Compressed air systems hold one of the keys to greater productivity, efficiency and profitability in your facility. The Compressed Air Challenge (CAC) is a voluntary collaboration of industrial users; manufacturers, distributors and their associations; facility operating personnel and their associations; consultants; state research and development agencies; energy efficiency organizations; and utilities. This group has one purpose in mind—helping you improve the performance of your compressed air system.
The CAC has developed two levels of training for plant engineers: Fundamentals of Compressed Air Systems and Advanced Management of Compressed Air Systems. This is the second in a series of articles that introduces some key points of CAC training.
The process of baselining compressed air system performance involves taking measurements to determine the effectiveness and efficiency of your compressed air system to meet productive air demands efficiently. Measurements of pressure, flow, power and energy consumption are the “vital signs” of a compressed air system.
Measurements can help you understand how the compressed air system is operating.
The information gained can be used to identify opportunities for system improvements.
Data logging system performance can help you better understand how to optimize your system.
Make sure you have the right tools for the job, know how to use them, understand their limitations, and know how to interpret the data being produced.
The resultant information will help you understand the business impact of compressed air system operations: namely its effect on productivity, product quality and the cost of compressed air per unit of production.
Compressed air system performance can be measured in many ways using several techniques and types of equipment. When gathering data, e.g., pressure, flow, power, and energy consumption, it’s important to remember that the ultimate goal is to reduce operating costs.
Measurements can be spot checks of performance during operating shifts. Although spot checks can provide some answers, they don’t produce a complete picture. Since compressed air systems are dynamic in nature, with frequent changes in operation, data logging performance will provide a more accurate baseline. Data logging documents the interactions occurring with changes in demand and the resultant supply side response.
The informational objectives below relate to the stability of system performance and energy consumed. The baseline measurement should document current performance and identify opportunities for improvement.
- Record the plant’s air demand profile through airflow measurements made during normal plant operations.
- Create a pressure profile to establish the current compressor control interactions, with particular attention to compressors operating in unloaded, or partially loaded states.
- Develop a power profile relating delivered airflow and power consumed.
- Evaluate overall supply-side efficiency by measuring total compressor energy consumption, delivered airflow to the system and energy cost.
- Determine the pressure drop through treatment equipment and evaluate the effect of increasing or decreasing airflow.
- Identify peak transient air demands by evaluating compressor control response and considering the potential benefit of engineered air storage.
- Measure pressure gradient across distribution system piping and document the effect of changing air demand.
- Profile dynamic air use at high-volume intermittent demands and consider potential air storage opportunities.
- Evaluate perceived high-pressure air demands and measure applied air pressure at the point of use.
Informational objectives may vary from system to system and will depend on the defined scope of study. However, measured data must be consistent with the information desired. Select appropriate locations to measure flow, pressure and power.
Several key pressure measurements may be made. On the supply side, for example, measure at each compressor, upstream and downstream of air treatment equipment, such as dryers and filters. The demand side might include pressure measurement at various points in the distribution system, at critical end uses, at perceived high-pressure air demands and high-volume intermittent air demands.
Airflow measurement at each system supply point will identify the plant air demand profile. Flow measurement can further help identify the existence of intermittent demands and transient events. Flow and pressure measurements at high-volume intermittent air demands can help determine the potential for application of secondary storage.
Power measurement at each compressor provides insight into the response of compressor controls to changing compressed air demand. Totaling power consumed during a particular time interval provides a measure of energy consumption.
Compressed air flow and energy consumed ultimately determine the cost of producing compressed air. Knowing this allows you to assess the cost of normal operations and waste. This provides the baseline for justifying improvements in the compressed air system and verification of results.
The tools required range from simple gauges and meters for spot check measurements to transmitters and data loggers for trending and dynamic analysis. When selecting tools, consider both accuracy and repeatability. Accuracy is the ability of a particular device to measure to a known value or standard. Repeatability is its ability to achieve the same measured value consistently.
Informational objectives determine the need for accuracy, repeatability or both. For example a 0 - 200 psig pressure transducer with 1.0% accuracy (full scale) could result in pressure readings that vary by 2.0 psi. Using two such transducers to measure the pressure drop across treatment equipment could result in significant error. Assuming the actual pressure drop was 5.0 psi, the measurements could vary from 3.0 to 7.0 psi. For this type of information, high accuracy is necessary. Pressure transducers with 0.15%accuracy would yield ± 0.3 psig; a range of 4.7 to 5.3 psi.
When data logging system performance, first evaluate data collection methods. In particular, sample rate (reading transducer signals), and data storage interval are critical. The time interval of logged data points can significantly affect performance evaluation. When referring to the time base of data acquisition, there are three parameters to consider.
- Sample rate—the frequency at which the transducer output is sampled.
- Data reduction—the method used to reduce multiple samples to a data point. (Averaging is common, although other methods, including filtering, can be used).
- Data interval—the frequency that an actual data point is stored.
The purpose of higher sample rate and data reduction is to minimize the effect of transducer noise on recorded data. For example, pulsations at the discharge of a reciprocating compressor can produce a noisy transducer condition. In this instance, a frequent sampling rate can be averaged to achieve a more stable reading.
There are no set values for sample rate and data interval. Rather, system performance and informational objectives must determine them. If dynamic system response is to be evaluated, the nature and time period of the underlying event must be considered to determine an appropriate sample rate and data interval.
The sampling rate and data storage interval should allow for at least three to five data points during the time interval of the event being captured. Any event captured with fewer than three data points may not be accurately depicted in the logged data. As a general rule, air system performance data should be acquired with a one-second sample rate and 10-second interval.
The data chart in Figure 1 shows measurements of air compressor load/unload control cycles.
Figure 1 Compressor load cycle pressure recorded at various data intervals.
Data compares the affect of different sampling rates and data intervals as described in Table 1.
The period of compressor load cycles in Figure 1 is less than 90 seconds. (The period is the time between the start of a compressor load cycle and the start of the next compressor load cycle.) The pressure data shown in the blue line and flow data (the red line) are taken at high sample rate and data interval. The pressure value shown in the green line is at slow sample rate and data interval.
The slow sample rate and data interval are inappropriate for collecting data in the time base of the underlying compressor load/unload cycling. Based on these data, conclusions regarding information on the compressor control pressure profile at the slow sample rate is incorrect.
Compressed air system baseline measurement may be made as a single snapshot or a moving picture. Collecting and analyzing data is the means to accomplish specific informational goals. Invest in accurate, reliable equipment or to work with someone who has the equipment. Make sure you have the right tools for the job, know how to install and use them, understand their limitations, and know how to interpret the data being produced.
Once the current operation is measured and analyzed, opportunities for improvement can be identified. Accurate information will open the door to greater productivity, efficiency and profitability in your facility.
Table and chart courtesy of the Compressed Air Challenge
Tom Taranto, is Manager of Compressed Air System Solutions for ConservAIR Technologies in Kenosha WI. He has over 20 years experience in design, auditing, testing, and application of fluid power systems, both pneumatic, and hydraulic. Beginning in 1992, Tom pioneered and developed data logging methods for compressed air system auditing, that are in common use today.
Tom is a graduate of Clarkson University, with a Bachelors Degree in Mechanical Engineering. He serves on the CAC technical review committee, AirMaster+™ committee, and is a CAC Instructor for both fundamental and advanced levels of training. Tom is a member of ASME, AFE and is a past President of the Fluid Power Society, Chapter 21 Syracuse, NY.