Another Successful Condition Monitoring System Installation

Last week our team successfully and safely installed another Boiler Monitoring System (BMS).  This system, a Sootblower Fouling Detection (SFD) system, monitors structural and vibration sensors that quantify the boiler’s response to sootblower operations. The SFD system analyzes the boiler response data and outputs Key Performance Indicators (KPIs) such as fouling level, sootblower efficiency, and sootblower health to automated boiler cleaning systems.

This boiler uses over 50 sootblowers located at different elevations to clean soot build-up from boiler steam tubes.  Since the vibration measurement locations are relatively far apart, the SFD system requires a distributed monitoring system consisting of several junction  boxes that monitor and process data for groups of sensors.  One team of engineers mounted the vibration sensors to the sootblowers and confirmed communication back to a local junction box containing the National Instruments condition monitoring hardware.  The other team installed the junction box panels and terminated the sensor cables.

After all the sensor installations and terminations were completed, each sensor’s location and calibration were verified.  While the sensor verification was being completed, one engineer worked with the mill IT department and the controls engineer to establish remote connection to the system and confirm communication with the mill’s automated cleaning system.

After commissioning the system and returning to our home base, our engineers are now monitoring the system through a VPN connection and assisting boiler operators with optimizing their cleaning process.

For more information about our boiler condition monitoring systems, contact Ryan Welker via email at or phone @ 1.844.837.8797 x702

Troubleshooting Machine Failures Caused by Intermittent Damaging Events

Over the years we have been tasked with identifying the root cause of machine structural failures. In many cases, we can determine the failure mode through strain and vibration testing, order analysis, modal analysis, and operating deflection shape analysis.  What tests can you run when the damaging conditions are intermittent and not easily identified?

In these cases, we like to install a cellular networked temporary data acquisition (DAQ) system that can autonomously log vibration and strain data along with machine status data. We have deployed two types of DAQ systems to collect data remotely.  An interactive system that includes an industrial PC running our iTestSystem software and National Instruments (NI) Compact DAQ hardware and a headless system that utilizes NI Compact RIO hardware.  Our test engineers prefer using the interactive solution for troubleshooting because they can view real-time signal waveforms and collected data files, and then adjust the test parameters accordingly without having to reprogram the hardware.

Figure 1: Headless networked data acquisition system

When potentially damaging events are identified in the vibration and strain data collected by these systems, it is important to know the machine’s operating status. Collecting the machine status information is just as important as collecting the structural data.  Many machines transmit these operating variables and operating stages over their network/bus.  Recently we have recorded process data from Allen Bradley Control Logix PLCs via Ethernet/IP, mining machine data from a Siemens controller via proprietary TCP/IP protocol, boiler condition data from a DCS via Modbus TCP,  machine pressures from PI historian via the UFL connector (TCP), and vehicle speeds and pressure via CAN.  Fortunately, we were able to use and adapt LabVIEW communication protocol tools to build applications and addons that allow this network tag data to be collected along with structural data.

Figure 2: Modbus to Shared Variable Tool

After the data collection phase, our engineers perform statistical analysis on the sensor and status channels in all data files and aggregate the results into a database for searchability. To identify the root cause probabilities, you can process the channel statistics data using your favorite correlation algorithm or application.  The image below shows an example data set containing related sensor data that was processed using a LabVIEW correlation test tool.

Figure 3: Correlation Test Example vi

Contact Information: For more information about our remote data acquisition service, our LabVIEW development service, or iTestSystem contact:

Mark Yeager – Integrated Test & Measurement (ITM), LLC.  Email: or Phone: 1.844.TestSys

ITM adds FieldDAQ Sound & Vibration Module compatibility to iTestSystem

The FieldDAQ™ FD-11634 sound and vibration input module from National Instruments (NI) can now be used with the latest version of iTestSystem (16.1.24).  The FD-11634 is similar to the NI-9234, NI-9232, NI-9231, and NI-9230 cDAQ dynamic input modules and can be used with IEPE type sensors such as accelerometers and microphones.  Like the other FieldDAQ™ modules, this module is IP65/IP67 dust and water resistant with an operating temperature range of  -40 °C to 85 °C.  Our test engineers would use these modules for collecting vibration data on mining and construction equipment, vibration data on rotating machinery within manufacturing facilities and test cells, and acoustic data for measuring equipment noise emissions.

The FieldDAQ™ FD-11634 module has 8 simultaneous sampled, ±1V or ±10 V, 24-bit differential input channels with AC/DC coupling. It has a maximum sample rate of 102.4kS/s and features built in anti-aliasing filters that automatically adjust to the sampling rate.

For advice about using the FieldDAQ™ FD-11634 sound and vibration modules in iTestSystem monitoring applications or with custom cRIO RT and FPGA control applications contact Mark Yeager or Chase Petzinger.

Click Here to view a video showing one of our test engineer collecting data from a submerged FieldDAQ™ module with iTestSystem.

Click Here for more information about iTestSystem.