CN113064399A - Industrial monitoring software prediction maintenance system based on big data distributed programming framework - Google Patents
Industrial monitoring software prediction maintenance system based on big data distributed programming framework Download PDFInfo
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- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B23/00—Testing or monitoring of control systems or parts thereof
- G05B23/02—Electric testing or monitoring
- G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
- G05B23/0218—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults
- G05B23/0243—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults model based detection method, e.g. first-principles knowledge model
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- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
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Abstract
The invention relates to the technical field of monitoring software maintenance systems, in particular to an industrial monitoring software prediction maintenance system based on a big data distributed programming framework, which comprises a data acquisition system, a relational database, a monitoring management maintenance platform and a monitoring management terminal, wherein the output end of the data acquisition system is unidirectionally and electrically connected with a data transmission node, and the data acquisition system and the data transmission node are in data transmission through a wireless network; the invention provides an industrial monitoring software prediction maintenance system based on a big data distributed programming framework, which has the advantages of being capable of predicting and maintaining monitoring software, effectively improving the processing efficiency of monitoring data and further ensuring the long-term stable operation of monitoring equipment, and solves the problems that the existing monitoring software maintenance system is poor in safety and cannot accurately judge the operation state of the monitoring equipment, so that the monitoring equipment is prone to failure and cannot timely troubleshoot potential safety hazards.
Description
Technical Field
The invention relates to the technical field of monitoring software maintenance systems, in particular to an industrial monitoring software prediction maintenance system based on a big data distributed programming framework.
Background
In the process of informatization, computer network equipment is widely applied to various management and business activities in industrial activities, and monitoring equipment which can be accessed by the existing computer network is provided. With the development of networks changing day by day, the data scale faced by people is huge, the use scene of the distributed system changes complicatedly, and although the Hadoop distributed system is designed to have a high fault-tolerant mechanism, few methods can perform fault early warning on the Hadoop distributed system in the use process to remind clients of maintaining the software system in time so as to avoid loss caused by faults. The method is a new branch of the software research field of the 'system health', and is used for representing whether the use condition of a Hadoop distributed system is normal or not. By software health is meant the degree of ability of software to perform a specified task during use.
Since the construction of the monitoring system cannot be done at once and needs to be invested by stages, a monitoring device with high expandability needs to be selected. When capacity expansion is needed in the future, the original equipment is continuously used, and only new equipment needs to be added. Instead of discarding the original equipment and purchasing the equipment again. When the monitoring equipment has a tiny program fault, an enterprise needs to send an engineer to a field for maintenance, but most of the enterprises face extensive client group regions, so that the equipment is isolated, the connection between the equipment and the plant level and the industry cannot be established, a large amount of manpower and material resources need to be invested, the operation cost of the enterprise is increased, and the market competitiveness of the enterprise is reduced.
The currently used monitoring software maintenance system is poor in safety, the running state of monitoring equipment cannot be accurately judged, the monitoring equipment is prone to failure, potential safety hazards cannot be timely eliminated, the normal production operation flow of an enterprise can be affected, and great economic loss is caused.
Disclosure of Invention
The invention aims to provide an industrial monitoring software prediction maintenance system based on a big data distributed programming framework, which has the advantages of being capable of predicting and maintaining monitoring software, effectively improving the processing efficiency of monitoring data and further ensuring the long-term stable operation of monitoring equipment, and solves the problems that the existing monitoring software maintenance system is poor in safety, cannot accurately judge the operation state of the monitoring equipment, is easy to break down and cannot timely troubleshoot potential safety hazards.
In order to achieve the purpose, the invention provides the following technical scheme: the utility model provides an industry monitoring software prediction maintenance system based on big data distributing type programming frame, includes data acquisition system, relational database, control management maintenance platform and control management terminal, the one-way electricity of data acquisition system's output is connected with data transmission node, and carries out data transmission through wireless network between data acquisition system and the data transmission node, the one-way electricity of data transmission node's number output end is connected with data processing center, data processing center's output is connected for one-way electricity with relational database's input, relational database's output is connected for one-way electricity with control management maintenance platform's input, be connected for one-way electricity between control management maintenance platform and the control management terminal.
Preferably, the data acquisition system comprises a data acquisition module, a data reading module and a wireless data terminal module, wherein the output end of the data acquisition module is in one-way electric connection with the input end of the data reading module, and the output end of the data reading module is in one-way electric connection with the input end of the wireless data terminal module.
Preferably, the data processing center comprises a data receiving module, a data analyzing module, a data processing module and a data converting module, wherein the data receiving module is in unidirectional electrical connection with the data analyzing module, and the data processing module is in unidirectional electrical connection with the data analyzing module and the data converting module respectively.
Preferably, the monitoring, managing and maintaining platform comprises a real-time diagnosis and analysis module, an exception handling module, a prediction and maintenance module and an energy consumption analysis module, the real-time diagnosis module is electrically connected with the exception handling module, and the input end and the output end of the prediction and maintenance module are respectively electrically connected with the exception handling module and the energy consumption analysis module.
Preferably, the output end of the data processing center is electrically connected with a storage module in a bidirectional manner, the storage module adopts a monitoring hard disk, and the storage space of the storage module is 4TB and the model is WD40EJRX or ST4000VX 007.
Preferably, the data acquisition module is an entrance guard lock controller, an environment monitoring collector and a remote controller, and the environment monitoring collector comprises a gas sensor, a water level sensor and a temperature and humidity sensor.
Preferably, the real-time diagnosis analysis module is configured to perform data analysis on the operation state data through a rule engine, and the exception handling module is configured to analyze the model operation state data of the monitoring hardware device.
Preferably, the prediction maintenance module is configured to perform data analysis on the operation state data to implement real-time inspection on the corresponding hardware device, and the energy consumption analysis module is configured to perform data analysis on the operation state data and the log data.
Preferably, the monitoring management terminal comprises a mobile management terminal, a printing terminal, a system application server, a communication gateway system and a screen wall.
Preferably, the monitoring management terminal displays data to operation and maintenance personnel in a page form, and supports real-time transmission of the displayed data to the mobile terminal, wherein the displayed data comprises operation state data, log data and related data obtained through data analysis service.
Compared with the prior art, the invention has the following beneficial effects:
the invention provides an industrial monitoring software prediction maintenance system based on a big data distributed programming framework, which has the advantages of being capable of predicting and maintaining monitoring software, effectively improving the processing efficiency of monitoring data and further ensuring the long-term stable operation of monitoring equipment, and solves the problems that the existing monitoring software maintenance system is poor in safety and cannot accurately judge the operation state of the monitoring equipment, so that the monitoring equipment is prone to failure and cannot timely troubleshoot potential safety hazards.
Drawings
FIG. 1 is a schematic block diagram of a predictive maintenance system of the present invention;
FIG. 2 is a schematic block diagram of a data acquisition system of the present invention;
FIG. 3 is a functional block diagram of a data processing center according to the present invention;
FIG. 4 is a schematic block diagram of a monitoring, management and maintenance platform according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1-4, an industrial monitoring software predicting and maintaining system based on a big data distributed programming framework includes a data collecting system, a relational database, a monitoring and managing platform and a monitoring and managing terminal, wherein an output end of the data collecting system is unidirectionally and electrically connected with a data transmission node, the data collecting system and the data transmission node perform data transmission via a wireless network, a data output end of the data transmission node is unidirectionally and electrically connected with a data processing center, an output end of the data processing center is unidirectionally and electrically connected with an input end of the relational database, an output end of the relational database is unidirectionally and electrically connected with an input end of the monitoring and managing platform, the monitoring and managing platform is unidirectionally and electrically connected with the monitoring and managing terminal, the system can predict and maintain monitoring software, and can effectively improve monitoring and managing data processing efficiency, and then can guarantee the advantage of supervisory equipment long-term steady operation, solve the monitoring software that uses at present and maintain the system security relatively poor, can not judge supervisory equipment's running state accurately, lead to supervisory equipment to break down easily, can't in time investigate the problem of potential safety hazard.
In this embodiment, the data acquisition system includes the data acquisition module, data reading module and wireless data terminal module, the output of data acquisition module is one-way electricity with the input of data reading module and is connected, the output of data reading module is one-way electricity with the input of wireless data terminal module and is connected, through the data acquisition module, data reading module and wireless data terminal module's setting, can monitor and information acquisition industrial equipment and environment, can send data integration to data transmission node simultaneously.
In this embodiment, the data processing center includes a data receiving module, a data analyzing module, a data processing module and a data conversion module, the data receiving module is in one-way electrical connection with the data analyzing module, the data processing module is in one-way electrical connection with the data analyzing module and the data conversion module, through the arrangement of the data receiving module, the data analyzing module, the data processing module and the data conversion module, the data collected by the monitoring equipment can be analyzed and processed to obtain queriable data, and the queriable data can be compared with the relational database.
In this embodiment, the monitoring, managing and maintaining platform includes a real-time diagnosis and analysis module, an exception handling module, a prediction and maintenance module and an energy consumption analysis module, the real-time diagnosis module is electrically connected to the exception handling module, an input end and an output end of the prediction and maintenance module are electrically connected to the exception handling module and the energy consumption analysis module, respectively, and through the setting of the real-time diagnosis and analysis module, the exception handling module, the prediction and maintenance module and the energy consumption analysis module, data analysis can be performed on the running state data of the monitoring software, so that the working state of the monitoring software can be predicted and maintained.
In this embodiment, the two-way electricity of data processing center's output is connected with storage module, and storage module adopts the control level hard disk, and storage module's memory space is 4TB, and the model is WD40EJRX or ST4000VX007, through storage module's setting, is convenient for store the inquiry data, is favorable to the calling of inquiry data, and can store the inquiry data in the relational database.
In this embodiment, the data acquisition module is entrance guard lock controller, environmental monitoring collector and remote control ware, and the environmental monitoring collector includes gas sensor, level sensor and temperature and humidity sensor, through data acquisition module's setting, is convenient for monitoring information's collection, is favorable to monitoring industrial environment data.
In this embodiment, the real-time diagnosis analysis module is configured to perform data analysis on the operation state data through the rule engine, the exception handling module is configured to analyze the model operation state data of the monitoring hardware device, and the real-time diagnosis analysis and the alarm of the corresponding hardware device can be implemented through the setting of the real-time diagnosis analysis module and the exception handling module, so that the exception condition of the corresponding hardware device can be analyzed and an exception point can be located.
In this embodiment, the prediction maintenance module is configured to perform data analysis on the operation state data to implement real-time inspection on corresponding hardware devices, the energy consumption analysis module is configured to perform data analysis on the operation state data and log data, and through the setting of the prediction maintenance module and the energy consumption analysis module, a potential abnormal problem of the device can be obtained according to real-time inspection, so as to obtain a use condition, a behavior habit and an energy consumption condition of the quantum computer.
In this embodiment, the monitoring management terminal includes a mobile management terminal, a printing terminal, a system application server, a communication gateway system and a screen wall, and through the setting of the monitoring management terminal, industrial monitoring data information can be visually represented, so that hidden dangers can be timely eliminated.
In this embodiment, the monitoring management terminal shows data to the operation and maintenance personnel in the form of a page, and supports real-time transmission of the shown data to the mobile terminal, and the shown data includes running state data, log data and related data obtained through data analysis service, and through the setting of the monitoring management terminal, the operation and maintenance personnel can conveniently check monitoring contents, and the running state of the operation and maintenance personnel monitoring equipment can be observed conveniently.
The working principle is as follows: firstly, a data acquisition module acquires industrial monitoring information, a data reading module reads the monitoring information and transmits the monitoring data to a wireless data terminal module, the wireless data terminal module transmits the monitoring data to a data transmission node, the data transmission node integrates and transmits the monitoring data to a data processing center, the data processing center can analyze and process the data acquired by monitoring equipment to obtain queryable data, and can compare the inquired data with the relational database, the relational database sends the inquired data to the monitoring management maintenance platform, the monitoring management maintenance platform performs data analysis on the running state data of the monitoring software, and the working state of the monitoring software can be predicted and maintained, and finally, operation and maintenance personnel can check monitoring contents and observe the running state of the monitoring equipment through the monitoring management terminal, so that the industrial monitoring system can be maintained in time.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (10)
1. The utility model provides an industry monitoring software predictive maintenance system based on big data distribution formula programming frame, includes data acquisition system, relational database, control management maintenance platform and control management terminal, its characterized in that: the one-way electricity of data acquisition system's output is connected with the data transmission node, and carries out data transmission through wireless network between data acquisition system and the data transmission node, the one-way electricity of data transmission node's number output end is connected with the data processing center, the output of data processing center is connected for one-way electricity with the input of relational database, the output of relational database is connected for one-way electricity with the input of control management maintenance platform, be connected for one-way electricity between control management maintenance platform and the control management terminal.
2. The industrial monitoring software predictive maintenance system based on the big data distributed programming framework is characterized in that: the data acquisition system comprises a data acquisition module, a data reading module and a wireless data terminal module, wherein the output end of the data acquisition module is in one-way electric connection with the input end of the data reading module, and the output end of the data reading module is in one-way electric connection with the input end of the wireless data terminal module.
3. The industrial monitoring software predictive maintenance system based on the big data distributed programming framework is characterized in that: the data processing center comprises a data receiving module, a data analyzing module, a data processing module and a data conversion module, wherein the data receiving module is in one-way electric connection with the data analyzing module, and the data processing module is in one-way electric connection with the data analyzing module and the data conversion module respectively.
4. The industrial monitoring software predictive maintenance system based on the big data distributed programming framework is characterized in that: the monitoring, managing and maintaining platform comprises a real-time diagnosis and analysis module, an exception handling module, a prediction and maintenance module and an energy consumption analysis module, wherein the real-time diagnosis module is electrically connected with the exception handling module, and the input end and the output end of the prediction and maintenance module are respectively electrically connected with the exception handling module and the energy consumption analysis module.
5. The industrial monitoring software predictive maintenance system based on the big data distributed programming framework is characterized in that: the data processing center is characterized in that the output end of the data processing center is electrically connected with a storage module in a bidirectional mode, the storage module adopts a monitoring hard disk, the storage space of the storage module is 4TB, and the model is WD40EJRX or ST4000VX 007.
6. The industrial monitoring software predictive maintenance system based on the big data distributed programming framework is characterized in that: the data acquisition module is entrance guard lock controller, environmental monitoring collector and remote control ware, the environmental monitoring collector includes gas sensor, level sensor and temperature and humidity sensor.
7. The big data distributed programming framework based industrial monitoring software predictive maintenance system according to claim 4, wherein: the real-time diagnosis analysis module is used for carrying out data analysis on the running state data through the rule engine, and the exception handling module is used for analyzing the model running state data of the monitoring hardware equipment.
8. The big data distributed programming framework based industrial monitoring software predictive maintenance system according to claim 4, wherein: the prediction maintenance module is used for carrying out data analysis on the operation state data so as to realize real-time inspection on corresponding hardware equipment, and the energy consumption analysis module is used for carrying out data analysis on the operation state data and the log data.
9. The industrial monitoring software predictive maintenance system based on the big data distributed programming framework is characterized in that: the monitoring management terminal comprises a mobile management terminal, a printing terminal, a system application server, a communication gateway system and a screen wall.
10. The industrial monitoring software predictive maintenance system based on the big data distributed programming framework is characterized in that: the monitoring management terminal displays data to operation and maintenance personnel in a page mode and supports real-time transmission of the displayed data to the mobile terminal, and the displayed data comprises operation state data, log data and related data obtained through data analysis service.
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| CN114396978A (en) * | 2022-01-20 | 2022-04-26 | 常州禾木信息科技有限公司 | Big data intelligent online real-time monitoring analysis method and early warning system |
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