CN108957236A - A kind of mechanical breakdown monitoring system based on internet big data - Google Patents
A kind of mechanical breakdown monitoring system based on internet big data Download PDFInfo
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- CN108957236A CN108957236A CN201810865419.1A CN201810865419A CN108957236A CN 108957236 A CN108957236 A CN 108957236A CN 201810865419 A CN201810865419 A CN 201810865419A CN 108957236 A CN108957236 A CN 108957236A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/08—Locating faults in cables, transmission lines, or networks
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Abstract
The invention discloses a kind of mechanical breakdown monitoring systems based on internet big data, electronic marker is carried out to various kinds of equipment first, then collected part of appliance key operation data is transferred in data analysis module using damage testing internet of things sensors and Corrosion monitoring internet of things sensors, data are subjected to fault diagnosis and fault prediction processing by data analysis module again, and data are transmitted to cloud by treated, constitution equipment cloud system, can remote real-time monitoring equipment running status by client；Data are acquired by internet sensor, internet big data is relied on and is analyzed, with remote real-time monitoring and predict equipment fault.
Description
Technical field
The present invention relates to internet big data technical field more particularly to a kind of mechanical breakdowns based on internet big data
Monitoring system.
Background technique
In the industrial production, equipment use for a long time will appear failure problems, and just the personnel of needing repairing safeguard for this, but
It is that major part is all that equipment goes wrong at this stage, notifies maintenance man to carry out maintenance of showing up by worker, and is unable to reach logical in real time
The effect known, and can not accurately be predicted in maintenance process, it solves the problems, such as, therefore, solves the problems, such as this kind of aobvious
It obtains particularly important.
Summary of the invention
In view of the deficiencies of the prior art, the present invention provides a kind of, and the mechanical breakdown based on internet big data monitors system
System, is acquired data by internet sensor, relies on internet big data and analyzed, with remote real-time monitoring and pre-
Measurement equipment failure.
To solve the above-mentioned problems, the present invention provides a kind of mechanical breakdown monitoring system based on internet big data,
Electronic marker is carried out to various kinds of equipment first, then utilizes damage testing internet of things sensors and Corrosion monitoring internet of things sensors
Collected part of appliance key operation data is transferred in data analysis module, then is carried out data by data analysis module
Fault diagnosis and fault prediction processing, and data are transmitted to cloud by treated, constitution equipment cloud system, passes through client
Remote real-time monitoring equipment running status.
Further improvement lies in that: unique identity is done to equipment using two dimensional code, RFID tag or Bluetooth label, is had
There is the equipment of sensor cluster to pass through network to transmit data, do not have the equipment of sensor cluster, then by handheld terminal into
Row two dimensional code, RFID tag or Bluetooth label are read out.
Further improvement lies in that: damage testing internet sensor be used to acquire cracky device data, as motor,
Pump, speed reducer, bearing, Corrosion monitoring internet sensor be used to acquire perishable equipment, as reaction kettle, measuring tank,
Delivery pump.
Further improvement lies in that: the cracky device data is using vibrating sensor and signal processing, sonic sensor
Data acquisition is carried out with the mode of signal processing and manual inspection data input.
Further improvement lies in that: the perishable equipment using sonic sensor and signal processing, imaging sensor with
Image recognition and the mode of manual inspection data input carry out data acquisition.
Further improvement lies in that: the equipment of easy to leak is using sonic sensor and signal processing, imaging sensor and image
The mode of identification and manual inspection data input carries out data acquisition.
Further improvement lies in that: the work inspection data input is carried out by industry APP, the work inspection data input packet
Life period of an equipment management information is included, such as equipment set-up time, inspection cycle, maintenance time, the maintenance frequency, maintenance and replacement
Situation facilitates device predicted property to safeguard that helping to find the problem in time timely feedbacks to arrange timing inspection to replace.
Further improvement lies in that: the equipment cloud system realizes reception, storage, display and the analysis of data；Receiving can be with
Using distributed high concurrent structure, the reliability of data communication is ensured；Storage uses high performance database and back mechanism,
Ensure the safety of data；Display is shown using industrial instrument display panel or big data visualization technique；Analyzing is then
The clusters of data, classification, incidence relation analysis are carried out using the technology of machine learning and artificial intelligence, realize the detection of failure with
Prediction.
The beneficial effects of the present invention are: be acquired data by internet sensor, rely on internet big data into
Row analysis, with remote real-time monitoring and predicts equipment fault, and development equipment monitoring and fault diagnosis cloud system all kinds of is set with above-mentioned
Standby sensor is attached with APP terminal, realizes that the on-line real time monitoring of equipment and visualization are alarmed, the event of timely discovering device
Barrier.
The problem of for the actual use of the chemical industry key equipment such as motor, pump, bearing, storage tank, measuring tank, to target
Equipment key production run data carry out real-time monitoring, and acquisition not only includes voltage, electric current, temperature, acceleration (vibration), pressure
Etc. physical quantitys data, further include the image datas such as picture, video.Data are transmitted to large data center, complete factory's key equipment
Digital intelligent upgrading, realize cloud in equipment, lay the foundation to set up industrial cloud platform, while it is remote to can establish equipment
Journey condition monitoring system completes acquisition and management to facility information and Condition Monitoring Data.Key equipment data are counted
According to analysis and signal processing, image analysis is carried out to image data, studies the model of system equipment fault diagnosis and fault prediction, is realized
The health control of the chemical industry key equipments such as chemical industry factory motor, pump, bearing, storage tank and measuring equipment, and further investigated can be effective
Reflect the state parameter index system of equipment fault and performance degradation degree.
Specific embodiment
In order to deepen the understanding of the present invention, the present invention is further described below in conjunction with embodiment, the present embodiment
For explaining only the invention, it is not intended to limit the scope of the present invention..
Present embodiments provide a kind of mechanical breakdown monitoring system based on internet big data, first to various kinds of equipment into
Then row electronic marker utilizes damage testing internet of things sensors and Corrosion monitoring internet of things sensors by collected equipment portion
Part key operation data is transferred in data analysis module, then data are carried out fault diagnosis and fault prediction by data analysis module
It manages, and data are transmitted to cloud by treated, constitution equipment cloud system, it can remote real-time monitoring equipment by client
Operating status.Unique identity is done to equipment using two dimensional code, RFID tag or Bluetooth label, with sensor cluster
Equipment transmits data by network, does not have the equipment of sensor cluster, then carries out two dimensional code by handheld terminal, RFID is marked
Label or Bluetooth label are read out.Damage testing internet sensor be used to acquire cracky device data, as motor,
Pump, speed reducer, bearing, Corrosion monitoring internet sensor be used to acquire perishable equipment, as reaction kettle, measuring tank,
Delivery pump.The cracky device data is using vibrating sensor and signal processing, sonic sensor and signal processing and people
The mode of work inspection data input carries out data acquisition.The perishable equipment is using sonic sensor and signal processing, figure
As the mode of sensor and image recognition and manual inspection data input carries out data acquisition.The equipment of easy to leak uses sound wave
Sensor and signal processing, imaging sensor and image recognition and the mode of manual inspection data input carry out data acquisition.
The work inspection data input is carried out by industry APP, and the work inspection data input includes life period of an equipment management letter
Breath such as the equipment set-up time, inspection cycle, maintenance time, repairs the frequency, maintenance and replacement situation, to arrange timing inspection
Replacement.The equipment cloud system realizes reception, storage, display and the analysis of data；Reception can use distributed high concurrent
Structure ensures the reliability of data communication；Storage uses high performance database and back mechanism, ensures the safety of data；It is aobvious
Show and is shown using industrial instrument display panel or big data visualization technique；Analysis is then using machine learning and artificial
The technology of intelligence carries out the cluster of data, classification, incidence relation analysis, realizes the detection and prediction of failure.
Data are acquired by internet sensor, internet big data is relied on and is analyzed, remotely to supervise in real time
Control and predict equipment fault, development equipment monitoring and fault diagnosis cloud system, with above-mentioned various kinds of equipment sensor and APP terminal into
Row connection realizes that the on-line real time monitoring of equipment and visualization are alarmed, the failure of timely discovering device.
The problem of for the actual use of the chemical industry key equipment such as motor, pump, bearing, storage tank, measuring tank, to target
Equipment key production run data carry out real-time monitoring, and acquisition not only includes voltage, electric current, temperature, acceleration (vibration), pressure
Etc. physical quantitys data, further include the image datas such as picture, video.Data are transmitted to large data center, complete factory's key equipment
Digital intelligent upgrading, realize cloud in equipment, lay the foundation to set up industrial cloud platform, while it is remote to can establish equipment
Journey condition monitoring system completes acquisition and management to facility information and Condition Monitoring Data.Key equipment data are counted
According to analysis and signal processing, image analysis is carried out to image data, studies the model of system equipment fault diagnosis and fault prediction, is realized
The health control of the chemical industry key equipments such as chemical industry factory motor, pump, bearing, storage tank and measuring equipment, and further investigated can be effective
Reflect the state parameter index system of equipment fault and performance degradation degree.
Claims (8)
1. a kind of mechanical breakdown monitoring system based on internet big data, it is characterised in that: carry out electricity to various kinds of equipment first
Son mark, is then closed collected part of appliance using damage testing internet of things sensors and Corrosion monitoring internet of things sensors
Key operation data is transferred in data analysis module, then data are carried out fault diagnosis and fault prediction processing by data analysis module,
And will treated that data are transmitted to cloud, constitution equipment cloud system, by client can remote real-time monitoring equipment transport
Row state.
2. a kind of mechanical breakdown monitoring system based on internet big data as described in claim 1, it is characterised in that: use
Two dimensional code, RFID tag or Bluetooth label do unique identity to equipment, and the equipment with sensor cluster passes through network
Data are transmitted, do not have the equipment of sensor cluster, then passes through handheld terminal and carries out two dimensional code, RFID tag or bluetooth mark
Label are read out.
3. a kind of mechanical breakdown monitoring system based on internet big data as described in claim 1, it is characterised in that: described
Damage testing internet sensor is used to acquire cracky device data, such as motor, pump, speed reducer, bearing, the Corrosion monitoring
Internet sensor is used to acquire perishable equipment, such as reaction kettle, measuring tank, delivery pump.
4. a kind of mechanical breakdown monitoring system based on internet big data as claimed in claim 3, it is characterised in that: described
Cracky device data is recorded using vibrating sensor and signal processing, sonic sensor and signal processing and manual inspection information
The mode entered carries out data acquisition.
5. a kind of mechanical breakdown monitoring system based on internet big data as claimed in claim 3, it is characterised in that: described
Perishable equipment is using sonic sensor and signal processing, imaging sensor and image recognition and manual inspection data input
Mode carry out data acquisition.
6. a kind of mechanical breakdown monitoring system based on internet big data as described in claim 1, it is characterised in that: easily seep
The equipment of leakage is using sonic sensor and signal processing, imaging sensor and image recognition and the side of manual inspection data input
Formula carries out data acquisition.
7. a kind of mechanical breakdown monitoring system based on internet big data as described in claim 4-6 is any, feature exist
In: the work inspection data input is carried out by industry APP, and the work inspection data input includes life period of an equipment management
Information such as the equipment set-up time, inspection cycle, maintenance time, repairs the frequency, maintenance and replacement situation, to arrange timing to patrol
Inspection replacement.
8. a kind of mechanical breakdown monitoring system based on internet big data as described in claim 1, it is characterised in that: described
Reception, storage, display and the analysis of equipment cloud system realization data；Distributed high concurrent structure can be used by receiving, and be ensured
The reliability of data communication；Storage uses high performance database and back mechanism, ensures the safety of data；Display is using industry
Instrument display panel or big data visualization technique are shown；Analysis is then the technology using machine learning and artificial intelligence
Cluster, the classification, incidence relation analysis for carrying out data, realize the detection and prediction of failure.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810865419.1A CN108957236A (en) | 2018-08-01 | 2018-08-01 | A kind of mechanical breakdown monitoring system based on internet big data |
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810865419.1A CN108957236A (en) | 2018-08-01 | 2018-08-01 | A kind of mechanical breakdown monitoring system based on internet big data |
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| CN108957236A true CN108957236A (en) | 2018-12-07 |
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| CN201810865419.1A Pending CN108957236A (en) | 2018-08-01 | 2018-08-01 | A kind of mechanical breakdown monitoring system based on internet big data |
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Cited By (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110657837A (en) * | 2019-09-29 | 2020-01-07 | 杭州和利时自动化有限公司 | Intelligent diagnosis device and intelligent diagnosis system |
| CN110703094A (en) * | 2019-10-15 | 2020-01-17 | 联桥网云信息科技（长沙）有限公司 | Motor monitoring method |
| CN110806734A (en) * | 2019-11-08 | 2020-02-18 | 河北大多科技有限公司 | Real-time intelligent inspection system for industrial equipment |
| CN111123096A (en) * | 2019-10-15 | 2020-05-08 | 联桥网云信息科技（长沙）有限公司 | Internet of things motor monitoring platform |
| CN111275213A (en) * | 2020-01-17 | 2020-06-12 | 安徽华创环保设备科技有限公司 | Mechanical equipment fault monitoring system based on big data |
| CN111597222A (en) * | 2020-04-01 | 2020-08-28 | 国网浙江省电力有限公司嘉兴供电公司 | Intelligent detection system and detection method for high-voltage combined fuse |
| CN111678708A (en) * | 2020-06-12 | 2020-09-18 | 石家庄开发区天远科技有限公司 | Vibration analysis system for predicting and identifying mechanical fault |
| CN111861215A (en) * | 2020-07-21 | 2020-10-30 | 重庆现代建筑产业发展研究院 | Community intelligent equipment autonomous maintenance order dispatching system and method based on Internet of things |
| CN112487216A (en) * | 2020-12-11 | 2021-03-12 | 苏州协同创新智能制造装备有限公司 | Mould fault prejudging system |
| CN113219913A (en) * | 2021-03-31 | 2021-08-06 | 宇辰系统科技股份有限公司 | Factory building management system |
| CN113483814A (en) * | 2021-06-22 | 2021-10-08 | 北京德风新征程科技有限公司 | Mechanical fault monitoring system based on internet big data |
| CN113483815A (en) * | 2021-06-23 | 2021-10-08 | 北京德风新征程科技有限公司 | Mechanical fault monitoring system based on industrial big data |
| CN113721207A (en) * | 2021-08-31 | 2021-11-30 | 北京无线电测量研究所 | Early warning method and system for radar time-lapse service life replacement based on big data |
-
2018
- 2018-08-01 CN CN201810865419.1A patent/CN108957236A/en active Pending
Cited By (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110657837A (en) * | 2019-09-29 | 2020-01-07 | 杭州和利时自动化有限公司 | Intelligent diagnosis device and intelligent diagnosis system |
| CN110703094A (en) * | 2019-10-15 | 2020-01-17 | 联桥网云信息科技（长沙）有限公司 | Motor monitoring method |
| CN111123096A (en) * | 2019-10-15 | 2020-05-08 | 联桥网云信息科技（长沙）有限公司 | Internet of things motor monitoring platform |
| CN110806734A (en) * | 2019-11-08 | 2020-02-18 | 河北大多科技有限公司 | Real-time intelligent inspection system for industrial equipment |
| CN111275213B (en) * | 2020-01-17 | 2020-09-15 | 安徽华创环保设备科技有限公司 | Mechanical equipment fault monitoring system based on big data |
| CN111275213A (en) * | 2020-01-17 | 2020-06-12 | 安徽华创环保设备科技有限公司 | Mechanical equipment fault monitoring system based on big data |
| CN111597222A (en) * | 2020-04-01 | 2020-08-28 | 国网浙江省电力有限公司嘉兴供电公司 | Intelligent detection system and detection method for high-voltage combined fuse |
| CN111678708A (en) * | 2020-06-12 | 2020-09-18 | 石家庄开发区天远科技有限公司 | Vibration analysis system for predicting and identifying mechanical fault |
| CN111861215A (en) * | 2020-07-21 | 2020-10-30 | 重庆现代建筑产业发展研究院 | Community intelligent equipment autonomous maintenance order dispatching system and method based on Internet of things |
| CN112487216A (en) * | 2020-12-11 | 2021-03-12 | 苏州协同创新智能制造装备有限公司 | Mould fault prejudging system |
| CN113219913A (en) * | 2021-03-31 | 2021-08-06 | 宇辰系统科技股份有限公司 | Factory building management system |
| CN113483814A (en) * | 2021-06-22 | 2021-10-08 | 北京德风新征程科技有限公司 | Mechanical fault monitoring system based on internet big data |
| CN113483815A (en) * | 2021-06-23 | 2021-10-08 | 北京德风新征程科技有限公司 | Mechanical fault monitoring system based on industrial big data |
| CN113721207A (en) * | 2021-08-31 | 2021-11-30 | 北京无线电测量研究所 | Early warning method and system for radar time-lapse service life replacement based on big data |
| CN113721207B (en) * | 2021-08-31 | 2023-10-31 | 北京无线电测量研究所 | Early warning method and system for replacing life parts in radar based on big data |
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Application publication date: 20181207 |
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