Grinding Machine State Detection Using Difference Sound Spectra
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Solution Overview
Problem
Conventional grinding machines require trained personnel to set up and monitor their operating states, which is time-consuming and prone to errors, as they rely on manual selection of frequency bands for evaluating structure-borne sound signals.
Innovation Solution
A machine tool with a measuring device equipped with structure-borne sound sensors that form a broadband difference spectrum between a reference and actual spectrum, allowing the control device to evaluate the power over time, enabling autonomous determination of the machine's state without manual intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual selection of frequency bands is used for evaluating structure-borne sound signals, then the machine tool requires trained personnel for setup and monitoring, but this approach is time-consuming and prone to errors
Solution Approach 1:
The machine tool system performs self-diagnosis by automatically analyzing structure-borne sound signals to determine its own operational state. The control device compares measured vibration spectra with stored reference spectra and autonomously identifies states such as idle running, machining, tool wear, or faults without requiring external expert intervention.
Solution Approach 2:
The patent replaces manual expert assessment with automated signal processing and spectral analysis. The control device uses computational methods to evaluate vibration spectra, compare them against reference data, and determine machine states, substituting the need for trained personnel with an automated diagnostic system.
2Reliability
If trained personnel are used to monitor machine operating states, then accurate detection can be achieved, but the cost and complexity increase due to requirement for specialized knowledge
Solution Approach 1:
The system autonomously performs state determination by comparing measured vibration spectra with stored reference spectra. The control device automatically identifies machine states including idle running, machining operations, tool wear conditions, and faults without requiring trained personnel to interpret the data.
Solution Approach 2:
The system continuously monitors structure-borne sound signals, compares them against reference data, and provides real-time feedback about machine states. This closed-loop approach ensures reliable detection of operational conditions, tool wear, and faults while eliminating the need for manual expertise.
3Adaptability or versatility
If broadband spectrum analysis is used instead of selective frequency band monitoring, then comprehensive machine state information can be obtained, but the data processing complexity increases
Solution Approach 1:
Reference spectra are stored in advance for different machine states (idle running, machining, tool wear, faults). During operation, the control device simply compares the current measured spectrum against these pre-stored references, eliminating the need for complex real-time analysis while maintaining comprehensive monitoring capability.
Solution Approach 2:
The system creates spectral copies of reference states and stores them for comparison. Instead of performing complex real-time analysis of broadband signals, the control device matches the current spectrum against stored spectral templates, simplifying the processing while maintaining versatility in detecting various operating conditions.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach reduces the need for trained personnel, allows for faster and more precise detection of machine states, and enables the machine to independently determine its operating conditions, improving setup efficiency and reducing the risk of human error.
Implementation Method 1
the sensor device arranged on the spindle housing, which has at least one structure-borne sound sensor which is designed to detect structure-borne sound waves or vibrations occurring during grinding operations
Data Source
Figure 1
Figure 2a~2b
Figure 3a~5
AI summary
The subject of the disclosure is a machine tool (10), in particular a grinding machine, comprising a measuring device (38) which is received on the machine tool (10), said measuring device (38) having at least one structure-borne sound sensor (36), and further comprising a control device (40) which is couplable to the measuring device (38) and a tool unit (22), the control device (40) being configured to sense structure-borne sound signals caused by the machine tool (10) by means of the measuring device (38) and to determine a state variable, describing an actual state of the machine tool (10), by forming a difference spectrum (56) from a broadband reference spectrum (50) and a broadband actual spectrum (54). The disclosure also relates to a method for determining an actual state of a machine tool (10).