In response to the challenges of identifying and reducing noise from multiple sources in construction machinery, this study focuses on a hydraulic source cart as the research subject and employs a sound-vibration fusion diagnostic method for noise identification. Firstly, by analyzing the noise distribution of hydraulic source car under different speed, the main source of noise is deduced. Then, by analyzing the vibration spectrum of each part and comparing with the noise test results, the frequency and location of the main noise are determined. The results show that this method can accurately identify the main noise source frequencies and locations under different gear positions. At 800 r/min, 1500 r/min, and 2600 r/min, the maximum sound pressure levels of the hydraulic source cart are 73.08 dB at the valve side, 75.89 dB at the reducer side, and 78.67 dB at the pump side, with the main source frequencies being 602 Hz, 450 Hz, and 390 Hz, respectively. The main source frequencies are 602 Hz, 450 Hz and 390 Hz, all of which are integer multiple frequencies of the gear pump meshing frequency at this gear position, so the gear pump is the main noise source, and the main noise reduction object of the cart is the gear pump and its valve body.
WeiWWangCLeeY. BIM-based construction noise hazard prediction and visualization for occupational safety and health awareness improvement. Computing in Civil Engineering2017; 2017: 262–269.
2.
OuyangYHuangGHeS. Impacts of adverse environmental factors on construction workers’ attention allocation during hazard identification: a study of noise and heat exposure. Eng Construct Architect Manag2024.
3.
SimonaJRossellJMSánchez-RoemmeleX, et al.Evolution in the law of transport noise in England. Transport Res Transport Environ2021; 100: 103050.
4.
GrimwoodCTurnerS. The evolution of noise policy and noise management in England during the life of the UK’s Institute of Acoustics. INTER-NOISE and NOISE-CON Congress and Conference Proceedings. Institute of Noise Control Engineering2014; 249(6): 1949–1958.
5.
BlombergLDBurgePL. The state of state noise regulations in New England. J Acoust Soc Am2005; 118(3_Supplement): 1849.
6.
CasiniD. From standard specifications to L Aeq uncertainty in environmental noise measurements. Acta Acustica united Acustica2018; 104(4): 707–719.
7.
YokoyamaSKobayashiT. Occupational noise legislation in Asia-Pacific region. Inter Noise2023; 265(5): 2473–2481.
8.
WangYMorganRKCashmoreM. Environmental impact assessment of projects in the People’s Republic of China: new law, old problems. Environ Impact Assess Rev2003; 23(5): 543–579.
9.
DonavanPRRymerBBlakeW. Localization of truck noise sources under passby conditions using acoustic beamforming methods. SAE Int J Commer Veh2009; 2: 128–137.
10.
LuMHJenMUde KlerkD. Case study: separating source contributions of vehicle interior noise by operational transfer path analysis. Noise Control Eng J2021; 69(1): 39–52.
11.
ChenJLiuCZhangXZ, et al.An approach for indoor prediction of the pass-by noise of a vehicle based on the time-domain equivalent source method. Mech Syst Signal Process2021; 146: 107037.
12.
LuoTSunMLiuH, et al.A novel feedforward narrow-broadband hybrid active noise control system for excavator interior noise control. Noise Control Eng J2024; 72(4): 347–367.
13.
LanXHanJZhangJ, et al.Interior noise characteristics, source identification and its quantification contribution of 400 km/h high-speed train in different operating environments. Appl Acoust2025; 228: 110321.
14.
VardhanHKarmakarNCRaoYV. Experimental study of sources of noise from heavy earth-moving machinery. Noise Control Eng J2005; 53(2): 37–42.
15.
LiaoLDHeQHHuZL, et al.Independent component analysis of excavator noise in strong interference surrounding. J Cent S Univ2012; 43(9): 3426–3430.
16.
ChengtaiHYunkaiGShuangL. Noise identify and control in excavator based on frequency spectral analysis and coherence analysis. J Vib Meas Diagnosis2013; 32(6): 1035–1036.
17.
JiangWLinJLiuB, et al.Distributed acoustic sensing for shallow structure imaging using mechanical noise: a case study in Guangzhou, China. J Appl Geophys2023; 215: 105139.
18.
WillemsenAMPoradekFRaoMD. Reduction of noise in an excavator cabin using order tracking and ultrasonic leak detection. Noise Control Eng J2009; 57(5): 400–412.
19.
LanCZhangLLvS, et al.Study on noise control effect of secondary sound source distribution in vehicle interior. J Comput2021; 32(6): 251–263.
20.
BaoWChenXZhaoQ, et al.Numerical study of acoustic source localization of rotor using a novel discrete noise analysis strategy. Int J Aeroacoustics2023; 22(3-4): 371–394.
21.
ZhangEPengZChenQ, et al.Active noise control modeling for an electric bus driving position and its effect on sound quality. Noise Vib Worldw2024; 55(3): 135–144.
22.
RaoMRaghavendranPSelvamE. Countermeasures for low frequency boom noise reductionin electric vehicle[R]. SAE Technical Paper, No. 2024-26-0214, 2024.
23.
BallesterosJAFernandezMDSarradjE, et al.Identification and analysis of the noise sources of an engine settled in a car using array-based techniques. Int J Veh Noise Vib2018; 14(2): 171–190.
24.
ShiTStuart BoltonJ. A comparison of near-field acoustical holography methods applied to noise source identification[R]. SAE Technical Paper, No. 2019-01-1533, 2019.
WuCYuP. A study on active noise reduction of automobile engine compartment based on adaptive LMS algorithm. Acoust Aust2020; 48: 431–440.
27.
JadhavSSaxenaSAswanYS. Design and development of partial engine encapsulation for interior noise reduction in commercial vehicles[R]. SAE Technical Paper, No. 2019-01-1589, 2019.
28.
ZhangZPanDWuW, et al.Vibration source identification of a heavy commercial vehicle cab based on operational transfer path analysis. Proc Inst Mech Eng - Part D J Automob Eng2020; 234(2-3): 669–680.
29.
PorghovehMShiraziKHYildizdagME. Engine noise cancellation with optimum array of speakers inside vehicle enclosures. J Vib Control2023; 29(19-20): 4628–4642.
30.
HorváthKZeleiA. Simulating noise, vibration, and harshness advances in electric vehicle powertrains: strategies and challenges. World Electric Vehicle Journal2024; 15(8): 367.
31.
WangR. Recognition and detection of vehicle noise and vibration signals relying on variable step size LMS algorithm. Mob Inf Syst2022; 2022(1): 1–11.
32.
SinghRNalawadeAPandeM, et al.Vibration and noise characteristics of an inverter for electric vehicle application. Vib proced2023; 50: 145–151.
33.
HazraSReddyJK. A review paper on recent research of noise and vibration in electric vehicle powertrain mounting system. SAE Int J Veh Dyn Stab NVH2021; 6: 3–22.
