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Record W2075554123 · doi:10.1115/imece2002-32037

Dynamic Compensation of Cutting Forces Measured From the Spindle Integrated Force Sensor System

2002· article· en· W2075554123 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueDynamic Systems and Control · 2002
Typearticle
Languageen
FieldEngineering
TopicAdvanced machining processes and optimization
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsAccelerationKalman filterCompensation (psychology)Bandwidth (computing)SIGNAL (programming language)Contact forceSignal processingAcousticsEngineeringControl theory (sociology)Computer scienceElectronic engineeringPhysicsDigital signal processing

Abstract

fetched live from OpenAlex

This paper presents a dynamically compensated Spindle Integrated Force Sensor (SIFS) system to measure cutting forces. Piezo-electric force sensors are integrated to the stationary spindle housing. The structural dynamic model between the cutting forces acting on the tool tip and the measured forces at the spindle housing is identified. The system is first calibrated to compensate the influence of spindle run-out and unbalance at different speeds. Using both the cutting force and acceleration sensor signals measured at the spindle housing, a Kalman Filter is designed to filter the influence of structural modes on the force measurements. The frequency bandwidth of the proposed sensor system is expanded from 300 Hz to about 800 Hz with the proposed sensing and the signal processing method.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.833
Threshold uncertainty score0.443

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.006
GPT teacher head0.187
Teacher spread0.181 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it