Wireless smart sensors coupled with a software interface that enables users to visualize the data provides a condition monitoring and predictive maintenance solution rooted in the Industrial Internet of Things, write Tad Orstad and Mario Calvo

The ever-changing competitive environment in today’s industrial markets is forcing owners and operators to maintain their assets in satisfactory operating condition.

Traditional monitoring of selected equipment or processes is labour intensive with parameters being monitored one at a time, recording their conditions, and analyzing trends. In addition to consuming valuable man-hours and creating potential dangerous situations, traditional monitoring results can be inaccurate thus increasing downtime and maintenance costs.

Today, the Industrial Internet of Things (IIoT) provides a means of consistently capturing, communicating, and recording real-time and historic data from networks of physical objects such as process equipment and vehicles with embedded sensors, software, and network connectivity.

This enables the IIoT components to collect and exchange data and allows plants to detect equipment problems and process inefficiencies sooner, resulting in efficiency improvements and reductions in costs.

Predictive beyond preventive

Routine inspections, system tests, lubrication, parts replacement and keeping records of equipment deterioration are all fundamental strategies for any preventive maintenance (PM) programme.

Asset managers or maintenance staff establish set schedules for PM activities with a major goal of reducing unplanned downtime. During PM, the systematic replacement of deteriorating components and the identification and correction of equipment issues will prevent equipment failure.

However, in and of itself, PM does little to reduce costs for labour and spare parts as determining the ideal time for PM is imprecise and focuses on estimates in lieu of the actual equipment condition. Oftentimes, perfectly good components are replaced periodically on a need-it-or-not basis. Further, some PM activities can cause collateral damage due to human error, and this only adds to downtime.

To minimize unplanned downtime beyond that achieved using PM, and to further reduce parts and labour costs, condition monitoring is the cornerstone for evolving predictive maintenance (PdM) solutions. Conditioning monitoring to track asset/system pressure, temperature and humidity levels allows asset managers and maintenance staff to perform maintenance only when necessary.

By providing real-time and historic data trends for assets and processes, the condition monitoring solution allows operators to detect and diagnose issues before they become problems.

Also, using smart sensor hardware and analytic software, alerts and analytics can be delivered to operators when needed. PdM with condition monitoring allows optimization of systems and assets based on actual data rather than reacting to unexpected events.

Particularly on process-critical assets and systems, integrating a PdM strategy into an existing PM programme can substantially save parts and labour costs, allow for fast and precise diagnoses reducing troubleshooting time, and maximize asset life spans.

Vital analytics

Wireless smart sensors coupled with a software interface that enables users to visualize data collected from the sensors provides a condition monitoring and predictive maintenance solution rooted in the IIoT.

Wireless sensors avoid the cost and complexity of a wiring infrastructure, and can be easily removed for modification as is typical during expansions. Monitoring a plant’s assets for temperature, pressure, humidity, dew point, flow and current usage plays a vital role in diagnosing inconsistencies, allowing users to predict and prevent downtime.

SensoNODE Blue and SensoNODE Gold wireless sensors, shown in Figure 1, are small in size and easy to install. They are well-suited for robust use in harsh environments as they are constructed using 17-4 stainless steel wetted parts (or brass with humidity sensors) housed within a polycarbonate housing with fluorocarbon or nitrile body seals.

Figure 1. SensoNODE Blue and SensiNODE Gold Wireless Sensors

SensoNODE Blue sensors utilize a Bluetooth radio module that lets users connect directly to a mobile device. They are ideal for quick troubleshooting of systems as well as assisting individuals who monitor the condition of assets in a route-based scenario.

Using Bluetooth technology, SensoNODE Blue sensors transmit data to the SCOUT Mobile software platform installed on a user’s mobile device (see Figure 2). This allows simple, wireless monitoring of pressure, temperature and humidity within a 300-metre range of the sensors.

SensoNODE sensors have two operating modes: Connect and Beacon. Through the SCOUT Mobile App, users can view, manage and record data while in range. The Connect mode is used to establish a private one-to-one session with the sensor to manage the settings. The Beacon mode allows multiple users to view data from the sensors. In both modes users can view measurements and visualize data with multiple tools. The direct link between the sensors and the mobile app puts vital information and analytics in the palm of the hand, enabling users to optimize asset performance.

Figure 2. SensoNODE Blue Sensor/Scout Mobile Software

SensoNODE Gold sensors are also wireless-based nodes that work on a 900 MHz frequency band. Users have the option of pressure, temperature, current, flow, humidity, dew point and a soon-to-be-released vibration node. The SensoNODE Gold sensors interface with a gateway located on the premises that collects and buffers data. The gateway enables secure connections to the sensors, manages the sensors’ operating status, and is the conduit for data to the SCOUT Cloud platform as well as push commands from the cloud to the sensors.

The SCOUT Cloud platform is accessed through a secure login internet-based portal. It enables users to manage sensors, set thresholds and alarms, and visualize the data gathered from their assets through easy to use dashboards. Figure 3 shows a typical Group Level View Dashboard with a sensor map, sensor list, and trend chart. Also, SCOUT Cloud delivers email or text alerts to users when sensor levels fall above or below user-defined thresholds. This allows detection of unexpected condition changes before they become problems by users anywhere in the world.

Enabling predictive maintenance

SensoNODE sensors and SCOUT software present new opportunities for IIoT solutions in any part of the power industry involving monitoring of rotary machinery and continuous running manufacturing equipment, especially where conditions of monitoring the asset condition can pose safety hazards to the user. Some type of rotary machinery is used in almost every manufacturing plant, and the moving parts can make the monitoring of these assets potentially dangerous. Such assets typically require a full shutdown for maintenance or monitoring.

Uptime of continuous manufacturing processes is critical to avoiding costs associated with unplanned maintenance and lost revenue. Any single issue can halt production, causing delays in getting end products to customers. SensoNODE and SCOUT solutions monitor continuous processes and alerts users when immediate actions are required to avoid potential issues and to keep operations running. As a predictive maintenance tool, it not only helps to increase throughput, but also maintain highest quality.

The wireless solution of SensoNODE sensors and SCOUT software allows workers to monitor assets and diagnose issues at a distance (Mobile) or remotely (Cloud), without having to enter any potentially dangerous situation. This not only ensures their safety, but also minimizes unnecessary shutdowns that would halt production. These processes and equipment areas can be difficult to monitor with traditional means and, without a shutdown, can put staff in potentially dangerous situations. Industries such as metal and aluminum foundries, steel plants, power generation, pulp & paper, material handling, and injection molding present just a few of many potential markets.

Saving costs and downtime

Minimizing maintenance costs and downtime is especially critical in the power generation market given pressures to remain competitive with respect to dispatch.

Assets must be well-maintained to maximize availability. Prime examples of process-critical assets in power generation are gas and steam turbines.

Monitoring of multiple state conditions of asset levels allows operators detect and diagnose problems or damage to turbines before they become major issues.

Figure 3. SensoNODE Gold Sensor/Scout Cloud Software


Turbines that aren’t well lubricated or cooled with clean oil are subject to overheating. Monitoring for drastic changes of a system’s temperature can help operators identify when filters and/or oil in the turbine may need to be replaced. Such changes can take place in a plant’s hydraulic lift oil pump, hydraulic power unit, or diverter camper controls.


Changes in a system’s pressure can also indicate turbine issues, and they can happen within several sections of a plant, including hydraulic lift oil pumps, hydraulic power units, hydraulic cylinders, diverter damper controls, and nitrogen generators. Increased fuel consumption and/or reduced output could be telltale signs of a more serious problem, such as compromised integrity of rotary components within the turbine and structural damage.

Such issues can lead to displacement or damage to toothed gears, blade damage or fatigue failures, and other structural damage that will ultimately impact a system’s performance.


Power generation plants can operate in some very harsh conditions, including inclement weather, high winds, and constant motion. Increased humidity levels translate to excessive moisture posing threats to a turbine’s gearbox, leading to corrosion, reduced efficiency, and ultimately breakdown.

SensoNODE humidity sensors are ideally suited for monitoring ambient relative humidity over the full 0-100% range.

Humidity and pressure monitoring is also critical for a plant’s nitrogen generators to ensure that a “dry lay-up” condition for heat recovery steam generators can be maintained.

During layup of heat recovery steam generators, nitrogen from a plant’s nitrogen generator is applied to prevent the onset of corrosion in the boiler tubes. Blanketing the tubes that have been exposed to moisture with nitrogen displaces oxygen and prevents tube corrosion.

Accurate diagnostics are vital in maintaining process critical assets throughout initial commissioning to operation and refurbishment.

Condition monitoring and predictive maintenance solutions rooted in the IIoT is allows power plants coordinate downtime rather than reacting to unscheduled outages, improving efficiencies and lowering maintenance costs.

Wireless sensors allow plants to avoid dangerous situations and locations while preserving plants and component life.

Tad Orstad is Applications Engineer, SensoControl, and Mario A. Calvo is Business Unit Manager, both at Parker Hannifin Corporation. www.parker.com