How can high-frequency electrical faults in large-scale machines be reliably detected and analyzed?

Diagnosing fast, intermittent faults requires high-resolution, continuous data acquisition in the millisecond range. With ibaPDA, several thousand signals can be captured in parallel at high sampling rates via interfaces (e.g., to SIMATIC S7 systems). The combination of high temporal resolution and synchronous signal recording enables precise reconstruction of fault sequences. This allows even short-lived anomalies to be clearly identified.

How can fault diagnostics be efficiently performed in remote or hazardous industrial environments?

In demanding environments, remote analysis is essential to minimize risks to personnel and machines. By using ibaPDA in combination with locally installed hardware such as ibaDAQ or ibaMDAQ, data can be acquired directly at the machine and analyzed remotely. This significantly reduces the need for intervention in live electrical systems. At the same time, the time required for fault identification is considerably shortened.

How can component replacement be optimized through data-driven analysis?

Precise fault localization makes it possible to clearly identify defective or wear-prone components. With continuous data storage in ibaHD-Server, historical signal trends can be analyzed and deviations detected at an early stage. This eliminates the need for trial-and-error component replacement. As a result, material costs are reduced and maintenance efficiency is improved.

How can data-driven maintenance strategies increase plant availability?

By analyzing trends and gradual signal changes, maintenance activities can be planned based on actual condition. ibaPDA provides the necessary data foundation, while historical data stored in ibaHD-Server enables long-term analysis. This allows targeted monitoring of critical components and extends their service life. In practice, this leads to a significant reduction in unplanned downtime.

How can virtual signals and models be used for predictive fault detection?

Virtual signals enable the derivation of additional state variables from existing measurement data. Using the Expression Builder in ibaPDA, such models can be defined directly within the system and calculated in real time. This allows potential fault conditions to be detected early, before failures occur. It supports proactive maintenance and reduces the need for manual on-site troubleshooting.

Locating High-Speed Faults

The Project

Strong vibrations, dust, and temperatures exceeding 45 degrees Celsius: It’s no surprise that the working environment of Electric Rope Shovels is classed as severe.

These gigantic machines also perform hard labor. 2024, around 3,230 kilograms of gold and 22 million tons of copper were produced worldwide, with the shovels playing a crucial role as primary loading units. Therefore, the highest possible availability of the shovels is of utmost importance for mining companies. However, due to the extreme external conditions, component failures or electrical problems are difficult to avoid. This is where the iba system comes into play for monitoring machine controls.

Benefits

Rapid Fault Diagnosis: Faults can be identified in minutes and not hours/days – also remotely. The iba system is perfect for intermittent fault finding at exceptionally high speed.
Live Works Elimination (LWE): Live works can practically be eliminated due to remote connections to the iba system eliminating the need for personnel to connect to live equipment.
Parts Usage Reduction: Pinpoints exactly which part has failed or is failing. Eliminates the need to swap parts to isolate/identify the fault.
Optimized Maintenance Straregy: Provides accurate feedback on components where deterioration can be better tracked. This allows for possible life expectancy in some very expensive parts.
Operator Training Tool: By using the ability to have multiple control signals on a single page, the interaction between machine functions allows excellent viewing of operational cadence.
Self Diagnosing: iba’s expression builder and virtual signals create the ability to monitor components well before failures occurs. Also eliminates the need for highly skilled technicians to troubleshoot the machine.

Solution

With ibaPDA, the mining company acquires some 1,500 signals in high resolution every 20 milliseconds via the S7-Xplorer interface, along with 26 analog values with a time base of one millisecond. The iba software runs on ibaDAQ which is a standalone device installed directly on the machine. The signals are then recorded in ibaHD-Server. In addition to improved fault diagnosis and the avoidance of live work on the machine in question, the customer has been able to reduce component consumption and optimize maintenance strategies and operations. It is stated that a dramatic reduction in the electrical downtime of the machines was seen. The meantime between failures has increased by over 200 percent. Overall, the company has been able to reduce unplanned downtime with the iba system from 49 hours to 5 hours over the past six months. Due to the success, the customer plans to expand the use of iba to other machines and other mining sites worldwide.

The iba system was a game-changer for the customer in machine diagnostics. Issues that arise are now captured based on facts. No more guesswork.

Fritz Woller
System Engineer, iba Oceania

Used Functions

The following functions of the iba system are used in this application.

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Frequently Asked Questions (FAQ)

How can high-frequency electrical faults in large-scale machines be reliably detected and analyzed?: Diagnosing fast, intermittent faults requires high-resolution, continuous data acquisition in the millisecond range. With ibaPDA, several thousand signals can be captured in parallel at high sampling rates via interfaces (e.g., to SIMATIC S7 systems). The combination of high temporal resolution and synchronous signal recording enables precise reconstruction of fault sequences. This allows even short-lived anomalies to be clearly identified.
How can fault diagnostics be efficiently performed in remote or hazardous industrial environments?: In demanding environments, remote analysis is essential to minimize risks to personnel and machines. By using ibaPDA in combination with locally installed hardware such as ibaDAQ or ibaMDAQ, data can be acquired directly at the machine and analyzed remotely. This significantly reduces the need for intervention in live electrical systems. At the same time, the time required for fault identification is considerably shortened.
How can component replacement be optimized through data-driven analysis?: Precise fault localization makes it possible to clearly identify defective or wear-prone components. With continuous data storage in ibaHD-Server, historical signal trends can be analyzed and deviations detected at an early stage. This eliminates the need for trial-and-error component replacement. As a result, material costs are reduced and maintenance efficiency is improved.
How can data-driven maintenance strategies increase plant availability?: By analyzing trends and gradual signal changes, maintenance activities can be planned based on actual condition. ibaPDA provides the necessary data foundation, while historical data stored in ibaHD-Server enables long-term analysis. This allows targeted monitoring of critical components and extends their service life. In practice, this leads to a significant reduction in unplanned downtime.
How can virtual signals and models be used for predictive fault detection?: Virtual signals enable the derivation of additional state variables from existing measurement data. Using the Expression Builder in ibaPDA, such models can be defined directly within the system and calculated in real time. This allows potential fault conditions to be detected early, before failures occur. It supports proactive maintenance and reduces the need for manual on-site troubleshooting.