Temperature Rise as a Common Cause of Power Outages
One of the most common reasons for power outages and a primary cause of arc flash incidents is increased temperature at a faulty connection. As equipment ages, faulty electrical connections in low- and medium-voltage equipment can increase—studies show that poorly maintained equipment is 62% more likely to fail.
Until recently, the accepted "best practice," or the only one that increases equipment reliability, has been a preventive maintenance program in the form of periodic thermal imaging inspections. These are typically annual and typically utilize a combination of an infrared thermal imaging camera and a thermal window.
However, while this is an evolutionary step forward from Reactive Maintenance, there remains a very significant “performance gap” between perceived levels of protection compared to the actual level of risk mitigation achieved from a Preventive Maintenance approach.
Predictive Maintenance
Predictive Maintenance (PdM) is the application of proactive, data-driven maintenance techniques designed to assess the condition of equipment to determine when repairs should be performed.
To plan corrective maintenance before an electrical asset fails, predictive maintenance software uses data science and predictive analytics to predict potential failures and defects. The goal is to schedule maintenance when it is most practical and cost-effective, maximizing equipment lifespan while preventing equipment from becoming compromised and limiting personnel contact with compromised assets.
The basic structure of a predictive maintenance solution typically consists of several components, a decision support system or platform (or DSS) with data collection, storage and processing, asset health assessment, prognostics and condition monitoring.
Preventive maintenance
Preventive Maintenance (PM) is a form of maintenance that regularly checks equipment and other assets to reduce the risk of failure and optimize working conditions.
This proactive maintenance strategy is time-based, also known as strategic maintenance, and includes planned maintenance that can be annual, quarterly, or monthly to streamline planning and implementation. This is typically organized with the help of a computerized maintenance management system, also known as CMMS software, to avoid machine downtime and extend asset life.
Operating an asset until it breaks down can cost a company up to ten times more in repairs and lost productivity than it would cost a company with a planned preventative maintenance policy.
Difference between Preventive and Predictive Maintenance
The difference between preventive and predictive maintenance is that preventive maintenance is routine maintenance or inspections scheduled at regular intervals, regardless of the equipment's condition. This often results in unnecessary costs, while predictive maintenance is only scheduled as needed, based on the asset's real-time condition. Predictive maintenance, therefore, reduces labor costs and operational downtime, while also increasing safety by removing personnel from hazardous locations and extending the asset's useful life.
While factual, the critical issues that create this performance gap situation are often not fully explained or understood.
They include:
- Workers continue to be exposed to risks;
- Annual thermography represents an inspection of less than 1% of operational time, leaving 99% dependent on luck;
- The timing of inspection often does not reflect the most critical operational electrical loads;
- The measurement depends on the skills of the equipment and the operator to correlate with the true internal temperature (therefore it will never be of uniform quality);
- Data remains independent and unintegrated, rather than dynamically integrated information;
- Infrared transmission rates through a thermal window can deteriorate significantly over time, affecting the accuracy of temperature readings.
Thermal imaging camera manufacturers say two requirements are essential to obtaining accurate temperature data when performing a thermal inspection of electrical equipment.
The first is that the camera must have a direct line of sight to the driver being inspected (thermal windows have varying and deteriorating levels of infrared transmission, thus not satisfying this requirement).
The second requirement is that the conductor being thermally imaged must operate at a minimum load of 40% of its design load. For example, a circuit designed for 3kA must operate at a minimum of 1.5kA during an inspection. This is rarely observed by those performing thermal inspections of electrical equipment and is unknown to most equipment owners/operators.
The maintenance performance gap
Fortunately, there's now a way to close this "performance gap" and improve protection by continuously monitoring and analyzing temperature data, not only identifying but also proactively predicting problems arising from faulty connections. Innovative, intelligent software like Bridgemeter® has evolved to provide the "next technological step" in Predictive Maintenance.
With 24×7 real-time monitoring, predictive analytics can detect approximately 70% more failure symptoms before failures actually occur than periodic inspection.
This is achieved through permanently installed temperature sensors specifically designed for thermal monitoring of electrical panels, MCCs and transformers.
Predictive technology using thermal sensors solves many of the critical issues identified above and bridges the performance gap, providing increased safety, more reliable operational uptime, and improved asset integrity.
The growing global demand for IoT devices and related products is also fueling the growth of industrial IoT, or IIoT, as it is known. This requires industrial equipment and machinery to have integrated condition monitoring sensors that acquire 24/7 condition data, with internet connectivity for subsequent analysis and real-time identification of fault conditions. This enables more efficient maintenance practices, enabling considerable benefits over the equipment's lifecycle, which can be delivered as part of the IIoT/digitization of critical electrical infrastructure. These IIoT benefits include:
- Elimination of unnecessary inspections and their associated costs;
- Reduction in preventive maintenance to comply with the equipment manual “as required”;
- Reduced downtime costs associated with periodic inspection/maintenance;
- Reduced repair/spare parts costs and associated downtime through greater early detection of failure symptoms;
- Increased safety by removing people from risky locations;
- Identification of equipment with better performance for future acquisition decisions;
- OPEX savings due to reduced ongoing periodic inspection/maintenance costs.
This accelerated shift from inspection to continuous asset monitoring is necessary as more global companies adopt digitalization strategies in their quest to become more competitive in this new digital world.
Modernizing your electrical infrastructure to include innovative technologies like 24/7 real-time smart monitoring will increase the safety, performance, and lifespan of your electrical infrastructure through predictive analytics. No matter what type of electrical installation you maintain, a continuous, digital monitoring approach will provide the most cost-effective and efficient way to ensure your electrical equipment is protected and operating at all times.
Finally, the best time to install predictive monitoring sensors is during scheduled maintenance shutdowns, thus updating equipment and enabling the full benefits of predictive maintenance through Intelligent IIoT, effectively closing the “performance gap” that exists with preventive maintenance.
Modernize your electrical infrastructure with Bridgemeter® from Above-Net. Schedule a consultation today and optimize your equipment with our cutting-edge predictive monitoring:
With information: Exertherm
