Increased Temperature 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 the temperature increase in a faulty connection. As equipment ages, faulty electrical connections in low/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 generally annual and typically utilize a combination of an infrared thermal imaging camera and a thermal window.
However, although this is an evolutionary step compared to Reactive Maintenance, there continues to be a very significant “performance gap” between the 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 employs data science and predictive analytics to forecast potential failures and defects. The goal is to schedule maintenance when it is most practical and cost-effective, maximizing equipment lifespan while preventing equipment damage and limiting personnel contact with compromised assets.
The basic structure of a predictive maintenance solution typically consists of several components: a decision support system (DSS) or platform with data collection, storage, and processing; asset health assessment; forecasting; 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 failures 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 aid of a computerized maintenance management system, also known as CMMS software, to prevent machine downtime and increase the lifespan of assets.
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 preventive maintenance policy.
Difference between Preventive and Predictive Maintenance
The difference between preventive and predictive maintenance is that preventive maintenance is routine maintenance or inspection, 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 increasing safety by removing people from hazardous areas and extending the asset's lifespan.
Although factual, the critical issues that create this performance gap are often not fully explained or understood.
They include:
- Workers remain exposed to risks;
- Annual thermography represents an inspection of less than 1% of operational time, leaving 99% dependent on luck;
- The timing of the inspection often does not reflect the most critical operational electrical loads;
- The measurement depends on the equipment and operator's ability to correlate with the true internal temperature (therefore, it will never be of uniform quality);
- The data remains independent and not integrated, instead of being dynamically integrated;
- Infrared transmission rates through a "thermal window" can deteriorate significantly over time, affecting the accuracy of temperature readings.
Manufacturers of thermal imaging cameras state that two requirements are essential for 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 variable and deteriorating levels of infrared transmission, therefore not meeting this requirement).
The second requirement is that the conductor being thermally photographed operates at a minimum load of 40% of its designed load. For example, a circuit designed for 3kA should operate at a minimum of 1.5kA during an inspection. This is rarely observed by those performing thermal inspections of electrical equipment and is not known to most equipment owners/operators.
The gap in maintenance performance
Fortunately, there is now a way to reduce this “performance gap” and improve protection by continuously monitoring and analyzing temperature data, not only identifying but proactively predicting problems arising from faulty connections. Innovative, intelligent software, such as 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 problems identified above and fills the performance gap, providing greater 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 condition data 24/7, with internet connectivity for subsequent analysis and real-time identification of fault conditions. This allows for more efficient maintenance practices, enabling considerable benefits over the equipment's lifespan, which can be delivered as part of IIoT/digitalization of critical electrical infrastructure. These IIoT benefits include:
- Elimination of unnecessary inspections and their associated costs;
- Reducing preventive maintenance to comply with the equipment manual "as required";
- Reducing downtime costs associated with periodic inspection/maintenance;
- Reducing repair/spare parts costs and associated downtime through earlier detection of failure symptoms;
- Increased safety by removing people from hazardous locations;
- Identifying equipment with the best performance for future procurement decisions;
- Cost savings in operating expenses (OPEX) due to reduced ongoing inspection/maintenance costs.
This accelerated shift from inspection to continuous asset monitoring is necessary as a growing number of global companies adopt digitization strategies in the pursuit of greater competitiveness in this new digital world.
Modernizing electrical infrastructure to include innovative technologies, such as 24/7 real-time intelligent monitoring, will increase the safety, performance, and lifespan of electrical infrastructure through predictive analytics. No matter the 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 most opportune time to install predictive monitoring sensors is during scheduled maintenance shutdowns, thus updating the equipment and enabling the full realization of the benefits of predictive maintenance through Intelligent IIoT, effectively closing the "performance gap" that exists with preventive maintenance.
Modernize your electrical infrastructure with the Bridgemeter® from Above-Net. Schedule a consultation today and optimize your equipment with our cutting-edge predictive monitoring
With information from: Exertherm
