How trending data supercharges performance prediction

From the telecom, wireless, and CATV industries to power utilities, data centers, and government agencies, the reliance on electrical energy is increasingly vital to the viability of businesses and communities. Having an accurate and timely understanding of the health and potential shortcomings of battery installations is not only advantageous but necessary for uninterrupted functionality in our digital world.

Present status vs. predicted performance

With manual testing of battery installations being the default for decades, organizations had a tool for assessing the current status of battery health and ascertaining where batteries were in their projected lifespan. However manually made measurements only provide a snapshot of what already exists at a given point in time, and the value of the data it produces is compromised by a multitude of factors, not the least of which is inconsistency among the technicians implementing and analyzing the testing.

A snapshot in time alone is insufficient to prevent the kind of catastrophic financial and operational loss that accompanies battery failure at critical facilities; what is needed is prediction. And prediction requires continual, consistent collection of data that allows a reliable pattern to emerge—hence the introduction of trending data as a game changer in predicting the performance of battery installations.


Remote monitoring for trending data

Remote monitoring that is automated provides continual and consistent collection of data on multiple aspects of battery health including temperature, admittance, voltage, and charge. This is generally attained via a sensor or transponder attached to each cell or battery in a bank.

PBT’s remote battery monitoring system (BMS) has the additional capacity to monitor systems facility-wide in a comprehensive approach that includes generators, chargers/inverters and HVAC systems, as well as building monitoring.  The easily installed and highly adaptable system replaces the expensive and elaborate configuration of wires and proprietary control units with common CAT-5 (Ethernet) jumper cables that send the data collected by sensors to a small standards-based site control unit. From there it is relayed via LAN, WAN, or the Internet to the monitoring program.

The end result is a continual stream of data that can be mined for trends, allowing for accurate and valuable prediction of performance and proactive troubleshooting of potential issues.


The value of trending data for prediction

When it comes to performance prediction, trending data offers superior value because of the accuracy, consistency, and frequency with which it is collected.

Because trending data is obtained via automated remote monitoring instead of manual testing, there is no possibility of procedural error or mistakes in recording and reporting. The proper performance of a test is not left to the potentially varying methods of individual technicians who, however skilled, are not immune from simple clerical errors like transposing a number. 

Automated remote monitoring also ensures consistency of data as the sensors remain in place, reading the battery the same way each time testing is done. Beyond this, the sheer volume of data from continual testing provides real time information as well as historical perspective that can be analyzed to predict the readiness of any given battery or bank of batteries to perform when called upon—knowledge that gives organizations and agencies the ability to be proactive in maintaining the operational integrity of mission-critical systems and facilities. 

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The value of enterprise-class monitoring

Battery monitoring is essential to the operational integrity of businesses and organizations of all sizes, providing not only alarm notification but trending data that enables