More than $1 trillion is spent each year to replace perfectly good equipment because no reliable and cost-effective method is available to predict the equipment’s remaining life. Now through careful design and a balance of technologies, a wireless condition-monitoring system provides a dependable and economically viable solution.
Christopher McLean and Dave Wolfe, Techkor Instrumentation
The next step in the evolution of CBM is online surveillance systems, which provide more frequent machine-condition information than data collectors. The online systems include hard-wired sensors connected to multiplexers, which are networked to a main database computer. Most manufacturing facilities can’t fully implement a surveillance system because of the high capital costs, installation difficulties, and overall complexity of the system. Online systems are most often used on the most critical pieces of equipment.
Online surveillance systems are more cost-effective than data collectors when the machinery they’re monitoring:
If an inexpensive process pump can halt a $140,000/hr. production line, an online system is easy to justify. Some machines will indicate problems and propagate failure hourly, so even daily route running won’t be sufficient .
Frequent condition monitoring can change the way maintenance and production decisions are made. After a fault is discovered, the next question is, can the machine continue to run or can it make it to the next outage? A system of thousands of sensors monitoring a facility’s equipment (including some with developing faults) provides management with a clear, up-to-date picture of its infrastructure’s condition. With analysis software that can predict the life expectancy of a failing component, plant maintenance and production can schedule downtime when it is the least disruptive, which maximizes process throughput and minimizes costs .
With the new online technology, facilities will be able to run leaner because they’ll have more confidence in their ability to eliminate unscheduled downtime. Up-to-date information can also ensure that equipment is not replaced too early. Most manufactuêers have excess production capacity in their facilities to handle unexpected breakdowns. In petrochemical and petroleum refining plants, as much as 10% of production capacity can be required to make up for unplanned maintenance .
Several companies have developed telemetry systems that are a step in the right direction, such as Wilcoxon’s BlueLynx and Oceana Sensor’s ICHM 20/20. In addition, Rockwell has the HiDRA, and SKF promotes its wireless system. All of these systems connect a couple hard-wired sensors to a radio hub, so significant cable installation is still required.
Computational Systems has introduced a true wireless sensor (i.e., devices that use no cables at all). The 4100RF’s installed cost is about $1000 per sensor, which is comparable to an online surveillance system. All of these wireless systems work well in difficult or dangerous-to-reach locations or in moving applications; however, they’re still expensive and offer an alternative only to a small portion of a facility’s locations.
Desired Wireless Features
So how does this apply to wireless CBM? For such a system to support thousands of low-cost sensors and meet customer expectations, it must incorporate intelligent sensors that are the same size as traditional sensors and offer plug-and-play connectivity, high reliability, and long battery life.
ühe installed cost of any CBM system is critical to its financial success. A $100 accelerometer becomes a $600–$1000 sensor when you consider installed costs. At these levels, it’s common to use hard-wired systems only on critical assets. Wireless systems limit the installed cost to a fraction of that incurred with cabled solutions. A $400 wireless sensor becomes a $450 sensor when installed.
The operating costs of the data collector program accumulate every year, including labor and training. This method can have significant operating costs when faced with a high number of points and high frequency of measurement. Surveillance systems, especially wireless systems, have minimal operating costs.
Ease of Use
The transceiver that receives the information from the wireless sensor network and connects to the main computer must also be easy to use and install. Of the existing enterprise networks available on the factory floor, Ethernet provides the most flexibility when compared with Modbus, DeviceNet, and Fieldbus. Many manufacturing facilities have Ethernet systems in place, so the transfer of data after the wireless portion is painless.
Once on the enterprise network, information on factory conditions can easily be sent anywhere in the world. Within this context, application software must be able to be used by multiple users. Typically, the sensor node data are stored in an Open Database Connectivity—compliant open architecture database using SQL language.
Physical Layer. The two potential choices for the physical layer are narrow band and spread spectrum. Both yield good results when properly implemented. Narrow-band radios can be broken down into two categories: those with only one frequency and those with multiple frequencies. A well-designed, multiple-frequency, narrow-band radio with spatial diversity can perform well in industrial environments. Spread-spectrum radios come in two main styles: frequency-hopping spread spectrum (FHSS) and direct-sequencing spread spectrum (DSSS). Spread-spectrum radios improve transmission reliability by distributing (hopping) the transmitted power over a large bandwidth. FHSS’s hopping rate is slower than the bit rate, but with DSSS, the hopping rate is faster. Spread-spectrum radios offer better physical-layer performance than narrow-band radios, but at the price of increased cost, size, and battery drain (see Table 1).
One of the potential benefits of spread-spectrum transmissions is process gain, which can improve receiver sensitivity at the expense of additional battery drain. Process gain is proportional to 20 db 3 log (chirp rate). However, almost all spread-spectrum systems used in wireless sensor networks are FHSS (e.g., Bluetooth), which hop too slowly to take advantage of the process gain. You have to use a DSSS radio (e.g., IEEE 802.11) to benefit from process gain.
You can use spatial diversity to improve signal reception and transmission. Spatial diversity refers to using multiple antennas, and it’s useful in both narrow-band and spread-spectrum systems. Simple multiple-antenna designs in narrow-band receivers can improve spatial resolution by removing the probability of multipath interference. Sophisticated multiple antenna systems use the antennas to provide receiver directional gain through beam forming.
All transmitters in the U.S. must meet FCC guidelines for licensed or unlicensed operation. Licensed operation is impractical for most industrial users because of the regulatory hurdles, so unlicensed operation is preferred whenever possible. For industrial applications, the Industrial-Scientific-Medical (ISM) bands (902–928 MHz or 2.4000–2.485 GHz) meet FCC requirements for unlicensed operation. Within the ISM bands, narrow-band operation is limited to 1 mW of radiated power, while spread-spectrum transmitters are allowed up to 1 W of transmitted power. Higher-frequency bands provide more signal bandwidth, but lower frequencies offer better performance in multipath environments, where reflections are common.
Communication Protocol. A wireless data-gathering network must be reliable in industrial environments, where RF interference from motors, lighting, and other wireless systems is typical. According to Glenn Allgood of Oak Ridge National Laboratory, most industrial interference is caused by intermittent bursts of narrow-band signals, random EMI (background noise), and deterministic EMI (radio stations).
At any given time, the wireless link does not have to be reliable, but there must be a 100% probability the message will get through within a reasonable time. It’s also necessary to guarantee that any errors in the message will be detected and corrected. Lost or corrupt data will show up as distortions and could produce false equipment-condition reporting. Collisions between packets and interference from other radio sources must also be addressed.
The wireless CBM communications method must allow thousands of sensors to coexist in a single network. Various techniques are available to ensure dependable coexistence. Some of the more common are time division multiple access (TDMA), frequency division multiple access (FDMA), and code division multiple access (CDMA). The circuit cost and complexity of TDMA is the lowest, followed by FDMA and then CDMA.
Time domain and frequency domain multiple access are the easiest to understand. In both, timing or frequency bands separate communications of multiple sensors. In code division, several communications channels can be open simultaneously, as long as the spread-spectrum chirping rates are high.
For CBM monitoring, you don’t need to have multiple, simultaneous communications. For example, for a 256-point sensor cell, where each accelerometer makes a 800-line FFT reading eight times a day and each communication to the network takes 5 s, the total air time is 2.84 hr. per day, or 12% network loading. Either FDMA or TDMA will perform nicely in these environments.
Wireless standards offer additional interplay between sensor manufacturers. Any wireless sensor standard will have to specify the physical layer (e.g., FHSS, DSSS, and narrow band), the communication protocol, and significant aspects of the application. In effect, the standard must define a universal wireless sensor node. The IEEE 1451.X working group and the Bluetooth SIG are doing some work in these areas.
Many possible solutions exist for wireless communications; however, a design must carefully balance performance, cost, size, and power consumption. This balance is particularly important in wireless sensors. For example, CDMA spread spectrum is reliable, but at a significant cost, size, and power drain penalty. A better solution is to use a less reliable physical layer but improve the communication protocol to achieve the same reliability.
Using a multiple-frequency, narrow-band radio with spatial diversity and an aggressively designed communication protocol, you can achieve impressive results while still meeting cost, size, and power consumption requirements. It’s important to remember that the timeliness of CBM data is somewhat relaxed. It’s more important to have correct data that’s 10 s old than erroneous data that is prompt.
Battery size is directly related to the power consumption and operational requirements of a device. Simply adding a wireless connection to existing sensor designs is not a good solution from the battery standpoint. Sensor electronic designs and operational methodology must be laid out with battery drain as a primary concern. Power-efficient circuit design and aggressive battery management (e.g., standby modes and duty cycling) can provide operational lives hundreds of times longer than those without.
Chemical batteries come in rechargeable and primary varieties. In either case, lithium chemistries exhibit the best performance, with 3.3 V output, high peak output, low self-discharge, low weight, high energy density, good cost-to-capacity ratio, and }ittle memory effect. For rechargeable and primary batteries, lithium ion and lithium thionyl chloride are superior choices.
Rechargeable batteries are used where recharging is desirable, such as in temporary testing. Only two viable rechargeable battery chemistries exist—lithium ion and lithium polymer. Both exhibit excellent energy density, good peak currents, low weight, hiýh voltage, and little memory effect. Lithium ion tends to be less expensive than lithium polymer, but lithium polymer is more rugged and environmentally robust. Lithium polymer can be formed into various shapes and lends itself to packaging. Both nickel cadmium and nickel metal hydride are poor solutions because of their self-discharge, higher weight, lower energy density, lower voltage, and memory effect. For permanent installations, recharging a battery is not desirable.
The life of the battery is critical, especially when considering the expense associated with either replacing or recharging it. A chemical battery should be designed to last more than three years under fairly heavy sensor use. For example, the Techkor wireless accelerometer is designed to operate on a half A-size lithium battery with a capacity of 1000 mAh. With a standby current draw of only 3 µA and an operational current of 16 mA—including the sensor, signal conditioner, microcontroller, memory, and transceiver—significant battery life results. For such a battery, the standby life would be 38 years, and that factor is neglected in this analysis because it is longer than the shelf life of the battery. The sensor should be able to perform 9000 operations (assuming 20 s duration) over its life. If the wireless sensor monitors eight times a day, this leads to a projected battery life of 3.08 years. The life is scalable, so for monitoring four times a day, the projected life would be six years. When performing battery projection, you must take into account network traffic and reliability of the physical layer. Additional transmissions caused by errors or collisions will reduce the battery life. In contrast, if the sensor is operating continuously, it would operate for only 50 hr. (2.08 days). For maximum confidence, wireless CBM sensors should be designed to perform periodic self-testing for power fluctuations and low battery power.
Hybrids. Thin film hybrid technology or chip-on-board technology can be used to significantly reduce the size of wireless sensors. A standard 4 by 4 by 0.25 in. printed circuit board with surface-mount components can be reduced to approximately 1 by 1 by 0.25 in. by using chip dice, subminiature components, and thin film hybrid technology.
Combining the radio, accelerometer, and circuitry in a thin film hybrid is not a simple matter. As packages shrink, interference problems and power dissipation increase. Packaging the digital radio in such a small space with the microcontrollers and analog accelerometer involves significant analysis.
MEMS. MEMS system-on-a-chip capabilities are just beginning to become a reality. While the components of MEMS have been around for some time (e.g., microsensors, microactuators, microelectronics, and microstructures), the ability to combine them in a reliable, cost-effective manner has been lacking.
With today’s MEMS technology, combining the radio transceiver, accelerometer, and circuitry is still in the development stage. MEMS accelerometer elements are not new, but MEMS accelerometer technology tends to have low frequency response and is more sensitive to shock. Special attention needs to be given to account for these shortcomings.
Industry is just beginning to produce viable MEMS radio components. Work being done at Georgia Tech (Chahal and Bhattacharya), DARPA (Tang), Carnegie Mellon University (Fedder, Luo, and Xie), Berkeley (Bilic), and others is furthering the advancement of MEMS accelerometers and radios. The announcement by MEMSCAP in May 2000 of a component library of MEMS inductors and variable capacitors ushers in a new generation of radio design.
ASICs. Historically, developing mixed-signal ASICs is cost prohibitive, and the devices are sensitive to layout. Only when dealing with volumes in the millions of pieces are ACICs cost-effective. Mixed-signal ASICs would still require external components to complete the circuitry. This is not considered a viable alternative for wireless accelerometers.
The CBM market can justify the cost of widespread implementation of wireless condition monitoring systems. With up-to-date machine condition, maintenance, and production, decisions can be made to optimize production, and manufacturing facilities can operate more efficiently.
2. William Broussard. “How to Justify and Calculate the Cost of an On-Line Reliability System” [PDF], Computational Systems, Inc.
For Further Reading
Federal Communications Commission, Office of Engineering Technology, Policy and Rules Division, “The FCC’s On-Line Table of Frequency Allocations,” 47 C.F.R. 2.106.
Harris, Cyril M. “Shock and Vibration Handbook,” 4th ed.
Mauk, Jeffrey M. 1999. “Collecting Data for Statistical Monitoring” Enteract ’99. Orlando FL.
Watkins, Jeffrey P. 1999. “RCM, Where Does it Fit?”, Enteract ’99, Orlando FL.
Christopher McLean, Ph.D., is Division Manager, and Dave Wolfe is a Sales Engineer, Techkor Instrumentation, A Division of Advanced Conversion Technology Inc., 2001 Fulling Mill Rd., Middletown, PA; firstname.lastname@example.org, email@example.com.