Signal Nonstationary Degree Evaluation Method Based on Moving Statistics Theory
Nonstationary signal refers to the signal whose statistics change with time, and its nonstationary degree evaluation can provide effective support for the evaluation of the operating state of the signal source. This paper introduced a variety of typical signal global and local nonstationary degree e...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-01-01
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| Series: | Shock and Vibration |
| Online Access: | http://dx.doi.org/10.1155/2021/5562110 |
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| _version_ | 1832550915685482496 |
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| author | Haoxiang He Shitao Cheng Xiaofu Zhang |
| author_facet | Haoxiang He Shitao Cheng Xiaofu Zhang |
| author_sort | Haoxiang He |
| collection | DOAJ |
| description | Nonstationary signal refers to the signal whose statistics change with time, and its nonstationary degree evaluation can provide effective support for the evaluation of the operating state of the signal source. This paper introduced a variety of typical signal global and local nonstationary degree evaluation methods and compared the applicable scope of different evaluation methods. In view of the limitations of the existing evaluation methods in the scope of application, considering the influence of adjacent signal points, this paper proposed the concepts and calculation methods of the moving mean, moving standard deviation, moving variation coefficient, and moving Hurst exponent based on the theory of moving statistics. According to different nonstationary degree evaluation methods, three different fields of signals (sinusoidal signal, mechanical fault signal, and ECG signal) are analyzed. The results show that, compared with the existing nonstationary degree evaluation methods, the signal nonstationary degree evaluation method proposed in this paper can reveal the time-varying details of the nonstationary signals, with high precision and strong stability, and has unique advantages in nonstationary signal processing. |
| format | Article |
| id | doaj-art-7fd98acddbec4beb8d15b1cb3242bbbc |
| institution | Kabale University |
| issn | 1070-9622 1875-9203 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Shock and Vibration |
| spelling | doaj-art-7fd98acddbec4beb8d15b1cb3242bbbc2025-02-03T06:05:27ZengWileyShock and Vibration1070-96221875-92032021-01-01202110.1155/2021/55621105562110Signal Nonstationary Degree Evaluation Method Based on Moving Statistics TheoryHaoxiang He0Shitao Cheng1Xiaofu Zhang2Beijing Key Lab of Earthquake Engineering and Structural Retrofit, Beijing University of Technology, Beijing 100124, ChinaBeijing Key Lab of Earthquake Engineering and Structural Retrofit, Beijing University of Technology, Beijing 100124, ChinaChina Academy of Building Research, Beijing 100013, ChinaNonstationary signal refers to the signal whose statistics change with time, and its nonstationary degree evaluation can provide effective support for the evaluation of the operating state of the signal source. This paper introduced a variety of typical signal global and local nonstationary degree evaluation methods and compared the applicable scope of different evaluation methods. In view of the limitations of the existing evaluation methods in the scope of application, considering the influence of adjacent signal points, this paper proposed the concepts and calculation methods of the moving mean, moving standard deviation, moving variation coefficient, and moving Hurst exponent based on the theory of moving statistics. According to different nonstationary degree evaluation methods, three different fields of signals (sinusoidal signal, mechanical fault signal, and ECG signal) are analyzed. The results show that, compared with the existing nonstationary degree evaluation methods, the signal nonstationary degree evaluation method proposed in this paper can reveal the time-varying details of the nonstationary signals, with high precision and strong stability, and has unique advantages in nonstationary signal processing.http://dx.doi.org/10.1155/2021/5562110 |
| spellingShingle | Haoxiang He Shitao Cheng Xiaofu Zhang Signal Nonstationary Degree Evaluation Method Based on Moving Statistics Theory Shock and Vibration |
| title | Signal Nonstationary Degree Evaluation Method Based on Moving Statistics Theory |
| title_full | Signal Nonstationary Degree Evaluation Method Based on Moving Statistics Theory |
| title_fullStr | Signal Nonstationary Degree Evaluation Method Based on Moving Statistics Theory |
| title_full_unstemmed | Signal Nonstationary Degree Evaluation Method Based on Moving Statistics Theory |
| title_short | Signal Nonstationary Degree Evaluation Method Based on Moving Statistics Theory |
| title_sort | signal nonstationary degree evaluation method based on moving statistics theory |
| url | http://dx.doi.org/10.1155/2021/5562110 |
| work_keys_str_mv | AT haoxianghe signalnonstationarydegreeevaluationmethodbasedonmovingstatisticstheory AT shitaocheng signalnonstationarydegreeevaluationmethodbasedonmovingstatisticstheory AT xiaofuzhang signalnonstationarydegreeevaluationmethodbasedonmovingstatisticstheory |