CN109407002A - Motor device is health management system arranged - Google Patents
Motor device is health management system arranged Download PDFInfo
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- CN109407002A CN109407002A CN201811094790.9A CN201811094790A CN109407002A CN 109407002 A CN109407002 A CN 109407002A CN 201811094790 A CN201811094790 A CN 201811094790A CN 109407002 A CN109407002 A CN 109407002A
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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
- G01R31/34—Testing dynamo-electric machines
- G01R31/343—Testing dynamo-electric machines in operation
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/24—Classification techniques
- G06F18/241—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
- G06F18/2415—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches based on parametric or probabilistic models, e.g. based on likelihood ratio or false acceptance rate versus a false rejection rate
- G06F18/24155—Bayesian classification
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Abstract
It is health management system arranged that the present invention provides motor devices, including local supervising and measuring equipment and data processing equipment, and the local supervising and measuring equipment includes sensor node, aggregation node；The sensor node is mounted on motor device, and when constructing network topology, multiple sensor nodes are divided into multiple clusters, and each cluster configures a cluster head；Sensor node acquires motor device characteristic parameter, and the motor device characteristic parameter of acquisition is passed to corresponding cluster head；The received motor device characteristic parameter of cluster head convergence institute is simultaneously transferred to aggregation node；The aggregation node is connect with data processing equipment, and the data processing equipment focuses on each motor device characteristic parameter and monitor equipment status.
Description
Technical field
The present invention relates to equipment faults to monitor field, and in particular to motor device is health management system arranged.
Background technique
In the production scene of modernization Standard Factory Room, widespread deployment has all kinds of Large-scale machine sets, and unit has " three is big " (body
Product is big, power is big, flow is big), " three high " (revolving speed is high, pressure is high, operating maintenance timeliness require high) the characteristics of, building ring
Border has both the features such as high temperature, high pressure (super-pressure), abrasion, these factors easily lead to the generation of equipment catastrophic failure, to industry
Equipment safety, continuous, reliable run threaten.
Decision tree be it is known it is various happen probability on the basis of, seek phase of net present value (NPV) by constituting decision tree
Prestige value is more than or equal to zero probability, and assessment item risk judges the method for decision analysis of its feasibility, is by all means with probability point
A kind of graphical method of analysis.Bayesian network is a directed acyclic graph, is intuitively expressed respectively by a conditional probability distribution
Dependence between a variable.Therefore decision tree-Bayesian network is applied in Diagnosing Faults of Electrical, can be effectively located
Uncertain information is managed, to obtain correct result.
Summary of the invention
In view of the above-mentioned problems, present invention offer motor device is health management system arranged.
The purpose of the present invention is realized using following technical scheme:
It is health management system arranged to provide motor device, including local supervising and measuring equipment and data processing equipment, the scene prison
Surveying device includes sensor node, aggregation node；The sensor node is mounted on motor device, when constructing network topology,
Multiple sensor nodes are divided into multiple clusters, and each cluster configures a cluster head；Sensor node acquires motor device characteristic parameter,
And the motor device characteristic parameter of acquisition is passed into corresponding cluster head；The received motor device characteristic parameter of cluster head convergence institute simultaneously passes
It is handed to aggregation node；The aggregation node is connect with data processing equipment, and the data processing equipment focuses on each motor
Equipment characteristic parameter and monitor equipment status.
Preferably, the sensor node includes sensor unit, power supply unit, radio frequency unit, processing unit；
Acquisition and data conversion of the sensor unit for the motor device characteristic parameter of monitoring；The processing unit
For the central processing unit of sensor node, the processing and control of each sensor acquisition data are handled, entire sensor section is coordinated
The work of point each unit；The radio frequency unit with other sensors node and aggregation node for communicating；The power supply is single
Member is responsible for providing power supply to entire sensor node each unit.
Wherein, the data processing equipment focuses on each motor device characteristic parameter and monitor equipment status, packet
It includes:
(1) electrical fault status information is arranged, expert knowledge library is constructed；
(2) it according to the operation manuals of motor and expert knowledge library and each motor device characteristic parameter, sorts out
Characteristic information when motor breaks down establishes failure decision-tree model, calculates each node of decision tree according to expert knowledge library
Probability；
(3) decision-tree model is converted into decision tree-Bayesian network model；
(4) real-time data acquisition judges electrical fault classification by expert knowledge library and operation manuals；
(5) decision tree-Bayesian network model that traversal is established；
(6) detection decision tree-Bayesian network bottoms out event, records if identical as real time fail classification traversed
Node；
(7) failure cause diagnosis report is formed according to decision tree-Bayesian network node probability.
The invention has the benefit that realizing the real-time of motor device characteristic parameter by wireless sensor network technology
Acquisition；It can be with the unascertained information in effective solution Diagnosing Faults of Electrical by establishing decision tree-Bayesian network model
Problem realizes the management to motor device health to obtain accurate and effective diagnosis effect.
Detailed description of the invention
The present invention will be further described with reference to the accompanying drawings, but the embodiment in attached drawing is not constituted to any limit of the invention
System, for those of ordinary skill in the art, without creative efforts, can also obtain according to the following drawings
Other attached drawings.
Fig. 1 is the health management system arranged structural schematic block diagram of the motor device of one embodiment of the invention；
Fig. 2 is the block diagram representation of the sensor node of one embodiment of the invention.
Appended drawing reference:
Local supervising and measuring equipment 1, data processing equipment 2, sensor unit 10, power supply unit 20, radio frequency unit 30, processing are single
Member 40.
Specific embodiment
The invention will be further described with the following Examples.
Referring to Fig. 1, motor device provided in this embodiment is health management system arranged, including at local supervising and measuring equipment 1 and data
Device 2 is managed, the local supervising and measuring equipment 1 includes sensor node, aggregation node；The sensor node is mounted on motor device
On, when constructing network topology, multiple sensor nodes are divided into multiple clusters, and each cluster configures a cluster head；Sensor node is adopted
Collect motor device characteristic parameter, and the motor device characteristic parameter of acquisition is passed into corresponding cluster head；Cluster head convergence institute is received
Motor device characteristic parameter is simultaneously transferred to aggregation node；The aggregation node is connect with data processing equipment 2, the data processing
Device 2 focuses on each motor device characteristic parameter and monitor equipment status.
Wherein, the data processing equipment 2 focuses on each motor device characteristic parameter and monitor equipment status, packet
It includes:
(1) electrical fault status information is arranged, expert knowledge library is constructed；
(2) it according to the operation manuals of motor and expert knowledge library and each motor device characteristic parameter, sorts out
Characteristic information when motor breaks down establishes failure decision-tree model, calculates each node of decision tree according to expert knowledge library
Probability；
(3) decision-tree model is converted into decision tree-Bayesian network model；
(4) real-time data acquisition judges electrical fault classification by expert knowledge library and operation manuals；
(5) decision tree-Bayesian network model that traversal is established；
(6) detection decision tree-Bayesian network bottoms out event, records if identical as real time fail classification traversed
Node；
(7) failure cause diagnosis report is formed according to decision tree-Bayesian network node probability.
In a kind of mode of preferred implementation, as shown in Fig. 2, the sensor node includes sensor unit 10, power supply
Unit 20, radio frequency unit 30, processing unit 40；
Acquisition and data conversion of the sensor unit 10 for the motor device characteristic parameter of monitoring；The processing is single
Member 40 is the central processing unit of sensor node, handles the processing and control of each sensor acquisition data, coordinates entire sensing
The work of device node each unit；The radio frequency unit 30 with other sensors node and aggregation node for communicating；It is described
Power supply unit 20 is responsible for providing power supply to entire sensor node each unit.
The above embodiment of the present invention realizes adopting in real time for motor device characteristic parameter by wireless sensor network technology
Collection；It can be asked by establishing decision tree-Bayesian network model with the unascertained information in effective solution Diagnosing Faults of Electrical
Topic, to obtain accurate and effective diagnosis effect.
In a kind of mode that can be realized, the other sensors node being defined in sensor node transmission range is it
Neighbor node；Each sensor node passes through periodically exchange acquisition of information neighbor node mark and location information.In a kind of energy
In the mode enough realized, the motor device characteristic parameter of acquisition is passed to corresponding cluster head by sensor node, comprising:
(1) source node is determined according to the following equation to the path-length k of corresponding cluster head, which is to need to right
Cluster head is answered to send the sensor node of motor device characteristic parameter collected:
In formula, dI, oFor source node i to the distance of corresponding cluster head, dminTo be preset apart from lower limit, int is bracket function；
Int indicates to be rounded；
(2) if k≤1, motor device characteristic parameter is directly transmitted to corresponding cluster head by source node；If k > 1, source node is at it
Select a neighbor node as next-hop, the as destination node of the jump in neighbor node, source node is using directly transmission side
Motor device characteristic parameter collected is sent to destination node in such a way that cooperative node transmits by formula；
(3) destination node of the jump is considered as to the source node of next-hop, enables k=k-1, the source node of the next-hop executes
(2), until motor device characteristic parameter is passed to cluster head.
In the present embodiment, determined to the path-length of corresponding cluster head according to source node for forwarding motor device special
The number for levying the next-hop node of parameter is conducive to avoid multi-hop to define the hop count of transmission electrical machine equipment characteristic parameter
Energy dissipation in transmission process.
Wherein, source node is set motor collected using direct mode or by way of cooperative node transmission
Standby characteristic parameter is sent to destination node, comprising: source node sends motor device characteristic parameter in first time and gives its destination node
When, motor device characteristic parameter is transferred to the destination node of the jump in such a way that cooperative node transmits, and in calculating process
Energy consumption, obtain the first energy consumption；When sending motor device characteristic parameter second, source node directly sets motor
Standby characteristic parameter is sent to the destination node of the jump, and the energy consumption in calculating process, obtains the second energy consumption；Source node
Compare first energy consumption and the second energy consumption, if first energy consumption less than the second energy consumption, subsequent
Motor device characteristic parameter transmission when, source node is by way of cooperative node cooperation transmission by motor device characteristic parameter
It is transferred to the destination node of the jump；It is special in subsequent motor device if first energy consumption is not less than the second energy consumption
When levying parameter transmission, motor device characteristic parameter is directly sent to the destination node of the jump by source node, wherein send every time
The quantity of motor device characteristic parameter is identical.
In the present embodiment, when motor device characteristic parameter is sent to destination node by source node, when starting by direct
Transmission mode, both modes are in such a way that cooperative node transmits come transmission electrical machine equipment characteristic parameter, so as to convenient
The energy consumption of the two ways is obtained, source node is also transmitted the smallest transmission mode of energy consumption as subsequent motor device characteristic parameter
Mode, advantageously reduce motor device characteristic parameter transmission energy consumption.
In one embodiment, described that motor device characteristic parameter is transferred to the jump in such a way that cooperative node transmits
Destination node, specifically:
(1) source node selects n neighbor node as cooperative node in its neighbor node, when the neighbor node of source node
When number is less than n, cooperative node of whole neighbor nodes as source node is selected, wherein the number of cooperative node is according to following
Formula determines:
WhenWhen, n=1；
WhenWhen,
In formula, N is the sensor node quantity disposed in network, and U is the area in the monitoring region, dmIt is arrived for source node
The distance of its destination node；
(2) source node modulating motor equipment characteristic parameter in the way of polynary quadrature amplitude modulation, then will be modulated
Motor device characteristic parameter pass to its each cooperative node in a broadcast manner；
(3) after source node and its each cooperative node carry out compressed encoding to motor device characteristic parameter, after compressed encoding
Motor device characteristic parameter be transferred to destination node.
Wherein, the motor device characteristic parameter after compressed encoding is decoded by cluster head, to reconstruct motor device feature
Parameter.
The present embodiment sets the concrete mode of single-hop cooperation transmission motor device characteristic parameter, wherein being arrived according to source node
The distance of destination node, the number for setting cooperative node determine formula, so that source node can determine single-hop according to the formula
The design parameter of cooperation transmission.Compressed encoding is carried out to motor device characteristic parameter by source node and each cooperative node to retransmit
To destination node, it is beneficial to save motor device characteristic parameter collection energy consumption.
In one embodiment, source node selects n neighbor node as cooperative node in its neighbor node, comprising:
(1) weight of each neighbor node is calculated:
In formula, WijIndicate the weight of j-th of neighbor node of source node i, 9 indicate the destination node of source node i, dipFor
Source node i is at a distance from its destination node 9, djpIt is j-th of neighbor node at a distance from destination node p, dijFor source node
I is at a distance from j-th of neighbor node, EjFor the current remaining of j-th of neighbor node, Ej0It is described j-th
The primary power of neighbor node, Ei0For the primary power of source node i；λ1、λ2For preset weight coefficient；f(djp, dip) it is judgement
Value function, works as djp<dipWhen, f (djp, dip)=1, works as djp≥dipWhen, f (djp, dip)=0；
(2) each neighbor node is arranged according to the sequence of weight from big to small, n neighbor node before source node selects
As cooperative node.
The present embodiment sets the weight computing formula of neighbor node, by the calculation formula it is found that dump energy is more, position
The bigger neighbor node of advantage is set with bigger weight.Source node according to weight sequence from big to small to each neighbor node into
Row arrangement, and select preceding n neighbor node as cooperative node, enable the cooperative node filtered out to efficiently accomplish cooperation and passes
The task of transmission of electricity machine equipment characteristic parameter, and be beneficial to save the energy consumption of cooperation transmission motor device characteristic parameter.
Finally it should be noted that the above embodiments are merely illustrative of the technical solutions of the present invention, rather than the present invention is protected
The limitation of range is protected, although explaining in detail referring to preferred embodiment to the present invention, those skilled in the art are answered
Work as understanding, it can be with modification or equivalent replacement of the technical solution of the present invention are made, without departing from the reality of technical solution of the present invention
Matter and range.
Claims (6)
1. motor device is health management system arranged, characterized in that including local supervising and measuring equipment and data processing equipment, the scene prison
Surveying device includes sensor node, aggregation node；The sensor node is mounted on motor device, when constructing network topology,
Multiple sensor nodes are divided into multiple clusters, and each cluster configures a cluster head；Sensor node acquires motor device characteristic parameter,
And the motor device characteristic parameter of acquisition is passed into corresponding cluster head；The received motor device characteristic parameter of cluster head convergence institute simultaneously passes
It is handed to aggregation node；The aggregation node is connect with data processing equipment, and the data processing equipment focuses on each motor
Equipment characteristic parameter and monitor equipment status.
2. motor device according to claim 1 is health management system arranged, characterized in that the sensor node includes sensing
Device unit, power supply unit, radio frequency unit, processing unit；
Acquisition and data conversion of the sensor unit for the motor device characteristic parameter of monitoring；The processing unit is to pass
The central processing unit of sensor node handles the processing and control of each sensor acquisition data, it is each to coordinate entire sensor node
The work of a unit；The radio frequency unit with other sensors node and aggregation node for communicating；Said supply unit is negative
It blames and provides power supply to entire sensor node each unit.
3. motor device according to claim 1 is health management system arranged, characterized in that at the data processing equipment concentration
Manage each motor device characteristic parameter and monitor equipment status, comprising:
(1) electrical fault status information is arranged, expert knowledge library is constructed；
(2) according to the operation manuals of motor and expert knowledge library and each motor device characteristic parameter, motor is sorted out
Characteristic information when breaking down establishes failure decision-tree model, calculates the general of each node of decision tree according to expert knowledge library
Rate；
(3) decision-tree model is converted into decision tree-Bayesian network model；
(4) real-time data acquisition judges electrical fault classification by expert knowledge library and operation manuals；
(5) decision tree-Bayesian network model that traversal is established；
(6) detection decision tree-Bayesian network bottoms out event, and traversed section is recorded if identical as real time fail classification
Point；
(7) failure cause diagnosis report is formed according to decision tree-Bayesian network node probability.
4. motor device according to claim 1 is health management system arranged, characterized in that be defined on sensor node transmission model
Other sensors node in enclosing is its neighbor node；Each sensor node is by periodically exchanging acquisition of information neighbor node
Mark and location information；The motor device characteristic parameter of acquisition is passed to corresponding cluster head by sensor node, comprising:
(1) source node is determined according to the following equation to the path-length k of corresponding cluster head, which is to need to corresponding cluster
Hair send the sensor node of motor device characteristic parameter collected:
In formula, dI, oFor source node i to the distance of corresponding cluster head, dminTo be preset apart from lower limit, int is bracket function；Int table
Show rounding；
(2) if k≤1, motor device characteristic parameter is directly transmitted to corresponding cluster head by source node；If k > 1, source node is in its neighbour
It occupies and selects a neighbor node as next-hop, the as destination node of the jump in node, source node uses direct mode
Or motor device characteristic parameter collected is sent to destination node in such a way that cooperative node transmits；
(3) destination node of the jump is considered as to the source node of next-hop, enables k=k-1, the source node of the next-hop executes (2), directly
Cluster head is passed to motor device characteristic parameter.
5. motor device according to claim 4 is health management system arranged, characterized in that source node uses direct mode
Or motor device characteristic parameter collected is sent to destination node in such a way that cooperative node transmits, comprising: source section
Point is when sending motor device characteristic parameter to its destination node first time, by motor device in such a way that cooperative node transmits
Characteristic parameter is transferred to the destination node of the jump, and the energy consumption in calculating process, obtains the first energy consumption；At second
When sending motor device characteristic parameter, motor device characteristic parameter is directly sent to the destination node of the jump by source node, and is counted
Energy consumption during calculation obtains the second energy consumption；Source node first energy consumption and the second energy consumption,
If first energy consumption is less than the second energy consumption, in the transmission of subsequent motor device characteristic parameter, source node is logical
Motor device characteristic parameter is transferred to the destination node of the jump by the mode for crossing cooperative node cooperation transmission；If first energy
Consumption is not less than the second energy consumption, and in the transmission of subsequent motor device characteristic parameter, source node is directly by motor device spy
Sign parameter is sent to the destination node of the jump, wherein the quantity of the motor device characteristic parameter sent every time is identical.
6. motor device according to claim 4 is health management system arranged, characterized in that it is described by cooperative node transmit
Motor device characteristic parameter is transferred to the destination node of the jump by mode, specifically:
(1) source node selects n neighbor node as cooperative node in its neighbor node, when the neighbor node number of source node
When less than n, cooperative node of whole neighbor nodes as source node is selected, wherein the number of cooperative node is according to the following formula
It determines:
WhenWhen, n=1；
WhenWhen,
In formula, N is the sensor node quantity disposed in network, and U is the area in the monitoring region, dmFor source node to its mesh
Node distance；
(2) source node modulating motor equipment characteristic parameter in the way of polynary quadrature amplitude modulation, then by modulated electricity
Machine equipment characteristic parameter passes to its each cooperative node in a broadcast manner；
(3) after source node and its each cooperative node carry out compressed encoding to motor device characteristic parameter, by the electricity after compressed encoding
Machine equipment characteristic parameter is transferred to destination node.
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2018
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| CA2806854A1 (en) * | 2010-06-24 | 2011-12-29 | Brian Pepin | Flat-hierarchy system for condition-based monitoring of distributed equipment |
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