CN101629407A - Pavement structural strength forecasting method - Google Patents

Abstract

The invention discloses a pavement structural strength forecasting method which comprises the following steps: obtaining a pavement quality grade through detecting pavement damage and pavement deflection data of each sampling road section, arranging according to a sequence of the pavement quality grade and obtaining each group of pavement condition indexes PCI and pavement structural strength indexes PSSI corresponding to each sampling road section; respectively computing PCI and PSSI moving average values from the PCI and PSSI values of each sampling road section; obtaining a PSSI gradient value through each group of moving average values and obtaining an interval value of two PCIs when the PSSI gradient value is changed correspondingly to the PCIs; forecasting an interval value of two corresponding PSSIs through the interval value of the two PCIs and obtaining a corresponding diagram of the PCI value and the PSSI value; measuring the PCI value of a to-be-detected pavement and obtaining the PSSI value of the to-be-detected pavement through the corresponding diagram. The invention has accurate detection, reduces the detection cost and improves the highway maintenance efficiency.

Description

A kind of pavement structural strength forecasting method

Technical field

The present invention relates to highway construction detection technique field, be meant a kind of pavement structural strength forecasting method especially.

Background technology

Highway is being keeped in repair early stage, can at first predict, after the pavement structural strength of each interval highway is predicted, selecting the maintenance scheme that is fit to again the pavement structural strength of highway.

At present according to the maintenance character of highway, with the maintenance character of flexible pavement be divided into routine maintenance, in repair and three types of overhauls.There is very large difference in the maintenance of surface activity of these three kinds of character at aspects such as maintenance effect, maintenance costs and maintenance plans.In the Maintenance Decision making on road surface, general at first according to the state indices (PCI on road surface, Pavement condition index) and surface evenness (RQI, riding quality index) evaluation result and pavement deflection data, and then definite pavement structural strength index (PSSI, pavement structure strength index) whether satisfies the judgement of pre-provisioning request, repair in determining to carry out large repairs still.

The testing process of above-mentioned pavement structural strength PSSI is to predict according to the detection data of pavement deflection, this detection DATA REASONING time overlength, only be fit to predict highway section among a small circle, as sampling Detection, large-scale drive test for the hundreds of thousands kilometer, but there is following problem in this prediction: 1) do not have flexure checkout equipment fast at present, extensive flexure is consuming time longer detection time; 2) because the flexure detected value is subjected to temperature, humidity, detection position and operator's factor affecting, the repeatable calculation process reliability that detects data is relatively poor; 3) pavement deflection testing cost height.More than these problems usually cause estimating pavement structural strength PSSI situation accurately, in time, all sidedly, thereby can't carry out the maintenance of surface analysis of science.

Summary of the invention

In view of this, the invention reside in provides a kind of pavement structural strength forecasting method, and when predicting pavement strength PSSI to solve above-mentioned detection data by pavement deflection, the data of existence are inaccurate, predict the outcome and can not determine the problem of road upkeep.

For addressing the above problem, the invention provides a kind of pavement structural strength forecasting method, comprise: by detecting the breakage rate and the pavement deflection data in each sampling highway section, obtain pavement quality grade, and arrange according to the pavement quality grade order, what obtains described each highway section correspondence of sampling respectively organizes pavement state indices P CI and pavement structural strength index PSSI; The PCI and the PSSI moving average that from the PCI in each group sampling highway section and PSSI value, calculate respectively; By the described Grad that moving average obtains PSSI, the interval value of two PCI that the corresponding PCI of acquisition PSSI Grad changes respectively organized; By the interval value of described two PCI, dope the interval value of two corresponding PSSI, and obtain the corresponding diagram of PCI value and PSSI value; Measure the PCI value on detected road surface, obtain the PSSI value on detected road surface by described corresponding diagram.

Preferably, the data number of pavement state indices P CI and pavement structural strength index PSSI is respectively more than 20 in each group of described each sampling highway section correspondence.

Preferably, described from each group sampling highway section PCI and the PSSI value calculate PCI and PSSI moving average respectively process comprise:

Obtain respectively between the sliding area of PCI and PSSI value, between described sliding area in, according to predetermined group distance with calculate step-length, and obtain PCI and PSSI moving average according to following formula;

PCI _j＝AVERAGE(PCI _i)，PCI _i∈[PCI _j1，PCI _j2]

PSSI _j＝AVERAGE(PSSI _i)，PCI _i∈[PCI _j1，PCI _j2]

PCI _j1＝100-(j-1)×δ

PCI _j2＝100-(j-1)×δ-l

$j=\mathrm{1,2},...,\mathrm{int}\left(\frac{100}{\mathrm{\δ}}\right)+1$

In the formula,

PCI _iThe PCI moving average of-Di j group;

PSSI _jThe PSSI moving average of-Di j group;

PCI _J1The PCI lower limit of-Di j group rolling average;

PCI _J2The PCI higher limit of-Di j group rolling average;

The group distance of d-rolling average;

Step-length is calculated in the l-rolling average.

Preferably, comprise by the described process of respectively organizing the Grad of moving average acquisition PSSI:

Respectively organize the respectively corresponding footnote of PCI and PSSI moving average 1 to K with what obtain, adopt formula Δ PSSI _k=(PSSI _K+1-PSSI _k)/(PCI _K+1-PCI _k) obtain the Grad of PSSI;

The process of the interval value of two PCI that the corresponding PCI of described acquisition PSSI Grad changes comprises:

According to 1 to K the PSSI Grad that obtains, respectively in proper order, backward obtains first PSSI Grad greater than threshold value, with the PCI moving average of two Grad correspondences respectively as the interval value of two PCI.

Preferably, by the interval value of described two PCI, dope the interval value of two corresponding PSSI, and the process of the corresponding diagram of acquisition PCI value and PSSI value comprises:

Adopt normal distribution to dope corresponding described two PSSI values, the described PCI value of acquisition and the corresponding diagram of PSSI value are:

Between the interval value of two PCI, PCI and PSSI value are linear corresponding; Outside the interval value of two PCI, PCI and PSSI value are non-linear correspondence.

Preferably, also comprise after this method:

Judge between the servicing area that current PSSI value belonged to, select corresponding highway maintenance rank.

Describe method of the present invention above in detail, the present invention can obtain road surface PSSI accurately by the highway section of sampling, and dopes the PSSI in whole highway section, and this method is simple, accurate, has reduced the pavement detection cost, has improved pavement detection efficient, good reliability.

Description of drawings

Fig. 1 is the flow chart of embodiment;

Fig. 2 is PSSI and PCI distribution corresponding relation schematic diagram.

The specific embodiment

For clearly demonstrating the scheme among the present invention, provide preferred embodiment below and be described with reference to the accompanying drawings.

Referring to Fig. 1, Fig. 1 is the flow chart of the embodiment of the invention, comprising:

Step 1: to selected highway section sampling Detection, by detecting the breakage rate and the pavement deflection data in each sampling highway section, obtain pavement quality grade, and arrange according to the pavement quality grade order, what obtains described each highway section correspondence of sampling respectively organizes pavement state indices P CI and pavement structural strength index PSSI;

In the embodiments of the invention, can be in advance to selected highway section sampling Detection, length can be set at less than 1 kilometer, detect the pavement deflection data in each highway section, measure the PSSI in each sampling highway section, select pavement distress to be in excellent respectively, very, in, each m of inferior and poor highway section (for eliminating the influence of randomness, m generally should be greater than 20), wherein, excellent, very, in, inferior and poor grade can be set by the index on various road surfaces, as the sectional curve on road surface, number ranges such as planeness detect the breakage rate and the pavement deflection in these highway sections, calculate the road surface using property data PCI and the PSSI in each highway section, draw n group data.

Step 2: from the n that obtained group PCI and PSSI data, calculate PCI and PSSI average respectively;

Adopt the rolling average algorithm in the statistical analysis, ask for the PCI of each group and the sliding average of PSSI respectively.To n group road condition data (PCI _i, PSSI _i), be calculated as follows sliding average:

PCI _j＝AVERAGE(PCI _i)，PCI _i∈[PCI _j1，PCI _j2]????????(2)

PSSI _j＝AVERAGE(PSSI _i)，PCI _i∈[PCI _j1，PCI _j2]??????(3)

PCI _j1＝100-(j-1)×δ?????????????????????????????(4)

PCI _j2＝100-(j-1)×δ-l???????????????????????????(5)

$j=\mathrm{1,2},...,\mathrm{int}\left(\frac{100}{\mathrm{\δ}}\right)+1$

In the formula,

PCI _jThe PCI moving average of-Di j group;

PSSI _jThe PSSI moving average of-Di j group;

PCI _J1The PCI lower limit of-Di j group rolling average;

PCI _J2The PCI higher limit of-Di j group rolling average;

The group distance of d-rolling average;

Step-length is calculated in the l-rolling average.

Detect data instance with somewhere test, the step-length l that gets rolling average when rolling average is calculated is 10, and each point d at interval is taken as 5, and each is organized PCI and PSSI and obtains the moving average of respectively organizing PCI and PSSI as table 1 altogether.

Period (K)	The PCI moving average	The PSSI moving average	??ΔPSSIk
				?1	??92.73	??90.90	??-
?2	??87.41	??88.90	??0.38
				?3	??82.71	??85.72	??0.68
?4	??77.66	??79.60	??1.21
				?5	??72.78	??72.84	??1.38
?6	??67.52	??61.70	??2.12
				?7	??62.61	??51.00	??2.18
?8	??57.50	??42.30	??1.70
				?9	??50.20	??39.10	??0.44

??10	??43.84	??36.96	??0.34
				??11	??37.78	??32.43	??0.75

The variable gradient of table 1PCI, PSSI moving average and PSSI

Step 3: by the described Grad of respectively organizing moving average acquisition PSSI; According to the some K=1 to n in each group moving average his-and-hers watches 1, calculate the PSSI variable gradient of each point as follows, promptly corresponding PCI moving average changes the fastest each point PSSI numerical value:

ΔPSSI _k＝(PSSI _k+1-PSSI _k)/(PCI _k+1-PCI _k)????????????(6)

Step 4: in the Grad of respectively organizing PSSI that draws, find out and respectively organize two interval values that the corresponding PCI of PSSI Grad changes;

The Trigger threshold value is set,, compares Δ PSSI successively earlier since the 1st _kWith the size of Trigger value, first PCI moving average greater than the some correspondence of Trigger value promptly can be used as PCI _aEstimated value; Then, use the same method and search for first point greater than the Trigger value from the last point reverse sequence, its corresponding PCI moving average promptly can be used as PCI _bEstimated value.

If Trigger=1 is as can be seen from Table 1 since first first Δ PSSI _kPoint greater than 1 is the 4th point, and corresponding PCI is 77.66; The last point reverse search is found first Δ PSSI from table 1 _kPoint greater than 1 is the 8th point, and the moving average of corresponding PCI is 57.50.Can determine PCI thus _aAnd PCI _bBe respectively 77.66 and 57.50, these two values also are to distinguish the triphasic threshold of PSSI-PCI.The relation of three phases as shown in Figure 2,, Fig. 2 is the corresponding diagram of PCI value and PSSI value, has following relation:

At PCI more than or equal to PCI _aThe time, PSSI Distribution PS SI _aTo 100 intervals; When PCI less than in or equal PCI _bThe time, PSSI distributes 0 to PSSI _bIn the interval; Work as PCI _a＜PCI＜PCI _bThe time, PSSI and PCI are linear, i.e. PSSI=aPCI+b+ ξ, ξ for meet normal distribution N (0, σ ²) (average is 0, and variance is σ ²) random number.

Step 5: by interval value PCI _a, PCI _bObtain the corresponding relation of PCI and PSSI in this interval, estimation procedure is as follows in the present embodiment:

The institute that the PCI value is in PCIa and PCIb in the his-and-hers watches 1 carries out linear regression a little and gets following regression equation:

PSSI＝1.91PCI-67.65?????????????????????(7)

Two other parameter a and the b that can be got in the model PSSI-RQI model by formula (7) are respectively 1.91 and-67.65.

The PCI value is in all groupings between PCIa and the PCIb in the his-and-hers watches 1, obtains the standard deviation of PSSI, and it is average, gets the estimated value of model parameter s:

$\mathrm{\σ}=(\sqrt{D\left({\mathrm{PSSI}}_4\right)}+\sqrt{D\left({\mathrm{PSSI}}_5\right)}+\sqrt{D\left({\mathrm{PSSI}}_6\right)}+\sqrt{D\left({\mathrm{PSSI}}_7\right)}+\sqrt{D\left({\mathrm{PSSI}}_8\right)})/5$

(8)

In the following formula (8), D (PSSI ₄)～D (PSSI ₈) be the 4th group of PSSI standard deviation in the table 1 to the 8th component group data.

Value by PCIa and PCIb estimates PSSI _a, PSSI _bNumerical value, estimation procedure is as follows:

Suppose to equal PCI as PCI _aThe time, PSSI is greater than PSSI _aProbability be 85%, also be that PSSI is less than PSSI _aProbability be 15%; In second stage and critical point place of phase III, promptly work as PCI and equal PCI _bThe time, PSSI is less than PSSI _bProbability be 85%.Then can be by following formula estimation model parameter PSSI _aAnd PSSI _b:

PSSI _a＝μ _0.85(a×PCI _a+b，σ)????????????????????????????(9)

PSSI _b＝μ _0.15(a×PCI _b+b，σ)????????????????????????????(10)

In formula (9), (10), μ _0.1And μ _0.85Be the upside quantile function of normally distributed random variable, i.e. P (x＜μ _0.15)=0.15, P (x＜μ _0.85)=0.85.

According to above step, obtain model parameter estimation value as shown in table 2.

??PCI a	??PCI b	??PSSI a	??PSSI b	??a	??b	??s
							??77.66	??57.50	??70.60	??52.50	??1.91	??-67.65	??10

Table 2PSSI-RQI model parameter estimation

Step 6: the PCI value of measuring by the road surface, obtain corresponding PSSI value according to the corresponding relation of Fig. 2, judge between the pairing servicing area of corresponding PSSI value, select corresponding highway maintenance rank, as light maintenance, in repair overhaul etc.

Describe method of the present invention above in detail, the present invention can obtain road surface PSSI accurately by the highway section of sampling, and dopes the PSSI in whole highway section, and this method is simple, accurate, has reduced the pavement detection cost, has improved pavement detection efficient, good reliability.

For the method for being set forth among each embodiment of the present invention, within the spirit and principles in the present invention all, any modification of being done, be equal to replacement, improvement etc., all should be included within protection scope of the present invention.

Claims (6)

1, a kind of pavement structural strength forecasting method, it is characterized in that, comprise: by detecting the breakage rate and the pavement deflection data in each sampling highway section, obtain pavement quality grade, and arrange according to the pavement quality grade order, what obtains described each highway section correspondence of sampling respectively organizes pavement state indices P CI and pavement structural strength index PSSI; The PCI and the PSSI moving average that from the PCI in each group sampling highway section and PSSI value, calculate respectively; By the described Grad that moving average obtains PSSI, the interval value of two PCI that the corresponding PCI of acquisition PSSI Grad changes respectively organized; By the interval value of described two PCI, dope the interval value of two corresponding PSSI, and obtain the corresponding diagram of PCI value and PSSI value; Measure the PCI value on detected road surface, obtain the PSSI value on detected road surface by described corresponding diagram.

2, pavement structural strength forecasting method according to claim 1 is characterized in that, the data number of pavement state indices P CI and pavement structural strength index PSSI is respectively more than 20 in each group of described each sampling highway section correspondence.

3, pavement structural strength forecasting method according to claim 1 is characterized in that, described from each group sampling highway section PCI and the PSSI value calculate PCI and PSSI moving average respectively process comprise:

Obtain respectively between the sliding area of PCI and PSSI value, between described sliding area in, according to predetermined group distance with calculate step-length, and obtain PCI and PSSI moving average according to following formula;

PCI _j＝AVERAGE(PCI _i)，PCI _i∈[PCI _j1，PCI _j2]

PSSI _j＝AVERAGE(PSSI _i)，PCI _i∈[PCI _j1，PCI _j2]

PCI _j1＝100-(j-1)×δ

PCI _j2＝100-(j-1)×δ-l

$j=\mathrm{1,2},...,\mathrm{int}\left(\frac{100}{\mathrm{\δ}}\right)+1$

In the formula,

PCI _jThe PCI moving average of-Di j group;

PSSI _jThe PSSI moving average of-Di j group;

PCI _J1The PCI lower limit of-Di j group rolling average;

PCI _J2The PCI higher limit of-Di j group rolling average;

The group distance of d-rolling average;

Step-length is calculated in the l-rolling average.

4, pavement structural strength forecasting method according to claim 1 is characterized in that, comprises by the described process of respectively organizing the Grad of moving average acquisition PSSI:

Respectively organize the respectively corresponding footnote of PCI and PSSI moving average 1 to K with what obtain, adopt formula Δ PSSI _k=(PSSI _K+1-PSSI _k)/(PCI _K+1-PCI _k) obtain the Grad of PSSI;

The process of the interval value of two PCI that the corresponding PCI of described acquisition PSSI Grad changes comprises:

According to 1 to K the PSSI Grad that obtains, respectively in proper order, backward obtains first PSSI Grad greater than threshold value, with the PCI moving average of two Grad correspondences respectively as the interval value of two PCI.

5, pavement structural strength forecasting method according to claim 1 is characterized in that, by the interval value of described two PCI, dope the interval value of two corresponding PSSI, and the process of the corresponding diagram of acquisition PCI value and PSSI value comprises:

Adopt normal distribution to dope corresponding described two PSSI values, the described PCI value of acquisition and the corresponding diagram of PSSI value are:

Between the interval value of two PCI, PCI and PSSI value are linear corresponding; Outside the interval value of two PCI, PCI and PSSI value are non-linear correspondence.

6, pavement structural strength forecasting method according to claim 1 is characterized in that, also comprises after this method:

Judge between the servicing area that current PSSI value belonged to, select corresponding highway maintenance rank.

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