Analysis of vibration signals of aviation hydraulic pumps using improved threshold singular value and wavelet methods can provide valuable insights into pump performance and condition. Here is an overview of the analysis process: 1. Data Acquisition: Vibration data is collected from hydraulic pumps using suitable sensors or accelerometers. Ensure that the data acquisition system has sufficient sampling rate to capture the relevant frequency range of the vibration signal. 2. Preprocessing: Preprocessing the vibration signal to remove noise and artifacts that may interfere with the analysis. Techniques such as filtering, signal conditioning, and baseline correction can be applied to improve data quality. 3. Wavelet transform: apply wavelet transform to decompose the vibration signal into different frequency components. The wavelet transform is particularly useful for analyzing non-stationary signals, such as vibration signals, because it provides time-frequency localization. 4. Feature extraction: Extract relevant features from wavelet coefficients to capture the characteristics of vibration signals. These characteristics may include energy, entropy, kurtosis, crest factor, or any other statistical or time-frequency domain measurement indicative of pump condition. 90R100-KA-5-BB-80-S-3-S1-E-03-GBA-29-29-24 90R100KA5BB80S3S1E03GBA292924 90-R-100-KA-5-BB-80-S-3-F1-E-02-GBA-45-45-24 90R100KA5BB80S3F1E02GBA454524 90R100-KA-5-BB-80-S-3-F1-E-02-GBA-45-45-24 90R100KA5BB80S3F1E02GBA454524 90-R-100-KA-5-BB-80-S-3-C7-E-03-GBA-35-35-20 90R100KA5BB80S3C7E03GBA353520 90-R-100-KA-5-BB-80-P-3-S1-F-03-GBA-42-42-24 90R100KA5BB80P3S1F03GBA424224 90R100-KA-5-BB-80-P-3-S1-F-03-GBA-42-42-24 90R100KA5BB80P3S1F03GBA424224 90-R-100-KA-5-BB-80-P-3-C7-E-03-GBA-42-42-24 90R100KA5BB80P3C7E03GBA424224 90R100-KA-5-BB-80-P-3-C7-E-03-GBA-42-42-24 90R100KA5BB80P3C7E03GBA424224 90-R-100-KA-5-BB-80-L-4-T2-E-03-GBA-32-32-24 90R100KA5BB80L4T2E03GBA323224 90R100-KA-5-BB-80-L-4-T2-E-03-GBA-32-32-24 90R100KA5BB80L4T2E03GBA323224 90-R-100-KA-5-BB-80-L-4-F1-E-03-GBA-35-35-24 90R100KA5BB80L4F1E03GBA353524 90R100-KA-5-BB-80-L-4-F1-E-03-GBA-35-35-24 90R100KA5BB80L4F1E03GBA353524 90-R-100-KA-5-BB-80-L-4-C7-F-03-GBA-35-35-24 90R100KA5BB80L4C7F03GBA353524 90R100-KA-5-BB-80-L-4-C7-F-03-GBA-35-35-24 90R100KA5BB80L4C7F03GBA353524 90-R-100-KA-5-BB-80-L-3-C7-F-03-GBA-35-35-24 90R100KA5BB80L3C7F03GBA353524 90R100-KA-5-BB-80-L-3-C7-F-03-GBA-35-35-24 90R100KA5BB80L3C7F03GBA353524 90-R-100-KA-5-BB-80-L-3-C7-E-03-GBA-42-42-26 90R100KA5BB80L3C7E03GBA424226 90R100-KA-5-BB-80-L-3-C7-E-03-GBA-42-42-26 90R100KA5BB80L3C7E03GBA424226 90-R-100-KA-5-BB-80-L-3-C7-E-03-GBA-42-42-24 90R100KA5BB80L3C7E03GBA424224 90R100-KA-5-BB-80-L-3-C7-E-03-GBA-42-42-24 90R100KA5BB80L3C7E03GBA424224 5. Improved threshold singular value (ITSV) algorithm: ITSVA is an enhancement of the traditional singular value decomposition (SVD) method. It is used to denoise wavelet coefficients by thresholding singular values. ITSVA adaptively determines the threshold according to the distribution of singular values, effectively separating the signal from the noise. 6. Denoising: Apply ITSVA to wavelet coefficients to remove noise components. Thresholding removes coefficients associated with noise or unwanted vibrations, enhancing visibility of relevant signal components. 7. Reconstruction: Reconstruct the denoised wavelet coefficients to obtain the vibration signal after time domain denoising. The reconstructed signal represents a clean vibration signal with reduced noise disturbances. 8. Feature analysis: further analyze the denoised vibration signal to extract additional features or patterns. This can include time domain analysis, frequency domain analysis, statistical analysis or pattern recognition techniques to identify specific fault characteristics or anomalies in pump operation. 9. Condition monitoring: compare the features extracted from the denoised vibration signal with the preset threshold or reference value. This allows for condition monitoring and detection of potential failures, anomalies or degradation in hydraulic pumps. 10. Interpretation and Decision Making: Interpret analysis results and make informed decisions based on identified failure modes or deviations from normal behavior. This may involve taking corrective action, scheduling maintenance, or conducting further investigation if necessary. 90-R-100-KA-5-BB-80-L-3-C7-E-03-GBA-29-29-24 90R100KA5BB80L3C7E03GBA292924 90R100-KA-5-BB-80-L-3-C7-E-03-GBA-29-29-24 90R100KA5BB80L3C7E03GBA292924 90-R-100-KA-5-BB-60-S-4-C7-E-03-GBA-42-42-24 90R100KA5BB60S4C7E03GBA424224 90R100-KA-5-BB-60-S-4-C7-E-03-GBA-42-42-24 90R100KA5BB60S4C7E03GBA424224 90-R-100-KA-5-BB-60-S-3-T2-E-03-GBA-26-26-24 90R100KA5BB60S3T2E03GBA262624 90R100-KA-5-BB-60-S-3-T2-E-03-GBA-26-26-24 90R100KA5BB60S3T2E03GBA262624 90-R-100-KA-5-BB-60-S-3-S1-F-03-GBA-42-42-24 90R100KA5BB60S3S1F03GBA424224 90R100-KA-5-BB-60-S-3-S1-F-03-GBA-42-42-24 90R100KA5BB60S3S1F03GBA424224 90-R-100-KA-5-BB-60-S-3-S1-E-03-GBA-30-30-24 90R100KA5BB60S3S1E03GBA303024 90R100-KA-5-BB-60-S-3-S1-E-03-GBA-30-30-24 90R100KA5BB60S3S1E03GBA303024 90-R-100-KA-5-BB-60-R-3-C7-F-03-GBA-26-26-24 90R100KA5BB60R3C7F03GBA262624 90R100-KA-5-BB-60-R-3-C7-F-03-GBA-26-26-24 90R100KA5BB60R3C7F03GBA262624 90-R-100-KA-5-BB-60-P-4-C6-F-03-GBA-26-26-24 90R100KA5BB60P4C6F03GBA262624 90R100-KA-5-BB-60-P-4-C6-F-03-GBA-26-26-24 90R100KA5BB60P4C6F03GBA262624 90-R-100-KA-5-BB-60-L-3-T2-E-03-GBA-35-35-24 90R100KA5BB60L3T2E03GBA353524 90-R-100-KA-5-AB-80-S-7-C7-F-00-FAC-35-35-30 90R100KA5AB80S7C7F00FAC353530 90R100-KA-5-AB-80-S-7-C7-F-00-FAC-35-35-30 90R100KA5AB80S7C7F00FAC353530 90-R-100-KA-5-AB-80-S-4-S1-E-03-GBA-40-40-24 90R100KA5AB80S4S1E03GBA404024 90R100-KA-5-AB-80-S-4-S1-E-03-GBA-40-40-24 90R100KA5AB80S4S1E03GBA404024 90-R-100-KA-5-AB-80-S-4-C7-E-03-GBA-42-42-24 90R100KA5AB80S4C7E03GBA424224 11. Fault Diagnosis: Utilize established fault diagnosis techniques to interpret analyzed vibration signals and identify specific pump faults or anomalies. This may involve comparing extracted features to known failure modes, or using machine learning algorithms for automated failure classification. By correlating vibration characteristics to specific pump faults such as worn bearings, misalignment or damaged impellers, appropriate maintenance actions can be taken. 12. Trend Analysis: Monitor the vibration signal over time to observe any trend or change in pump status. Analyze extracted features and track their values or trends to identify degradation or potential failure modes. Trend analysis provides valuable information for predictive maintenance, allowing proactive intervention before serious damage occurs. 13. Comparative analysis: Comparative analysis is carried out by analyzing the vibration signals of multiple hydraulic pumps of the same model or under similar working conditions. By comparing the vibration characteristics of different pumps, it is possible to establish a baseline pattern and identify deviations that indicate abnormal behavior. This approach increases the accuracy of fault diagnosis and helps differentiate between normal variations and actual pump failures. 14. Integrate with other parameters: Consider integrating vibration analysis with other parameters such as temperature, pressure, and flow rate. By combining multiple data sources, a more complete picture of the condition of the pump can be obtained. Correlations between vibration patterns and changes in other parameters provide greater insight into the root cause of pump anomalies. 15. Continuous monitoring: Implement a continuous monitoring system to collect vibration data in real time or periodically. Continuous monitoring can detect changes in vibration signals in time and help make decisions quickly. Automatic monitoring systems can provide alerts or alerts when vibration levels exceed predefined thresholds or detect unusual patterns. 90R100-KA-5-AB-80-S-4-C7-E-03-GBA-42-42-24 90R100KA5AB80S4C7E03GBA424224 90-R-100-KA-5-AB-80-S-4-C7-E-03-GBA-35-35-24 90R100KA5AB80S4C7E03GBA353524 90R100-KA-5-AB-80-S-4-C7-E-03-GBA-35-35-24 90R100KA5AB80S4C7E03GBA353524 90-R-100-KA-5-AB-80-S-4-C7-E-03-GBA-26-26-24 90R100KA5AB80S4C7E03GBA262624 90R100-KA-5-AB-80-S-4-C7-E-03-GBA-26-26-24 90R100KA5AB80S4C7E03GBA262624 90-R-100-KA-5-AB-80-S-3-S1-E-03-GBA-40-40-26 90R100KA5AB80S3S1E03GBA404026 90R100-KA-5-AB-80-S-3-S1-E-03-GBA-40-40-26 90R100KA5AB80S3S1E03GBA404026 90-R-100-KA-5-AB-80-S-3-S1-E-03-GBA-35-35-24 90R100KA5AB80S3S1E03GBA353524 90R100-KA-5-AB-80-S-3-S1-E-03-GBA-35-35-24 90R100KA5AB80S3S1E03GBA353524 90-R-100-KA-5-AB-80-S-3-C7-F-03-GBA-42-42-24 90R100KA5AB80S3C7F03GBA424224 90R100-KA-5-AB-80-S-3-C7-F-03-GBA-42-42-24 90R100KA5AB80S3C7F03GBA424224 90-R-100-KA-5-AB-80-S-3-C7-F-03-GBA-38-38-26 90R100KA5AB80S3C7F03GBA383826 90R100-KA-5-AB-80-S-3-C7-F-03-GBA-38-38-26 90R100KA5AB80S3C7F03GBA383826 90-R-100-KA-5-AB-80-S-3-C7-E-03-GBA-42-42-24 90R100KA5AB80S3C7E03GBA424224 90R100-KA-5-AB-80-S-3-C7-E-03-GBA-42-42-24 90R100KA5AB80S3C7E03GBA424224 90-R-100-KA-5-AB-80-R-4-S1-F-03-GBA-38-38-24 90R100KA5AB80R4S1F03GBA383824 90-R-100-KA-5-AB-80-R-3-F1-F-03-GBA-20-20-24 90R100KA5AB80R3F1F03GBA202024 90R100-KA-5-AB-80-R-3-F1-F-03-GBA-20-20-24 90R100KA5AB80R3F1F03GBA202024 90-R-100-KA-5-AB-80-R-3-C7-E-03-GBA-35-35-24 90R100KA5AB80R3C7E03GBA353524 90R100-KA-5-AB-80-R-3-C7-E-03-GBA-35-35-24 90R100KA5AB80R3C7E03GBA353524 16. Maintenance plan: use analysis results to optimize maintenance plan and scheduling. By assessing the severity and urgency of identified faults or anomalies, maintenance activities can be prioritized and planned accordingly. This helps minimize downtime, lower costs and improve overall pump reliability. 17. Documentation and record keeping: Maintain comprehensive records of analysis results, including raw data, processed data, extracted features, and diagnostic results. Proper documentation enables historical analysis, trend tracking, and knowledge sharing among maintenance teams. It can also serve as a valuable resource for future reference and analysis. 18. Verification and Validation: Verify the accuracy and validity of the vibration analysis by comparing the results of the analysis with the actual pump conditions observed through visual inspection, testing, or disassembly. This ensures the reliability of the analytical technique and provides confidence in the diagnostic results. Analysis of vibration signals using improved threshold singular value and wavelet methods can be enhanced by considering these additional points. The combination of advanced signal processing techniques, fault diagnosis methods and continuous monitoring can help to make effective maintenance decisions and improve the overall performance and reliability of aviation hydraulic pump systems.