fault analysis processing system and method.
For achieving the above object, the present invention adopts the following technical scheme that
A kind of repair and maintenance platform fault analysis process system, including fault distribution module, failure analysis module, Fault processing module, field data interface.Field data interface fault-signal, and according to fault The signal characteristic of signal distinguishes the type of fault-signal, and by type Write fault signal.Fault is divided Join module and connect field data interface, receive the fault-signal after writing type and fault-signal is added Adding allocation field, further according to allocation field and fault type, the fault-signal after processing sends to event Barrier analyzes module or fault processing module.
According to one embodiment of the invention, fault-signal includes data field, reserved field and check word Section, data field is the content of fault-signal, and reserved field is writeable clear data section.
According to one embodiment of the invention, in the reserved field of the type Write fault signal of fault-signal.
According to one embodiment of the invention, allocation field was added before data field, allocation field bag Include the identification code that instruction current failure signal should transmit to failure analysis module or fault processing module.
For achieving the above object, the present invention adopts the following technical scheme that
A kind of repair and maintenance platform fault analysis and processing method, including: receive fault-signal, and according to fault The signal characteristic of signal distinguishes the type of fault-signal, and by type Write fault signal.Reception is write Enter the fault-signal after type and fault-signal is added allocation field, further according to allocation field and event Barrier type, the fault-signal after processing sends to failure analysis module or fault processing module.
According to one embodiment of the invention, fault-signal includes data field, reserved field and check word Section, data field is the content of fault-signal, and reserved field is writeable clear data section.
According to one embodiment of the invention, by the reserved field of the type Write fault signal of fault-signal In.
According to one embodiment of the invention, allocation field was added before data field, allocation field The mark should transmitted to failure analysis module or fault processing module including instruction current failure signal Code.
In technique scheme, the repair and maintenance platform fault analysis process system of the present invention and method can Diagnose at short notice, effectively, accurately, timely and safeguard, solving subscriber equipment event Barrier, shorten crane downtime.
Accompanying drawing explanation
Fig. 1 is the structural representation of repair and maintenance platform fault analysis process system of the present invention;
Fig. 2 is the structural representation of fault-signal;
Fig. 3 is the flow chart of repair and maintenance platform fault analysis and processing method of the present invention.
Detailed description of the invention
Technical scheme is further illustrated below in conjunction with the accompanying drawings with embodiment.
With reference to Fig. 1, the first open a kind of repair and maintenance platform fault analysis process system of the present invention, it is main Framework includes that fault distribution module 2, failure analysis module 3, fault processing module 4, field data connect Mouth 1 etc..The system of the present invention using fault-signal (real time fail data and historical data) as system The input of system, by failure analysis result (the such as information such as rate of breakdown and the fault generation degree of association) And for the suggested solution of dependent failure as the output of system, and present in webpage and fixed Phase submits to user.Simultaneously at server end by setting up a database relation mould reasonable, efficient Type, makes the management information system of the data after collection and company combine, so that the utilization of Various types of data reaches To optimum state, reach the Deep integrating of industrial equipment and information system, and thus bring more preferably Consumer's Experience.
As depicted in figs. 1 and 2, field data interface 1 receives fault-signal, and according to fault-signal Signal characteristic distinguish the type of fault-signal, and by type Write fault signal.Fault-signal bag Including data field 102, reserved field 103 and check field 104, data field 102 is believed for fault Number content, reserved field 103 is writeable clear data section.The type write event of fault-signal In the reserved field 103 of barrier signal.
With continued reference to Fig. 1, fault distribution module 2 connects field data interface 1, receive write type it After fault-signal and to fault-signal add allocation field 101, further according to allocation field 101 and therefore Barrier type, the fault-signal after processing sends to failure analysis module 3 or fault processing module 4. Preferably, allocation field 101 was added before data field 102, and allocation field 101 includes instruction Current failure signal should transmit to failure analysis module 3 or the identification code of fault processing module 4.
The position that allocation field 101 is added, before data field 102, is namely believed in whole fault Number beginning data segment, such benefit is when system is at read failure signal and when process, can With several bytes at first by only read data packet, current fault-signal just can be known at first Should transmit to failure analysis module 3 or fault processing module 4, thus shorten what data processed Time.
The above-mentioned reprocessing for fault-signal can be referred to as again information fusion.The letter of multiple data sources Breath is blended in the data base being pre-designed, and sets up include fault, bypasses, controls including conjunction etc. Crane fault model, controls dividing of conjunction including accident analysis, bypass analysis, crane working condition The models such as analysis.
Based on fault, bypass, control conjunction etc. and analyze model, normalized fault after utilizing data cleansing And status information, carry out statistical analysis by means of big data analysis tool simultaneously, can be with analytic statistics Correlation degree between fault and the frequency of fault generation, the probability of fault generation in future.According to Big data results and FTA, can the fault of generation real-time to harbour, just make True decision-making, it is recommended that reasonably solution.Utilize the correlation degree between the fault analyzed, and It not by equipment fault isolation, it appeared that the potential problems that fault occurs, finds out the root of problem, And solve rapidly the chain problem of fault, reduce rate of breakdown further.Added up by big data tool The fault occurrence frequency analyzed will quickly position high frequency fault and is efficiently treated through it.It is simultaneous for Fault can be predicted by the probability of equipment fault generation in future, and its accuracy rate is largely Relying on capacity and the accuracy of initial data, failure predication model based on machine learning is carried out point Analysis processes, and utilizes analysis result to form preventive maintenance decision-making, and then is committed to preventive maintenance row Dynamic, find the device element need to safeguarded or change in time, it is provided that maintenance decision support and spare parts purchasing meter Draw the service of grade.
The above-mentioned fault correlation that focuses on analyzes and processes, according to user scene feedback information and history Breakdown Maintenance information upload onto the server according to unified standard, server end is according to big data analysis The model that instrument is set up in advance carries out continuous machine learning, and constantly iteration, forms optimum fault solution Certainly scheme, the judgement of the fastest time causes the most possible association reason of field device failure.Use simultaneously Family can be according to the fault correlation of the solution offer that big data analysis draws to carry out failure cause Location, can investigate failure cause in conjunction with on-the-spot complicated actual environment simultaneously flexibly.User can be by The fault solution updated uploads onto the server end, for the optimization of fault solution model library, Be conducive to improving the accuracy of fault solution.
Use Construction of Fault Tree phenomenon of the failure-failure cause relational model and combine big data analysis Expert's fault diagnosis realizes fault correlation and processes.Fault correlation diagnosis point is carried out as a example by motor Analysis illustrates.Fault diagnosis tree describes the inherence between phenomenon of the failure and failure cause with tree structure figure Contact;Following table is the basic data of fault tree.
According to the phenomenon of the failure that motor is different, set up corresponding failure tree-model, carry out qualitative point of fault tree Analysis (fault tree simplifies or modularity), it is judged that electrical fault comes from mechanical breakdown or electrically event Barrier, after determining fault type, (calculation of relationship degree and probability divide then to carry out quantitative analysis Analysis etc.), it is judged that determine most possible failure cause, it is possible to be preliminary failure cause with this conclusion Qualitative.
Under the failure cause premise that above-mentioned fault tree models is derived, utilize big data analysis and based on The model construction of the complicated algorithms such as neutral net, for fault existing in diagnosis rule storehouse, Ke Yigeng Add and accurately judge its failure cause.And for the new fault not having in diagnosis rule storehouse, fault tree due to Lack corresponding diagnostic knowledge, and it is qualitative to cannot be carried out preliminary fault, can be by means of neutral net On the model of complicated algorithm, new fault sample is learnt automatically, train, update fault knowledge, shape The Failure Diagnostic Code storehouse of Cheng Xin, it is simple to exact failure diagnoses.
Neural network algorithm has the strongest robustness, has the strongest self-learning capability, by training Unceasing study, is continuously replenished and improves the knowledge of self.Neutral net through suitably training has solution Certainly simple mathematical model and the difficult tractable control Process Problems of description rule.Support to adapt to simultaneously Line runs, and can the most qualitatively and quantitatively operate, the strong adaptability of neutral net and information fusion energy Power allows to be simultaneously entered the most different fault messages, and carries out parallel processing, it is achieved fault is believed Cease integrated and fusion treatment.The neutral net trained can store the knowledge about fault treating procedure, Can be directly from historical failure information learning.Its failure diagnostic process is as follows: 1) calls in fault diagnosis and knows Know storehouse, including weights and threshold values.2) the every phenomenon of the failure being known to occur is inputted.3) base is utilized Big data analysis tool in neural network failure model carries out mass data analysis thus carries out fault and examine Disconnected.The output layer neuron that output result probability is forward the most at last is found out, and obtains it most possible Failure cause, obtain out of order final solution.
On the other hand, as it is shown on figure 3, for above-mentioned processing system, invention additionally discloses a kind of repair and maintenance Platform fault analysis and processing method, comprises the following steps:
S1: receive fault-signal, and the type of the signal characteristic differentiation fault-signal according to fault-signal, And by type Write fault signal.
S2: by the reserved field of the type Write fault signal of fault-signal.Fault-signal includes number According to field, reserved field and check field, data field is the content of fault-signal, and reserved field is Writeable clear data section.
S3: receive the fault-signal after write type and to fault-signal interpolation allocation field, will divide Join field to add before data field.Allocation field includes indicating current failure signal should transmit to event Barrier analyzes module or the identification code of fault processing module.
S4: further according to allocation field and fault type, the fault-signal transmission after processing divides to fault Analysis module or fault processing module.
Unlike the most traditional fault handling method.The present invention is by fault unified, that concentrate Information management, is presented on distributed, scattered fault message in Central Control Room, and its fault message includes In stockyard, all of bridge crane, tyre crane, the mechanical breakdown of AGV, electric fault, automatization's task are held Row procedure fault, and present in Central Control Room gui interface in a unified format, its format content is main Lasting including source of failure fault rank, fault type, failure-description, time of failure, fault The information such as time.Operator must check in time and select affect the fault of situ machine work and submit to To project manager, if submitting to fault message will affect its work efficiency, and then impact operation the most in time Member's job rating, actively monitors fault, and positive feedback by urging operator further.Project manager The fault submitted to by centralized distribution operator, and distributing by type to each chief technology officer, can very fast, More precisely find fault to be correlated with director and corresponding service engineer, as early as possible operator is fed back Failure problems solve, improve further fault and solve efficiency, reduce machine stopping time, improve machine Device work efficiency, is greatly lowered the economic loss that machine down is caused.
Project management system is used to carry out crane facility troubleshooting, can be from macroscopic view and microcosmic point Hold the progress of overall crane facility troubleshooting and the occurrence cause of concrete crane fault and Result, accomplishes fault precise positioning, and fault person liable precisely process, and can effectively carry out project General safety management and control.And the priority that crane breaks down can be considered simultaneously, totally manage from project Reason aspect carries out the resource optimization such as technical staff, equipment and balance, effectively arranges the use of resource, Critical breakdowns can be solved as early as possible, recover the safety in production of crane facility as early as possible.
Repair and maintenance platform fault analysis process system of the present invention and method can reach following economy, safety Property, the beneficial effect such as technical.
Economy aspect
For manufacturer, reach remote supervisory and maintenance by repair and maintenance platform, it is possible to reduce safeguard Engineer, to on-the-spot time and expense, has not only saved the cost of substantial amounts of man power and material, also can Maintenance service is provided to equipment fault within the shortest time.For the customer, fault can be passed through Analysis processing computer aid system, understands the ruuning situation of equipment and various abundant statistical report form, And quickly understood the solution of dependent failure by Web, simultaneously by means of project group manage-ment system Carry out classification troubleshooting, it will help the quick solution of on-the-spot crane fault, further reduce Owing to shutting down the loss that operation brings, it is achieved provide the clipper service of doulbe-sides' victory for client and enterprise.
Safety aspect
Native system safety mainly uses procotol to limit, the many pregnancies of simultaneity factor reinforced by safety equipment The means such as part checking ensure.General headquarters and harbour is carried out in virtual VPN mode by Internet network On-the-spot network connects, it is ensured that the safety of network connection and stability, can effectively prevent weight Data are wanted to leak and network attack.Safety equipment reinforcing aspect, make use of fort machine, carries out whole dimension Platform core system O&M of keeping tie examines management and control with safety, it is possible to each in real-time collecting and monitoring network environment The system mode of individual ingredient, security incident, network activity, it is possible to effective guarantee network and number According to not being damaged, the most all operations in system carry out videograph, in order to late problems is reviewed.
Technical aspect
The big data resource of fault is the core realizing remote online fault diagnosis omnibearing to crane fault Heart resource.Big data analysis technique can be by the different pieces of information such as structuring and unstructured data source Fault message standardizes, and is gathered in consistent system.The process processed at big data fault with In place of simple structural data processing mode is very different.One of such as ETL instrument The big data analysis tool of Power Center of Informatica company, is pointed to the lifting of each harbour The fusion of machine fault message etc. is the important ring building data warehouse with convergence, by from dissimilar Data source extraction needed for data (fault message, control conjunction etc.), through data cleansing, finally According to the data warehouse model pre-defined, load data in data warehouse.Extract (carries Take) by interface extraction source data, such as ODBC, specific database connection, Transform (turns Change) data that will extract, be converted to target data structure through service logic analysis, and realize collecting, Load (loading) is loaded in server target warehouse through conversion and the data collected, it is achieved fault The batch such as information loads, it is possible to by the data of the fault message unification of different systems to same data structure In storehouse, in order in the displaying on foreground.
Phenomenon of the failure based on fault tree-failure cause model carries out initial characterization as described above And quantitative failure reason analysis, then by based on the big number of ETL instrument combining neural network algorithm According to analysis, jointly build the fault model of equipment, more Accurate Analysis failure cause, and constantly will What the physical fault reason input of user scene feedback carried out fault model storehouse does not stops iteration and engineering Practise, derive failure reason analysis the most accurately, will be able to science, effectively analysis fault occur Relatedness, can provide the user with fault solution and later maintenance suggestion the most accurately simultaneously.
Being incorporated into by project management system in fault analysis and handling computer aided system, the division of labor is clear and definite, Responsibility is clear, can be effectively improved the efficiency of troubleshooting.
The present invention has expanded the fault analysis processing system application in crane field the most further, fills up The market vacancy that crane field is long-term, the present invention and the information system of company is integrated simultaneously, Further increase the whole-process management level of company's crane facility.
Those of ordinary skill in the art is it should be appreciated that above embodiment is intended merely to The bright present invention, and it is not used as limitation of the invention, as long as at the spirit of the present invention In, change, the modification of embodiment described above all will be fallen in the range of claims of the present invention.

Claims (8)

1. a repair and maintenance platform fault analysis process system, it is characterised in that including:
Fault distribution module, failure analysis module, fault processing module, field data interface;
Described field data interface fault-signal, and distinguish event according to the signal characteristic of fault-signal The type of barrier signal, and by type Write fault signal;
Described fault distribution module connects described field data interface, receives the fault after write type Fault-signal is also added allocation field by signal, further according to described allocation field and fault type, at general Fault-signal after reason sends to failure analysis module or fault processing module.
2. repair and maintenance platform fault analysis process system as claimed in claim 1, it is characterised in that:
Described fault-signal includes that data field, reserved field and check field, described data field are The content of fault-signal, described reserved field is writeable clear data section.
3. repair and maintenance platform fault analysis process system as claimed in claim 2, it is characterised in that:
In the reserved field of the type Write fault signal of described fault-signal.
4. repair and maintenance platform fault analysis process system as claimed in claim 2, it is characterised in that:
Described allocation field was added before data field, and described allocation field includes indicating current failure Signal should transmit the identification code to failure analysis module or fault processing module.
5. a repair and maintenance platform fault analysis and processing method, it is characterised in that including:
Receive fault-signal, and the type of the signal characteristic differentiation fault-signal according to fault-signal, and By in type Write fault signal;
Receive the fault-signal after write type and to fault-signal interpolation allocation field, further according to institute Stating allocation field and fault type, the fault-signal after processing sends to failure analysis module or fault Processing module.
6. repair and maintenance platform fault analysis and processing method as claimed in claim 5, it is characterised in that:
Described fault-signal includes that data field, reserved field and check field, described data field are The content of fault-signal, described reserved field is writeable clear data section.
7. repair and maintenance platform fault analysis and processing method as claimed in claim 6, it is characterised in that:
By in the reserved field of the type Write fault signal of fault-signal.
8. repair and maintenance platform fault analysis and processing method as claimed in claim 6, it is characterised in that:
Allocation field being added before data field, described allocation field includes indicating current failure letter Number identification code that should transmit to failure analysis module or fault processing module.
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Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106698197A (en) * 2016-12-01 2017-05-24 上海振华重工电气有限公司 System for online diagnosis and preventive maintenance of container crane based on big data
CN108563945A (en) * 2018-03-26 2018-09-21 烽火通信科技股份有限公司 A kind of isomery method for realizing redundancy and realize system
CN111930081A (en) * 2020-07-15 2020-11-13 西门子工厂自动化工程有限公司 Method and device for monitoring AGV state, edge device and storage medium
CN112249910A (en) * 2020-10-20 2021-01-22 上海振华重工(集团)股份有限公司 Processing method and system for shore bridge abnormity, computing equipment and storage medium
CN112541170A (en) * 2020-12-21 2021-03-23 武汉联影医疗科技有限公司 System maintenance method, device, computer equipment and storage medium
CN114604768A (en) * 2022-01-24 2022-06-10 杭州大杰智能传动科技有限公司 Intelligent tower crane maintenance management method and system based on fault identification model

Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2009037084A1 (en) * 2007-09-18 2009-03-26 Siemens Aktiengesellschaft A method and system for failure analysis and diagnosis
CN102024181A (en) * 2009-09-10 2011-04-20 上海宝信软件股份有限公司 Artificial intelligence maintenance system and method
CN102570602A (en) * 2011-12-04 2012-07-11 江苏省电力公司南京供电公司 Fault comprehensive processing platform and method of distribution network
CN103178974A (en) * 2011-12-21 2013-06-26 中国银联股份有限公司 Fault processing system and method
CN103618945A (en) * 2013-11-18 2014-03-05 乐视致新电子科技(天津)有限公司 Remote maintenance method and equipment for terminal
CN103902731A (en) * 2014-04-16 2014-07-02 国家电网公司 Intelligent information maintenance method based on knowledge base inquiry
CN104320075A (en) * 2014-10-13 2015-01-28 晖保智能科技(上海)有限公司 Photovoltaic power station fault analysis and diagnosis system
CN104486673A (en) * 2014-12-15 2015-04-01 四川长虹电器股份有限公司 Fault handling platform system and fault handling method
CN105262616A (en) * 2015-09-21 2016-01-20 浪潮集团有限公司 Failure repository-based automated failure processing system and method

Patent Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2009037084A1 (en) * 2007-09-18 2009-03-26 Siemens Aktiengesellschaft A method and system for failure analysis and diagnosis
CN102024181A (en) * 2009-09-10 2011-04-20 上海宝信软件股份有限公司 Artificial intelligence maintenance system and method
CN102570602A (en) * 2011-12-04 2012-07-11 江苏省电力公司南京供电公司 Fault comprehensive processing platform and method of distribution network
CN103178974A (en) * 2011-12-21 2013-06-26 中国银联股份有限公司 Fault processing system and method
CN103618945A (en) * 2013-11-18 2014-03-05 乐视致新电子科技(天津)有限公司 Remote maintenance method and equipment for terminal
CN103902731A (en) * 2014-04-16 2014-07-02 国家电网公司 Intelligent information maintenance method based on knowledge base inquiry
CN104320075A (en) * 2014-10-13 2015-01-28 晖保智能科技(上海)有限公司 Photovoltaic power station fault analysis and diagnosis system
CN104486673A (en) * 2014-12-15 2015-04-01 四川长虹电器股份有限公司 Fault handling platform system and fault handling method
CN105262616A (en) * 2015-09-21 2016-01-20 浪潮集团有限公司 Failure repository-based automated failure processing system and method

Cited By (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106698197A (en) * 2016-12-01 2017-05-24 上海振华重工电气有限公司 System for online diagnosis and preventive maintenance of container crane based on big data
CN108563945A (en) * 2018-03-26 2018-09-21 烽火通信科技股份有限公司 A kind of isomery method for realizing redundancy and realize system
CN108563945B (en) * 2018-03-26 2020-07-07 烽火通信科技股份有限公司 Heterogeneous redundancy implementation method and system
CN111930081A (en) * 2020-07-15 2020-11-13 西门子工厂自动化工程有限公司 Method and device for monitoring AGV state, edge device and storage medium
CN112249910A (en) * 2020-10-20 2021-01-22 上海振华重工(集团)股份有限公司 Processing method and system for shore bridge abnormity, computing equipment and storage medium
CN112249910B (en) * 2020-10-20 2023-06-27 上海振华重工(集团)股份有限公司 Method, system, computing equipment and storage medium for processing bank bridge exception
CN112541170A (en) * 2020-12-21 2021-03-23 武汉联影医疗科技有限公司 System maintenance method, device, computer equipment and storage medium
CN114604768A (en) * 2022-01-24 2022-06-10 杭州大杰智能传动科技有限公司 Intelligent tower crane maintenance management method and system based on fault identification model

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