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ERBESSD-INSTRUMENTS
Masters of Machine Health, Industry 4.0, Balancing, Vibration, Video Vibration Analysis & Wireless Sensor Technology
The Impact of Increased Mass on a Vibration Shaker Table's Calibration and Output Signal
Insights from Dr. M David Howard, CEO
Vibration shaker tables are essential tools for calibrating sensors, testing equipment, and simulating real-world vibrational environments. These tables generate controlled vibrations to ensure accuracy and reliability in various applications. However, when additional mass is applied to a shaker table, the system's dynamics are affected, leading to measurable changes in performance and output signals.
Effects of Increased Mass on the Shaker Table
Applying additional mass to a vibration shaker table influences several key parameters, including resonance frequency, amplitude response, and system stability.
Resonance Frequency Shift A shaker table operates within a defined frequency range, often targeting specific resonant frequencies for calibration. Increased mass lowers the natural frequency of the system, meaning the shaker table may struggle to achieve higher frequencies effectively. This shift can impact calibration accuracy, especially if the intended test frequencies exceed the modified system's capabilities.
Reduced Vibration Amplitude Additional mass alters the dynamic response of the shaker table, leading to a reduction in vibration amplitude at a given input force. This effect occurs due to the increased inertia resisting movement, requiring greater force to maintain the desired amplitude. If the shaker table’s actuator is not sufficiently powerful, it may not be able to compensate for the mass increase, limiting its effectiveness.
Higher Energy Demand The system requires more power to vibrate heavier loads, leading to increased energy consumption. In cases where the power supply or control system cannot meet these demands, output signal distortions or irregularities may occur. Over time, excessive energy demands can strain components, accelerating wear and reducing operational lifespan.
Possible Structural Concerns:
Excessive mass can push the shaker table beyond its design limits, potentially causing mechanical failure.
Overloading can stress joints, bearings, and support structures, increasing maintenance needs and reducing longevity.
Some shaker tables include weight limits, and exceeding them may compromise system integrity.
Impact on Output Signal Accuracy
The accuracy of a vibration shaker table’s output signal directly correlates to the system's ability to generate consistent vibrations. Increased mass can introduce signal distortions in several ways:
Nonlinear Response: Larger masses may induce nonlinear system behaviors, affecting signal fidelity and calibration precision.
Phase Shift: Changes in inertia can introduce phase lag in the output signal, impacting synchronization during calibration procedures.
Variability in Frequency Response: The shaker table may exhibit inconsistent amplitude across different frequencies, requiring adjustments to maintain calibration integrity.
Mitigating the Effects of Increased Mass
To counteract the negative effects of increased mass, operators can:
Use higher-capacity actuators capable of handling greater loads.
Adjust control system parameters to maintain consistent vibration amplitudes.
Implement damping mechanisms to stabilize excessive mass-induced vibrations.
Ensure proper weight distribution to minimize mechanical stress on the shaker table.
Conclusion
While vibration shaker tables are versatile calibration tools, applying additional mass influences their frequency response, energy efficiency, and structural integrity. Operators must consider these effects to maintain calibration accuracy and prevent system degradation. By implementing corrective measures, shaker tables can continue providing reliable calibration results despite increased mass loads, however in the field we often do not consider the necessary corrective measures nor consider the test mass used to calibrate the portable shaker tables we use as analysts and engineers.
Detection of a Critical Electrical Fault Using EI-Analytic & PHANTOM
📌 Project Context
In an automotive manufacturing plant based in Morocco, a critical production asset began to exhibit abnormal vibration behavior.
Key Context Elements:
• Client: International automotive manufacturer
• Location: Morocco
• Machine Type : 1000 T stamping machine
• Initial Issue: Unusual noise and suspected abnormal vibration
• Partner Involved: CBM Partners
• Intervention Date: May 16, 2025
• Project Lead: Abdelilah SERDI, CBM Consultant
• Objective: Identify the source of the anomaly through structured vibration monitoring The client aimed to detect potential faults early, without interrupting production or performing intrusive maintenance.
🧠 Technology Used
• 12 PHANTOM wireless sensors – Erbessd Instruments
• EI-Analytic cloud-based monitoring platform
• Monitoring based on continuous data acquisition.
• Alarm system configured according to machine-specific thresholds
⚠️ Symptom Detected After 12 Hours of Data Acquisition
Twelve hours after activating the PHANTOM sensors, the EI-Analytic platform triggered an automatic alarm indicating abnormal vibration behavior.
FFT Spectrum Characteristics:
• Clear, repeated peaks at 100 Hz, 200 Hz, and 300 Hz
• Frequencies perfectly aligned with multiples of the power supply frequency (50 Hz)
• No typical mechanical components present (e.g., imbalance, misalignment, gear mesh)
🔎 Diagnosis
✔ Likely fault origin:
– Phase imbalance
– Insulation defect
– PWM switching noise from the motor drive
✔ Detection was only possible through continuous vibration monitoring
📊 Observed Vibration Spectrum
📋 Recommended Actions (Pending Execution)
Perform motor current analysis (imbalances and harmonics)
Inspect electrical connections and grounding
Verify motor drive settings
Conduct insulation resistance testing
💰 Estimated Economic Impact
Thanks to early analysis:
• The fault was identified before failure
• A targeted intervention is being prepared
• An estimated €300,000 motor replacement cost was avoided
🏆 Client Benefits
✔ Continuous monitoring without halting operations
✔ Early detection of an invisible electrical fault
✔ Prevention of an unplanned shutdown
✔ €300,000 cost avoidance
✔ Full validation of predictive maintenance strategy
💬 Project Testimonial
“Thanks to the power of the EI-Analytics platform and PHANTOM sensors from Erbessd Instruments, we were able to trigger a reliable alert in less than 12 hours.
🔍 Further measurements later revealed signs of lubrication deficiency and a bearing defect, reinforcing the severity and confirming a mechanical degradation.
This is a concrete demonstration of the value predictive maintenance brings in a high-stakes industrial environment.”
— Abdelilah SERDI, CBM Consultant – CBM Partners
Erbessd Instruments Is Responding to Industry Trends
In late 2024, Erbessd Instruments proudly sponsored an industry-wide survey—The Landscape of Predictive Maintenance—to better understand how condition monitoring professionals are adapting to a rapidly evolving maintenance landscape. We partnered with Mobius Institute and Machine Instrumentation Group to reach more than 300 technicians, analysts, engineers, and maintenance leaders across sectors to uncover real-world challenges, technology adoption patterns, and future priorities. The results? Eye-opening—and incredibly motivating. Now, we're excited to share those insights with you. More than just a snapshot of the current state of predictive maintenance (PdM), this data is helping us fine-tune our innovations, enhance our support, and stay laser-focused on what matters most: your success.
Here’s how Erbessd Instruments is turning insight into action
Adoption Is Rising, but Maturity Varies
🔹 74% of respondents are pursuing or using predictive maintenance, yet only 23% feel their programs are advanced.
Why it matters:
- Analysts often operate with tools and systems in various stages of readiness. Without program maturity, data consistency and diagnostic accuracy suffer.
- Decision-makers must recognize that PdM success isn't binary—it's a gradual evolution. According to ResearchGate (2020), lack of maturity in PdM programs often results in misalignment between investment and outcome expectations.
How Erbessd Is Responding:
We’re committed to meeting customers wherever they are on the PdM journey. From plug-and-play sensor kits to enterprise-level vibration systems, our solutions are modular, scalable, and tailored to every maturity level.
Barriers to Industrial IoT Adoption:
🔹 “Vibration-based fault detection may not be reliable enough” was the #1 inhibitor reported.
🔹 Many also cited difficulties with deployment and integration, echoing the findings below that complexity presents a systemic challenge.
🔹 Pricing risk and lack of clear technical specs for non-experts rounded out the list of prevalent obstacles.
Why it matters:
-For Analysts: Reliability skepticism suggests past experiences with false positives or insufficient insights have left a mark. This concern is reinforced by findings in ResearchGate (2020), which highlight inconsistent sensor performance and limited diagnostic depth as common limitations in early implementations.
-For Decision-Makers: Investment decisions stall when the tech is perceived as immature or opaque—especially to non-technical stakeholders responsible for budget approval. ScienceDirect (2021) underscores that unclear ROI, integration hurdles, and limited internal buy-in are persistent inhibitors to full-scale adoption of condition-based maintenance.
How Erbessd Is Responding:
Erbessd’s hardware is built for the real world—designed, tested, and field-proven in demanding industrial environments to ensure reliability you can trust. We also bridge the gap for non-technical stakeholders with visual dashboards, automated reports, and intuitive alerts that simplify decision-making. And when it comes to integration, our systems are engineered to fit seamlessly into existing workflows, whether you're augmenting legacy equipment or building from the ground up.
Cost and Complexity Still Stand in the Way
🔹 61% cite implementation cost as a barrier
🔹 45% point to system complexity
Why it matters:
- For Analysts: Complex systems can be overwhelming, increasing the chances of misuse or underutilization. ResearchGate (2020) confirms that insufficient user training and system usability contribute directly to poor outcomes.
- For Decision-Makers: Financial justification can be difficult without immediate savings. According to ScienceDirect (2021), unclear ROI calculations often result in hesitation or abandonment of projects.
Learn more about the ROI of an effective Condition Monitoring Program
How Erbessd Is Responding:
We design with simplicity and ROI in mind. Our wireless sensors, cloud-based dashboards, and intuitive analytics platforms reduce both training overhead and capital expenditure. Likewise, with a constant customer-first approach, and a flat organizational structure, connection to leadership and support teams who are able to not only train and assist in implementation but also pivot and innovate quickly to meet unique needs, truly differentiates Erbessd Instruments in the market.
Reasons Behind the Results & How Erbessd is Overcoming the Obstacles
Organizational Culture and Change Aversion
Why it matters:
- For Analysts: Resistance at higher levels can undermine their work, regardless of technical accuracy.
- For Decision-Makers: ResearchGate (2020) highlights that management commitment is one of the most influential success factors in CBM implementation.
Data Overload and Skill Gaps
Why it matters:
- For Analysts: They become overwhelmed by “big data” without proper tools or training.
- For Decision-Makers: A shortage of skilled staff creates bottlenecks in data processing and decision cycles.
Integration and Interoperability Challenges
Why it matters:
- For Analysts: Disconnected systems require manual processes that are time-consuming and error-prone.
- For Decision-Makers: Integration issues delay ROI and increase the total cost of ownership.
Financial Constraints and ROI Uncertainty
Why it matters:
- For Analysts: Without funding, analysts lack the hardware and software needed for optimal performance.
- For Decision-Makers: ResearchGate (2020) notes that ROI is one of the most commonly misunderstood or neglected aspects of condition-based maintenance planning.
How Erbessd Is Responding:
Our condition monitoring sensors are built with user-friendliness in mind, offering fast setup and intuitive operation right out of the box. Our software enhances accessibility with clear dashboards, supervised AI-powered diagnostics, and automated reporting that simplifies complex data. With a global network of distributors, we provide localized support and minimize downtime wherever you are both physically and on your CBM journey. And from initial onboarding to advanced training, our team of experts is always available to ensure you're fully equipped for success.
Looking Ahead: Smarter Tools, Better Support
Condition monitoring is becoming more intelligent, and so are we. Responsible, supervised AI-based diagnostics, enhanced remote support, elevated security protocols to ensure data security, and proactive service models are helping analysts make more data-driven decisions they can feel confident in—and giving decision-makers the clarity they need to justify ongoing investment.
The Erbessd Commitment
The survey results make one thing clear: success in predictive maintenance isn’t just about tools—it’s about people, experience, and adaptability. At Erbessd Instruments, we’re future-focused and customer-obsessed. We build tech that works for you, not the other way around. Let’s shape the future of asset health—together.
--Megh Howard, Erbessd Instruments
📚 References
ScienceDirect. (2021). Overcoming Barriers to Condition Monitoring Adoption. Journal of Cleaner Production, 280, 124458. https://doi.org/10.1016/j.jclepro.2020.124458
García Márquez, F. P., Tobias, A. M., Pinar Pérez, J. M., & Papaelias, M. (2020). Condition-based maintenance implementation: A literature review. ResearchGate. https://www.researchgate.net/publication/347069076_Condition-based_maintenance_implementation_a_literature_review
Tech Tip: Mastering FFT in EI Analytic
Fast Fourier Transform (FFT) is a cornerstone of vibration analysis, converting time-domain signals into frequency-domain data to identify machinery issues like imbalance, misalignment, and bearing defects. EI Analytic enhances this process with user-friendly features that make pinpointing problems more intuitive.
Enhancing FFT Resolution
To achieve higher resolution in your FFT analysis, consider increasing the recording time of your vibration data. Longer recordings allow for more data points, resulting in finer frequency resolution and more detailed spectra. This is particularly useful when diagnosing complex machinery issues where subtle frequency components are critical.
Step-by-Step:
Access Recording Settings: In EI Analytic, navigate to your machine's settings and select the desired measurement point.
Adjust Recording Time: Increase the recording duration to capture more data. For example, extending from 3 seconds to 12 seconds can significantly enhance frequency resolution.
Analyze Enhanced FFT: With the longer recording, generate the FFT spectrum. You'll notice a more detailed frequency spectrum, aiding in the accurate identification of potential faults.
In Action:
Check out how we improved resolution from 20.19 CPM between 2 points with 3s recording to 5.05 CPM between 2 points: with a sample rate of 44100 s/s and a Recording Time of 96 seconds, we can achieve more than 2 million resolution points, Max frequency of 17 kHz or 1.3 million CPM, and 63 CPM between points. Read More Here
By optimizing your recording time, EI Analytic's FFT function becomes a more powerful tool in your predictive maintenance arsenal, enabling earlier detection and resolution of machinery issues.
Thanks for sharing, ERBESSD-INSTRUMENTS! 🙌