{"id":12380,"date":"2025-07-02T11:27:36","date_gmt":"2025-07-02T08:27:36","guid":{"rendered":"https:\/\/www.razor-labs.com\/?p=12380"},"modified":"2025-08-08T13:43:55","modified_gmt":"2025-08-08T10:43:55","slug":"case-study-datamind-ai-detects-lubrication-fault-in-ventilation-fan","status":"publish","type":"post","link":"https:\/\/www.razor-labs.com\/es\/case-study-datamind-ai-detects-lubrication-fault-in-ventilation-fan\/","title":{"rendered":"Case Study: DataMind AI™ Detects Lubrication Fault in Ventilation Fan"},"content":{"rendered":"\t\t
Razor Labs deployed DataMind AI<\/a>\u2122 to monitor critical rotating equipment at a major coal mining site with underground operations – including a key ventilation fan essential for maintaining airflow and ensuring safe working conditions below ground.<\/p> In May 2025, DataMind AI<\/a>\u2122 detected rising bearing friction through multi-sensor analysis, pinpointing lubrication failure as the root cause. The system initially classified the trend as an Alarm and later escalated it to Critical as the condition worsened. Through multi-sensor analysis, the system helped isolate the mechanical root cause: a progressive rise in The site team confirmed that the fan\u2019s automated greasing system had malfunctioned – a jammed grease cartridge had prevented lubricant from reaching the bearings. This fault had gone undetected until DataMind AI<\/a>\u2122 flagged the trend. Based on these insights, the team manually re-greased the bearings and restored proper lubrication – Sensor Fusion Analytics allowed DataMind AI<\/a>\u2122 to distinguish real mechanical changes from operational noise. The fan operates in fluctuating conditions \u2013 flow, pressure, and motor load \u2013 which often mask early signs of mechanical deterioration.<\/p> By synchronizing vibration, tacho, and motor current signals, along with advanced vibration analysis using envelope demodulation algorithms, the system confidently isolated the degradation pattern and identified its mechanical origin.<\/p> Key insights included:<\/strong><\/p> Following manual greasing, the system recorded a clear reduction in bearing vibration. This validated the diagnosis and eliminated the need for premature bearing replacement. The team avoided unscheduled shutdown, extended component life, and restored safe ventilation – a mission-critical function in underground mining.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t This case demonstrates the unique value of DataMind AI<\/a>\u2122 in identifying hidden mechanical issues that standard inspections miss. By pinpointing the true root cause of friction-related degradation in the underground ventilation fan, the system enabled fast resolution and prevented costly disruption.<\/p>
friction levels leading to lubrication failure.<\/p>
preventing premature bearing wear, unplanned downtime, and potential airflow disruption.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
Fan flagged as Critical<\/i><\/h6>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
Detection & Diagnosis<\/h2>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
Operational mode filtering reduces noise from load and speed variations, enabling clear visibility of the <\/em>underlying deterioration trend.<\/em><\/h6>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
Envelope demodulation analysis<\/em><\/h6>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
Spectrum analysis of NDE bearing of the fan<\/em><\/h6>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
Resolution<\/h2>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
Conclusion<\/h2>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t