{'fraction_non_alphanumeric': 0.017454545454545455, 'fraction_numerical': 0.002181818181818182, 'mean_word_length': 5.460093896713615, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Speed Dependency of the Induction Machine Phase Current Spectrum Under Fault Conditions

Induction machines are used in a wide range of industrial applications due to their simplicity, low costs and robustness. However, several fault mechanisms exist which can lead to machine failures. Many of these faults induce specific frequency components in the motor current spectrum and can thus be used for fault detection and classification.This work investigates the speed dependency of the phase current spectrum of an induction machine. Bearing faults and broken rotor bars are failure mechanisms that induce speed-dependent frequency components. For inverter-fed variable-speed induction machine drives, a constant operating point in terms of phase voltage and frequency can be maintained for different motor speeds. Thus, speed-dependent frequency components can be identified and examined.This technique is applied to steady-state measurements of an inverter-fed 400 V induction machine and it is shown that the identified speed-dependent frequency components can be attributed to different fault mechanisms in the machine. The classical MCSA (motor current signature analysis) approach is applied to the fifth and the seventh harmonic and their respective sidebands. This leads to a significant improvement in fault detection capability, especially for low slip frequencies.