| Summary: | Thesis (MScEng (Process Engineering))--University of Stellenbosch, 2010. === Thesis presented in fulfilment of the requirements for the degree
of Master of Science in Engineering
at
Stellenbosch University === ENGLISH ABSTRACT: Weigh-in-motion (WIM) scales are installed on various higher order South African roads to
provide traffic loading information for pavement design, strategic planning and law
enforcement using a scientific approach. The two most respected international guideline
documents for WIM systems are the American ASTM E1318 Standard and the COST 323
European Specification, yet neither are fully suited to be applied to local WIM systems.
The author developed a post-calibration method for WIM data, called the Truck Tractor (TT)
Method, to correct the magnitude of recorded axle loads in retrospect. It incorporates a series
of powerful data quality checks. The TT Method is robust, accurate and adequately simple to
be used on a routine basis.
The TT Method uses the truck tractor loads of articulated 6- and 7-axle trucks with single
steering- and double driving axles – these vehicle are called Eligible Trucks. Only Eligible
Trucks with average axle loads between 6.5 t and 8.5 t are used in the calibration process –
these vehicles are called Selected Trucks. A calibration factor, kTT, is determined using a fully
automated iterative procedure, and multiplied with all axle load measurements to produce
data for which the average truck tractor load of Selected Trucks, TTT, is equal to 21.8 t. The
TT Method can be used for WIMs in various operating environments and is not sensitive to
the extent of miss-calibration of a WIM, clipping of sensors owing to poor lane discipline or
different extents of loading on different routes.
The TT Method includes a series of data quality checks that can be used on a routine basis.
They are summarised as follows:
- The standard deviation of truck tractor loads for Selected Trucks, STTT, should always
be below 2.0 t, but preferably below 1.9 t.
- The standard deviation of front axle loads for Selected Trucks, SFTT, should always be
below 0.9 t, but preferably below 0.8 t.
- The post-calibration factor from the TT Method, kTT, should be between 0.9 and 1.1.
The factor for any month should not deviate by more than 3% from the moving
average of the previous five months.
- The average of front axle loads of Selected Trucks, FTT, should be between 5.6 t and
6.6 t; the exact values are influenced by load transfer between the steering and driving
axles.
- A procedure was formulated using the Front axle / Truck tractor Ratio, FTR, to
identify the percentage of Eligible Trucks that in all probability clipped the sensor.
The percentage of these records must be below 10 %, but preferably below 6 %.
The TT Method has the potential to significantly improve WIM data collection in South
Africa. The calibration module of the TT Method, i.e. the procedure to calculate kTT, has
already been accepted by SANRAL. Most of the data quality checking concepts associated
with the TT Method were also accepted, although their threshold values are still being refined. === AFRIKAANSE OPSOMMING: Weeg-in-beweging (“weigh-in-motion”, WIM) skale word op talle hoë orde paaie in Suid-
Afrika gebruik om op wetenskaplike wyse verkeersinligting te verskaf wat gebruik word vir
plaveiselontwerp, strategiese beplanning en wetstoepassing met betrekking tot oorlading. Nie
een van die twee vooraanstaande internasionale riglyne vir WIM sisteme, die ASTM E1318
Standaard en die COST 323 Europese Spesifikasie, is in geheel geskik vir Suid-Afrikaanse
kondisies nie.
Die outeur het ‘n unieke kalibrasie metode, genaamd die TT Metode, ontwikkel wat ’n reeks
roetine kwaliteitsbeheertoetse vir WIM data insluit. Die TT Metode is eenvoudig, akkuraat en
toepaslik vir ’n wye verskeidenheid WIM sisteme in Suid-Afrika.
Die massa van trekkers van geartikuleerde 6- en 7-as vragmotors met enkel stuur- en dubbel
dryf-aste en ’n gemiddelde asmassa tussen 6.5 en 8.5 ton (ook genoem Geselekteerde
Vragmotors) word as verwysingsmassa gebruik. ’n Iteratiewe prosedure word gevolg vir die
bepaling van die kalibrasie faktor, kTT. Dieselfde faktor word met alle asmassas in die data vir
die analise periode vermenigvuldig, met die einddoel dat die gemiddelde trekker massa van
die Geselekteerde Vragmotors, TTT, gedryf word na die teikenwaarde van 21.8 ton. Die TT
Metode is ewe toepaslik ongeag die tipiese belading van trokke op ’n roete, hoe goed die
WIM sisteem oorspronklik gekalibreer was of hoe goed laandissipline by die WIM sensor is.
Die kwaliteitsbeheertoetse kan op ’n roetine basis toegepas word as deel van die uitvoering
van WIM kalibrasie prosedure, en word soos volg saamgevat:
- Die standaard afwyking van trekker massas van Geselekteerde Vragmotors, STTT,
behoort altyd laer as 2.0 ton, maar verkieslik laer as 1.9 ton te wees.
- Die standaard afwyking van voor-as massas van Geselekteerde Trokke, SFTT, behoort
altyd laer as 0.9 ton, maar vekieslik laer as 0.8 ton te wees.
- Die kalibrasiefaktor, kTT, moet verkieslik tussen 0.9 en 1.1 wees, en mag nie met
meer as 3 % van die gemiddelde kTT vir die voorafgaande vyf maande verskil nie.
- Die gemiddeld van voor-as massas van Geselekteerde Vragmotors, FTT, behoort
tussen 5.6 ton en 6.6 ton te wees. Die presiese waarde hang af van die mate waartoe
gewig tussen die voor-as en dubbel dryf-as oorgedra word weens dinamiese effekte
op die trekker.
- Die verhouding tussen die voor-as en dubbel dryf-as, bekend as die FTR, kan gebruik
word as ‘n aanduiding of ’n trok weens swak laandissipline slegs gedeeltelik oor die
WIM sensor gery het. Die persentasie gedeeltelike metings moet laer as 10%, maar
verkieslik laer as 6 % wees.
Die TT Metode het die potensiaal om die insameling en kwaliteit van verkeersdata deur
middel van WIM sisteme noemenswaarding te verbeter. Die kalibrasie module van die
TT Metode, m.a.w. die prosedure om kTT te bereken, is reeds deur SANRAL aanvaar. Die
meeste van die kwaliteitsbeheerkonsepte wat met die TT Metode gepaard gaan is ook
aanvaar, maar die drempelwaardes hiervoor word nog verfyn.
|
|---|
