Proceedings of Meetings on Acoustics

Transcription

1 Proceedings of Meetings on Acoustics Volume 19, ICA 2013 Montreal Montreal, Canada 2-7 June 2013 Engineering Acoustics Session 1pEAa: Active and Passive Control of Fan Noise 1pEAa11. Upgrade of a multi-channel active noise control system for an industrial stack Andre L'Esperance*, Louis-Alexis Boudreault and Alex Boudreau *Corresponding author's address: Soft db, 1040, avenue Belvedere, Quebec, G1S 3G3, Quebec, Canada, a.lesperance@softdb.com Active Noise Control (ANC) has been studied in the 90s as an innovative way to reduce the noise in specific situations. Some applications are well known today and found commercial success such as noise-cancelling headphones. However, the use of ANC in industrial applications is more complex, thus being an uncommon solution in this field. The use of ANC for industrial stack noise is one of these applications. One of the first large-scale implementation has been set up at the end of the 90s. This system was a 10-Channel ANC system installed on a 1.8 m wide chimney to attenuate a 320 Hz pure tone. At that time an 8 db noise reduction was achieved at error microphones. In 2011, it has been decided to upgrade the system with the latest generation of Digital Signal Processor (DSP) allowing a real-time optimization and a better tracking speed. This paper describes the overall system and the updated multi-channel controller developed for this application. It also presents the improvements, the achieved noise reduction and the associated environmental benefits. Published by the Acoustical Society of America through the American Institute of Physics 2013 Acoustical Society of America [DOI: / ] Received 16 Jan 2013; published 2 Jun 2013 Proceedings of Meetings on Acoustics, Vol. 19, (2013) Page 1

2 UPGRADE OF A MULTI-CHANNEL ACTIVE NOISE CONTROL SYSTEM FOR AN INDUSTRIAL STACK L.A. Boudreault, ing. jr., A. L Espérance, ing. Ph. D. and A. Boudreau, ing. Ph.D. Soft db. inc. ( CANADA Active Noise Control (ANC) has been studied in the 90s as an innovative way to reduce the noise in specific situations. Some applications are well known today and found commercial success such as noise-cancelling headphones. However, the use of ANC in industrial applications is more complex, thus being an uncommon solution in this field. The use of ANC for industrial stack noise is one of these applications. One of the first large-scale implementation has been set up at the end of the 90s. This system was a 10-Channel ANC system installed on a 1.8 m wide chimney to attenuate a 320 Hz pure tone. At that time an 8 db noise reduction was achieved at error microphones. In 2011, it has been decided to upgrade the system with the latest generation of Digital Signal Processor (DSP) allowing a real-time optimization and a better tracking speed. This paper describes the overall system and the updated multi-channel controller developed for this application. It also presents the improvements, the achieved noise reduction and the associated environmental benefits. Previous Work In the early 90s, an extensive environmental noise survey was conducted at a large industrial site to identify the major noise sources. Among the most significant noise sources, a large industrial stack was identified. Three fans are pushing air through a 1.8 m diameter chimney causing a 320 Hz pure-tone which was distinguishable from the background noise. Unfortunately, a classic silencer was too heavy for the chimney structure and would have generated too much air restriction. Thus, an ANC solution was considered. FIGURE 1. Industrial stack causing a 320 Hz pure tone Commonly available ANC systems were not applicable to this situation because the stack diameter is too large compared to the wavelength causing a multi-modal acoustic field in the chimney. To control such a sound field, a multi-channel system is necessary. Several experiments were conducted at that time to develop an efficient and stable multi-channel ANC system. The results showed that ANC of higher order modes within a duct can be obtained with a plurality of error microphones located in a plane perpendicular to the longitudinal axis of the duct. Each sensor controls the noise at its precise location and its vicinity called zone of influence. The sensors on the error plane must be distributed to minimize the mean square distance between each error sensor thus optimizing the area of the error plane. Proceedings of Meetings on Acoustics, Vol. 19, (2013) Page 2

3 Additionally, the results showed that the radius of influence of each error sensor is maximally 1/3 the wavelength to control. Hence for a 1.8 m diameter duct and 320 Hz, the minimal number of microphones is 10. FIGURE 2. Attenuation provided by a multi-channel ANC system on a duct The system was implemented using 10 loudspeakers and 10 error microphones located inside a covered platform on the chimney. The error microphones were inserted in probes (waveguides) and were isolated from heat and corrosive gas. The loudspeakers were housed in enclosures and were mounted vertically on a bent duct to avoid particle build-up on the loudspeakers membranes. The loudspeakers were also treated to protect their membrane and suspension surround from heat and corrosive gas. The controller used in the 90s project was implemented using a VME rack with a PC and a floating-point DSP. Using this hardware, the ANC system was not able to perform the optimization in real-time but proved to be able to control the noise appropriately. The system was put into operation in FIGURE 3. Microphone probes and speakers on chimney Proceedings of Meetings on Acoustics, Vol. 19, (2013) Page 3

4 Updated ANC System System Description The Figure 4 shows the overall ANC system. The controller sits in the same cabinet as the amplifiers in the chimney covered platform. The controller directly manages the error microphone signals and tachometer signals, it performs the low-level real-time XLMS optimization to generate the speakers signals to drive the amplifiers and loudspeakers. A high-level automation software located on a remote computer provides an interface to the controller via Ethernet. FIGURE 4. Overall System Schematic Proceedings of Meetings on Acoustics, Vol. 19, (2013) Page 4

5 Updated Controller Architecture and Low-Level Algorithm The controller hardware architecture is based on a signal processing board with a C64x+ DSP from Texas Instruments. The controller includes: - A Soft db Signal Ranger MK3-PRO DSP board to perform signal processing in real time. - A high-resolution (32-bits) acquisition board: 13 ADCs and 10 DACs with anti-aliasing filters. - Three tachometer inputs with integrated optocouplers. - A USB and Ethernet communication interfaces. This controller is a compact solution that can be installed in the rack-mount cabinet on the chimney covered platform close to the system equipment. This helps to reduce the cost of the installation and simplifies the maintenance since all the equipment (microphones, loudspeakers, amplifier and the controller itself) are at the same location and close to the chimney. The Ethernet interface allows to configure and to manage the controller with a remote computer over the network. Compared to the previously used DSP in 1995, this current one is about 25 times more powerful. TABLE 1. DSP Platform Comparison implementation 2012 implementation DSP TMS320C40 TMS320C6424 Arithmetic 16 bits floating-point 32 bits fixed-point Processor Speed 50 MHz 600 MHz Performance 200 MFLOPS 4800 MIPS The next figure shows a schematic of the signal processing done in real-time at low-level on the DSP of the controller: FIGURE 5. Low-level algorithm schematic Proceedings of Meetings on Acoustics, Vol. 19, (2013) Page 5

6 The process is based on two sampling rate levels (F acq. and F deci.). The first sampling rate level is the acquisition process at 12 khz (the black sections of the schematic). The second sampling rate level is the optimization process rate at 1 khz (the blue sections of the schematic). This approach allows to minimize the group delay without sacrificing the real-time optimization. The relatively high sample rate for the acquisition allows keeping the group delay of the ADC/DACs low while the optimization is done at much lower speed. As illustrated on the schematic, the input and output signals are filtered when they travel across the sampling rate levels. These IIR filters are software adjustable and act like decimation filters. A better control is achieved over the compromise between the group delay and precision of the anti-aliasing filter. Also, these band-pass filters are used to guide the LMS algorithm on the frequency band of interest (around 320 Hz). For the tachometer input, the decimation filter is adjusted to remove the low and high harmonics of the tachometer reference signal. On the schematic, the optimization of the control filters is illustrated for the first reference signal only. The process shown on this schematic is repeated for all three reference signals coming from the tachometers. A XLMS technique is used to optimize the control filters. The adaptation step-size is normalized following the reference signal level, the number of coefficients for the control filters and the gain of the secondary path filters at 320 Hz. The information for the normalization is known before the control phase and the adaptation step-size is fixed afterward. The CxEx filters are identified while the control is off using an LMS algorithm and a white noise generated at the loudspeakers. However, this process is done in the chimney in the presence of the noise to control which affects the identification process. To achieve an adequate precision, the adaptation step-size is gradually reduced while the identification time is proportionally increased. High-Level Automation Software A high-level automation software was developed to provide an interface to the controller. It has been designed to provide two operation modes: manual and automatic. The manual mode allows the user to take control of every aspect of the controller manually whereas the automatic mode handles every aspect of the process automatically without any user intervention. The automatic mode follows parameters which are defined using the manual mode. This allows the manual tuning of the system and its stand-alone operation using the same software. When the program is launched, it tries to connect to the controller on a previously defined communication port (USB, DHCP or fixed address). Then the automation process (Figure 5) is executed. It checks the system components to detect any defective elements, identifies transfer functions between each microphone and loudspeaker, selects the appropriate reference signals from the tachometers and starts the control. This preliminary process is performed every day at 12:00 AM to ensure an up-to-date identification. When the ANC is ON, the software logs and displays a time-history of the error levels. It also checks in real-time for any control divergence or output saturations. When this occurs, it performs a system components check and complete identification. It also tracks any changes on the tachometer signals (Reference signals) and adapts the control accordingly. When a defective component is identified, a message is displayed to the user and an error message is transferred to the industrial HMI. This system is integrated to the industrial HMI using ModBus over Ethernet. Simple tasks like ANC enabling and disabling are provided to the industrial HMI and high-level information such as error microphone estimated attenuation is also provided. FIGURE 6. High-level automation software interface Proceedings of Meetings on Acoustics, Vol. 19, (2013) Page 6

7 FIGURE 7. High-level automation process (automation software) Basic Components Most of the basic components, such as the microphones, loudspeakers and amplifiers use the same technology that was installed in the 90s project, though every component has been replaced. Similarly to the previous system, three tachometers on the fans arbors provide reference signals to the controller. However, the previous tachometers were optical sensors and proved to be sensible to dust and ware. The current tachometers are proximity sensors which are more reliable. Additionally, optocouplers inputs were added to the controller to connect the tachometers thus avoiding any ground problems and providing a strong and stable reference signal. Proceedings of Meetings on Acoustics, Vol. 19, (2013) Page 7

8 Experimental Results To evaluate the ANC performance, an environmental noise measuring station was installed about 400 m from the chimney (Figure 8). During several hours, the control was enabled and disabled for short periods of about 10 minutes. Both in-the-field and chimney noise levels were recorded as base of comparison (Figure 9 and 10). FIGURE 8. Measurement Location and Chimney 100 Time History Hz Levels Field Level at 320 Hz (db) FFT Graph Chimney Level at 320 Hz (db) :00 9:30 10:00 10:30 11:00 11:30 12:00 Time on Instant Field Level Equivalent Field Level Instant Chimney Level Equivalent Chimney Level Control State FIGURE 9. Time history (320 Hz), field and chimney noise levels 60 Field FFT Spectrum Comparison Level (dba) db 10:25-10:33 Leq (Control OFF) 10:33-10:41 Leq (Control ON) FIGURE 10. Field equivalent FFT spectrums of two consecutive periods Proceedings of Meetings on Acoustics, Vol. 19, (2013) Page 8

9 Figure 9 and figure 10 show that the ANC system has also a significant effect on the noise level. From a period to the other, an average attenuation of 10.6 db is achieved in the chimney and an attenuation of 10.3 db is achieved in the field. These numbers were determined over 34 distinct periods of operation over 6 hours. An interesting observation is the lower variations in chimney noise level with ANC enabled compared to the greater variations observed with ANC disabled. Current Limitations of ANC for Industrial Chimneys Nowadays, ANC systems can be implemented to reduce efficiently the noise of industrial stacks. The XLMS control algorithm is comprehended and modern DSPs allow the processing of this algorithm in real-time. Besides, the knowledge regarding the number and location of error microphones allowing efficient control of higher modes is also well understood. However, there are still some limitations on use of ANC systems on industrial chimneys: the power and durability of loudspeakers. Indeed, the noise levels commonly found in chimneys are very high, often greater than 120 db and are low frequency tones. To perform active noise control, the loudspeakers must be able to generate these levels continuously, 24/7. In addition, the size of the speakers must be quite small to fit on the perimeter of the chimney. Only a small number of loudspeakers available on the market meet these requirements. Moreover, in many circumstances gas in smokestacks are hot and possibly corrosive. Thus loudspeakers need to be resistant to these harsh conditions. The lack of powerful, compact and rugged loudspeakers is the undoubtedly the main limitation of ANC for industrial chimneys. Conclusion The upgrade of a multi-channel ANC on an industrial chimney was successfully conducted. A better system integration using the latest DSP technology and greater performance in attenuation and speed were achieved. The field measurements proved the ANC to be an effective solution to reduce the noise of an industrial chimney. REFERENCES Widrow, B., Stearns, S.D. (1985). Adaptative Signal Processing. (Prentice-Hall) L Espérance, A., Bouchard, M. Paillard, B. and Dubé, J.C. (1997). Investigation of an active noise control system to reduce the noise emitted by an industrial stack, CIM Bulletin, Vol. 90, N L Espérance, A., Bouchard, M. Paillard, B. and Guigou C. (1998). Method and Apparatus for Active Noise Control of High Order Modes in Ducts, US Patent 5,748,750. Proceedings of Meetings on Acoustics, Vol. 19, (2013) Page 9