CN109708882A - Horizontal feed device drives axis fatigue failure prediction technique and device - Google Patents
Horizontal feed device drives axis fatigue failure prediction technique and device Download PDFInfo
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- CN109708882A CN109708882A CN201910144511.3A CN201910144511A CN109708882A CN 109708882 A CN109708882 A CN 109708882A CN 201910144511 A CN201910144511 A CN 201910144511A CN 109708882 A CN109708882 A CN 109708882A
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Abstract
The present invention relates to a kind of horizontal feed device drives axis fatigue failure prediction technique and devices, belong to mechanical equipment technical field.This method acquires drive shaft stress data by cycle sensor first according to the actual condition of drive shaft；And then judge whether the collected stress data of each period exceeds preset range, if then damage value；Finally given a warning when judging that impairment value reaches threshold value.It is calculated to realize one kind based on sensor information acquisition, big data modeling, data, and establishes drive shaft fatigue failure prediction model, realization carries out life prediction according to actual operating mode, and accuracy and the convenience of prediction greatly improved.And horizontal feed device drives axis fatigue failure prediction technique and device of the invention, its implementation is easy, and cost of implementation is cheap, and application range is also quite extensive.
Description
Technical field
The present invention relates to mechanical equipment technical field, in particular to mechanical equipment data analysis technique field, in particular to
A kind of horizontal feed device drives axis fatigue failure prediction technique and device.
Background technique
Currently, rolling bed is a kind of common levels conveying equipment in auto manufacturing.When the drive shaft of rolling bed is carried in fatigue
It is gradually worn out under the action of lotus until fracture, not only results in the failure of single device, fortunately cause the production of this production line
It interrupts.In production system, if being unable to the faulted condition of accurate evaluation drive shaft, often massive losses are brought.Therefore
Exploitation is directed to the fatigue failure prediction model of drive shaft, it is possible to prevente effectively from, equipment disorderly closedown reduces maintenance cost, mentions
High economic benefit.
It is found through market survey, current drive shaft life appraisal is not adapted under design load, theoretical operating condition
The operating condition of production scene quick production capacity adjustment and variation.
Therefore, how by sensor, information system and big data modeling developing go out drive shaft fatigue failure prediction model,
It is more accurate to provide one kind, effective fatigue failure prediction technique becomes this field urgent problem to be solved.
Summary of the invention
The purpose of the present invention is overcome it is above-mentioned in the prior art the shortcomings that, provide it is a kind of based on sensor, information collection,
Big data modeling, data calculate, to establish drive shaft fatigue failure prediction model, realize that the level of accurate failure anticipation is defeated
Send device drives axis fatigue failure prediction technique and device.
In order to achieve the above purpose, horizontal feed device drives axis fatigue failure prediction technique of the invention includes following
Step:
(1) according to the actual condition of drive shaft, drive shaft stress data is acquired by cycle sensor；
(2) judge whether the collected stress data of each period exceeds preset range, if then progressive damage
Value；
(3) judge whether impairment value reaches threshold value, given a warning if reaching.
In the horizontal feed device drives axis fatigue failure prediction technique, the step (1) specifically includes the following steps:
(11) biography between drive shaft load parameter and shear stress is established according to the actual condition of the conveying equipment
Delivery function；
(12) the drive shaft load parameter described by the cycle sensor acquisition；
(13) corresponding stress data is calculated according to the drive shaft load parameter and the transmission function.
In the horizontal feed device drives axis fatigue failure prediction technique, the step (13) is specifically, utilize following formula
Calculate stress data Stress:
Stress=g (MT, SC)=a × MT × SC
Wherein, MT is torque；SC is braking state, and 0 indicates brake locking, and 1 indicates brake release；A is variable.
In the horizontal feed device drives axis fatigue failure prediction technique, the step (2) specifically includes the following steps:
It (21) is the damage Δ D=F of single cycle by stress conversion according to the fatigue properties of the driving shaft material
(Stress)；
(22) judge whether the damage Δ D in single cycle exceeds preset range, if so, (23) are entered step, if it is not,
Then return step (22) enters circulation next time；
(23) impairment value for accumulating single cycle, obtains the fatigue failure damage forecast D=Σ Δ D of the drive shaft.
In the horizontal feed device drives axis fatigue failure prediction technique, the step (3) specifically:
Judge whether impairment value reaches threshold value, the prompting of replacement drive shaft is issued the user with if reaching.
The present invention also provides a kind of horizontal feed device drives axis fatigue failure prediction meanss, which includes:
Multiple sensors are distributed in the drive shaft, to acquire the actual condition of the drive shaft；
Stress calculation module acquires drive shaft by cycle sensor to the actual condition according to the drive shaft
Stress data；
Impairment value statistical module, to judge whether the collected stress data of each period exceeds default model
It encloses, if then damage value；
Alert module gives a warning if reaching to judge whether impairment value reaches threshold value.
In the pre- measurement equipment of horizontal feed device drives axis fatigue failure, the stress calculation module is specifically to root
The transmission function between drive shaft load parameter and shear stress is established according to the actual condition of the conveying equipment；By described
The cycle sensor acquisition drive shaft load parameter；And according to the drive shaft load parameter and the transmitting
Function calculates corresponding stress data.
In the pre- measurement equipment of horizontal feed device drives axis fatigue failure, under the stress calculation module utilizes
Formula calculates stress data Stress:
Stress=g (MT, SC)=a × MT × SC
Wherein, MT is torque；SC is braking state, and 0 indicates brake locking, and 1 indicates brake release；A is variable.
In the pre- measurement equipment of horizontal feed device drives axis fatigue failure, the impairment value statistical module specifically to:
According to it is described driving shaft material fatigue properties by stress conversion be single cycle damage Δ D=F (Stress)；
(22) judge whether the damage Δ D in single cycle exceeds preset range, if so, the damage of accumulation single cycle
Value, obtains the fatigue failure damage forecast D=Σ Δ D of the drive shaft, if it is not, entering circulation next time.
Using the horizontal feed device drives axis fatigue failure prediction technique and device of the invention, first according to drive shaft
Actual condition, pass through cycle sensor acquire drive shaft stress data；And then judge that each period is collected described
Whether stress data exceeds preset range, if then damage value；Finally given a warning when judging that impairment value reaches threshold value.
It is calculated to realize one kind based on sensor information acquisition, big data modeling, data, and establishes drive shaft fatigue failure and predict
Model is realized and carries out life prediction according to actual operating mode, accuracy and the convenience of prediction greatly improved.And the present invention
Horizontal feed device drives axis fatigue failure prediction technique and device, its implementation it is easy, cost of implementation is cheap, using model
It encloses also quite extensively.
Detailed description of the invention
Fig. 1 is the step flow chart of horizontal feed device drives axis fatigue failure prediction technique of the invention.
Fig. 2 is service life curve graph of the horizontal feed device drives axis under different operating conditions.
Fig. 3 is the implementation process of horizontal feed device drives axis fatigue failure prediction meanss of the invention in practical applications
Schematic diagram.
Fig. 4 is the data of multiple sensor acquisitions in horizontal feed device drives axis fatigue failure prediction technique of the invention
Schematic diagram.
Fig. 5 is to be illustrated using the damage accumulation curve of horizontal feed device drives axis fatigue failure prediction technique of the invention
Figure.
Fig. 6 is the application change that cycle-index is corresponded in horizontal feed device drives axis fatigue failure prediction technique of the invention
Change curve graph.
Fig. 7 is the damage of the drive shaft obtained using horizontal feed device drives axis fatigue failure prediction technique of the invention
The visual presentation effect picture that value sorts sequentially in time.
Specific embodiment
In order to be more clearly understood that technology contents of the invention, spy lifts following embodiment and is described in detail.
Refering to Figure 1, being the step process of horizontal feed device drives axis fatigue failure prediction technique of the invention
Figure.
In one embodiment, the horizontal feed device drives axis fatigue failure prediction technique the following steps are included:
(1) according to the actual condition of drive shaft, drive shaft stress data is acquired by cycle sensor；
(2) judge whether the collected stress data of each period exceeds preset range, if then progressive damage
Value；
(3) judge whether impairment value reaches threshold value, given a warning if reaching.
In a kind of more preferably embodiment, the step (1) specifically includes the following steps:
(11) biography between drive shaft load parameter and shear stress is established according to the actual condition of the conveying equipment
Delivery function；
(12) the drive shaft load parameter described by the cycle sensor acquisition；
(13) corresponding stress data is calculated according to the drive shaft load parameter and the transmission function.
In a kind of further preferred embodiment, the step (13) is specifically, calculate stress number using following formula
According to Stress:
Stress=g (MT, SC)=a × MT × SC
Wherein, MT is torque；SC is braking state, and 0 indicates brake locking, and 1 indicates brake release；A is variable.
In another further preferred embodiment, the step (2) specifically includes the following steps:
It (21) is the damage Δ D=F of single cycle by stress conversion according to the fatigue properties of the driving shaft material
(Stress)；
(22) judge whether the damage Δ D in single cycle exceeds preset range, if so, (23) are entered step, if it is not,
Then return step (22) enters circulation next time；
(23) impairment value for accumulating single cycle, obtains the fatigue failure damage forecast D=Σ Δ D of the drive shaft.
In preferred embodiment, the step (3) specifically:
Judge whether impairment value reaches threshold value, the prompting of replacement drive shaft is issued the user with if reaching.
The present invention also provides a kind of horizontal feed device drives axis fatigue failure prediction meanss, in one embodiment,
The device includes:
Multiple sensors are distributed in the drive shaft, to acquire the actual condition of the drive shaft；
Stress calculation module acquires drive shaft by cycle sensor to the actual condition according to the drive shaft
Stress data；
Impairment value statistical module, to judge whether the collected stress data of each period exceeds default model
It encloses, if then damage value；
Alert module gives a warning if reaching to judge whether impairment value reaches threshold value.
In a kind of more preferably embodiment, the stress calculation module specifically to: set according to the conveying
Standby actual condition establishes the transmission function between drive shaft load parameter and shear stress；Pass through the cycle sensor
The acquisition drive shaft load parameter；And it is calculated according to the drive shaft load parameter and the transmission function corresponding
Stress data.
In further preferred embodiment, the stress calculation module calculates stress data using following formula
Stress:
Stress=g (MT, SC)=a × MT × SC
Wherein, MT is torque；SC is braking state, and 0 indicates brake locking, and 1 indicates brake release；A is variable.
In preferred embodiment, the impairment value statistical module specifically to: according to the driving shaft material
Fatigue properties by stress conversion be single cycle damage Δ D=F (Stress)；
(22) judge whether the damage Δ D in single cycle exceeds preset range, if so, the damage of accumulation single cycle
Value, obtains the fatigue failure damage forecast D=Σ Δ D of the drive shaft, if it is not, entering circulation next time.
The purpose of the present invention is can not accurately assess drive shaft actual motion state for the prior art, propose that one is roots
The method of the injury tolerance of drive shaft is accurately assessed according to actual condition.
In practical applications, the present invention is had found by the failure mode of analysis-driven axis, is periodically sheared caused by heavy duty
Stress is excessive the main reason for being its failure, and shear stress has no idea directly to measure, therefore arranges suitable sensor and set
Appropriate transmission function is counted to accurately calculate in drive shaft shear stress with regard to particularly significant.
In suitable position placement sensor, the associated load parameter of drive shaft is taken out, passes through associated mechanical principle and control
Principle establishes transmission function.
After obtaining shear stress, then pass through damage Δ D of the fatigue properties of material by stress conversion for each circulation
=F (Stress) is damaged when stress is lower than fatigue limit as minimum (close to 0)；When stress is more than tensile strength, damages and be
1.Each impairment value recycled is added up one by one, obtains drive shaft fatigue failure damage forecast D=Σ Δ D
D=0 think drive shaft be it is completely new, D=1 thinks that drive shaft is in theory breaks state.It can be according to user
As soon as needing that a threshold value is arranged in D=0.85~0.95, reaches threshold value and trigger warning.User arranges non-life in the specified period
The time is produced by drive shaft replacement while model sets 0.
As shown in Fig. 2, 1. drive shaft that curve represents equipment uses under super design conditions, lesion development is very fast, quickly
Reach threshold value, needs to replace in advance；2. drive shaft that curve represents equipment is run under design conditions, conventional maintenance；Curve is 3.
The drive shaft of equipment is represented lower than running under design conditions, damage is smaller, can extend the service life.
Specifically, horizontal feed device drives axis fatigue failure prediction meanss of the invention include four parts: data
Real-time acquisition/storage, single acquisition item monitoring, model prediction, maintenance one shot.Firstly, the physical state of equipment is passed through sensing
Device is changed into digital signal, passes to industrial gateway, and industrial gateway transmits data to time series database storage；Then industrial
Data are also sent to platform and do data monitoring by gateway, monitoring content include but is not limited to data value whether meet setting requirements,
Whether the quality of data meets the requirements；Time series data based on accumulation can further develop the mould of prediction drive shaft fatigue failure
Type, and be deployed on platform, automatic operating is carried out according to real time data, provides prediction result；According to prediction result, can touch
Hair maintenance is single, guide maintenance operation.Above-mentioned implementation process is as shown in Figure 3.
The N number of sensing data Xn=of devices collect data (X1, X2, X3, X4 ..., Xn), to the data of each sensor into
Row validity check, Xi ∈ Ui, wherein Ui indicates there is specific physical significance one set, such as { 0,1 }, and x | 0 < x < 200 }
Etc., for being unsatisfactory for Xi ∈ Ui, warning of transfiniting is provided, the number that transfinites is counted.The schematic diagram data of multiple sensor acquisitions is such as
Shown in Fig. 4.
Then, to data progress performance analysis is collected, data and operating status are connected.Whole process include with
Row fixture enters and exits two parts, each part include starting, at the uniform velocity with deceleration three phases.
Then the relationship between sensor parameters and fatigue stress is established by fatigue stress analysis.
Stress=g (X 1, X2, X3 ...)
In practical applications:
MT indicates that torque, SC indicate braking state, and only 0 and 1 two value, 0 indicates brake locking, and 1 indicates brake release.
MT and SC are obtained by sensor.A indicates a variable, is obtained by the calculation formula in stress analysis, a can take in present case
376552。
Stress=g (MT, SC)=a*MT*SC
After obtaining shear stress, then pass through damage Δ D of the fatigue properties of material by stress conversion for each circulation
=F (Stress).Formula is as follows:
That is:
When stress is lower than fatigue limit, damage as minimum (close to 0)；When stress is more than tensile strength, damaging is 1.It will
The impairment value of each circulation adds up one by one, obtains drive shaft fatigue failure damage forecast D=Σ Δ D.Damage accumulation curve is such as
Shown in Fig. 5.The application change curve of corresponding cycle-index is then as shown in Figure 6.
The impairment value for finally calculating drive shaft, when impairment value is 0 to be defined as intact, impairment value is 1 to be defined as damaging, and is used
Family can set between 0~1 some numerical value as threshold value (usually 0.85~0.95), when impairment value reaches threshold value, triggering dimension
List is repaired, user is reminded to replace drive shaft.
This process is related to using the sensing data of magnanimity, and each period largely computes repeatedly, while considering can
It by property and timely responds to, it is impossible to manually complete, need using computer information system and big data processing technique.Past number
According to memory technology and analytical technology all do not reach respective horizontal, realize the process, cost is very high, with industrial Internet of Things
The development of network technology, these technical bottlenecks are all broken.
If the impairment value of drive shaft sorted sequentially in time, can visualize as shown in Figure 7.Wherein, horizontal
Axis is the time, and the longitudinal axis is damage forecast (impairment value).Certainly more combined applications can also be done using the impairment value of drive shaft
It is applied with visualization.
Using the horizontal feed device drives axis fatigue failure prediction technique and device of the invention, first according to drive shaft
Actual condition, pass through cycle sensor acquire drive shaft stress data；And then judge that each period is collected described
Whether stress data exceeds preset range, if then damage value；Finally given a warning when judging that impairment value reaches threshold value.
It is calculated to realize one kind based on sensor information acquisition, big data modeling, data, and establishes drive shaft fatigue failure and predict
Model is realized and carries out life prediction according to actual operating mode, accuracy and the convenience of prediction greatly improved.And the present invention
Horizontal feed device drives axis fatigue failure prediction technique and device, its implementation it is easy, cost of implementation is cheap, using model
It encloses also quite extensively.
In this description, the present invention is described with reference to its specific embodiment.But it is clear that can still make
Various modifications and alterations are without departing from the spirit and scope of the invention.Therefore, the description and the appended drawings should be considered as illustrative
And not restrictive.
Claims (9)
1. a kind of horizontal feed device drives axis fatigue failure prediction technique, which comprises the following steps:
(1) according to the actual condition of drive shaft, drive shaft stress data is acquired by cycle sensor；
(2) judge whether the collected stress data of each period exceeds preset range, if then damage value；
(3) judge whether impairment value reaches threshold value, given a warning if reaching.
2. horizontal feed device drives axis fatigue failure prediction technique according to claim 1, which is characterized in that described
Step (1) specifically includes the following steps:
(11) the transmitting letter between drive shaft load parameter and shear stress is established according to the actual condition of the conveying equipment
Number；
(12) the drive shaft load parameter described by the cycle sensor acquisition；
(13) corresponding stress data is calculated according to the drive shaft load parameter and the transmission function.
3. horizontal feed device drives axis fatigue failure prediction technique according to claim 2, which is characterized in that described
Step (13) is specifically, calculate stress data Stress using following formula:
Stress=g (MT, SC)=a × MT × SC
Wherein, MT is torque；SC is braking state, and 0 indicates brake locking, and 1 indicates brake release；A is variable.
4. horizontal feed device drives axis fatigue failure prediction technique according to claim 2, which is characterized in that described
Step (2) specifically includes the following steps:
It (21) is the damage Δ D=F (Stress) of single cycle by stress conversion according to the fatigue properties of the driving shaft material；
(22) judge whether the damage Δ D in single cycle exceeds preset range, if so, (23) are entered step, if it is not, then returning
It goes back to step (22) and enters circulation next time；
(23) impairment value for accumulating single cycle, obtains the fatigue failure damage forecast D=Σ Δ D of the drive shaft.
5. horizontal feed device drives axis fatigue failure prediction technique according to claim 4, which is characterized in that described
Step (3) specifically:
Judge whether impairment value reaches threshold value, the prompting of replacement drive shaft is issued the user with if reaching.
6. a kind of horizontal feed device drives axis fatigue failure prediction meanss, which is characterized in that the device includes:
Multiple sensors are distributed in the drive shaft, to acquire the actual condition of the drive shaft；
Stress calculation module acquires driving axial stress by cycle sensor to the actual condition according to the drive shaft
Data；
Impairment value statistical module, to judge whether the collected stress data of each period exceeds preset range, if
It is then damage value；
Alert module gives a warning if reaching to judge whether impairment value reaches threshold value.
7. the pre- measurement equipment of horizontal feed device drives axis fatigue failure according to claim 6, which is characterized in that described
Stress calculation module specifically to: drive shaft load parameter and shear stress are established according to the actual condition of the conveying equipment
Between transmission function；Pass through the cycle sensor acquisition drive shaft load parameter；And according to the drive
Moving axis load parameter and the transmission function calculate corresponding stress data.
8. horizontal feed device drives axis fatigue failure prediction technique according to claim 7, which is characterized in that described
The stress calculation module calculates stress data Stress using following formula:
Stress=g (MT, SC)=a × MT × SC
Wherein, MT is torque；SC is braking state, and 0 indicates brake locking, and 1 indicates brake release；A is variable.
9. horizontal feed device drives axis fatigue failure prediction technique according to claim 8, which is characterized in that described
Impairment value statistical module specifically to: according to it is described driving shaft material fatigue properties by stress conversion be single cycle damage
Δ D=F (Stress)；
(22) judge whether the damage Δ D in single cycle exceeds preset range, if so, the impairment value of accumulation single cycle,
The fatigue failure damage forecast D=Σ Δ D of the drive shaft is obtained, if it is not, entering circulation next time.
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| CN111709110A (en) * | 2020-04-30 | 2020-09-25 | 工业互联网创新中心（上海）有限公司 | Method and device for predicting service life of seventh shaft sliding table synchronous belt of industrial robot |
| CN112383236A (en) * | 2020-10-26 | 2021-02-19 | 华北电力大学 | Modular multilevel converter maintenance method and system based on online monitoring |
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