Skip to main content
Glama
LGDiMaggio

Predictive Maintenance MCP Server

by LGDiMaggio

calculate_bearing_characteristic_frequencies

Calculate bearing characteristic frequencies (BPFO, BPFI, BSF, FTF) from geometry and RPM to identify potential faults.

Instructions

    Calculate bearing characteristic frequencies from geometry.

    Standard rolling-element kinematic formulas (Randall & Antoni 2011,
    "Rolling element bearing diagnostics — A tutorial", MSSP 25(2)).
    Requires the EXACT geometry — from the manual, the catalog
    (search_bearing_catalog), or the user; never guessed. Deep-groove
    ball bearings have contact_angle_deg = 0.

    Args:
        num_balls: Number of rolling elements (Z)
        ball_diameter_mm: Ball/roller diameter (Bd) in mm
        pitch_diameter_mm: Pitch circle diameter (Pd) in mm
        contact_angle_deg: Contact angle (alpha) in degrees
        rpm: Shaft rotation speed in RPM
        ctx: MCP context

    Returns:
        Dictionary with BPFO, BPFI, BSF, FTF in Hz.

    Example:
        >>> # 6205 geometry (CWRU Bearing Data Center) at 1797 RPM
        >>> freqs = calculate_bearing_characteristic_frequencies(
        ...     num_balls=9, ball_diameter_mm=7.94,
        ...     pitch_diameter_mm=39.04, rpm=1797
        ... )
        >>> round(freqs['BPFO'], 2)
        107.36
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rpmNo
num_ballsYes
ball_diameter_mmYes
contact_angle_degNo
pitch_diameter_mmYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description carries full burden. Discloses use of standard formulas and requirement for exact geometry. Does not mention input validation or error handling, but for a pure calculation tool the key transparency is the formula source, which is provided.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Well-structured with description, Args, Returns, and Example sections. Some redundancy between introductory sentence and Args section (e.g., repeating parameter names). Example adds value. Could be slightly more concise but overall effective.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 5 parameters, no enums, and an output schema (dictionary with BPFO etc.), the description is complete. Includes example with realistic values, formula source, and instructions for obtaining geometry. No missing pieces for a calculation tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, but description compensates fully. Explains each parameter with symbols: num_balls (Z), ball_diameter_mm (Bd), pitch_diameter_mm (Pd), contact_angle_deg (alpha), rpm. Notes default for contact_angle and explains that deep-groove ball bearings use 0. The example further clarifies usage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states the tool calculates bearing characteristic frequencies from geometry using standard formulas. It names the outputs (BPFO, BPFI, BSF, FTF) and distinguishes from siblings like compute_power_spectral_density by being a specific geometric calculation. The reference to Randall & Antoni 2011 adds clarity.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides strong guidance: requires exact geometry from manual or catalog, never guessed. Also notes contact_angle_deg = 0 for deep-groove ball bearings. However, it does not explicitly compare with alternatives like check_bearing_faults or when not to use this tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/LGDiMaggio/predictive-maintenance-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server