TY  - EJOU
AU  - Hu, Zhuyou 
AU  - Lin, Ping 
AU  - Guo, He 
AU  - Zhang, Yumei 
AU  - Xiang, Zhihai 

TI  - Mechanism	of	the	Passive	Tap-Scan	Damage	Detection	Method
T2  - The International Conference on Computational \& Experimental Engineering and Sciences

PY  - 2023
VL  - 26
IS  - 1
SN  - 1933-2815

AB  - In	recent	years,	the	vehicle	scanning	method	for	bridge	inspection	has	drawn	much	attention	by	researchers	
because	of	its	simple	operation	and	high	efficiency	 [1].	Besides	 the	natural	 frequency,	modal	modes	and	
other	information	of	bridges,	damage	can	also	be	detected	in	this	way	[2].	For	example,	we	proposed	the	
passive	tap-scan	damage	detection	method	[3],	which	scans	the	bridge	with	the	tapping	force	generated	by	
a	toothed	wheel,	mimicking	the	hunting	behavior of	woodpeckers.	In	this	talk,	we	will	discuss	two	critical	
aspects	related	to	the	mechanism	of	this	method.	One	is	the	quantitative	relationship	between	the	vehicle	
acceleration	 and	 the	 damage.	 Another	is	 the	 details	 of	 the	 tapping	 force.	 To	 discuss	 the	 first	 aspect,	we	
establish	a	theoretical	model	that	implies	the	amplitude	of	the	vehicle	acceleration	is	very	sensitive	to	the	
stiffness	transition	in	bridge	girders	and	can	be	quantified	as	a	quadratic	function	of	the	stiffness	change	
ratio	 [4].	To	discuss the	second	aspect,	we	propose	a	novel	moving	 force	identification	 (MFI)	method	 to	
identify	the	tapping	force.	To	improve	the	well-posedness	of	MFI,	the	response	matrix	is	transformed	to	the	
time-frequency	 domain	 by	 wavelets	 and	 the	 Element-wise	 Bayesian	 regularization	 is	 adopted	 to	 apply	
regularization	on	each	force	element	[5,6].	Since	regularization	weights	are	determined	by	the	measurement	
with	 noise,	 the	 optimal	 weights	 can	 be	 obtained	 by	 adding	 certain	 white	 noises,	 showing	 a	 stochastic	
resonance	 phenomenon.	 All	 these	 findings	 are	 quantitatively	 verified	 by	 numerical	 simulations	 and	
experimental	tests.
KW  - Vehicle-bridge	 interaction;	 tap-scan	 method;	 stiffness	 transition;	 moving	 force	 identification;	 noiseenhancement

DO  - 10.32604/icces.2023.09475