CN103226752A - Automatic real-time tracking method and automatic real-time tracking system for construction progress of house building - Google Patents

Abstract

The invention discloses an automatic real-time tracking method for a construction progress of a house building. The method comprises the steps that tracking points are arranged on a tower crane; height readings of different angle tracking points and a target building (a target) are obtained by rotating the tower crane, stored, screened, averaged and sent to scale units; data of the scale units is calculated; the height (target height) from the target to the tower crane is stored; angle scale values are read; target height values are screened and averaged when the stored data size reaches a preset value or the setting time is elapsed from storing the first data; the average target height value, the angle scale values, horizontal positions of the tracking points, and the like are transmitted to a server; the server screens and averages the all-day target height of each scale unit; and the average all-day target height, the angle scale values and data quality information are stored in a database. The screening is reliability screening; a corresponding system mainly comprises a range sensor, an angle measurement element, a processor, an AD (Analog to Digital) converter, a wireless communication module and the server; the range sensor is connected with the processor by the AD converter; and the angle measurement element outputs a signal to the processor.

Description

Housing construction progress automatic real-time track method and tracker

Technical field

The present invention relates to a kind of building operation progress automatic real-time track method, especially a kind of housing construction progress automatic real-time track method.Also relate to a kind of housing construction progress automatic real-time track system.

Background technology

The acquisition mode of traditional housing construction progress, the one, hand dipping, manual making a report on: by manual making a report on behind technician's hand dipping.The 2nd, hand dipping, software are made a report on: by making a report on by software (networking, offer) behind technician's hand dipping.

The drawback of aforesaid way is obvious, and the one, untimely, data often become when arriving the related personnel " historical data " by making a report on layer by layer.The 2nd, inaccurate, data are through manual measurement, and the data deviation that is caused by measurement means or other non-technical reasons (driving as performance appraisal, interests) happens occasionally.The 3rd, imperfect, progress data often is made of jointly a series of progress parameters, and traditional means is often ignored the globality and the relevance of these parameters, causes the data integrity disappearance.

The tower machine is one of topmost instrument in the building construction, and it comprises body of the tower, and forearm, tail arm, operation room are arranged at the body of the tower top, and forearm is the part of the force that promotes weight; The tail arm is used to keep balance, and the tower machine also comprises slew gear, and slewing limiter is housed on the slew gear, and slewing limiter comprises a pivoting part and a coupling shaft.The tower machine is realized the rising of tower machine self by the jacking stock.Stock upwards raises earlier during jacking, in the middle of raise back body of the tower and the stock space is arranged, and standard knot is installed in this inside, space, and stock raises once more, and at the inner installation code joint of the stock that soars, along with standard knot constantly increases, the tower machine has just uprised once more.The tower machine is positioned at the working-yard highest point, can look down whole building site, broad view.The task character of tower machine determines the All Jobs face of its operation process coverage goal buildings, does not have the dead angle.

In view of this, special proposition the present invention.

Summary of the invention

The technical problem to be solved in the present invention is to overcome the deficiencies in the prior art, provides a kind of data acquisition in time, accurately, prevents or reduce greatly the data deviation of artificial generation, the housing construction progress automatic real-time track method that cost is low.

The present invention also provides a kind of housing construction progress automatic real-time track system.

For solving the problems of the technologies described above, the present invention adopts the basic design of technical scheme to be:

A kind of housing construction progress automatic real-time track method may further comprise the steps:

1) on the tower machine, trace point is set, along with the uninterrupted 360 degree scanning target buildingss of tower machine operation, the distance of tower machine trace point and target buildings on the measurement different angles, obtain altitude reading and store the height storage unit into, when the data in the height storage unit reach predetermined amount of data, carry out the confidence level screening, calculate the mean value of screening back data and data are sent to scale unit;

2) altitude reading according to the scale unit storage calculates and the storage object height, and the reading angular scale value;

When the scale unit data quantity stored reaches predetermined value or when depositing first data in and begin to have experienced setting-up time, a plurality of object height values are carried out the confidence level screening, data after the screening are averaged, transfer to server together with the trace point horizontal level and the tower machine height of angle index value, the scale unit that prestores; Otherwise continue storage;

Described object height is the height of target buildings apart from foundation for tower crane;

3) server object height that each scale unit whole day is submitted to carries out the confidence level screening, and the data after the screening are averaged as the object height value on the same day this scale unit, deposits database in together with angle index value, quality of data information;

Wherein, quality of data information comprises degree of freedom after data volume on the same day, the screening and the coefficient of dispersion that calculates, described same day, data volume was the target bar number that whole day is submitted on a scale unit, and the degree of freedom after the screening is a remaining data amount behind the data screening in the angle index unit.

The trace point that is installed on different building sites, the different tower machine is coupled to a network.

Object height h _tComputing formula:

h _t=H-s _t

H is the current height of tower machine, s _tAltitude reading for trace point

H=h ₀+n×h _t

H wherein ₀Be tower machine elemental height, n rises joint number amount, h for tower machine accumulative total _iBe the standard knot height.

Described coefficient of dispersion computing formula is

$v_t=\frac{1}{{\mathrm{\δ}}_t}\sqrt{\frac{{\mathrm{\Σ}}_{i=0}^{n_t}{(x_i-{\mathrm{\δ}}_t)}^2}{d_t}}$

x _iBe the height value that the same day, this scale unit was submitted to, d _tBe the degree of freedom after the screening, δ _tBe the object height value on the same day scale unit, n _tRefer to the data volume that t scale unit whole day submitted to.

When the trace point that is numbered t at scale unit n _tServer did not carry out the data polishing when last whole day was submitted any object height value to;

The data polishing divides spatial prediction and two steps of time prediction:

Spatial prediction is by computed altitude growth slope in ± m meter full scale,

k _-m, k _-m+1... k _M-1, k _m, ask average gradient

And calculate scale unit n under this slope _tHeight on interior all angles, m is the absolute value of maximum abnormal some scale value of setting;

The degree of freedom median f of data in ± m meter full scale _mRequire f less than setting lowest degrees of freedom _Min, perhaps coefficient of dispersion median v _mGreater than setting mxm. v _MaxThe time, also need to carry out time prediction;

Time prediction is that the interior preceding D days data of scale of right ± m are carried out above-mentioned spatial prediction, draw the average gradient of every day, simultaneously by the high growth amount on day each angle index of calculating, and with spatial prediction result contrast on the same day, if the same day, high growth amount or average gradient were exceptional value with the screening of Grubbs algorithm, then recomputate height on each angle of this day, D according to average gradient〉3.

Described height storage unit, scale unit, server preferably adopt the Grubbs method to carry out the confidence level screening.

Suppose that it is μ that measured value X obeys average, variance is δ ²Normal distribution, i.e. X～N (μ, δ ²), random sample data of establishing X are: x ₁, x ₂X _n, above-mentioned sample data is arranged in from small to large: x ₍₁₎, x ₍₂₎X _(n), n is for measuring number of times;

The concrete steps of carrying out the confidence level screening with the Grubbs algorithm are:

The first step is calculated offset delta ₁And δ _n

${\mathrm{\δ}}_i=|x_{\left(i\right)}-\stackrel{\‾}{x}|$

In the formula, Be sample mean;

$\stackrel{\‾}{x}=\frac{1}{n}\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{x}_i$

Then

${\mathrm{\δ}}_1=|x_{\left(1\right)}-\stackrel{\‾}{x}|$

${\mathrm{\δ}}_n=|x_{\left(n\right)}-\stackrel{\‾}{x}|$

Second step, relatively δ ₁And δ _n, calculate the wherein deviation ratio G of higher value _i

$G_i=\frac{{\mathrm{\δ}}_i}{s}$

In the formula, s is a standard deviation,

$s=\sqrt{\frac{{\mathrm{\Σ}}_{i=1}^n{(x_{\left(i\right)}-\stackrel{\‾}{x})}^2}{n-1}}$

The 3rd step, determine critical value GP (n), be specially:

Detect horizontal α;

Calculate fiducial probability P, P=1-α according to detecting horizontal α:

According to detecting horizontal α, fiducial probability P and measuring frequency n and look into Grubbs table acquisition critical value GP (n);

The 4th step, relatively G _iWith GP (n), i=1 or n, if G _i＞GP (n), then data x _(i)Be exceptional value, abandoned;

Repeat above step,, perhaps measure frequency n＜3 until there not being exceptional value.

Server detects abnormal some angle index in the database, carries out denoising, is specially:

Detect abnormal point: travel through all angle indexs and calculate the high growth slope k of adjacent angle index _i, if | k _i-k _I-m|＞x, then angle index i-m is judged to be abnormal point to angle index i, and wherein, m is the absolute value of maximum abnormal some scale of setting, and x is the absolute value of maximum abnormal some change;

Denoising: calculate k _I+1And k _I-m-1Average gradient, recomputate angle index i-m all height to the angle index i scope with this slope.

Preferably, the distance of every tower machine trace point of 9-11ms measurement and target buildings.

A kind of housing construction progress automatic real-time track system comprises the tower machine, and described tower machine comprises forearm, tail arm, slew gear, on described tower machine slew gear slewing limiter is housed, and also comprises

Range sensor, obtains altitude reading and also stores to target buildings distance in order to the measurement trace point, when data reach predetermined amount of data, carries out the confidence level screening, calculates the mean value of data after screening and data storage is arrived processor;

The measurement of angle element is gathered described preceding boom slew, the output angle scale value;

Processor comprises a plurality of scale unit, in order to storage trace point horizontal level, tower machine height, calculates and the storage object height according to altitude reading, and the reading angular scale value; When the scale unit data quantity stored reaches predetermined value or when depositing first data in and begin to have experienced setting-up time, a plurality of object height values are carried out the confidence level screening, data after the screening are averaged, transfer to server together with angle index value, the trace point horizontal level that prestores and tower machine height;

AD converter, display, keyboard;

Wireless communication module and server, the object height that server is submitted to each scale unit whole day carry out the confidence level screening, and the data after the screening are averaged, and deposit database in together with angle index value, quality of data information;

Described range sensor is installed on the forearm and/or tail arm of tower machine, described measurement of angle element comprises a coupling shaft, the coupling shaft of described measurement of angle element is connected with the coupling shaft of described slewing limiter by shaft coupling, described measurement of angle element is fixed on the last pivoting part of tower machine slew gear, described range sensor connects described AD converter, described AD converter connects described processor, described measurement of angle element outputs signal to described processor, described keyboard connects described processor, the output terminal of described processor connects described display, and the output terminal of described processor connects described server by described wireless communication module.

Preferably, the coupling shaft of described measurement of angle element is connected with the coupling shaft of described slewing limiter by spring coupling, the coupling shaft of described measurement of angle element is through on the horizontal brace, this horizontal brace is connected with a vertical fixed support, and vertical fixed support is fixed on the last pivoting part of tower machine slew gear.

Preferably, described measurement of angle element is photoelectric encoder or range limiter.

When described measurement of angle element adopts photoelectric encoder,

Described photoelectric encoder output simulating signal, then photoelectric encoder connects described processor by AD converter; Described photoelectric encoder output Gray code, photoelectric encoder directly connects described processor; Described range sensor adopts radar.

Preferably, described processor, AD converter, wireless communication module, display, keyboard are one, adopt data acquisition unit; Described range sensor and data acquisition unit are one on hardware.

After adopting technique scheme, the present invention compared with prior art has following beneficial effect:

This method realizes automatic collection, the transmission of the unmanned intervention of building construction progress, and manual intervention is less, and the confidence level of progress msg is got a promotion, and data acquisition in time, accurately prevents or reduce greatly the data deviation of artificial generation, and cost is low.System architecture is simple.

Below in conjunction with accompanying drawing the specific embodiment of the present invention is described in further detail.

Description of drawings

Fig. 1 is the structural representation of tower machine of the present invention and target buildings;

Fig. 2 is the track while scan figure of three radars among Fig. 1;

Fig. 3 is a data plot in the server database;

Fig. 4 is a housing construction progress automatic real-time track system chart;

Fig. 5 is the wiring layout of photoelectric encoder and slewing limiter;

Fig. 6 is through the radar emission of sawtooth wave modulation and the time correlation curve map of received signal.

Embodiment

The present invention is a housing construction progress automatic real-time track method, may further comprise the steps:

1) sees figures.1.and.2, trace point (the A of Fig. 1 is set on the tower machine, B, C 3 points, be three trace points, A point radar LA is housed respectively, B point radar LB, C point radar LC), along with the uninterrupted 360 degree scanning target buildingss of tower machine operation (3 radars), as the building A district that does not highly wait among Fig. 1 and Fig. 2, building B district, building C district, every 10ms measures the distance (Measuring Time can between 9-11ms value) of tower machine trace point and target buildings, thereby the distance of tower machine trace point and target buildings on the measurement different angles, obtain altitude reading and store into the height storage unit (adopt processor on the hardware, Fig. 1, the processor of the processor adopting data acquisition unit 6 among Fig. 2), when the data in the height storage unit reach predetermined amount of data n, carry out confidence level screening, calculate the mean value of screening back data and with data storage to scale unit (seeing hereinafter introduction for details); R among Fig. 2 _A, r _BAnd r _CThe track while scan of representing A point radar LA, B point radar LB, C point radar LC respectively;

The selection of predetermined amount of data n should be considered following factor: the one, and the actual maximum angular velocity of rotation of tower machine, the 2nd, the actual measurement accuracy of range sensor, the 3rd, the disturbed condition of site environment.When tower machine angular velocity was big, n too conference made the data accumulation overlong time, the relevance variation of final data and angle.When the site environment complexity, serious interference, when the measurement accuracy of range sensor was relatively poor, the too little meeting of n diminished the data volume after the screening, and degree of freedom reduces.

2) altitude reading according to the scale unit storage calculates and the storage object height, and the reading angular scale value;

When the scale unit data quantity stored reaches predetermined value or when depositing first data in and begin to have experienced setting-up time, a plurality of object height values are carried out the confidence level screening, data after the screening are averaged, transfer to server together with the trace point horizontal level and the tower machine height of angle index value, the scale unit that prestores; Otherwise continue storage; Reach the max cap. x of scale unit as data volume _t, as x _t=100 handle when both data volume had reached 100; Or begin to have experienced schedule time m from depositing first data in, as m=5400s, begin to handle after promptly experiencing one and a half hours.

Described object height h _tBe the height of target buildings apart from foundation for tower crane, computing formula is:

h _t＝H-s _t

H is the current height of tower machine, s _tAltitude reading for trace point

H＝h ₀+n×h _i

H wherein ₀Be tower machine elemental height, n rises joint number amount, h for tower machine accumulative total _iBe the standard knot height.

3) server object height that each scale unit whole day is submitted to carries out the confidence level screening, and the data after the screening are averaged as the object height value on the same day this scale unit, deposits database in together with angle index value, quality of data information;

Wherein, quality of data information comprises degree of freedom after data volume on the same day, the screening and the coefficient of dispersion that calculates, described same day, data volume was the target bar number that whole day is submitted on a scale unit, and the degree of freedom after the screening is a remaining data amount behind the data screening in the angle index unit.

Described coefficient of dispersion computing formula is

$v_t=\frac{1}{{\mathrm{\δ}}_t}\sqrt{\frac{{\mathrm{\Σ}}_{i=0}^{n_t}(x_i-{\mathrm{\δ}}_t{)}^2}{d_t}}$

x _iBe the height value that the same day, this scale unit was submitted to, d _tBe the degree of freedom after the screening, δ _tBe the object height value on the same day scale unit, n _tRefer to the data volume that t scale unit whole day submitted to.d _tBig more, v _tMore little, the quality of data is high more.

The present invention is by being provided with trace point on the tower machine, obtain the distance of tower machine forearm 11 and target on the different angles along with the uninterrupted 360 degree scanning target buildingss (calling target in the following text) of tower machine operation, try to achieve the mean value of believable object height, transfer to server together with angle index value, the trace point horizontal level (apart from the distance of a certain point of fixity, as the horizontal range of distance operation room) and the tower machine height that prestore.Server carries out averaging after the confidence level screening as the object height on the same day scale unit to data again, together with depositing database in together with angle index value, quality of data information, construction unit and the related personnel of unit in charge of construction and other modules of management information system can check that database learns the building construction progress, realize the automatic real-time track of building construction progress.The trace point that can be installed on the most at last on different building sites, the different tower machine is coupled to a network, makes information sharing, makes different local people all can check the building progress by the internet.

This method realizes automatic collection, the transmission of the unmanned intervention of building construction progress, and manual intervention is less, and the confidence level of progress msg is got a promotion, and data acquisition in time, accurately prevents or reduce greatly the data deviation of artificial generation, and cost is low.

Server end should also provide following function:

1, rights management: the authority of checking of managing different user.

2, highly manual the rectification: authorized user can carry out manual rectification to elevation information.

3, progress is checked: check progress msg by browser, client (PC or mobile phone).

4, far call: by the Webservice service, other softwares (as ERP system) can the Load Game system.

Server can carry out the progress evaluation by obtaining down column data

1, continuously highly

Highly be used to describe the whole height situation of target continuously.Its describing mode is that a series of angle indexs-highly " name value " are right.Typical describing mode following " typical case is the height description list continuously ":

The typical case is the height description list continuously

Sequence number	Scale	Scope	Highly
				1	-270	170	15.50
2	170	100	38.50

2, maximum height

Maximum height is the describing mode that traditional vivid progress is paid close attention to most.Its value is the maximal value of continuous height, promptly goes up second continuous height in the example: 38.50.

3, progress is described

Progress is to the comparison of height on two time points, comprises scale progress and vivid progress.The scale progress be to specific (or all) continuously scale aspect ratio, vivid progress is the comparison to maximum height.

If because certain reason, when the trace point that is numbered t at scale unit n _tLast whole day is not submitted any object height value to, is called at scale unit n _tLast data incompleteness, this moment, server need be at the enterprising line data polishing of this scale.Cause the reason of data incompleteness relevant with tower machine operation state or radio communication quality.

The data polishing divides spatial prediction and two steps of time prediction:

Spatial prediction is by computed altitude growth slope in ± m meter full scale,

k _-m, k _-m+1K _M-1, k _m, ask average gradient And calculate scale unit n under this slope _tHeight on interior all angles, m is the absolute value of maximum abnormal some scale value of setting;

The degree of freedom median f of data in ± m meter full scale _mRequire f less than setting lowest degrees of freedom _Min, perhaps coefficient of dispersion median v _mGreater than setting mxm. v _MaxThe time, also need to carry out time prediction;

Time prediction is that the interior preceding D days data of scale of right ± m are carried out above-mentioned spatial prediction, draw the average gradient of every day, simultaneously by the high growth amount on day each angle index of calculating, and with spatial prediction result contrast on the same day, if the same day, high growth amount or average gradient were exceptional value with the screening of Grubbs algorithm, then recomputate height on each angle of this day, D according to average gradient〉3.

Make data integrity behind the polishing, do not lack, make the globality of progress parameter and relevance stronger, make data continuous, complete.

Be subjected to site environment (piling up as material) and tower machine operation (interfering as multitower) influence, the height razor-edge or the sharp paddy (being called abnormal point) of similar noise may occur on some scale, Fig. 3 is a data plot in the server database." scabble " abnormal point and help objectively responding the target truth, accurate evaluation objective height, this process is called denoising.Concrete steps are: server detects abnormal some angle index in the database, carries out denoising, is specially:

Detect abnormal point: travel through all angle indexs and calculate the high growth slope k of adjacent angle index _i, if | k _i-k _I-m|＞x, then angle index i-m is judged to be abnormal point to angle index i, and wherein, m is the absolute value of maximum abnormal some scale of setting, and x is the absolute value of maximum abnormal some change;

Denoising: calculate k _I+1And k _I-m-1Average gradient, recomputate angle index i-m all height to the angle index i scope with this slope.Denoising can guarantee the accuracy of data in the server.

Described height storage unit, scale unit, server preferably adopt Grubbs method (Grubbs) to carry out the confidence level screening.In one group of measurement data, if the individual data deviation average is far, these (these) data are called " dubious value " so.From then on the Grubbs method can be organized " dubious value " in the measurement data and to reject and do not participate in the calculating of mean value.Should " dubious value " be called " exceptional value (gross error) ".

Suppose that it is μ that measured value X obeys average, variance is δ ²Normal distribution, i.e. X～N (μ, δ ²), random sample data of establishing X are: x ₁, x ₂X _n, above-mentioned sample data is arranged in from small to large: x ₍₁₎, x ₍₂₎X _(n), n is for measuring number of times;

The concrete steps of carrying out the confidence level screening with the Grubbs algorithm are:

The first step is calculated offset delta ₁And δ _n

${\mathrm{\δ}}_i-|x_{\left(i\right)}-\stackrel{\‾}{x}|$

In the formula,

Be sample mean;

$\stackrel{\‾}{x}=\frac{1}{n}\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{x}_i$

Then

${\mathrm{\δ}}_1=|x_{\left(1\right)}-\stackrel{\‾}{x}|$

${\mathrm{\δ}}_n=|x_{\left(n\right)}-\stackrel{\‾}{x}|$

Second step, relatively δ ₁And δ _n, calculate the wherein deviation ratio G of higher value _i

$G_i=\frac{{\mathrm{\δ}}_i}{s}$

In the formula, s is a standard deviation,

$s=\sqrt{\frac{{\mathrm{\Σ}}_{i=1}^n(x_{\left(i\right)}-\stackrel{\‾}{x}{)}^2}{n-1}}$

The 3rd step, determine critical value GP (n), be specially:

Detect horizontal α;

Calculate fiducial probability P, P=1-α: if strict, detect horizontal α and can decide smallerly, for example decide α=0.01, so fiducial probability P=1-α according to detecting horizontal α.If require not strictly, α can decide more greatly, for example decides α=0.10, i.e. P=0.90.Usually decide α=0.05, P=0.95.

According to detecting horizontal α, fiducial probability P and measuring frequency n and look into Grubbs table acquisition critical value GP (n);

The 4th step, relatively G ₁With GP (n), i=1 or n, if G ₁＞GP (n), then data x _(i)Be exceptional value, abandoned;

Repeat above step,, perhaps measure frequency n＜3 until there not being exceptional value.

The confidence level screening improves the data confidence level.

With reference to Fig. 1 and Fig. 4, a kind of housing construction progress automatic real-time track system comprises the tower machine, and described tower machine comprises forearm 11, tail arm 12, slew gear, on described tower machine slew gear slewing limiter is housed, and described tracker comprises

Range sensor in order to measure trace point to target buildings distance, obtains altitude reading and storage, when data reach predetermined amount of data, carries out the confidence level screening, calculates the mean value of screening back data and with the scale unit of data storage to processor; Describe as range sensor with radar in this article.With reference to Fig. 1, tail arm 12, B point radar LB and C point radar LC that A point radar LA is installed on the tower machine are installed on the forearm 11 of tower machine, (mounting points is apart from the distance of body of the tower in concrete installation site, be negative when being installed on the tail arm 12) and quantity determine according to the concrete condition of target, be as the criterion with the true altitude form that can detect the target different azimuth.Range sensor installation site, forearm 11 height (the tower machine is also wanted typing after rising joint) are by installation personnel typing processor.The range sensor mounting points can reach tens of rice even rice up to a hundred apart from pilothouse, and modes such as employing 485,422, CAN bus connect.Described range sensor connects described AD converter, and described AD converter connects described processor, as Fig. 4;

The measurement of angle element is gathered described forearm 11 angles of revolution, the output angle scale value; The described measurement of angle element 2 preferred photoelectric encoder 21(that adopt require also can select range limiter when hanging down to angle precision both target progress orientation, connected mode and measurement of angle element are together), with reference to Fig. 5, the coupling shaft of photoelectric encoder 21 is connected with the coupling shaft of described slewing limiter 4 by spring coupling 3, the coupling shaft of described photoelectric encoder 21 is through on the horizontal brace, this horizontal brace is connected with a vertical fixed support 5, and vertical fixed support is fixed on the last pivoting part of tower machine slew gear.The photoelectric encoder number of active coils is not less than 64 circles, and individual pen resolution is not less than 512 gratings.Exportable Gray code of dissimilar photoelectric encoders or simulating signal, the former links to each other with the IO port of processor by data line, insert AD converter when being output as the latter earlier, AD converter connects described processor, synoptic diagram when Fig. 4 is the latter, processor is according to corresponding time sequence reading angular data from photoelectric encoder or AD converter.

Processor adopts MCU, and MCU opens up a buffer zone for each range sensor when initialization, and the buffer zone that is numbered the range sensor of t claims buff _t, be used to deposit the object height of different trace points.Each buffer zone is divided into n scale unit, is used to deposit forearm 11 and revolves one group of object height value on the different scale groups in the three-sixth turn scope.N should be able to divide exactly 360.N=120 for example, promptly per 3 degree be as a grouping, totally 120 scale unit, and element number is 1,2 ... 120.Processor calculates and the storage object height according to altitude reading also in order to storage trace point horizontal level, tower machine height, and the reading angular scale value; When the scale unit data quantity stored reaches predetermined value or when depositing first data in and begin to have experienced setting-up time, a plurality of object height values are carried out the confidence level screening, data after the screening are averaged, transfer to server together with angle index value, the trace point horizontal level that prestores and tower machine height;

AD converter, display, keyboard; Keyboard and display provide man-machine interface, make installation site that installation personnel can the typing radar, tower machine elemental height, rise the joint number amount.

Wireless communication module and server, the object height that each scale unit whole day is submitted to carries out the confidence level screening, and the data after the screening are averaged, and deposits database in together with angle index value, quality of data information.Described keyboard connects described processor, and the output terminal of described processor connects described display, and the output terminal of described processor connects described server by described wireless communication module, as Fig. 4.

The native system range sensor adopts K wave band flat plane antenna radar.

Radar is the electronic equipment that utilizes the electromagnetic wave detection target, its principle of work can be sketched and be: launching electromagnetic wave shines (transmitting RF) to target and receives its echo (receive RF), obtains target thus to information such as the distance of electromagnetic wave launching site, range rate (radial velocity), orientation, height.Radar working frequency range commonly used at present has: 10.525GHz-X wave band, 24GHz-K wave band, 35GHz-Ka wave band, 77GHz-V wave band.It is K band microwave radar that native system is selected 24GHz for use.24GHz is a radar working frequency range of the global general-use of ISM regulation, and suffered interference is less when working on this frequency range.

The critical piece and the parameter thereof of radar comprise

MCU(is the microprocessor of radar): obtain altitude reading and storage, when data reach predetermined amount of data, carry out the confidence level screening, calculate mean value that screens the back data and the scale unit (situation for adopting data acquisition unit just stores data acquisition unit into) that data storage is arrived processor.

VCO: signal generator.

Emitting antenna: signal transmission path.

Receiving antenna: target echo signal RX path.

RF prime amplifier: echoed signal is carried out processing and amplifying, can improve the sensitivity of sensor long-range detection to a certain extent.

Frequency mixer: synchronization is transmitted and the received signal mixing.

The IF prime amplifier: preliminary filtering interfering and noise signal, the restricting signal bandwidth, and can avoid sensor to suffer electrostatic hazard to a certain extent.

Vtune: the magnitude of voltage that refers to the sawtooth signal of modulating.Modulation signal adopts sawtooth wave, and the interference of this moment mostly is Doppler signal greatly, and aspect interference free performance, the sawtooth wave modulation is better than triangular modulation.Select linear uphill slope curve or descending grade curve time correlation function for use, and regularly repeat these ripples, in the hope of obtaining possible mean value as transmission frequency.

Modulation amplitude: the range of adjustment of choosing one section best definite Vtune of tuning curve neutral line degree.In theory, the modulation amplitude maximum magnitude is 0.5V～10V;

Modulating frequency: maximum is no more than 150kHz in theory, adopts the modulating frequency of 100～200Hz when surveying the distant object of 30～100m, adopts the modulating frequency of 500～1kHz when surveying the close-in target of 10～20m.

The distance measurement process of radar

By frequency of signal generator VCO output is f _TraTransmit, wherein one the tunnel go out through transmission antennas transmit, the one tunnel is split in the frequency mixer that two-way enters I, Q passage respectively, wherein the Q channel signal before mixing earlier through 90 ° of phase shifts.The echoed signal that receiving antenna receives after the low noise processing and amplifying, is carried out mixing through frequency mixer and the two paths of signals of shunting in real time respectively earlier again; The signal that obtains after the mixing finally obtains I, Q two-way intermediate-freuqncy signal again through the intermediate frequency filtering processing and amplifying.All carry the range information of the detection of a target in I, the Q two-way intermediate frequency output signal.

The range observation algorithm of radar

Range information in the difference frequency signal is to reflect by the difference frequency signal that is caused by time delay, as Fig. 6.

Transmission frequency curve (F _Transmit) and receive frequency curve (F _Receive) unique difference be time delay.T at a time ₀Instantaneous received signal, its frequency is lower than instantaneous transmission frequency (for the uphill slope curve), reason is that sensor raises in the synchronization transmission frequency.Transmit and received signal if in frequency mixer, mix, will generate a constant difference frequency signal f _d, wherein comprising required range information, this frequency is high more, and the distance of target is far away more, satisfies following formula:

$R=\frac{{\mathrm{<figure-callout\; id="0"\; label="c"\; filenames="HDA00003030312000031.png"\; state="\{\{state\}\}">c</figure-callout>}}_0}{2}\&CenterDot;T\&CenterDot;\frac{f_d}{\mathrm{\&Delta;f}}---\left(1\right)$

Or

$R=\frac{{\mathrm{<figure-callout\; id="0"\; label="c"\; filenames="HDA00003030312000031.png"\; state="\{\{state\}\}">c</figure-callout>}}_0}{2}\&CenterDot;\frac{1}{f}\&CenterDot;\frac{f_d}{\mathrm{\&Delta;f}}---\left(2\right)$

Wherein:

f _dDifference frequency

The variation range of Δ f oscillator transmission frequency, i.e. frequency modulation width

The T tooth ripple repetition period

The distance of R target

c ₀The light velocity

F frequency modulation speed,

The flow chart of data processing of radar and algorithm

Radar carries out a range observation for per 10 milliseconds, produce a reading, the MCU of radar self is temporary in reading in the buffer zone, after waiting to reach certain data volume n, these group data are carried out the confidence level screening, send the mean value of screening back data to processor storage (, just send to data acquisition unit and handle) for the situation that adopts data acquisition unit.The selection of constant n should be considered following factor: the one, and the actual maximum angular velocity of rotation of tower machine, the 2nd, the actual measurement accuracy of radar, the 3rd, the disturbed condition of site environment.When tower machine angular velocity was big, n too conference made the data accumulation overlong time, the relevance variation of final data and angle.When the site environment complexity, serious interference, when the measurement accuracy of radar was relatively poor, the too little meeting of n diminished the data volume after the screening, and degree of freedom reduces.

Simple in structure for system, described processor, AD converter, wireless communication module, display, keyboard are one, adopt ripe data acquisition unit 6, data acquisition unit 6 can be installed on tower machine pilothouse, in particular cases also can be installed in other positions of tower machine, this moment, the appearance design of data acquisition unit 6 should be considered waterproof.

Described range sensor and data acquisition unit 6 also can be one on hardware.

The above only is a preferred implementation of the present invention; should be pointed out that for those skilled in the art, under the prerequisite that does not break away from the principle of the invention; can also make some improvements and modifications, these improvements and modifications also should be considered as protection scope of the present invention.

Claims (14)

1. housing construction progress automatic real-time track method is characterized in that: may further comprise the steps:

1) on the tower machine, trace point is set, along with the uninterrupted 360 degree scanning target buildingss of tower machine operation, the distance of tower machine trace point and target buildings on the measurement different angles, obtain altitude reading and store the height storage unit into, when the data in the height storage unit reach predetermined amount of data, carry out the confidence level screening, calculate the mean value of screening back data and data are sent to scale unit;

2) altitude reading according to the scale unit storage calculates and the storage object height, and the reading angular scale value;

When the scale unit data quantity stored reaches predetermined value or when depositing first data in and begin to have experienced setting-up time, a plurality of object height values are carried out the confidence level screening, data after the screening are averaged, transfer to server together with the trace point horizontal level and the tower machine height of angle index value, the scale unit that prestores; Otherwise continue storage;

Described object height is the height of target buildings apart from foundation for tower crane;

3) server object height that each scale unit whole day is submitted to carries out the confidence level screening, and the data after the screening are averaged as the object height value on the same day this scale unit, deposits database in together with angle index value, quality of data information;

Wherein, quality of data information comprises degree of freedom after data volume on the same day, the screening and the coefficient of dispersion that calculates, described same day, data volume was the target bar number that whole day is submitted on a scale unit, and the degree of freedom after the screening is a remaining data amount behind the data screening in the angle index unit.

2. housing construction progress automatic real-time track method according to claim 1 is characterized in that: the trace point that will be installed on different building sites, the different tower machine is coupled to a network.

3. housing construction progress automatic real-time track method according to claim 1 is characterized in that: object height h _tComputing formula:

h _t＝H-s _t

H is the current height of tower machine, s _tAltitude reading for trace point

H＝h ₀+n×h _i

H wherein ₀Be tower machine elemental height, n rises joint number amount, h for tower machine accumulative total _iBe the standard knot height.

4. housing construction progress automatic real-time track method according to claim 1, it is characterized in that: described coefficient of dispersion computing formula is

$v_t=\frac{1}{{\mathrm{\&delta;}}_t}\sqrt{\frac{{\mathrm{\&Sigma;}}_{i=0}^{n_t}{(x_i-{\mathrm{\&delta;}}_t)}^2}{d_t}}$

x _iBe the height value that the same day, this scale unit was submitted to, d _tBe the degree of freedom after the screening, δ _tBe the object height value on the same day scale unit, n _tRefer to the data volume that t scale unit whole day submitted to.

5. housing construction progress automatic real-time track method according to claim 4 is characterized in that: when the trace point that is numbered t at scale unit n _tServer did not carry out the data polishing when last whole day was submitted any object height value to;

The data polishing divides spatial prediction and two steps of time prediction:

Spatial prediction is by computed altitude growth slope in ± m meter full scale,

k _-m, k _-m+1K _M-1, k _m, ask average gradient

And calculate scale unit n under this slope _tHeight on interior all angles, m is the absolute value of maximum abnormal some scale value of setting;

The degree of freedom median f of data in ± m meter full scale _mRequire f less than setting lowest degrees of freedom _Min, perhaps coefficient of dispersion median v _mGreater than setting mxm. v _MaxThe time, also need to carry out time prediction;

Time prediction is that the interior preceding D days data of scale of right ± m are carried out above-mentioned spatial prediction, draw the average gradient of every day, simultaneously by the high growth amount on day each angle index of calculating, and with spatial prediction result contrast on the same day, if the same day, high growth amount or average gradient were exceptional value with the screening of Grubbs algorithm, then recomputate height on each angle of this day, D according to average gradient〉3.

6. housing construction progress automatic real-time track method according to claim 1 is characterized in that: described height storage unit, scale unit, server adopt the Grubbs method to carry out the confidence level screening.

7. according to claim 5 or 6 described housing construction progress automatic real-time track methods, it is characterized in that: it is μ that supposition measured value X obeys average, and variance is δ ²Normal distribution, i.e. X～N (μ, δ ²), random sample data of establishing X are: x ₁, x ₂X _n, above-mentioned sample data is arranged in from small to large: x ₍₁₎, x ₍₂₎X _(n), n is for measuring number of times;

The concrete steps of carrying out the confidence level screening with the Grubbs algorithm are:

The first step is calculated offset delta ₁And δ _n

${\mathrm{\&delta;}}_i=|x_{\left(i\right)}-\stackrel{\&OverBar;}{x}|$

In the formula,

Be sample mean;

$\stackrel{\&OverBar;}{x}=\frac{1}{n}\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{x}_i$

Then

${\mathrm{\&delta;}}_1=|x_{\left(1\right)}-\stackrel{\&OverBar;}{x}|$

${\mathrm{\&delta;}}_n=|x_{\left(n\right)}-\stackrel{\&OverBar;}{x}|$

Second step, relatively δ ₁And δ _n, calculate the wherein deviation ratio G of higher value ₁

$G_i=\frac{{\mathrm{\&delta;}}_i}{s}$

In the formula, s is a standard deviation,

$s=\sqrt{\frac{{\mathrm{\&Sigma;}}_{i=1}^n(x_{\left(i\right)}-\stackrel{\&OverBar;}{x}{)}^2}{n-1}}$

The 3rd step, determine critical value GP (n), be specially:

Detect horizontal α;

Calculate fiducial probability P, P=1-α according to detecting horizontal α:

According to detecting horizontal α, fiducial probability P and measuring frequency n and look into Grubbs table acquisition critical value GP (n);

The 4th step, relatively G _iWith GP (n), i=1 or n, if G ₁＞GP (n), then data x _(i)Be exceptional value, abandoned;

Repeat above step,, perhaps measure frequency n＜3 until there not being exceptional value.

8. housing construction progress automatic real-time track method according to claim 5 is characterized in that: server detects abnormal some angle index in the database, carries out denoising, is specially:

Detect abnormal point: travel through all angle indexs and calculate the high growth slope k of adjacent angle index _i, if | k _i- _Ki-m|＞x, then angle index i-m is judged to be abnormal point to angle index i, and wherein, m is the absolute value of maximum abnormal some scale of setting, and x is the absolute value of maximum abnormal some change;

Denoising: calculate k _I+1And k _I-m-1Average gradient, recomputate angle index i-m all height to the angle index i scope with this slope.

9. housing construction progress automatic real-time track method according to claim 1 is characterized in that: the distance of every tower machine trace point of 9-11ms measurement and target buildings.

10. a housing construction progress automatic real-time track system comprises the tower machine, and described tower machine comprises forearm, tail arm, slew gear, on described tower machine slew gear slewing limiter is housed, and it is characterized in that: also comprise

Range sensor, obtains altitude reading and also stores to target buildings distance in order to the measurement trace point, when data reach predetermined amount of data, carries out the confidence level screening, calculates the mean value of data after screening and data storage is arrived processor;

The measurement of angle element is gathered described preceding boom slew, the output angle scale value;

Processor comprises a plurality of scale unit, in order to storage trace point horizontal level, tower machine height, calculates and the storage object height according to altitude reading, and the reading angular scale value; When the scale unit data quantity stored reaches predetermined value or when depositing first data in and begin to have experienced setting-up time, a plurality of object height values are carried out the confidence level screening, data after the screening are averaged, transfer to server together with angle index value, the trace point horizontal level that prestores and tower machine height;

AD converter, display, keyboard;

Wireless communication module and server, the object height that server is submitted to each scale unit whole day carry out the confidence level screening, and the data after the screening are averaged, and deposit database in together with angle index value, quality of data information;

Described range sensor is installed on the forearm and/or tail arm of tower machine, described measurement of angle element comprises a coupling shaft, the coupling shaft of described measurement of angle element is connected with the coupling shaft of described slewing limiter by shaft coupling, described measurement of angle element is fixed on the last pivoting part of tower machine slew gear, described range sensor connects described AD converter, described AD converter connects described processor, described measurement of angle element outputs signal to described processor, described keyboard connects described processor, the output terminal of described processor connects described display, and the output terminal of described processor connects described server by described wireless communication module.

11. housing construction progress automatic real-time track according to claim 10 system, it is characterized in that: the coupling shaft of described measurement of angle element is connected with the coupling shaft of described slewing limiter by spring coupling, the coupling shaft of described measurement of angle element is through on the horizontal brace, this horizontal brace is connected with a vertical fixed support, and vertical fixed support is fixed on the last pivoting part of tower machine slew gear.

12. according to claim 10 or 11 described housing construction progress automatic real-time track systems, it is characterized in that: described measurement of angle element is photoelectric encoder or range limiter.

13. housing construction progress automatic real-time track according to claim 12 system is characterized in that: when described measurement of angle element adopts photoelectric encoder,

Described photoelectric encoder output simulating signal, then photoelectric encoder connects described processor by AD converter; Described photoelectric encoder output Gray code, photoelectric encoder directly connects described processor; Described range sensor adopts radar.

14. housing construction progress automatic real-time track according to claim 10 system, it is characterized in that: described processor, AD converter, wireless communication module, display, keyboard are one, adopt data acquisition unit; Described range sensor and data acquisition unit are one on hardware.

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