Abstract:This paper presents a simple feedback methodology that uses second order filters to control narrowband resonant and non-resonant vibration of a structural system. In particular, a single degree-of-freedom system is studied throughout the paper. The idea of the methodology is based on the fact that direct feedback is effective for in-phase vibration control. Thus, the position, velocity and acceleration are respectively fed back to control the low, resonant and high frequency vibration of the system. Each of th… Show more
“…In the first case, a reduction of more than 40 dB has been achieved in a narrow frequency band around 35 Hz. It is even possible in principle to completely nullify the target tonal noise at the error microphone position [20]. The results here are comparable to those in [6,10].…”
Section: Discussionsupporting
confidence: 85%
“…As the fixed-structure filter of the controller (i.e., the compensator in classical terms), a single filter of second order is commonly employed for both cases studied. This is because it has been known in active vibration control that this order of filter is effective for controlling vibration in a single frequency band [12][13][14][15][16][17][18][19][20]. Active vibration control is similar to active noise control in that they are both disturbance rejection control.…”
Section: Introductionmentioning
confidence: 99%
“…Each control filter above can thus be designed under an optimal, robust design framework based on Nyquist robustness criterion, which has been widely used in both active noise [6,9,10] and vibration [15][16][17][18][19][20] control. The particular loop shaping (i.e., design) method employed is then a data-based technique, for example see [20], that uses the measured plant response to tune the parameters of the fixed-structure candidate controller in a graphical way by repeatedly plotting the open loop frequency response until a desirable shape is obtained in terms of both performance and robustness. Thus, no (or minimum) knowledge is required regarding the physics involved, the mathematics on modeling and optimization, and the formalism of modern robust control theory.…”
A simple loop shaping technique is applied to design an optimal, robust feedback controller to reduce the interior noise of an acoustic cavity. It is a data-based technique that uses the measured plant response to tune the parameters of a fixed-structure controller in a graphical way. The two cases studied are narrowband noise control in a small cavity and broadband noise control in a long duct. Each control system consists of a microphone, a loudspeaker, and a controller connecting the two transducers that are further collocated. The fixed-structure of each controller should be chosen ahead of loop shaping and is determined in this paper solely based on the Nyquist plot of each plant measured. It turns out that a single band (high) pass filter of second order is suitable for the narrowband (broadband) noise control case considered. It is finally demonstrated with experiments that the technique is practical and a second order filter can be effectively used for active control of cavity noise in a single narrow or broad frequency band.
“…In the first case, a reduction of more than 40 dB has been achieved in a narrow frequency band around 35 Hz. It is even possible in principle to completely nullify the target tonal noise at the error microphone position [20]. The results here are comparable to those in [6,10].…”
Section: Discussionsupporting
confidence: 85%
“…As the fixed-structure filter of the controller (i.e., the compensator in classical terms), a single filter of second order is commonly employed for both cases studied. This is because it has been known in active vibration control that this order of filter is effective for controlling vibration in a single frequency band [12][13][14][15][16][17][18][19][20]. Active vibration control is similar to active noise control in that they are both disturbance rejection control.…”
Section: Introductionmentioning
confidence: 99%
“…Each control filter above can thus be designed under an optimal, robust design framework based on Nyquist robustness criterion, which has been widely used in both active noise [6,9,10] and vibration [15][16][17][18][19][20] control. The particular loop shaping (i.e., design) method employed is then a data-based technique, for example see [20], that uses the measured plant response to tune the parameters of the fixed-structure candidate controller in a graphical way by repeatedly plotting the open loop frequency response until a desirable shape is obtained in terms of both performance and robustness. Thus, no (or minimum) knowledge is required regarding the physics involved, the mathematics on modeling and optimization, and the formalism of modern robust control theory.…”
A simple loop shaping technique is applied to design an optimal, robust feedback controller to reduce the interior noise of an acoustic cavity. It is a data-based technique that uses the measured plant response to tune the parameters of a fixed-structure controller in a graphical way. The two cases studied are narrowband noise control in a small cavity and broadband noise control in a long duct. Each control system consists of a microphone, a loudspeaker, and a controller connecting the two transducers that are further collocated. The fixed-structure of each controller should be chosen ahead of loop shaping and is determined in this paper solely based on the Nyquist plot of each plant measured. It turns out that a single band (high) pass filter of second order is suitable for the narrowband (broadband) noise control case considered. It is finally demonstrated with experiments that the technique is practical and a second order filter can be effectively used for active control of cavity noise in a single narrow or broad frequency band.
“…Similar dynamics are used in resonant controllers. In these methods, a controller is a second-order element with its resonance frequency tuned to the frequency of the mode to be damped [4][5][6]. The resonance peak of the controller is used to increase the gain in the vicinity of the target mode.…”
In this paper, a fractional-order extension of a negative position feedback (NPF) controller for active damping is proposed. The design of the controller is motivated by the frequency-domain loop shaping analysis, and the controller dynamics are defined to maintain the high-pass characteristics of an integer-order NPF. The proposed controller provides greater attenuation of a resonance peak of a flexible plant than the integer order equivalent with the same high-frequency gain. The stability and influence of tuning parameters on the behaviour of the proposed controller are analysed. The efficiency and feasibility of the fractional-order controller are demonstrated by implementing it on an experimental setup.
“…Therefore, it is difficult to directly measure the mine-hoist lifting load. Vibration signals can effectively provide health information on a large rotary machine, and many studies on vibration usage have been performed by researchers throughout the world [1][2][3][4]. That is, vibration signal analysis constitutes a new method of monitoring the lifting load of mine hoist.…”
Mine hoists play a crucial role in vertical-shaft transportation, and one of the main causes of their faults is abnormal lifting load. However, direct measurement of the load value is difficult. Further, the original structure must be destroyed for sensor installation. To facilitate efficient and accurate monitoring of the lifting load of mine hoist, this paper presents a novel condition-monitoring method based on variational mode decomposition (VMD) and support vector machine (SVM) through vibration signal analysis. First, traditional empirical mode decomposition (EMD) is used to analyze the vibration signal collected by an acceleration sensor, and the number of obtained intrinsic mode functions (IMFs) is employed to set the VMD mode number. Second, the obtained vibration signal is processed by the parameterized VMD, and the useful IMFs of VMD are selected through correlation analysis for feature extraction. Third, the obtained features are used to train an SVM model, and the trained SVM is used to monitor the mine-hoist lifting load. In this study, experiments on an operated mine hoist are also conducted to verify the reliability and validity of the proposed method. The experimental results show that the proposed method can accurately identify the considered lifting load conditions.
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