Individual projects allow the DCs to gain experience working with all stages of the noise solution development from analysis and design to application and industrial evaluation, in tandem with their academic studies. Their training will be undertaken in some of the world’s key laboratories for sound and vibration research and in Europe’s leading companies of global reach. The table below presents planned for IN-NOVA: the titles of PhD projects, the experts guiding the Doctoral Candidate, the host institution and the institution offering a PhD programme for that candidate. The consortium reserves the right to justified changes under specific circumstances.
Individual Research Projects
Fellow: DC1 - Amir Hafez
Host institution: SUT
Enrolment in Doctoral degree: SUT
International Supervisory Council (ISC): Prof. M. Pawelczyk (SUT), Dr. S. Wrona (SUT), Dr. M. de Diego (UPV), Prof. L. Cheng (SAB), Dr. C. Thomas (AB)
Project Title: Distributed control algorithms for active device casings
Objectives: The active casing wall panels’ vibrations can be controlled to reduce the device noise emission. Such concept has been originally proposed and its efficiency has been preliminarily confirmed by the researchers of SUT. Developed prototypes are based on high-end laboratory grade controller with mostly centralized control architecture. However, further research is required to advance this solution for real applications. In particular, the DC will design a new control system architecture in order to improve system feasibility and scalability. The DC will develop a real-time implementation of distributed control algorithms on a dedicated modular hardware. The DC will address a design of distributed controller, necessary data exchange between control nodes, reduction of computational complexity and control performance experimental evaluation. The main goal is to provide global noise reduction in the entire enclosure, with reduced energy consumption and system complexity.
Expected results: The project is expected to deliver a novel distributed adaptive control algorithm tailored for the active casing. Another result is a new prototype of distributed controller that will push the investigated method beyond the current state-of-the-art.
Fellow: DC2 - Khaled Maamoun
Host institution: SUT
Enrolment in Doctoral degree: SUT
International Supervisory Council (ISC): Prof. M. Pawelczyk (SUT), Dr. S. Wrona (SUT), Prof. H. Karimi (PDM), Prof. W.S. Gan (SAB), Dr. R. Schirmacher (MBBM)
Project Title: Active device casings with an open part or made from a different material
Objectives: The idea of the active casing originally proposed at SUT is to control vibration of device walls in order to reduce noise emission globally to the entire room or area, where the devices are located. However, there are many practical situations, where the devices are not fully enclosed e.g., to be reached by an operator. Then, the problems go to another level. Controlling vibration of the remaining walls should be performed in a very specific way not only to reduce the noise just transmitted through the respective walls, but also contribute to controlling the noise going out through the opening. Additional sound sources are needed to support the vibrating walls in order to reduce the noise globally in the room.
Expected results: This DC’s project is expected to originally analyse the problem of active casings with an opening, develop and experimentally verify control systems and algorithms to make them practically applicable.
Fellow: DC3 - Alkahf Aboutiman
Host institution: PDM
Enrolment in Doctoral degree: PDM
International Supervisory Council (ISC): Prof. H. Karimi (PDM), Prof. F. Ripamonti (PDM), Prof. M. Pawelczyk (SUT), Prof. Y. Kajikawa (SAB), Dr. R. Schirmacher (MBBM)
Project Title: Deep learning-based active control of noise transmission through encapsulated structures
Objectives: In active noise control, especially dedicated for problems considered in IN-NOVA, in most cases deterministic components are mixed with a broadband part. Considering the difficulty to measure the acoustic pressure in advance to apply classical active noise control methods, artificial intelligence tools such as deep learning algorithms can be an effective datadriven approach. They can be applied to compute/predict the acoustic pressure due to their ability to capture spatial coherent patterns in the radiated acoustic pressure fields. In addition, deep learning-based ANC design can potentially play an important role in dealing with nonlinearities unavoidable in electro-acoustic system as well as broadband noise removal. Deep learning algorithms will also allow for including holistic aspects in the design. Knowledge about physical behavior of the plant will be incorporated to enhance performance.
Expected results: The DC will develop: a) deep-learning algorithms for calculating time-propagation of acoustic waves; (b) time-domain methods for deep learning-based ANC; (c) a simulation environment for deep learning algorithms applied to calculations of propagation of acoustic waves with acceptable accuracy levels and made available to other researchers in the project and beyond.
Fellow: DC4 - Chao Liang
Host institution: PDM
Enrolment in Doctoral degree: PDM
International Supervisory Council (ISC): Prof. H. Karimi (PDM), Prof. F. Ripamonti (PDM), Prof. S. Wrona (SUT), Prof. R. Paurobally (SAB), Dr. J. Calpe-Maravilla (AD)
Project Title: Direct data-driven active noise cancelation design based on near-field acoustic holography
Objectives: Traditional control design methods mainly follow the two steps: model parameters identification; model-based control design. However, direct data driven control algorithms are introduced in time domain to merge the two steps by directly using input-output data for controller design purposes and making the system less dependent on a pre-identified model. Performance of noise control systems strongly depends on the primary path (noise propagation) and secondary path (compensation) models’ quality used for designing the feedback control law. Considering that it is hard to find the correct model for control design, the direct data-driven approaches can be used to compute controllers that are suitable for ANC using only near-field acoustic holography by arranging microphones on the appliance fuselage, ex. study of the acoustic emission of a noisy device, and sound field produced by loudspeaker array, without any detailed knowledge of the system model. In this configuration, the near-field acoustic holography predicts the global sound field through near-field noise. Then, the direct data-driven method is applied to develop tractable algorithms for a novel noise canceller design.
Expected results: The DC will develop: a) input-output data acquisition under an experimental protocol; b) acoustic modal analysis of the device noise; c) optimization algorithms to compute structure controllers that are suitable for noise reduction.
Fellow: DC5 - Tahmida Islam
Host institution: UPV
Enrolment in Doctoral degree: UPV
International Supervisory Council (ISC): Prof. A. Gonzalez (UPV), Dr. M. de Diego (UPV), Dr. S. Wrona (SUT), Prof. R. Paurobally (SAB), Dr. J. Calpe-Maravilla (AD)
Project Title: Development of fast and distributed signal processing algorithms for active noise control
Objectives: The objective of this project is to develop and investigate distributed ANC systems in static and dynamic environments using acoustic nodes. The DC will search for algorithm solutions that could be used for network self-adapting of nodes placements or clustering objectives when we consider movement of listeners or transducers. He/she will develop and implement fast and distributed algorithms based on fast least squares. Moreover, the DC will implement and test novel sound field control strategies adapted to the environments where control points may vary with time. The base of the study will be both the remote microphone technique and the moving virtual sensing method.
Expected results: The DC will develop (a) distributed multichannel algorithms based on fast least squares and (b) algorithms that dynamically adapt the network topology. The project will also produce scientific results to improve signal processing tools. The prototypes and applications are expected to evolve into marketable products.
Fellow: DC6 - Gavin Dies
Host institution: KUL
Enrolment in Doctoral degree: KUL
International Supervisory Council (ISC): Dr. B. Pluymers (KUL), Prof. N.B. Roozen (KUL), Prof. M. Pawelczyk (SUT), Prof. L. Cheng (SAB), Dr. S. Tong (SISW)
Project Title: Passive and active approaches in automotive applications
Objectives: Hybrid-electric vehicles (HEVs) and battery-electric vehicles (BEVs) are cleaner and produce less exterior noise than cars with internal combustion engines. However, the interior noise is characterized by high-frequency noise components which can be subjectively perceived as annoying and unpleasant. The challenge is to reduce the interior noise levels in (H/B)EV, without adding too much weight to the car. The objective of this DC is to develop a passive/active approach to reduce the annoyance of acoustic sound field in a car. The DC will focus on the vibro-acoustic modelling of structural vibrations and acoustic radiation of typical automotive structural parts (e.g., body panels), actively controlled by means of electromechanical actuators. The active control approach will be complemented with passive reduction approaches, e.g. exploiting metamaterials.
Expected results: Develop a trade-off between active control and passive control of typical automotive structural parts such as a firewall in terms of vibro-acoustic radiation. The main deliverable will be a laboratory test rig comprising of these parts, which is excited (through an electrodynamic shaker) by realistic vibro-acoustic forces occurring in an (H/B)EV.
Fellow: DC7 - Andrey Hense
Host institution: SISW
Enrolment in Doctoral degree: KUL
International Supervisory Council (ISC): Dr. F. Chauvicourt (SISW), Prof. N.B. Roozen (KUL), Dr. M. de Diego (UPV), Dr. B. Pluymers (KUL), Prof. Y. Kajikawa (SAB)
Project Title: Vibro-acoustic design feature extraction using Artificial Intelligence
Objectives: Noise in the interior of an automotive cabin depends on many design factors of the cars, thus making it difficult for Original Equipment Manufacturers to optimize and/or define targets for new innovative designs. Overall system-level modelling strategies are required and must incorporate component behavior details; while making sure not to reinvent the wheel. To this end, the objectives of the DC will be to develop a holistic modelling framework that combines knowledgebased and data-based simulators to generate feature of unknown designs (interior cabin noise focus). Artificial intelligence will support the classification of a priori known data, and the prediction of new design features.
Expected results: This DC project is expected to define a set of design features for reducing interior cabin noise from knowledge-based and data-based engineering, which will be of high practical importance.
Fellow: DC8 - María Juliana Garzón
Host institution: UPV
Enrolment in Doctoral degree: UPV
International Supervisory Council (ISC): Prof. A. Gonzalez (UPV), Dr. M. de Diego (UPV), Prof. J. Kang (UCL), Prof. W.S. Gan (SAB), J. Kirchhof (MBBM)
Project Title: Perceptual broadband ANC equalizer with spatially distributed user-selected profiles
Objectives: Active noise equalization algorithms have been proposed to deal with multi-frequency noise generated by mechanical systems such as the car engines to improve passenger comfort. These algorithms keep a desired residue of the noise by assigning simultaneously different equalization gains to each frequency and thus achieving pleasant sound spaces. However, broadband noises such as the road noise should be also considered in those complex scenarios, where warning sounds and communication between passengers are also present. In this regard, and addressing the need of a personalized active equalization of broadband noise, the DC will develop broadband active noise equalization algorithms and schemes. A practical road active noise equalization system that could provide different noise profiles at a set of spatially confined regions around the head of different passengers will be developed. When music is played in the vehicle cabin, the algorithm could also benefit from the masking effect of the music, leading to a perceptual broadband active noise equalizer. Remote microphone techniques will assist to address the personalized equalization challenges.
Expected results: The DC will develop: a) broadband multichannel active noise equalization algorithms and (b) perceptual broadband multichannel strategies. The prototypes will gain interest as marketable offer.
Fellow: DC9 - Said El Kadmiri Pedraza
Host institution: DLR
Enrolment in Doctoral degree: DLR
International Supervisory Council (ISC): Prof. H.P. Monner (OVGU), Dr. S. Algermissen (DLR), Dr. S. Wrona (SUT), Prof. J. Arenas (SAB), Dr. F. Chauvicourt (SISW)
Project Title: Contribution analysis of vibrating aircraft interior parts to overall cabin noise
Objectives: The objective is to develop an acoustic cabin simulator that allows the identification of cabin noise sources with simulation. The aircraft cabin is surrounded by various vibrating structures (ceiling and sidewall panel, hatrack, floor) which act as noise sources and contribute differently to the cabin noise depending of the load case. By identifying the most important noise sources for different load cases, effective treatments can be investigated and evaluated in the numerical framework on cabin level. Relevant load cases will be obtained from measurement data of full-scale aircraft on ground or in-flight operation.
Expected results: The key interior components which contribute to the cabin noise will be identified. Therefore, noise maps of the cabin with vibrating surroundings will be calculated in order to understand sound pressure distributions caused by different parts. A numerical framework will be available to evaluate the efficiency of individual cabin treatments.
Fellow: DC10 - Praaveesh Raaj
Host institution: DLR
Enrolment in Doctoral degree: DLR
International Supervisory Council (ISC): Prof. H.P. Monner (OVGU), Dr. M. Misol (DLR), Prof. N.B. Roozen (KUL), Prof. Y. Kajikawa (SAB), J. Kirchhof (MBBM)
Project Title: Active aircraft interior parts with structurally integrated sensors for cabin noise reduction
Objectives: The vibration excitation of aircraft interior structural parts through external noise sources plays a major role for cabin noise. It is assumed that this transmission path is inherent to all aircraft and that it is not possible to completely eliminate this transmission path. Therefore, the main objective of this project is the development of active noise control for aircraft interior parts to counteract noise close to the passengers. Key features of such an active component are the structure-based sensing scheme and the modularity. The structure-based modular concept avoids the distribution of microphones in the cabin and permits each active interior part to act independently and decentralized. The active component is also able to emit useful sound (e.g. passenger announcement) or improve sound quality through noise masking or psychoacoustic features.
Expected results: A modular and robust aircraft interior part with active noise reduction capability will be available at the end of the project. Major intermediate results for the development of such a part are the selection of a suitable structure-based sensing scheme, the optimization of actuators and sensors, the design and implementation of a controller and the structural integration of the active components. Each active part will contribute to the reduction of noise in a neighbouring region of the cabin and their assembly will facilitate a global reduction in a dedicated section of the aircraft or even in the whole cabin.
Fellow: DC11 - Chung Kwan Lai
Host institution: UOS
Enrolment in Doctoral degree: UOS
International Supervisory Council (ISC): Dr. J. Cheer (UOS), Prof. S. Elliott (UOS), Prof. A. Gonzalez (UPV), Prof. R. Paurobally (SAB), Dr. C. Thomas (AB)
Project Title: Head tracking for local active sound control
Objectives: Initial experiments on the use of head tracking to improve the performance of local active control at a listener’s ear have demonstrated its potential, but further research is required in a number of areas before this technique is practical. In particular, this PhD will address the tracking of head rotation as well as head translation, the speed at which the tracking needs to be implemented for seamless operation, and the trade-off between using large lookup tables of responses for different head positions and the use of interpolation between a smaller set of responses.
Expected results: The project is expected to evaluate head tracking for local active sound control in detail beyond the current state-of-the-art. It is expected that the project will develop advanced control strategies that effectively integrate head tracking information into novel active control algorithms and a real-time technology demonstrator will be implemented and tested.
Fellow: DC12 - Achilles Kappis
Host institution: UOS
Enrolment in Doctoral degree: UOS
International Supervisory Council (ISC): Prof. S. Elliott (UOS), Dr. J. Cheer (UOS), Prof. M. Pawelczyk (SUT), Prof. W.S. Gan (SAB), Dr. S. Tong (SISW)
Project Title: Directional microphone arrays for remote microphone virtual sensing
Objectives: The remote microphone technique is used to estimate the acoustic signal at a virtual sensor location using the outputs from a remote array of monitoring sensors, and is used in the implementation of active sound systems for both local control and for noise barriers. Current arrangements use pressure microphones as the monitoring sensors, but it is known that complimentary information about the sound field is available from pressure gradient microphones. Directional microphones, such as cardioids, are also available that combine elements of pressure and pressure gradient response. This PhD would investigate the optimum directivity and geometry of the microphones in a monitoring array for a local active control problem.
Expected results: The project is expected to evaluate the performance of different microphone directivities in the context of local active sound control. As a result of this insight, it is then expected that the project will develop optimised strategies for the definition of microphone directivity in remote sensing strategies and validate these strategies experimentally.
Fellow: DC13 - Zulfi Aulia Rachman
Host institution: UCL
Enrolment in Doctoral degree: UCL
International Supervisory Council (ISC): Prof. J. Kang (UCL), Dr. F. Aletta (UCL), Prof. A. Gonzalez (UPV), Prof. J. Arenas (SAB), Dr. F. Chauvicourt (SISW)
Project Title: Noise barriers with a soundscape approach
Objectives: The general aim of this DC’s research project will be investigating how to extend the scope of conventional noise barriers using the soundscape holistic approach. In the context of this research, noise barriers will not necessarily be considered as “physical infrastructures” that impede sound propagation, but rather as a set of technological solutions and/or implementation of psychoacoustics that can create quiet areas indoor or in car/aircraft cabins, offering opportunities for recovery and restoration from noise pollution. The DC will explore a number of alternative strategies: (1) energetic and attentional masking; (2) exploitation of benefits provided by non-acoustic (e.g., vision, smell) factors; (3) smart noise control engineering.
Expected results: Return research outcomes and recommendations to be used at small- and building scale by architects and interior designers to deliver indoor spaces and cabins with high acoustic comfort. The project deliverables will also lay the ground to develop further learning materials/syllabi or teaching programmes to be integrated into academic courses.