CN108535033A - Virtual-sensor and its health monitoring intelligent decision system - Google Patents
Virtual-sensor and its health monitoring intelligent decision system Download PDFInfo
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- CN108535033A CN108535033A CN201710123469.8A CN201710123469A CN108535033A CN 108535033 A CN108535033 A CN 108535033A CN 201710123469 A CN201710123469 A CN 201710123469A CN 108535033 A CN108535033 A CN 108535033A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
- G01M99/00—Subject matter not provided for in other groups of this subclass
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
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Abstract
The present invention provides a kind of virtual-sensors, configuration part setting emulation relational model, storage part stores the emulation relational model, parameter in emulation relational model is directly measured by physical sensors to be obtained, physical sensors are mounted on equipment and are easy the position measured, the initial parameter of measurement is sent to processing unit by physical sensors, initial parameter is brought in emulation relational model into the parameter that measured point is calculated by processing unit, due to the parameter of the indirect measurement point using indirect method measuring apparatus, therefore it can be in measuring limit environment and cannot measure to avoid measuring point, or be not suitable for placing physical sensors and the parameter at measuring point cannot being obtained at the measuring point of equipment, therefore, the virtual-sensor of the present invention can not only adapt to measuring point is not suitable for placing physical sensors measurement in extreme environment or at measuring point, and it is at low cost.
Description
Technical field
The invention belongs to computer based modeling technique fields, and in particular to a kind of virtual-sensor and its health monitoring
Intelligent decision system.
Background technology
In industry 4.0 a critically important application system be exactly physical message system (Cyber Physical System,
CPS).In the CPS of health monitoring of equipment, need largely to carry out collecting device status data using sensor, to accumulate data
It is analyzed.
Physical sensors have been widely used in the measurement and monitoring of the multiple products such as modern mechanical, electronics.Physics passes
Sensor usually to physical phenomenon directly measure and these measurement amounts is converted into measurement data, passes to control system into one
Step processing.Since the relevant hardware cost of physical sensors is usually very high and sometimes unreliable, it is measured point sometimes and is in the limit
In environment, be not suitable for placing the reasons such as physical hardware devices.Such as：The variation of the blowing pressure of tire and road in automobilism
Friction etc. between face；Pressure sensor, which is placed on wheel, can face many difficulties, and the friction between tire and road surface is difficult to directly
Connect measurement.
Invention content
The present invention is to carry out to solve the above-mentioned problems, and it is an object of the present invention to provide a kind of when the measuring point of equipment is measuring pole
Be not suitable for the physical parameter for capableing of the measuring point of measuring apparatus when placing physical sensors in limit environment or at the measuring point of equipment,
And virtual-sensor at low cost.
The present invention provides a kind of virtual-sensor, the parameters for being measured point in measuring apparatus, which is characterized in that packet
It includes：At least one physical sensors, the initial parameter for measuring each indirect measurement point of equipment under test in real time；Configuration part is used for
The emulation relational model for setting initial parameter and being measured between the parameter of point；Storage part, for storing emulation relational model；Place
Reason portion is connect with all physical sensors, and the initial parameter of measurement is sent to processing unit by physical sensors, and processing unit is according to object
The initial parameter for managing sensor measurement obtains initial parameter and the parameter for being measured point based on emulation relational model.
Further, it in virtual-sensor provided by the invention, can also have the feature that：Wherein, relationship is emulated
It can also include the virtual initial parameter obtained by Virtual Machining Process or virtual emulation process in model.
Further, it in virtual-sensor provided by the invention, can also have the feature that：Wherein, configuration part is also
For setting Virtual Machining Process or virtual emulation process.
The present invention also provides a kind of health monitoring intelligent decision systems, which is characterized in that including：Sensor unit is used
In the data of collecting device different monitoring points, including above-mentioned virtual-sensor and physical sensors；Data memory module,
Data for storing virtual-sensor and physical sensors acquisition；Data analysis module, for storing data memory module
Data carry out analyzing processing obtain analysis result；Display module, the analysis result obtained for display data analysis module；With
And alarm module, alarm signal is sent out according to analysis result.
Further, it in health monitoring intelligent decision system provided by the invention, can also have the feature that：Its
In, analysis result includes：The health status of the equipment of simulation, the life of equipment of prediction and service life, prediction generate failure
Position.
Advantages of the present invention is as follows：
According to virtual-sensor according to the present invention, configuration part setting emulation relational model, storage part stores the emulation
Relational model, the parameter emulated in relational model are directly measured by physical sensors and are obtained, and physical sensors are mounted on equipment appearance
The initial parameter of measurement is sent to processing unit by the position easily measured, physical sensors, and processing unit brings initial parameter into emulation
The parameter of measured point is calculated in relational model, the parameter of the indirect measurement point due to using indirect method measuring apparatus, because
This can be in measuring limit environment to avoid measuring point cannot measure or the measuring point of equipment at be not suitable for place physical sensors
And the parameter at measuring point cannot be obtained, therefore, virtual-sensor of the invention can not only adapt to measuring point in extreme environment or
Be not suitable for placing the measurement of physical sensors at measuring point, and at low cost.
The health monitoring intelligent decision system of the present invention is total due to virtual-sensor using the present invention and physical sensors
Same monitoring device, therefore it is capable of the parameter of the various needs of monitoring device, so as to simulate health status, assisted diagnosis equipment
State, prediction life of equipment, service life, the position of the failure of judgement.
Description of the drawings
Fig. 1 is the structural schematic diagram of virtual-sensor in the present invention；
Fig. 2 is the structural schematic diagram of health monitoring intelligent decision system in the present invention.
Specific implementation mode
It is real below in order to make the technical means, the creative features, the aims and the efficiencies achieved by the present invention be easy to understand
Example combination attached drawing is applied to be specifically addressed the virtual-sensor and its health monitoring intelligent decision system of the present invention.
<Structure one>
Virtual-sensor 100 is for the parameter at measuring point 210 on detection device 200.
As shown in Figure 1, in the present embodiment, virtual-sensor 100 includes：Configuration part 110, storage part 120, processing unit
130, at least one physical sensors 140.
Initial parameter of the physical sensors 140 for measuring each indirect measurement point of equipment under test 200 in real time.Configuration part 110
Relational model is emulated for setting.Storage part 120 is used to store the emulation relational model of the setting of configuration part 110.Emulation relationship mould
The parameter at measuring point 210 that type obtains as needed is based on scheduled rule settings.The quantity of physical sensors 140 and each object
Reason sensor 140 needs the indirect measurement point in the equipment measured directly to measure obtained ginseng by what is needed in emulation relational model
Number determines.It needs directly to measure obtained parameter in emulation relational model to be the simple parameter for being easy measurement and obtaining, using letter
Single physical sensors measurement can be obtained.
Processing unit 130 is connected with physical sensors 140, and physical sensors 140 are by the original of each indirect measurement point of measurement
Beginning parameter is sent to processing unit 130, at the emulation relational model that processing unit 130 is set based on configuration part 110 according to initial parameter
Reason obtains the parameter at measuring point 210.
In addition, the parameter in emulation relational model can also include to be obtained by Virtual Machining Process or virtual emulation process
Virtual initial parameter.Virtual Machining Process or virtual emulation process are set by configuration part 110.Storage part 120 can also be deposited
The parameter at measuring point 210 that the real-time initial parameter and processing unit 130 that storage physical sensors 140 measure obtain after handling.
<Structure two>
Health monitoring intelligent decision system 300 is used for simulating health status, assisted diagnosis equipment state, pre- measurement equipment
Period, service life, the position of the failure of judgement.
Health monitoring intelligent decision system 300 includes：Sensor unit 310, data memory module 320, data analysis mould
Block 330, display module (not shown), alarm module 340.
Sensor unit 310 is used for the real time data of each monitoring point of measuring apparatus, and sensor unit 310 includes at least one
Above-mentioned virtual-sensor 100 and physical sensors 311, all virtual-sensors 100 and physical sensors 311 are according to equipment
It is distributed, all monitoring points disclosure satisfy that the key position of monitoring device, simulate whole equipment health status, and prediction makes
With period and service life and failure.The parameter that all virtual-sensors 100 and physical sensors 311 acquire is by signal processing, number
It is sent to data memory module 320 after being packed according to preparation, data processing.
Data memory module 320 is used to store the data that virtual-sensor 100 and physical sensors 311 acquire, and data are deposited
It stores up module 320 and the data received from sensor unit 310 is subjected to data cleansing, then stored in a predetermined manner.
The data of storage are sent to data analysis module 330 by data memory module 320.
Data analysis module 330 is used to the data that data memory module 320 stores carrying out analyzing processing to obtain analysis knot
Fruit.The data stored in data memory module 320 are counted, analyzed, compared, emulated etc. by data analysis module 330 pair to be set
For healthy simulation is carried out, life of equipment and service life are predicted, and equipment event is judged according to the real time data that each sensor is sent
Barrier.
Display module for display data analysis module 330 simulate health status, the service life of prediction, prediction longevity
The position etc. of life and the failure judged.
Alarm module 340 is used to alarm when the equipment somewhere that data analysis module 330 judges is broken down.
The above embodiment is the preferred case of the present invention, is not intended to limit protection scope of the present invention.
Claims (5)
1. a kind of virtual-sensor, the parameter for being measured point in measuring apparatus, which is characterized in that including：
At least one physical sensors, the initial parameter for measuring each indirect measurement point of equipment under test in real time；
Configuration part, for setting the emulation relational model between the initial parameter and the parameter of the measured point；
Storage part, for storing the emulation relational model；
Processing unit is connect with all physical sensors,
The initial parameter of measurement is sent to processing unit by the physical sensors, and the processing unit is according to the physical sensing
The initial parameter that device measures obtains the parameter of the initial parameter and the measured point based on the emulation relational model.
2. virtual-sensor according to claim 1, it is characterised in that：
It wherein, can also be virtual comprising being obtained by Virtual Machining Process or virtual emulation process in the emulation relational model
Initial parameter.
3. virtual-sensor according to claim 2, it is characterised in that：
Wherein, the configuration part is additionally operable to set the Virtual Machining Process or virtual emulation process.
4. a kind of health monitoring intelligent decision system, which is characterized in that including：
Sensor unit is used for the data of collecting device different monitoring points, including described in claims 1 to 3 any claim
Virtual-sensor and physical sensors；
Data memory module, the data for storing the virtual-sensor and physical sensors acquisition；
Data analysis module, the data for storing the data memory module carry out analyzing processing and obtain analysis result；
Display module, the analysis result obtained for showing the data analysis module；And
Alarm module sends out alarm signal according to the analysis result.
5. health monitoring intelligent decision system according to claim 4, it is characterised in that：
Wherein, the analysis result includes：The health status of the equipment of simulation, the life of equipment of prediction and service life, prediction
Generate the position of failure.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
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| CN201710123469.8A CN108535033A (en) | 2017-03-03 | 2017-03-03 | Virtual-sensor and its health monitoring intelligent decision system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
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| CN201710123469.8A CN108535033A (en) | 2017-03-03 | 2017-03-03 | Virtual-sensor and its health monitoring intelligent decision system |
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| CN108535033A true CN108535033A (en) | 2018-09-14 |
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| Application Number | Title | Priority Date | Filing Date |
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| CN201710123469.8A Pending CN108535033A (en) | 2017-03-03 | 2017-03-03 | Virtual-sensor and its health monitoring intelligent decision system |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110070603A (en) * | 2019-03-21 | 2019-07-30 | 江苏东方国信工业互联网有限公司 | One kind is based on the twinborn furnace body analogue system of number and its method |
| CN111259494A (en) * | 2020-01-08 | 2020-06-09 | 上海索辰信息科技有限公司 | Health monitoring and analyzing method for heavy machine equipment |
| CN113632024A (en) * | 2019-03-27 | 2021-11-09 | 西门子股份公司 | Virtual sensor on superior machine platform |
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| US5864773A (en) * | 1995-11-03 | 1999-01-26 | Texas Instruments Incorporated | Virtual sensor based monitoring and fault detection/classification system and method for semiconductor processing equipment |
| CN105627981A (en) * | 2016-03-20 | 2016-06-01 | 西安科技大学 | Mining subsidence deformation prediction and forecast system |
| CN105738587A (en) * | 2016-01-12 | 2016-07-06 | 山东科技大学 | Water quality monitoring system |
| CN106355811A (en) * | 2016-07-22 | 2017-01-25 | 河南城建学院 | Electrical fire monitoring system |
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2017
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Patent Citations (4)
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| US5864773A (en) * | 1995-11-03 | 1999-01-26 | Texas Instruments Incorporated | Virtual sensor based monitoring and fault detection/classification system and method for semiconductor processing equipment |
| CN105738587A (en) * | 2016-01-12 | 2016-07-06 | 山东科技大学 | Water quality monitoring system |
| CN105627981A (en) * | 2016-03-20 | 2016-06-01 | 西安科技大学 | Mining subsidence deformation prediction and forecast system |
| CN106355811A (en) * | 2016-07-22 | 2017-01-25 | 河南城建学院 | Electrical fire monitoring system |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110070603A (en) * | 2019-03-21 | 2019-07-30 | 江苏东方国信工业互联网有限公司 | One kind is based on the twinborn furnace body analogue system of number and its method |
| CN113632024A (en) * | 2019-03-27 | 2021-11-09 | 西门子股份公司 | Virtual sensor on superior machine platform |
| CN111259494A (en) * | 2020-01-08 | 2020-06-09 | 上海索辰信息科技有限公司 | Health monitoring and analyzing method for heavy machine equipment |
| CN111259494B (en) * | 2020-01-08 | 2021-01-15 | 上海索辰信息科技股份有限公司 | Health monitoring and analyzing method for heavy machine equipment |
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