CN108196616A - The method for synchronizing time of pipeline detection reducing inertial navigation subsystem data - Google Patents
The method for synchronizing time of pipeline detection reducing inertial navigation subsystem data Download PDFInfo
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Abstract
The invention discloses a kind of PIG reducings based on the mileage time, the simultaneously operating flows of inertial navigation subsystem output data.The flow first arranges the mileage in reducing and inertial navigation output data matrix graphically, using sampling number as horizontal axis；Then mileage is marked in both figures respectively using startup point searching method from static to the flashy sampling number of movement；And then mileage is obtained in respective system clock from static to movement corresponding time in a flash；Finally, the difference of two clocks is obtained, the clock of reducing and inertial navigation subsystem is modified to the same time, realizes the synchronization of data.Synchronous method using the present invention, relative to using method of whole mileages as synchronous base, it can effectively solve the problems, such as in PIG motion processes odometer failure or synchronization failure caused by later stage mileage is corrected, as long as ensureing the complete of service cylinder stage mileage, operation can be synchronized to two subsystems whole output data.
Description
Technical field
The present invention relates to the synchronous method of the internal subsystems output data of in-pipeline detection device, concretely relate to
Reducing and inertial navigation two subsystems in in-pipeline detection device, detecting system is all in the reducings of various pipe diameters/inertial navigation combination
The synchronous method can be used.
Background technology
1. pipeline detection
In-pipeline detection device (PIG) in motion process, can survey defect of pipeline or deformation in pipeline
Amount.PIG is needed generally according to current task, can carry multiple detection subsystems.It is flexible according to different task due to needing
Each detection subsystem is combined, each subsystem usually has independent data acquisition and storage capacity.Since diameter changing device occupies PIG skies
Between it is relatively small, therefore be often mounted in the cavity of PIG with inertial nevigation apparatus, spatially see integrally, can share
One mileage.
Stationary problem between 2.PIG internal subsystems
When needing to be used cooperatively between multiple detection subsystems, the synchronized relation between data is extremely important.For example, work as
Reducing detect and inertial navigation detection and localization two subsystems is mounted on same PIG platforms, be carried out at the same time on-line checking, theoretically under
The data of load should be high level of synchronization, i.e., when detection work terminates, according to the data that detection obtains, inertial navigation positioning and reducing are examined
The object of survey must keep same scale over time and space.Specifically, if reducing detector detects some tube wall
Defect, same time, inertial navigation positioning device should just provide the corresponding geographical coordinate of the defect.
But due to sensor testing principle difference, the electrical structure of corresponding detection device is also different, sample rate, letter
The form of number form, system clock or even output data is all entirely different.Therefore, it is difficult to determine two subsystems of inertial navigation and reducing
The one-to-one relationship of the output data of system in time.
This is just needed after two subsystems all complete data output, and operation is synchronized to two batches output data.It is real
Matter is to ensure two batches output data on respective time shaft using scale at the same time.
3. the limitation of existing synchronous method
The method for solving the problems, such as this before is directly to use method of the mileage as synchronous base.With mileage all the way
Meter signal introduces different detection subsystems respectively, makes its row as output data matrix.So-called output data matrix, refers to
Include multiple data item (mileage is one of them) per data line, be referred to as a sampled point；All data sources of sampled point
In the sampling of the detection subsystem synchronization；By introducing the parameters such as subsystem sample frequency, the signal format, can calculate
Go out sampling time of the row sampled point under the subsystem clock.It, can since each sampled point includes a mileage item
With in output data, using mileage as the horizontal axis of coordinate.When different detection subsystems uses common mileage
As the horizontal axis of coordinate system, it is achieved that the synchronization of different sub-systems output data.
It is above-mentioned directly to use the shortcomings that mileage is as synchronizing datum signal as follows：
1) easily failure.Odometer operates in the protection hull outside of PIG, and relative to other detection subsystems, data are lost
The probability higher of effect.Inside oil-gas pipeline, working environment very severe, the mechanical structure failure rate of odometer is very high.Even if
Odometer keeps mechanical structure not deform and damage, but high viscosity oil, height under the adverse circumstances of 100 hours or so
Corrosive natural gas, inner wall of the pipe defect etc. may all cause odometer skidding, stuck, electric component failure etc. seriously to ask
Topic.Once mileage partly or entirely fails, then all simultaneously operating can not carry out.
2) mileage amendment causes relevant synchrodata also to re-start amendment.After measurement, the precision of mileage
Also there is modified necessity, such as compensation calculation to skid to odometer etc..But mileage is as synchronous base data, once into
Row is corrected, and the detection data of relevant all subsystems will also synchronize amendment respectively.That is, in two subsystems
Simultaneously operating before, in order to ensure output data inside two subsystems and current mileage output data " binding " one
It rises, it is necessary to " synchronization " operation is first carried out inside subsystem output data, and " synchronization " operation of this subsystem internal is also
It may carry out multiple.Which substantially increases the complexity of system data processing, reduce system reliability.
Invention content
Goal of the invention
Present invention aim to address the above problems of reducing and the mileage synchronous method of inertial navigation two subsystems so that inner
Number of passes is according to after the motion parts data failure after service cylinder is left or mileage carries out amendment locally or globally
Afterwards, the startup point time still can be calculated as synchronous base, ensure relatively high synchronization accuracy.
Technical solution
The method for synchronizing time of pipeline detection reducing inertial navigation subsystem data, an odometer signal of PIG systems are same
When be introduced into reducing and inertial navigation two subsystems mounted on a nacelle；In the service cylinder stage, mileage is complete；It is powering on
In operational process, the respective system clock of two subsystems is in identical precision level；It is characterized in that：Method and step is such as
Under：
Step 1 respectively by the odometer initial data figure in reducing and inertial navigation output data matrix, is defined as being used to
Guide system odometer raw-data map and reducing subsystem odometer raw-data map；
Inertial navigation subsystem is similar with the form of reducing subsystem output data, is all organized into two-dimensional table form, each
Row data include multiple data item, and odometer original signal is also one of them, are referred to as a sampled point per data line；From
Power on, self-test, normal acquisition data start after startup, sampled point is known as sampling number according to the positive integer sequence of Time alignment,
M is defined as, m is positive integer；
Obtain after the power is turned on first sampled point is placed in coordinate axis origin, i.e., 0 point, by subsequent sampling number m
The positive integer of mapping horizontal axis, i.e., 1 arrives N number of sampling number；Each corresponding odometer original signal value of sampling number is as the longitudinal axis；
Step 2 defines PIG and is transformed into moment of motion state to start point from stationary state in cylinder of serve a ball, reducing with
The physical time of the startup point of inertial navigation two subsystems is the same；The odometer original signal of two subsystems is used and is started
Point search algorithm marks in inertial navigation subsystem odometer raw-data map and reducing subsystem odometer raw-data map respectively
Start the sampling number of point, be defined as m1 and m2；
The startup point search algorithm is as follows：
1) determine that search starts the precision target search_time of point algorithm, which must be with entire synchronized algorithm
The precision target of precision destination matches, i.e. searching algorithm an order of magnitude higher than the precision target of entire synchronized algorithm, that is, search
The error time search_time of rope algorithm is N/mono- of synchronized algorithm error time goal_time；
2) step-size in search step is determined：The sample frequency (the sampled point number of one second) for defining some subsystem is
Sample_times, the then step-length searched for are that the precision target of search startup point algorithm is multiplied by sample frequency
Step=search_time × sample_times
In search process, when the sampling number of ith search is mi, then the sampling number m of i+1 time searchi+1Have
mi+1=mi+step
3) search space S is defineds：
SsSection is the set of sampling number composition, is one section of continuum on mileage initial data abscissa, by searching
Starting point m_start and terminal the m_end definition of rope；
Define SsPrinciple be：Ensure the target of search, that is, start a little, between m_start and m_end；
Set SsMethod it is as follows：The figure of mileage initial data is observed, starts point and is necessarily in flat region to oscillation
The left margin of this transitional region is set as m_start by the transitional region in region；
M_start is the sampling number for starting search, and m_end is the sampling number for terminating search, carries out subsequent search
It calculates, can determine maximum search times N at this timesFor
Ns=(m_end-m_start)/step
The number that i is current search is enabled, defines search space
Ss={ mi∣m_start≤mi≤ m_end, i=1,2 ..., Ns}
Wherein miSampling number for ith search；
4) the standing section S of PIG in service cylinder is determined；Section is stood, i.e., is got the bid in subsystem odometer original signal figure
Note, PIG is in static condition, and without the set section of the sampling number of minute movement, definition stands interval border sampled point
Number is respectively ms0And ms1, then can define
S={ (m, SV)∣ms0≤m≤ms1}
Wherein m be stand section sampling number, SVFor the odometer original signal corresponding to m；
The method for setting S is as follows：It is observed on mileage raw-data map, since origin, image can tend towards stability rapidly,
And enter a straight region, and which will continue many sampling numbers in terms of abscissa, in this flat region,
Image only has the noise signal of high frequency, without the relatively macrorelief of ordinate, the left margin in this region is labeled as adopting
Number of samples ms0, right margin is labeled as sampling number ms1；
Under the premise of ensureing that PIG remains static, S sections should be as big as possible, from the statistical significance can be more accurate
S when standing is obtainedVObservation, that is, stand section S in all SVMean value, be defined as E (SV)；
5) parameter used in setting search：
The destination sample points for defining ith search are mi, mi∈Ss；
Two used set are needed when defining ith search：Left set (Sl) and right set (Sr), define left set packet
The sampling number contained is ml, it is m to define the right sampling number included of gatheringr；Two set SlAnd Sr, they are with current respectively
The sampling number m of searchiCentered on, positioned at miTwo sampled point set of arranged on left and right sides, the number of the two set interior elements
The number of whole sampled points in 1 second is set as, i.e. sample_times has
Sl={ (ml,SV)∣mi- sample_times≤ml≤mi,mi∈Ss}
Sr={ (mr,SV)∣mi≤mr≤mi+sample_times,mi∈Ss}
Two set whole SVMean value be respectively defined as El(SV) and Er(SV), i.e. El(SV) it is SlInterior whole SVSight
Measured value, Er(SV) it is SrInterior whole SVObservation, work as miIt is to start point, then El(SV) necessarily level off to E (SV), and Er(SV)
It is naturally larger than E (SV)；Work as miIt is not to start point, then El(SV) and Er(SV) the inevitable E (S that equally level off toV) or also greater than E
(SV)；
Define two threshold value εs of this search for judgementlAnd εr, the principle of initial setting is εl＞ 0, and as far as possible
It is small, and εrCompare εlIt is order of magnitude greater, i.e. εrCompare εlM times big, M takes 2 to 10 integer；What if initial setting was searched for opens
Dynamic point more than one, then reduce εlAnd increase εr, re-search for；
6) in SsIn the range of, since m_start, terminate to m_end, search starts point, carries out N altogethersSecondary search calculates；
Ith is searched for, i=1,2 ..., Ns, when having
∣El(SV)-E (SV) ∣ ＜ εlAnd Er(SV)-E (SV) ＞ εr
It sets up, then receives miTo start point；When
∣El(mi)-E (SV)∣≥εlOr Er(mi)-E (SV)≤εr
It sets up, then needs to mi+1Sampling number continues i+1 time search, wherein mi+1=mi+step；
If 7) search completion above, there are one obtained startup points, then the startup point search algorithm of the subsystem
Terminate, if in entire SsIn the range of, according to current εlAnd εrSearch, can obtain multiple startup points, then needs to adjust εlWith
εr, re-start search, until it is surplus it is next until；The method of adjustment is to reduce εlOr increase εr；The εlAnd εrIt must be two
It is used simultaneously in the odometer initial data of a subsystem, respectively obtains and start point m1 and m2；
Step 3, according to reducing and the respective sample frequency sample_times of inertial navigation two subsystems, respectively in reducing
Correspondence times of each sampling number m under respective system clock is obtained in inertial navigation two subsystems odometer original signal figure
T, including m1 and m2 in respective system clock corresponding time t1 and t2,
T=m/sample_times
The horizontal axis of original sampling number m is converted into the horizontal axis of current sub-system clock t；
The difference DELTA t of t1 and t2 is obtained in step 4：The difference of Δ t=t2-t1, Δ t as two subsystems clock；
The clock of two subsystems using Δ t, is modified to the same time, realizes two reducing, inertial navigation subsystems by step 5
The synchronization for data of uniting；
When needing using reducing subsystem clock as during the standard time of subsequent processing, then all sampled points of inertial navigation subsystem
The correspondence time need to subtract Δ t；When it is the standard time to need inertial navigation subsystem time, then institute's having time of reducing subsystem is joined
Number needs plus Δ t.
Advantage and effect
Compared with prior art, the beneficial effects of the invention are as follows：
First, significantly solve the problems, such as that then simultaneously operating can not carry out for odometer failure.Odometer main part is
Mechanical structure, failure be nearly all happened at leave service cylinder after motion process in, service the cylinder stage usually can't go wrong.
And the present invention only requires that service cylinder phase data is complete, you can to find the m1 of step 2 and m2, entire algorithm is not subsequently by shadow
It rings.Substantially the influence that odometer fails to subsequent synchronizing operation is eliminated.
Secondly, caused by completely solving odometer data correction the problem of simultaneously operating result failure before.Mileage number
According to amendment mainly for PIG emerged in operation skidding and data consistency the problems such as, do not interfere with service cylinder stand the stage
Data, therefore do not interfere with the value of the m1 and m2 of step 2, would not influence subsequent simultaneously operating yet.
Description of the drawings
Fig. 1 is inertial navigation subsystem odometer initial data；
Fig. 2 is reducing subsystem odometer initial data；
Fig. 3 is inertial navigation subsystem odometer output data；
Fig. 4 is reducing subsystem odometer output data；
Fig. 5 is reducing and the mileage of inertial navigation output under same time scale；
Fig. 6 is that inertial navigation subsystem odometer initial data starts the neighbouring partial enlargement of point.
Specific embodiment
The present invention is described further below in conjunction with the accompanying drawings：
Fig. 1 is the initial data that typical inertial navigation detects subsystem mileage, and horizontal axis is sampling number, and the longitudinal axis is a large amount of to contain
The mileage signal of noise, the signal are substantially a triangle wave level, and the m1 on horizontal axis is opened for inertial navigation subsystem in service cylinder
The sampling number of dynamic point.
Fig. 2 is the initial data that typical reducing detects subsystem mileage, and horizontal axis is sampling number, and the longitudinal axis is a large amount of to contain
The mileage signal of noise, the signal are substantially a triangle wave level, and m2 is that reducing subsystem starts adopting for point in service cylinder
Number of samples.
Fig. 3 is the output data of typical inertial navigation subsystem, and horizontal axis is the time, and the longitudinal axis is mileage, unit rice.T1 is inertial navigation
Under system clock standard, through the time for startup point in cylinder of serving a ball by the inertial navigation subsystem that m1 is calculated.
Fig. 4 is the output data of typical reducing subsystem, and horizontal axis is the time, and the longitudinal axis is mileage, unit rice.T2 is reducing
Under system clock standard, through the time for startup point in cylinder of serving a ball by the reducing subsystem that m2 is calculated.
The mileage that Fig. 5 detects typical reducing subsystem and inertial navigation detection subsystem output is placed on a coordinate system
Interior, horizontal axis is the time.T1 is under inertial navigation subsystem clock standard, and the inertial navigation subsystem being calculated by m1 passes through in cylinder of serving a ball
Start the time of point.T2 is under reducing subsystem clock standard, and the reducing subsystem being calculated by m2 passes through in cylinder of serving a ball
Start the time of point；Δ t is the synchronous error of reducing and inertial navigation two subsystems clock.
Fig. 6 is that inertial navigation subsystem odometer initial data starts the neighbouring partial enlargement of point, to start the signal near point,
At this point, since the factors such as noise exist, manual method cannot be accurately positioned m1 points, so needing using startup point search algorithm.
Pipeline detection system (PIG) usually carries multiple detection devices, and each device has independent data acquisition and storage
Ability.Due to the limitation of the size of service cylinder and ball collecting chamber, inertial navigation positioning device (core is IMU systems) and reducing diameter detecting device warp
It carries PIG simultaneously frequently as two subsystems and enters pipeline.When needing to be used cooperatively between multiple detection devices, between data
Synchronized relation it is extremely important.But due to reducing system and inertial navigation system, respectively sensor testing principle is different, corresponding electricity
Device structure is also different, and sample rate, signal format etc. are also entirely different, it is likely that causes the dissimilar sensor number of same time
According to the dislocation on unified time axis, it is therefore necessary to synchronize operation.This operation is mainly made with the time data being calculated
For synchronous foundation, the premise performed is：The odometer signal of PIG systems is introduced into reducing and inertial navigation two subsystems simultaneously；
The respective system time of two subsystems is in identical precision level.
The method for synchronizing time of pipeline detection reducing inertial navigation subsystem data, an odometer signal of PIG systems are same
When be introduced into reducing and inertial navigation two subsystems mounted on a nacelle；In the service cylinder stage, mileage is complete；It is powering on
In operational process, the respective system clock of two subsystems is in identical precision level；It is characterized in that：Method and step is such as
Under：
Step 1 respectively by the odometer initial data figure in reducing and inertial navigation output data matrix, is defined as being used to
Guide system odometer raw-data map (as shown in Figure 1) and reducing subsystem odometer raw-data map (as shown in Figure 2)；
Inertial navigation subsystem is similar with the form of reducing subsystem output data, is all organized into two-dimensional table form, each
Row data include multiple data item, odometer original signal (voltage value, unit V, behind be S defined in formulaV) it is also wherein
One of, it is referred to as a sampled point per data line；Since power on, self-test, after startup normal acquisition data, sampled point according to
The positive integer sequence of Time alignment is known as sampling number, is defined as m, and m is positive integer；
Obtain after the power is turned on first sampled point is placed in coordinate axis origin, i.e., 0 point, by subsequent sampling number m
The positive integer of mapping horizontal axis, i.e., 1 arrives N number of sampling number；Each corresponding odometer original signal value of sampling number is as the longitudinal axis；
Odometer original signal is substantially triangular wave, participates in needing according to odometer product description during follow-up data processing
The method migration of offer is into the mileage that unit is rice, such as the ordinate of Fig. 3, Fig. 4 and Fig. 5；
Step 2 defines PIG and is transformed into moment of motion state to start point from stationary state in cylinder of serve a ball, reducing with
The physical time of the startup point of inertial navigation two subsystems is the same.The odometer original signal of two subsystems is used and is started
Point search algorithm marks in inertial navigation subsystem odometer raw-data map and reducing subsystem odometer raw-data map respectively
Start the sampling number of point, be defined as m1 and m2；
Startup point search algorithm can solve the problems, such as follows：Since PIG is under pressure in service cylinder, can be perceived in entrance
Before the motion state of observable, actually there are one process is slowly accelerated, this process at most can be persistently several
The time of ten seconds, the sampling number being related to is related with the sample frequency of two subsystems, at maximum up to up to ten thousand (such as Fig. 1 and Fig. 6
Shown in two figures).When the method for directly using handmarking obtains startup point, in inertial navigation and the odometer of reducing two subsystems
The sampling number of startup point is successively judged in raw-data map (such as Fig. 1 and Fig. 2), 0.1 second to the 10 seconds error not waited can be generated.
Two possible startup point A and B shown in fig. 6 when inertial navigation subsystem sample frequency is 500Hz, are converted into the time, differ energy
Enough reach 5 seconds or more.And the target of two subsystems simultaneously operating, the system clock for being desirable to two subsystems are faced with for the moment
It carves, the difference of output time, i.e., synchronous time precision goal_time is as small as possible.By detecting engineering in entire PIG
Accuracy of target measurement backstepping, the time precision goal_time of two subsystems simultaneously operating have to be lower than 0.1 second, therefore can not
Ignore manually-operated error.A kind of status tracking method for needing to select machine to perform judges two figures with equal scale
Data inflection point starts point search algorithm.Using the searching algorithm, PIG two subsystems can be obtained under same scale and are opened
The precise sample point number at dynamic point moment, the data are most important for two subsystems, and substance, which determines, is based ultimately upon the time
Synchronization process precision.
Initial data (such as Fig. 1 and figure of inertial navigation and reducing two subsystems odometer must be used by starting point search algorithm
2), there is its necessity.Otherwise denoising, granulating, softening, data conversion etc. are carried out to the odometer initial data of inertial navigation and reducing
After processing, some information can be lost, and the situation of different sub-systems data degradation information is also different, and be difficult assessment,
Therefore the data after handling cannot be guaranteed to obtain more accurate startup point under same scale, it is necessary to use initial data.
The startup point search algorithm is as follows：
1) determine that search starts the precision target search_time of point algorithm, which must be with entire synchronized algorithm
The precision target of precision destination matches, i.e. searching algorithm an order of magnitude higher than the precision target of entire synchronized algorithm, that is, search
The error time search_time of rope algorithm is N/mono- of synchronized algorithm error time goal_time；
2) step-size in search step is determined：The sample frequency (the sampled point number of one second) for defining some subsystem is
Sample_times, the then step-length searched for are that the precision target of search startup point algorithm is multiplied by sample frequency
Step=search_time × sample_times
In search process, when the sampling number of ith search is mi, then the sampling number m of i+1 time searchi+1Have
mi+1=mi+step
3) search space S is defined for Fig. 6s：
SsSection is the set of sampling number composition, is one section of continuum on mileage initial data abscissa, by searching
Starting point m_start and terminal the m_end definition of rope；
Define SsPrinciple be：Ensure the target of search, that is, start a little, between m_start and m_end.
Set SsMethod it is as follows：The figure of mileage initial data is observed, starts point and is necessarily in flat region to oscillation
The left margin of this transitional region is set as m_start, such as m_start=195000, right margin by the transitional region in region
It is set as m_end, such as m_end=204000；
M_start is the sampling number for starting search, and m_end is the sampling number for terminating search, carries out subsequent search
It calculates, can determine maximum search times N at this timesFor
Ns=(m_end-m_start)/step
The number that i is current search is enabled, defines search space
Ss={ mi∣m_start≤mi≤ m_end, i=1,2 ..., Ns}
Wherein miSampling number for ith search；
4) the standing section S of PIG in service cylinder is determined；Section is stood, i.e., is got the bid in subsystem odometer original signal figure
Note, PIG is in static condition, and without the set section of the sampling number of minute movement, definition stands interval border sampled point
Number is respectively ms0And ms1, then can define
S={ (m, SV)∣ms0≤m≤ms1}
Wherein m be stand section sampling number, SVFor the odometer original signal corresponding to m；
With shown in Fig. 1 and Fig. 6, the method for setting S is as follows：It is observed on mileage raw-data map, since origin, image
It can tend towards stability rapidly, and enter a straight region, which will continue many sampling numbers in terms of abscissa,
In this flat region, image only has the noise signal of high frequency, without the relatively macrorelief of ordinate, this region
Left margin is labeled as sampling number ms0, right margin is labeled as sampling number ms1, such as ms0=1000, ms1=190000, it is fixed in this way
The S regions of justice ensure that period PIG is placed on stationary state in service cylinder, not interfered by other factors；
Under the premise of ensureing that PIG remains static, S sections should be as big as possible, from the statistical significance can be more accurate
S when standing is obtainedVObservation, that is, stand section S in all SVMean value, be defined as E (SV)；
5) parameter used in setting search：
The destination sample points for defining ith search are mi, mi∈Ss；
Two used set are needed when defining ith search：Left set (Sl) and right set (Sr), define left set packet
The sampling number contained is ml, it is m to define the right sampling number included of gatheringr；Two set SlAnd Sr, they are with current respectively
The sampling number m of searchiCentered on, positioned at miTwo sampled point set of arranged on left and right sides, the number of the two set interior elements
The number of whole sampled points in 1 second is set as, i.e. sample_times has
Sl={ (ml,SV)∣mi- sample_times≤ml≤mi,mi∈Ss}
Sr={ (mr,SV)∣mi≤mr≤mi+sample_times,mi∈Ss}
Two set whole SVMean value be respectively defined as El(SV) and Er(SV), i.e. El(SV) it is SlInterior whole SVSight
Measured value, Er(SV) it is SrInterior whole SVObservation, work as miIt is to start point, then El(SV) necessarily level off to E (SV), and Er(SV)
It is naturally larger than E (SV)；Work as miIt is not to start point, then El(SV) and Er(SV) the inevitable E (S that equally level off toV) or also greater than E
(SV)；
As certain search sampling number mi=195005, then SlRange Representation is as follows：Sl={ (ml,SV)∣194505≤ml≤
195005}；SrRange Representation is as follows：Sr={ (mr,SV)∣195005≤mr≤195505}；
Define two threshold value εs of this search for judgementlAnd εr, the principle of initial setting is εl＞ 0, and as far as possible
It is small, and εrCompare εlIt is order of magnitude greater, i.e. εrCompare εlM times big, M takes 2 to 10 integer；What if initial setting was searched for opens
Dynamic point more than one, then reduce εlAnd increase εr, re-search for；
6) in SsIn the range of, since m_start, terminate to m_end, search starts point, carries out N altogethersSecondary search calculates.
Ith is searched for, i=1,2 ..., Ns, when having
∣El(SV)-E (SV) ∣ ＜ εlAnd Er(SV)-E (SV) ＞ εr
It sets up, then receives miTo start point；When
∣El(mi)-E (SV)∣≥εlOr Er(mi)-E (SV)≤εr
It sets up, then needs to mi+1Sampling number continues i+1 time search, wherein mi+1=mi+step；
If 7) search completion above, there are one obtained startup points, then the startup point search algorithm of the subsystem
Terminate, if in entire SsIn the range of, according to current εlAnd εrSearch, can obtain multiple startup points, then needs to adjust εlWith
εr, re-start search, until it is surplus it is next until；The method of adjustment is to reduce εlOr increase εr；The εlAnd εrIt must be two
It is used simultaneously in the odometer initial data of a subsystem, respectively obtains and start point m1 and m2；
Step 3, according to reducing and the respective sample frequency sample_times of inertial navigation two subsystems, respectively in reducing
Correspondence times of each sampling number m under respective system clock is obtained in inertial navigation two subsystems odometer original signal figure
T, including m1 and m2 in respective system clock corresponding time t1 and t2, such as the abscissa of Fig. 3 and Fig. 4；
T=m/sample_times
The horizontal axis of original sampling number m is converted into the horizontal axis of current sub-system clock t；
The difference DELTA t of t1 and t2 is obtained in step 4：The difference of Δ t=t2-t1, Δ t as two subsystems clock, such as
Shown in Fig. 5；
The clock of two subsystems using Δ t, is modified to the same time, realizes two reducing, inertial navigation subsystems by step 5
The synchronization for data of uniting；
When needing using reducing subsystem clock as during the standard time of subsequent processing, then all sampled points of inertial navigation subsystem
The correspondence time need to subtract Δ t；When it is the standard time to need inertial navigation subsystem time, then institute's having time of reducing subsystem is joined
Number needs plus Δ t.
Practical operation example：
Step 1：
Fig. 1 is obtained by step 1, the initial data of subsystem mileage is detected for typical inertial navigation, horizontal axis is sampling number, is indulged
Axis is the mileage signal for containing much noise, which is substantially a triangle wave level, and the m1 on horizontal axis is service cylinder
Middle inertial navigation subsystem starts the sampling number of point, starts the S regions near point and amplifies in figure 6；
It is the initial data that typical reducing detects subsystem mileage to obtain Fig. 2 by step 1, and horizontal axis is sampling number, the longitudinal axis
To contain the mileage signal of much noise, which is substantially a triangle wave level, and m2 is reducing subsystem in service cylinder
System starts the sampling number of point.Obvious Fig. 2 data and Fig. 1 data waveforms are just the same, are same source datas, but need to carry out same
Step.
Step 2：
Start the necessity of point search algorithm：
Fig. 6 is the signal for starting S regions near point, and A (sampling number 199246), B (sampling number 202419) may
It is to start point, sample frequency 500Hz, time phase difference 6.346 seconds between A, B, therefore since the factors such as noise exist at this time, people
Work method is difficult explication m1 points.
Start point search algorithm 1)
As the synchronization accuracy goal_time of two subsystems, it is desirable that reach 0.1 second, then search for the precision for starting point algorithm
Search_time should be between 0.05 to 0.01 second；
Start point search algorithm 2)
Sample frequency 500Hz, search_time=0.01, then step is 5,
Start point search algorithm 3)
As shown in fig. 6, it can set：M_start=195000, m_end=204000, Ns=1800.
Start point search algorithm 4)
As shown in Figure 1, it may be determined that ms0=1000, ms1=190000, E (SV)=1.772130
Start point search algorithm 5)
With Fig. 6 data instances, εlInitial set value is 0.001, εrInitial set value is 0.01.
Start point search algorithm 6)
When the 1st search, i.e. i=1, sampling number m is searched for1=195000, SlRange Representation is as follows：Sl={ (ml,SV)
∣194500≤ml≤ 195000 }, E is obtainedl(SV)=1.772128；SrRange Representation is as follows：Sr={ (mr,SV)∣195000≤mr
≤ 195500 }, E is obtainedr(SV)=1.772234.It is unsatisfactory for Er(SV)-E (SV) ＞ εr, therefore do not receive m1=195000 is open
Dynamic point.
When the 2nd search, i.e. i=2, sampling number m is searched for2=195005, SlRange Representation is as follows：Sl={ (ml,SV)
∣194505≤ml≤ 195005 }, E is obtainedl(SV)=1.772127；SrRange Representation is as follows：Sr={ (mr,SV)∣195005≤mr
≤ 195505 }, E is obtainedr(SV)=1.772151.It is unsatisfactory for Er(SV)-E (SV) ＞ εr, therefore do not receive m2=195005 is open
Dynamic point.
When the 1640th search, i.e. i=1640, sampling number m is searched for1640=203195, SlRange Representation is as follows：Sl
={ (ml,SV)∣202695≤ml≤ 203195 }, E is obtainedl(SV)=1.772517；SrRange Representation is as follows：Sr={ (mr,SV)∣
203195≤mr≤ 203695 }, E is obtainedr(SV)=1.783518.Meet Rule of judgment, receive m1640=203195 is start
Point.
Start point search algorithm 7)
1800 search are completed, it is found that the startup searched point reaches 22, not uniquely, change εrIt is 0.03 to be worth, again
Search, obtains m1724=203615.SlRange Representation is as follows：Sl={ (ml,SV)∣203115≤ml≤ 203615 }, E is obtainedl(SV)
=1.772802；SrRange Representation is as follows：Sr={ (mr,SV)∣203615≤mr≤ 204115 }, E is obtainedr(SV)=
1.803518.Meet Rule of judgment, receive m1724=203615 uniquely start a little for inertial navigation subsystem, i.e. m1=203615.
Similar approach can obtain m2=106710.
Step 3：
Fig. 3 is obtained by step 3, for the output data of typical inertial navigation subsystem, horizontal axis is the time, and the longitudinal axis is mileage, unit
Rice.T1 be inertial navigation subsystem clock standard under, by the inertial navigation subsystem that m1 is calculated in cylinder of serve a ball through startup put when
Between 407.23 seconds.
Fig. 4 is obtained by step 3, for the output data of typical reducing subsystem, horizontal axis is the time, and the longitudinal axis is mileage, unit
Rice.T2 be reducing subsystem clock standard under, by the reducing subsystem that m2 is calculated in cylinder of serve a ball through startup put when
Between 213.42 seconds.
From Fig. 3,4 it can be seen that, because the processing such as being filtered to initial data, the mileage in many low speed sections
" disappearance ", if seeking startup point at this time, starting can occur " to move ", and mobile distance is not consistent, therefore must
Initial data search must be used to start point.
Step 4：
Fig. 5 is obtained by step 4, the mileage for typical reducing being detected subsystem and inertial navigation detection subsystem output is put
In a coordinate system, Δ t is the synchronous error of reducing and inertial navigation two subsystems clock, obtains Δ t=210.08 seconds.
Step 5：
Using reducing clock as standard, then all inertial navigation output datas (include but not limited to mileage) corresponding time
It must subtract 210.08 seconds.
Claims (1)
1. the method for synchronizing time of pipeline detection reducing inertial navigation subsystem data, an odometer signal of PIG systems is simultaneously
It is introduced into reducing and inertial navigation two subsystems mounted on a nacelle；In the service cylinder stage, mileage is complete；Powering on fortune
During row, the respective system clock of two subsystems is in identical precision level；It is characterized in that：Method and step is as follows：
Step 1 respectively by the odometer initial data figure in reducing and inertial navigation output data matrix, is defined as inertial navigation
System odometer raw-data map and reducing subsystem odometer raw-data map；
Inertial navigation subsystem is similar with the form of reducing subsystem output data, is all organized into two-dimensional table form, each line number
According to including multiple data item, odometer original signal is also one of them, is referred to as a sampled point per data line；From upper
Normal acquisition data start after electricity, self-test, startup, and sampled point is known as sampling number according to the positive integer sequence of Time alignment, fixed
Justice is m, and m is positive integer；
Obtain after the power is turned on first sampled point is placed in coordinate axis origin, i.e., 0 point, by subsequent sampling number m mappings
The positive integer of horizontal axis, i.e., 1 arrives N number of sampling number；Each corresponding odometer original signal value of sampling number is as the longitudinal axis；
Step 2 defines PIG and is transformed into the moment of motion state from stationary state in cylinder of serving a ball to start point, reducing and inertial navigation
The physical time of the startup point of two subsystems is the same；The odometer original signal of two subsystems is searched using point is started
Rope algorithm marks in inertial navigation subsystem odometer raw-data map and reducing subsystem odometer raw-data map start respectively
The sampling number of point, is defined as m1 and m2；
The startup point search algorithm is as follows：
1) determine that search starts the precision target search_time of point algorithm, which must be with the precision of entire synchronized algorithm
The precision target of destination matches, i.e. searching algorithm an order of magnitude higher than the precision target of entire synchronized algorithm, i.e. search are calculated
The error time search_time of method is N/mono- of synchronized algorithm error time goal_time；
2) step-size in search step is determined：The sample frequency (the sampled point number of one second) for defining some subsystem is sample_
Times, the then step-length searched for are that the precision target of search startup point algorithm is multiplied by sample frequency
Step=search_time × sample_times
In search process, when the sampling number of ith search is mi, then the sampling number m of i+1 time searchi+1Have
mi+1=mi+step
3) search space S is defineds：
SsSection is the set of sampling number composition, is one section of continuum on mileage initial data abscissa, by having searched for
Point m_start and terminal m_end definition；
Define SsPrinciple be：Ensure the target of search, that is, start a little, between m_start and m_end；
Set SsMethod it is as follows：The figure of mileage initial data is observed, starts point and is necessarily in flat region to oscillation area
The left margin of this transitional region is set as m_start by transitional region；
M_start is the sampling number for starting search, and m_end is the sampling number for terminating search, carries out subsequent search and calculates,
It can determine maximum search times N at this timesFor
Ns=(m_end-m_start)/step
The number that i is current search is enabled, defines search space
Ss={ mi∣m_start≤mi≤ m_end, i=1,2 ..., Ns}
Wherein miSampling number for ith search；
4) the standing section S of PIG in service cylinder is determined；Section is stood, i.e., is marked in subsystem odometer original signal figure,
PIG is in static condition, and without the set section of the sampling number of minute movement, definition stands interval border sampling number difference
For ms0And ms1, then can define
S={ (m, SV)∣ms0≤m≤ms1}
Wherein m be stand section sampling number, SVFor the odometer original signal corresponding to m；
The method for setting S is as follows：It is observed on mileage raw-data map, since origin, image can tend towards stability rapidly, go forward side by side
Enter a straight region, which will continue many sampling numbers, in this flat region, image in terms of abscissa
The left margin in this region without the relatively macrorelief of ordinate, is labeled as sampled point by the only noise signal of high frequency
Number ms0, right margin is labeled as sampling number ms1；
Under the premise of ensureing that PIG remains static, S sections should be as big as possible, can more accurately ask from the statistical significance
Go out S when standingVObservation, that is, stand section S in all SVMean value, be defined as E (SV)；
5) parameter used in setting search：
The destination sample points for defining ith search are mi, mi∈Ss；
Two used set are needed when defining ith search：Left set (Sl) and right set (Sr), define what left set included
Sampling number is ml, it is m to define the right sampling number included of gatheringr；Two set SlAnd Sr, they are with current search respectively
Sampling number miCentered on, positioned at miTwo sampled point set of arranged on left and right sides, the number of the two set interior elements are set as 1
The number of whole sampled points in second, i.e. sample_times have
Sl={ (ml,SV)∣mi- sample_times≤ml≤mi,mi∈Ss}
Sr={ (mr,SV)∣mi≤mr≤mi+sample_times,mi∈Ss}
Two set whole SVMean value be respectively defined as El(SV) and Er(SV), i.e. El(SV) it is SlInterior whole SVObservation,
Er(SV) it is SrInterior whole SVObservation, work as miIt is to start point, then El(SV) necessarily level off to E (SV), and Er(SV) inevitable big
In E (SV)；Work as miIt is not to start point, then El(SV) and Er(SV) the inevitable E (S that equally level off toV) or also greater than E (SV)；
Define two threshold value εs of this search for judgementlAnd εr, the principle of initial setting is εl＞ 0, and it is as small as possible, and
εrCompare εlIt is order of magnitude greater, i.e. εrCompare εlM times big, M takes 2 to 10 integer；If the startup point that initial setting is searched for is more
In 1, then reduce εlAnd increase εr, re-search for；
6) in SsIn the range of, since m_start, terminate to m_end, search starts point, carries out N altogethersSecondary search calculates；To i-th
Secondary search, i=1,2 ..., Ns, when having
∣El(SV)-E (SV) ∣ ＜ εlAnd Er(SV)-E (SV) ＞ εr
It sets up, then receives miTo start point；When
∣El(mi)-E (SV)∣≥εlOr Er(mi)-E (SV)≤εr
It sets up, then needs to mi+1Sampling number continues i+1 time search, wherein mi+1=mi+step；
If 7) search completion above, there are one obtained startup points, then the startup point search algorithm of the subsystem terminates,
If in entire SsIn the range of, according to current εlAnd εrSearch, can obtain multiple startup points, then needs to adjust εlAnd εr, weight
Newly scan for, until it is surplus it is next until；The method of adjustment is to reduce εlOr increase εr；The εlAnd εrIt must be in two sons
It is used simultaneously in the odometer initial data of system, respectively obtains and start point m1 and m2；
Step 3, according to reducing and the respective sample frequency sample_times of inertial navigation two subsystems, respectively in reducing and used
It leads and correspondence time ts of each sampling number m under respective system clock is obtained in two subsystems odometer original signal figure, wrap
Include m1 and the m2 corresponding time t1 and t2 in respective system clock；
T=m/sample_times
The horizontal axis of original sampling number m is converted into the horizontal axis of current sub-system clock t；
The difference DELTA t of t1 and t2 is obtained in step 4：The difference of Δ t=t2-t1, Δ t as two subsystems clock；
The clock of two subsystems using Δ t, is modified to the same time, realizes reducing, inertial navigation two subsystems number by step 5
According to synchronization；
When needing using reducing subsystem clock as during the standard time of subsequent processing, then pair of all sampled points of inertial navigation subsystem
It needs to subtract Δ t between seasonable；When it is the standard time to need inertial navigation subsystem time, then all time parameters of reducing subsystem need
Add Δ t.
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP1604096A1 (en) * | 2003-02-24 | 2005-12-14 | Nederlandse Organisatie voor toegepast-natuurwetenschappelijk Onderzoek TNO | Method for determining a position of an object |
| CN101281115A (en) * | 2008-04-15 | 2008-10-08 | 天津市嘉信技术工程公司 | Correlation analysis recognition method of detection signal in closed spacing corrosion |
| US8001858B2 (en) * | 2007-01-19 | 2011-08-23 | Cogen William | Pipeline inspection apparatus and method using radio frequency identification and inertial navigation |
| CN102563361A (en) * | 2012-01-18 | 2012-07-11 | 中国石油大学(华东) | Device and method for detecting and positioning leakage of gas transmission pipeline based on conventional data and sound wave signals |
| CN105549057A (en) * | 2015-12-07 | 2016-05-04 | 韩厚增 | Inertial auxiliary GPS/BDS fusion large-scale measurement device and method for quickly measuring land parcel |
| CN106499957A (en) * | 2016-12-28 | 2017-03-15 | 沈阳工业大学 | A kind of pressure wave signal generator and in-pipeline detector real-time tracking localization method |
-
2017
- 2017-12-28 CN CN201711457704.1A patent/CN108196616B/en not_active Expired - Fee Related
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP1604096A1 (en) * | 2003-02-24 | 2005-12-14 | Nederlandse Organisatie voor toegepast-natuurwetenschappelijk Onderzoek TNO | Method for determining a position of an object |
| US8001858B2 (en) * | 2007-01-19 | 2011-08-23 | Cogen William | Pipeline inspection apparatus and method using radio frequency identification and inertial navigation |
| CN101281115A (en) * | 2008-04-15 | 2008-10-08 | 天津市嘉信技术工程公司 | Correlation analysis recognition method of detection signal in closed spacing corrosion |
| CN102563361A (en) * | 2012-01-18 | 2012-07-11 | 中国石油大学(华东) | Device and method for detecting and positioning leakage of gas transmission pipeline based on conventional data and sound wave signals |
| CN105549057A (en) * | 2015-12-07 | 2016-05-04 | 韩厚增 | Inertial auxiliary GPS/BDS fusion large-scale measurement device and method for quickly measuring land parcel |
| CN106499957A (en) * | 2016-12-28 | 2017-03-15 | 沈阳工业大学 | A kind of pressure wave signal generator and in-pipeline detector real-time tracking localization method |
Non-Patent Citations (1)
| Title |
|---|
| 靳鹏: "《管道惯性测绘原始数据迭代去噪算法》", 《无损检测》 * |
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