CN107505511A - life cycle prediction method, device and system of direct current support capacitor - Google Patents
life cycle prediction method, device and system of direct current support capacitor Download PDFInfo
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- CN107505511A CN107505511A CN201610417707.1A CN201610417707A CN107505511A CN 107505511 A CN107505511 A CN 107505511A CN 201610417707 A CN201610417707 A CN 201610417707A CN 107505511 A CN107505511 A CN 107505511A
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- 230000011218 segmentation Effects 0.000 claims description 6
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- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
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Abstract
The embodiment of the invention provides a life cycle prediction method, a life cycle prediction device and a life cycle prediction system of a direct current support capacitor. The method comprises the following steps: acquiring multiple groups of operating condition data of the direct current support capacitor in real time according to a preset time length; dividing the preset time length into two or more time periods reflecting different temperature states of the direct current support capacitor, and counting operation condition data in each time period; and calculating the service life of each section according to the operation condition data in each time period, and calculating the life cycle of the direct current support capacitor according to the plurality of section service lives. According to the method, the device and the system for predicting the life cycle of the direct-current support capacitor, the prediction accuracy of the life cycle of the direct-current support capacitor can be improved.
Description
Technical field
The present invention relates to electronic reliability detection technique field, more particularly to a kind of Life Cycle of DC support electric capacity
Phase Forecasting Methodology, apparatus and system.
Background technology
With being continuously increased for wind-driven generator installation amount, crucial portion of the DC support electric capacity as current transformator power module
Part, its life problems gradually show.Fig. 1 is the structural representation of power model in the prior art, and Fig. 1 shows direct current branch
Position of the electric capacity in power model is supportted, is connected between positive busbar DC+ and negative busbar DC-.Unsteady flow in wind generator system
Device is longer due to run time so that DC support electric capacity fatigue easily occurs and then causes to damage, and such as finds and takes not in time
Related measure, even result in the serious consequence of grade on fire from explosion.
Thus, to avoid the generation of DC support capacitance damage and above-mentioned adverse consequences, most important technology and data
According to the life cycle for being exactly DC support electric capacity.However, the phase in the life-span of DC support electric capacity can not be predicted at present
Pass method.
The content of the invention
The purpose of the embodiment of the present invention is, there is provided a kind of life cycle Forecasting Methodology of DC support electric capacity, device and
System, it is possible to increase the prediction accuracy of the life cycle of DC support electric capacity.
For achieving the above object, the embodiment provides a kind of prediction of the life cycle of DC support electric capacity
Method, methods described include：Obtain multigroup operating condition data of DC support electric capacity in real time according to predetermined time period；By institute
State predetermined time period and be divided into the time that two or more described DC support electric capacity of reflection are in different temperature condition
Section, and count the operating condition data in each period；Respectively according to the operating condition number in each period
According to being calculated stage-life, and the life cycle of the DC support electric capacity is calculated according to multiple stage-lifes.
Embodiments of the invention additionally provide a kind of life cycle prediction meanss of DC support electric capacity, described device bag
Include：Data acquisition module, for obtaining multigroup operating condition data of DC support electric capacity in real time according to predetermined time period；Number
According to processing module, reflect that the DC support electric capacity is in for the predetermined time period to be divided into two or more
The period of different temperature condition, and count the operating condition data in each period；Life cycle prediction module, use
Stage-life is calculated in the operating condition data in each period of basis respectively, and according to multiple segmentation longevity
Life calculates the life cycle of the DC support electric capacity.
The embodiment of the present invention additionally provides a kind of life cycle forecasting system of DC support electric capacity, and the system includes：
The life cycle prediction meanss of data acquisition device and DC support electric capacity as in the foregoing embodiment, the data acquisition
Device includes temperature measuring equipment and current sensor, and the temperature measuring equipment includes temperature sensor or infrared temperature measurement apparatus；Wherein,
The current sensor is connected on the branch road residing for the DC support electric capacity, and the temperature measuring equipment is arranged at the direct current branch
On the shell surface for supportting electric capacity, the signal output part of the current sensor, and the signal output part difference of the temperature measuring equipment
It is connected with the life cycle prediction meanss of the DC support electric capacity.
The life cycle Forecasting Methodology of DC support electric capacity provided in an embodiment of the present invention, apparatus and system, with direct current branch
State of temperature residing for supportting electric capacity is time slice foundation, and predetermined time period is divided into the period, counts straight in each period
The operating condition data of Support Capacitor are flowed, further respectively according to the operating condition data of the DC support electric capacity in each period
Stage-life is calculated, and then the life-span of DC support electric capacity is calculated according to stage-life.Embodying the time of different temperature condition
The stage-life of DC support electric capacity is calculated in section, final bimetry is calculated further according to each stage-life, due to predicting
Link considers influence of the temperature to the life-span, improves the prediction of the life cycle to DC support electric capacity compared to existing technologies
The degree of accuracy.
Brief description of the drawings
Fig. 1 is the structural representation of power model in the prior art；
Fig. 2 is the schematic flow sheet of the life cycle Forecasting Methodology of the DC support electric capacity of the embodiment of the present invention one；
Fig. 3 is the schematic flow sheet of the life cycle Forecasting Methodology of the DC support electric capacity of the embodiment of the present invention two；
Fig. 4 is the structural representation of the life cycle prediction meanss of the DC support electric capacity of the embodiment of the present invention three；
Fig. 5 is another structural representation of the life cycle prediction meanss of the DC support electric capacity of the embodiment of the present invention three；
Fig. 6 is the structural representation of the life cycle forecasting system of the DC support electric capacity of the embodiment of the present invention four；For just
In understanding, the also exemplary miscellaneous part given in power model.
Embodiment
The life cycle Forecasting Methodology to DC support electric capacity of the embodiment of the present invention, apparatus and system enter below in conjunction with the accompanying drawings
Row is described in detail.
Embodiment one
Fig. 2 is the schematic flow sheet of the life cycle Forecasting Methodology of the DC support electric capacity of the embodiment of the present invention one, can be
This method is performed in the life cycle prediction meanss of DC support electric capacity as shown in Figure 4：
Step 210：Obtain multigroup operating condition data of DC support electric capacity in real time according to predetermined time period.
Here, operating condition data may include voltage data, ripple current data and surface temperature data, but be not limited to
This.That is, the gathered data at set time intervals within the period of setting, for example, according to each moment t1、t2…
tnGather operating condition data, t1、t2…tnIn difference two-by-two between the moment it is identical, t1Moment collects one group and includes voltage
V1, ripple current I1With surface temperature Ts1Operating condition data, similarly, t2Moment collects one group and includes voltage V2, ripple electricity
Flow I2With surface temperature Ts2Operating condition data, by that analogy, will not be repeated here.
Step 220：Predetermined time period is divided into two or more reflection DC support electric capacity and is in not equality of temperature
The period of degree state, and count the operating condition data in each period.
, can be using state of temperature residing for DC support electric capacity as segmentation foundation, by above-mentioned setting with continued reference to aforementioned exemplary
Period is divided into multiple sub- periods, such as t1~t6It is the sub- time that a reflection DC support electric capacity is in low-temperature condition
Section, temperature range corresponding to low-temperature condition such as (0 DEG C, 60 DEG C).For another example t7~t15It is at a reflection DC support electric capacity
In the sub- period of middle temperature state, temperature range corresponding to middle temperature state such as (60 DEG C, 70 DEG C).Also, each sub- period
Multiple collection moment are inside all included, the collection moment corresponds to the operating condition data collected at the moment again.Thus, it can count every
Operating condition data in the individual sub- period, it is the place of the operating condition data in statistics each period in this step
Reason.
Step 230：Stage-life is calculated according to the operating condition data in each period respectively, and according to multiple
Stage-life calculates the life cycle of DC support electric capacity.
That is, according to each period distinguish mathematic(al) expectation i.e. stage-life after the division period, then further according to
Stage-life calculates the life cycle that entire life is DC support electric capacity.
The present invention DC support electric capacity life cycle Forecasting Methodology, using state of temperature residing for DC support electric capacity as when
Between be segmented foundation, predetermined time period is divided into the period, counts the operating condition number of the DC support electric capacity in each period
According to, further respectively according to the operating condition data of the DC support electric capacity in each period calculating stage-life, and then according to
Stage-life calculates the life-span of DC support electric capacity.Improve the prediction accuracy of the life cycle to DC support electric capacity.From
And it is the maintenance of important devices and the foundation in running state data storehouse, and manual decision repairs and provides technical basis.
Embodiment two
Fig. 3 is the schematic flow sheet of the life cycle Forecasting Methodology of the DC support electric capacity of the embodiment of the present invention two, described
Embodiment can be considered Fig. 2 another concrete implementation scheme.Can DC support electric capacity as shown in Figure 5 life cycle it is pre-
Survey on device and perform this method：
Step 310：Obtain multigroup operating condition data of DC support electric capacity in real time according to predetermined time period.
Here, this step is identical with step 210 processing mode in above-described embodiment one, for details, reference can be made to above-mentioned steps 210
Step content, will not be repeated here.
Step 320：Multiple core temperature data of DC support electric capacity are calculated according to multigroup operating condition data.
Here, operating condition data may include voltage data, ripple current data and surface temperature data.
According to exemplary embodiments of the present invention, step 320 may include：According to the surface temperature of multigroup DC support electric capacity
Multiple inner cores are calculated to the thermal resistance on shell surface in data, ripple current data, and the internal resistance of DC support electric capacity and inner core
Temperature data.
In concrete implementation mode, core temperature data can be calculated according to below equation (1)：
T=Ts+Irms 2*r*Rth... ... ... ... ... ... ... ... ... ... formula (1)
Wherein, T be DC support electric capacity core temperature data, TsFor the surface temperature data of DC support electric capacity, Irms
For the ripple current data of DC support electric capacity, r is the internal resistance of DC support electric capacity, RthFor DC support electric capacity inner core to shell
The thermal resistance on surface.
Or core temperature data are calculated according to below equation (2)：
T=Ts+KIrms 2·r·Rth... ... ... ... ... ... ... ... ... ... formula (2)
Wherein, T be DC support electric capacity core temperature data, TsFor the surface temperature data of DC support electric capacity, Irms
For the ripple current data of DC support electric capacity, r is the internal resistance of DC support electric capacity, RthFor DC support electric capacity inner core to shell
The thermal resistance on surface, K are predetermined constant.
Step 330：According to the core temperature data that are calculated and two or more default core temperature threshold values,
Predetermined time period is divided into two or more periods of two or more corresponding temperature ranges, and counts every
Operating condition data in the individual period.
For example, by taking thin-film capacitor as an example, it is assumed that default core temperature threshold value is 60 DEG C and 70 DEG C, will be calculated
Core temperature data compared with default core temperature threshold value, in addition, every group of operating condition data correspond to the moment, by running
The core temperature data that floor data is calculated also correspond to the moment, and thus, predetermined time period can be divided into three periods,
It it is the period corresponding to low-temperature condition i.e. less than 60 DEG C, when more than or equal to 60 DEG C and being less than or equal to 70 DEG C corresponding to middle temperature state
Between section, be the period corresponding to the condition of high temperature more than 70 DEG C.So as to can also count the operating condition data in each period.
Meanwhile it can also obtain the time duration of temperature range corresponding to each period.
Step 340：Stage-life is calculated according to the operating condition data in each period respectively.
In concrete implementation mode, stage-life can be calculated according to below equation (3)：
Wherein, L is stage-life, L0For the theoretical principle life-span of DC support electric capacity, T0For the theory of DC support electric capacity
Highest core temperature, TaveFor the average value of the core temperature data in each period, VrateFor the specified of DC support electric capacity
Voltage, VaveFor the average value of the voltage data in each period.
Or stage-life is calculated according to below equation (4)：
Wherein, L is stage-life, L0For the theoretical principle life-span of DC support electric capacity, T0For the theory of DC support electric capacity
Highest core temperature, TaveFor the average value of the core temperature data in each period, VrateFor the specified of DC support electric capacity
Voltage, VnFor the voltage data of n-th of moment collection.
Step 350：According to time duration corresponding to two or more periods and each stage-life, calculate
The average value of each stage-life is obtained, the average value of each stage-life is the life cycle of DC support electric capacity.
In concrete implementation mode, the life cycle of DC support electric capacity can be calculated according to below equation (5)：
Wherein, LaveFor life cycle, n is the number of period, tnFor the duration of temperature range corresponding to the period
Length, LnFor the stage-life of period.
Or the life cycle of DC support electric capacity is calculated according to below equation (6)：
Wherein, LaveFor life cycle, n is the number of period, tnFor the duration of temperature range corresponding to the period
Length, LnFor the stage-life of period.
Continue to be divided into low-temperature condition, middle temperature state, exemplified by three periods of the condition of high temperature by foregoing, it is assumed that by foregoing public affairs
Formula (3) calculates the stage-life L of low-temperature condition prediction01, medium temperature status predication stage-life L02With condition of high temperature prediction
Stage-life L03, then apply mechanically above-mentioned formula (5) and obtain below equation (7)：
Wherein, LaveFor life cycle, L01For the stage-life of low-temperature condition prediction, L02For the segmentation of medium temperature status predication
Life-span, L03For the stage-life of condition of high temperature prediction, tsum1For the time duration of low-temperature condition, tsum2For middle temperature state
Time duration, tsum3For the time duration of the condition of high temperature.
Step 360：If meet it is at least one in default abnormal state conditions, judge DC support electric capacity be in
Abnormality.Wherein, default abnormal state conditions include：The life cycle of the DC support electric capacity of calculating exceedes default life
Ct value is ordered, the voltage data of DC support electric capacity exceedes default voltage threshold, the ripple current number of DC support electric capacity
Exceed default temperature threshold according to more than the surface temperature data of default current threshold and DC support electric capacity.
That is, according to working voltage, ripple current and the surface temperature of the DC support electric capacity of acquisition, and prediction
Life cycle, compared with the specified limit parameter of DC support electric capacity, if beyond if show the DC support electric capacity
In abnormality.
Step 370：Alarm is carried out after judging that DC support electric capacity is in abnormality.
The life cycle Forecasting Methodology of the DC support electric capacity of the present invention, has the following technical effect that：
On the one hand, by calculating the core temperature of DC support electric capacity, being partitioned into for period is carried out according to core temperature
And mathematic(al) expectation is segmented, also, consider the proportion of duration corresponding to each period and corresponding stage-life, obtain
Go out the life-span of DC support electric capacity, improve the prediction accuracy of the life cycle of DC support electric capacity.
On the other hand, the floor data according to the DC support electric capacity of monitoring carries out abnormal judgment step and alarm step
Suddenly, realize and judged and alarmed for transfinite electric capacity, abnormal electric capacity of life-span in time, improve the work of DC support electric capacity
The security of environment.
Embodiment three
Fig. 4 is the structural representation of the life cycle prediction meanss of the DC support electric capacity of the embodiment of the present invention three.It can use
In the life cycle Forecasting Methodology step for the DC support electric capacity for performing the embodiment of the present invention one.
Reference picture 4, the life cycle prediction meanss of the DC support electric capacity include data acquisition module 410, data processing
Module 420 and life cycle prediction module 430.
Data acquisition module 410 is used for the multigroup operating condition for obtaining DC support electric capacity in real time according to predetermined time period
Data.
Data processing module 420 is used to predetermined time period being divided into two or more reflection DC support electric capacity
Period in different temperature condition, and count the operating condition data in each period.
Life cycle prediction module 430 is used to segmentation be calculated according to the operating condition data in each period respectively
Life-span, and according to the life cycle of multiple stage-lifes calculating DC support electric capacity.
The present invention DC support electric capacity life cycle prediction meanss, using state of temperature residing for DC support electric capacity as when
Between be segmented foundation, predetermined time period is divided into the period, counts the operating condition number of the DC support electric capacity in each period
According to, further respectively according to the operating condition data of the DC support electric capacity in each period calculating stage-life, and then according to
Stage-life calculates the life-span of DC support electric capacity.Improve the prediction accuracy of the life cycle to DC support electric capacity.From
And it is the maintenance of important devices and the foundation in running state data storehouse, and manual decision repairs and provides technical basis.
Further, on the basis of the embodiment shown in Fig. 4, Fig. 5 is the DC support electric capacity of the embodiment of the present invention three
Life cycle prediction meanss another structural representation.
Specifically, data processing module 420 as shown in Figure 4 may include：
Core temperature computing unit 4201 is used to the more of DC support electric capacity be calculated according to multigroup operating condition data
Individual core temperature data.Here, operating condition data may include ripple current data and surface temperature data.
Period divides and data statistics unit 4202 is used for according to the core temperature data being calculated and two or two
Default core temperature threshold value more than individual, the predetermined time period is divided into two or more corresponding temperature ranges
Two or more periods, and count the operating condition data in each period.
Life cycle prediction module 430 as shown in Figure 4 may include：
Stage-life computing unit 4301 is used to be calculated point according to the operating condition data in each period respectively
Duan Shouming.
Life cycle calculations unit 4302 be used for according to corresponding to two or more periods time duration with
And each stage-life, the average value of each stage-life is calculated, the average value of each stage-life is the life of DC support electric capacity
Order the cycle.
Preferably, the life cycle prediction meanss of the DC support electric capacity can also include：
If abnormal state determination module 440 is at least one in default exceptional condition for meeting, direct current is judged
Support Capacitor is abnormal.
Wherein, default abnormal state conditions include：The life cycle of the DC support electric capacity of calculating exceedes default life
Ct value is ordered, the voltage data of DC support electric capacity exceedes default voltage threshold, the ripple current number of DC support electric capacity
Exceed default temperature threshold according to more than the surface temperature data of default current threshold and DC support electric capacity.Here, run
Floor data may include the voltage data of DC support electric capacity, ripple current data and surface temperature data.
Alarm module 450 is used to after abnormal state determination module 440 judges DC support electric capacity exception be reported
Alert prompting.
Further, the life cycle prediction meanss of the DC support electric capacity can be integrated in the driving measurement of power model
In protection circuit plate.
Further, the DC support electric capacity can be the thin-film electro of the power model for wind generator system perhaps
Electrochemical capacitor.
In actual applications, the life cycle prediction meanss of the DC support electric capacity can also include communication module.Specifically
Ground, such as established and connected with industrial computer using wireless telecommunications, the life cycle data of the DC support electric capacity predicted will be carried
And/or the floor data of DC support electric capacity is sent to industrial computer, in order to which related management attendant receives according to industrial computer
To data know the running situation of DC support electric capacity in time, and easily trigger the dangerous situation compared with major break down, and then take phase
Close safeguard measure.Here, the implementation of wireless telecommunications can be bluetooth, it is WLAN 802.11, infrared data transmission, non-
The short-distance wireless communication technologies such as contact radio frequency identification.
To sum up, the present invention also has the following technical effect that：
First, the core temperature by calculating DC support electric capacity, according to core temperature carry out the period division and then
Mathematic(al) expectation is segmented, also, considers the proportion of duration corresponding to each period and corresponding stage-life, is drawn
In the life-span of DC support electric capacity, improve the prediction accuracy of the life cycle of DC support electric capacity.
Second, the floor data according to the DC support electric capacity of monitoring carries out abnormal judgment step and alarm step,
Realize and judged and alarmed for transfinite electric capacity, abnormal electric capacity of life-span in time, improve the building ring of DC support electric capacity
The security in border, avoid the generation of hazardous events.
Example IV
Fig. 6 is the structural representation of the life cycle forecasting system of the DC support electric capacity of the embodiment of the present invention four.Reference
Fig. 6, the life cycle forecasting system of DC support electric capacity include：Data acquisition fills 610 and as described in previous embodiment three
The life cycle prediction meanss 620 of DC support electric capacity, wherein, data acquisition device 610 and the electricity of life cycle prediction meanss 620
Connection.
Specifically, data acquisition device may include but be not limited to temperature measuring equipment, and voltage sensor and current sensor.
Wherein, temperature measuring equipment can include temperature sensor or infrared temperature measurement apparatus.With continued reference to Fig. 6, for wind generator system
Power model DC support electric capacity exemplified by, the positive pole and negative pole of voltage sensor respectively with the positive pole of DC support electric capacity and
Negative pole is corresponding to be connected, and on the branch road residing for current sensor series direct current Support Capacitor, temperature measuring equipment is arranged at DC support electricity
On the shell surface of appearance, the signal output part of voltage sensor, the signal output part of current sensor, and the signal of temperature measuring equipment
Output end is connected with the life cycle prediction meanss of DC support electric capacity respectively.
Further, the life cycle forecasting system of the DC support electric capacity (can also not shown including industrial computer in figure
Go out), industrial computer to connected life cycle prediction meanss send query statement, and receive life cycle prediction meanss according to
The Query Result data that query statement returns, wherein, the life cycle data of Query Result data including DC support electric capacity and/
Or floor data.
In concrete implementation mode, communication module can be set in the life cycle prediction meanss of DC support electric capacity.
Established and connected by communication module and industrial computer, so that after query statement is received, Query Result are sent into industrial computer,
In order to which the data that related management attendant foundation industrial computer receives know the running situation of DC support electric capacity in time, with
And the easy dangerous situation triggered compared with major break down, and then take related safeguard measure.Here, Query Result data may include for example to predict
The life cycle data of the DC support electric capacity gone out, and/or such as voltage, ripple current, surface temperature floor data.Communication side
Formula can be the short-distance wireless communication skills such as bluetooth, WLAN 802.11, infrared data transmission, non-contact radio-frequency identification
Art.
The life cycle forecasting system of the DC support electric capacity of the present invention, DC support electricity is gathered by data acquisition device
The operating condition data of appearance, life cycle prediction meanss obtain data acquisition device collection operating condition data, further with
Operating condition data are data basis, realize the life cycle of Accurate Prediction DC support electric capacity.So as to be important devices
Safeguard that the foundation with running state data storehouse, and manual decision are repaired and provides technical basis.
The foregoing is only a specific embodiment of the invention, but protection scope of the present invention is not limited thereto, any
Those familiar with the art the invention discloses technical scope in, change or replacement can be readily occurred in, should all be contained
Cover within protection scope of the present invention.Therefore, protection scope of the present invention should be based on the protection scope of the described claims.
Claims (11)
1. a kind of life cycle Forecasting Methodology of DC support electric capacity, it is characterised in that methods described includes：
Obtain multigroup operating condition data of DC support electric capacity in real time according to predetermined time period；
The predetermined time period is divided into two or more and reflects that the DC support electric capacity is in different temperatures shape
The period of state, and count the operating condition data in each period；
Stage-life is calculated according to the operating condition data in each period respectively, and according to multiple segmentations
Life-span calculates the life cycle of the DC support electric capacity.
2. according to the method for claim 1, it is characterised in that described that the predetermined time period is divided into two or two
Reflect that the DC support electric capacity is in the period of different temperature condition more than individual, and count the fortune in each period
The processing of row floor data includes：
Multiple core temperature data of the DC support electric capacity are calculated according to multigroup operating condition data；The fortune
Row floor data includes ripple current data and surface temperature data；
According to the core temperature data that are calculated and two or more default core temperature threshold values, when will be described default
Between length be divided into two or more periods of two or more corresponding temperature ranges, and when counting each described
Between operating condition data in section.
3. method according to claim 1 or 2, it is characterised in that described according to calculating multiple stage-lifes
The processing of the life cycle of DC support electric capacity includes：
According to time duration corresponding to two or more periods and each stage-life, each institute is calculated
The average value of stage-life is stated, the average value is the life cycle of the DC support electric capacity.
4. according to the method for claim 3, it is characterised in that methods described also includes：
If meeting at least one in default abnormal state conditions, judge that the DC support electric capacity is in abnormal shape
State；
Alarm is carried out after judging that the DC support electric capacity is in abnormality；
Wherein, the default abnormal state conditions include：The life cycle of the DC support electric capacity calculated exceedes default
Life cycle threshold value, the voltage data of the DC support electric capacity exceedes default voltage threshold, the DC support electric capacity
Ripple current data exceed the surface temperature data of default current threshold and the DC support electric capacity and exceed default temperature
Spend threshold value；The operating condition data include voltage data, ripple current data and the surface temperature of the DC support electric capacity
Data.
5. a kind of life cycle prediction meanss of DC support electric capacity, it is characterised in that described device includes：
Data acquisition module, for obtaining multigroup operating condition data of DC support electric capacity in real time according to predetermined time period；
Data processing module, reflect the DC support electricity for the predetermined time period to be divided into two or more
Hold the period in different temperature condition, and count the operating condition data in each period；
Life cycle prediction module, for the segmentation longevity to be calculated according to the operating condition data in each period respectively
Life, and according to the life cycle of multiple stage-lifes calculating DC support electric capacity.
6. device according to claim 5, it is characterised in that the data processing module includes：
Core temperature computing unit, for the more of the DC support electric capacity to be calculated according to multigroup operating condition data
Individual core temperature data；The operating condition data include ripple current data and surface temperature data；
Period divides and data statistics unit, for pre- with two or more according to the core temperature data being calculated
If core temperature threshold value, the predetermined time period is divided into two or two of two or more corresponding temperature ranges
The individual above period, and count the operating condition data in each period.
7. the device according to claim 5 or 6, it is characterised in that the life cycle prediction module includes：
Stage-life computing unit, for being calculated point according to the operating condition data in each period respectively
Duan Shouming；
Life cycle calculations unit, for the time duration according to corresponding to two or more periods and it is each described in
Stage-life, is calculated the average value of each stage-life, and the average value is the Life Cycle of the DC support electric capacity
Phase.
8. device according to claim 7, it is characterised in that described device also includes：
Abnormal state determination module, if at least one in default exceptional condition for meeting, judge the direct current branch
It is abnormal to support electric capacity；
Alarm module, for being alarmed after the abnormal state determination module judges the DC support electric capacity exception
Prompting；
Wherein, the default abnormal state conditions include：The life cycle of the DC support electric capacity calculated exceedes default
Life cycle threshold value, the voltage data of the DC support electric capacity exceedes default voltage threshold, the DC support electric capacity
Ripple current data exceed the surface temperature data of default current threshold and the DC support electric capacity and exceed default temperature
Spend threshold value；The operating condition data include voltage data, ripple current data and the surface temperature of the DC support electric capacity
Data.
9. device according to claim 8, it is characterised in that described device is integrated in the driving measurement protection of power model
In circuit board.
10. a kind of life cycle forecasting system of DC support electric capacity, it is characterised in that the system includes：Data acquisition fills
Put and the life cycle prediction meanss of DC support electric capacity as any one of claim 5~9, the data acquisition
Device includes temperature measuring equipment and current sensor；
Wherein, the current sensor is connected on the branch road residing for the DC support electric capacity, and the temperature measuring equipment is arranged at
On the shell surface of the DC support electric capacity；The signal output part of the current sensor, and the signal of the temperature measuring equipment
Life cycle prediction meanss of the output end respectively with the DC support electric capacity are connected.
11. system according to claim 10, it is characterised in that the system also includes industrial computer, the industrial computer to
The connected life cycle prediction meanss send query statement, and receive the life cycle prediction meanss according to
The Query Result data that query statement returns, wherein, the Query Result data include the Life Cycle issue of DC support electric capacity
According to and/or floor data.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610417707.1A CN107505511A (en) | 2016-06-14 | 2016-06-14 | life cycle prediction method, device and system of direct current support capacitor |
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| CN112230066A (en) * | 2020-12-11 | 2021-01-15 | 南京华士电子科技有限公司 | Traction converter direct current bus capacitance health assessment method and system |
| CN112782498A (en) * | 2019-11-11 | 2021-05-11 | 株洲中车时代电气股份有限公司 | Fault monitoring method and device for capacitor |
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