CN113804388A - Mechanical equipment rotation impact fault detection method and system based on time domain analysis - Google Patents
Mechanical equipment rotation impact fault detection method and system based on time domain analysis Download PDFInfo
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Abstract
The invention belongs to the field of mechanical equipment state monitoring and predictive maintenance, and discloses a mechanical equipment rotating impact fault detection method and system based on time domain analysis, wherein vibration time domain waveform data of mechanical equipment is divided according to a preset time interval to obtain a peak sequence; dividing the maximum value of the peak sequence by the mode of the peak sequence to obtain a comparison value, and when the comparison value is greater than a preset first threshold value, acquiring a suspected impact position sequence; otherwise, detecting as no fault; acquiring the number of elements in the suspected impact position sequence, wherein when the number of elements in the suspected impact position sequence is less than or equal to 1, the detection result is no fault; otherwise, acquiring a periodic impact interval, and detecting that a fault exists when the error between the periodic impact interval and the rotating shaft running period of the mechanical equipment is within a preset error; otherwise, no fault is detected. The method has more advantages for equipment running at low speed, and provides a stable and efficient method for detecting and diagnosing low-speed impact faults.
Description
Technical Field
The invention belongs to the field of mechanical equipment state monitoring and predictive maintenance, and relates to a mechanical equipment rotating impact fault detection method and system based on time domain analysis.
Background
Mechanical equipment operating under the low-speed heavy-load working condition is easy to break down due to the self attribute problem, and has the characteristics of weak vibration signal, low failure frequency, long impulse response period and the like after the failure due to the low operating rotating speed, so that the low-speed rotating machinery is difficult to detect the failure. Among the types of faults of low-speed rotating machines, the faults caused by rolling bearings or gears account for the most part, and these faults are highly dangerous and are the types of faults that need to be detected and diagnosed.
In the low-speed rotating machinery failure, one of the main key characteristics of the failure caused by the rolling bearing and the gear is the periodic impact vibration in the time domain. At present, a common method for identifying periodic impact is an envelope demodulation method, and the method is widely applied to fault diagnosis of bearings and gears and can accurately extract periodic impact components.
However, due to the characteristic of low-speed operation, the number of periodic impacts contained in the actually acquired vibration signal cannot be determined in advance, for some online monitoring scenes, the number of periodic impacts is small (less than 10) due to factors such as hardware acquisition limitation, and the envelope demodulation method is a frequency domain analysis method, and the periodic components identified by Fourier transform (FFT) need to be more accurate only when the number of periods is large (more than 10), so that the impact interval cannot be accurately extracted by using envelope demodulation in such a scene, and the fault diagnosis accuracy is low.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides a mechanical equipment rotation impact fault detection method and system based on time domain analysis.
In order to achieve the purpose, the invention adopts the following technical scheme to realize the purpose:
in a first aspect of the present invention, a method for detecting a rotational impact fault of a mechanical device based on time domain analysis includes the following steps:
acquiring original vibration time domain waveform data of mechanical equipment, and performing signal enhancement processing to obtain enhanced vibration time domain waveform data;
carrying out preset standardization processing on the enhanced vibration time domain waveform data to obtain vibration time domain waveform data;
dividing the vibration time domain waveform data according to a preset time interval to obtain a plurality of sub-vibration time domain waveform data, obtaining the maximum value of each sub-vibration time domain waveform data, and combining to obtain a peak value sequence;
obtaining a mode and a maximum value of the peak sequence, dividing the maximum value of the peak sequence by the mode of the peak sequence to obtain a comparison value, and obtaining subscripts corresponding to elements, of which the results of dividing the mode of the peak sequence are larger than or equal to a second threshold value, in the peak sequence when the comparison value is larger than a preset first threshold value to obtain a suspected impact position sequence; otherwise, the detection result is no fault;
acquiring the number of elements in the suspected impact position sequence, wherein when the number of elements in the suspected impact position sequence is less than or equal to 1, the detection result is no fault;
otherwise, obtaining a periodic impact interval according to the suspected impact position sequence, obtaining the rotating shaft running period of the mechanical equipment, and when the error between the periodic impact interval and the rotating shaft running period of the mechanical equipment is within a preset error, determining that a fault exists in the detection result; otherwise, the detection result is no fault.
The mechanical equipment rotation impact fault detection method based on time domain analysis is further improved as follows:
the specific method for acquiring the original vibration time domain waveform data of the mechanical equipment comprises the following steps:
the method comprises the steps of collecting original vibration signals of the mechanical equipment through a vibration sensor arranged on a preset part of the mechanical equipment, and obtaining original vibration time domain waveform data of the mechanical equipment according to the original vibration signals of the mechanical equipment.
The preset parts comprise a rolling bearing and/or a reduction gearbox gear, and the original vibration signal comprises a speed signal and/or an acceleration signal.
The specific method for performing signal enhancement processing comprises the following steps:
and squaring the original vibration time domain waveform data of the mechanical equipment.
The specific method for obtaining the vibration time domain waveform data by carrying out preset standardized processing on the enhanced vibration time domain waveform data comprises the following steps:
normalizing the enhanced vibration time-domain waveform data by:
wherein, amplitude _ vib _ arr is the enhanced vibration time domain waveform data, i is 0,1,2,3, … n-1, and amplitude _ vib _ arriThe data is ith vibration enhancement time domain waveform data, and n is the number of the vibration enhancement time domain waveform data; the amplitude _ vib _ arr is normalized enhanced vibration time domain waveform data;
and rounding the normalized enhanced vibration time domain waveform data and keeping one decimal to obtain the vibration time domain waveform data.
The preset time interval is 1/10-1/2 of the time of one week of operation of the mechanical equipment.
The first threshold value is more than or equal to 2, and the number of 1< the second threshold value < the first threshold value.
The specific method for obtaining the periodic impact interval according to the suspected impact position sequence comprises the following steps:
obtaining a differential sequence result of the suspected impact position sequence, and calculating a median of the differential sequence result;
the periodic shock interval shock is obtained bycycle：
shockcycle＝delta_T×idx_median
Wherein, delta _ T is a preset time interval, and idx _ mean is a median of the differential sequence result.
The preset error is 10%.
In a second aspect of the present invention, a mechanical device rotation impact fault detection system based on time domain analysis includes:
the acquisition module is used for acquiring original vibration time domain waveform data of the mechanical equipment and performing signal enhancement processing to obtain enhanced vibration time domain waveform data;
the preprocessing module is used for carrying out preset standardization processing on the enhanced vibration time domain waveform data to obtain vibration time domain waveform data;
the peak processing module is used for dividing the vibration time domain waveform data according to a preset time interval to obtain a plurality of sub-vibration time domain waveform data, obtaining the maximum value of each sub-vibration time domain waveform data and combining the sub-vibration time domain waveform data to obtain a peak sequence;
the first detection module is used for acquiring the mode and the maximum value of the peak sequence, dividing the maximum value of the peak sequence by the mode of the peak sequence to obtain a comparison value, and acquiring subscripts corresponding to elements, of which the results of dividing the mode of the peak sequence are larger than or equal to a second threshold value, in the peak sequence to obtain a suspected impact position sequence when the comparison value is larger than a preset first threshold value; otherwise, the detection result is no fault;
the second detection module is used for acquiring the number of elements in the suspected impact position sequence, and when the number of elements in the suspected impact position sequence is less than or equal to 1, the detection result is no fault;
otherwise, obtaining a periodic impact interval according to the suspected impact position sequence, obtaining the rotating shaft running period of the mechanical equipment, and when the error between the periodic impact interval and the rotating shaft running period of the mechanical equipment is within a preset error, determining that a fault exists in the detection result; otherwise, the detection result is no fault.
Compared with the prior art, the invention has the following beneficial effects:
the invention relates to a mechanical equipment rotation impact fault detection method based on time domain analysis, which realizes accurate detection of low-speed mechanical equipment fault detection, and comprises the steps of dividing signals through a preset time interval, carrying out first-step dispersion and carrying out second-step dispersion on the signals through preset standardized treatment by utilizing obvious impact characteristics expressed in vibration time domain waveform data and carrying out discretization analysis on the vibration time domain waveform data after impact amplification and enhancement; and extracting a suspected impact position sequence by judging the ratio of each discrete value to the whole mode in the vibration time domain waveform data, and finally realizing fault detection through the suspected impact position sequence. The method is based on time domain analysis and does not depend on frequency domain analysis, so that the method has universality in an application scene compared with the traditional envelope demodulation analysis and other methods, and the reason is that the vibration signals collected aiming at low-speed mechanical equipment are difficult to ensure to contain enough running periods (usually, impact periods) in the practical application scene, and the traditional frequency domain method finally needs to obtain periodic components through FFT (fast Fourier transform), so that the FFT is difficult to obtain effective and accurate results under the condition of insufficient period number according to a sampling principle. In conclusion, the mechanical equipment rotation impact fault detection method based on time domain analysis has stronger universality, particularly has more advantages aiming at a low-speed operation scene, and provides a stable and efficient method for impact fault detection and diagnosis of low-speed mechanical equipment.
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FIG. 1 is a flow chart of a mechanical equipment rotation impact fault detection method based on time domain analysis according to the present invention;
FIG. 2 is a graph of vibration acceleration data collected during a low speed device failure condition in accordance with the present invention;
FIG. 3 is a graph of envelope demodulated spectrum of vibration acceleration in the event of a low speed device failure in accordance with the present invention;
fig. 4 is a schematic diagram of a periodic impact interval extraction result based on time domain analysis under a certain low-speed device fault condition.
Detailed Description
In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
The invention is described in further detail below with reference to the accompanying drawings:
referring to fig. 1, in an embodiment of the present invention, a method for detecting a rotational impact fault of a mechanical device based on time domain analysis is provided, which is particularly suitable for a low-speed mechanical device. Then, the enhanced vibration time domain waveform data are subjected to normalized processing, and normalized data are provided for subsequent processing; after the normalization processing, the suspected impact position point is judged and extracted through time segmentation discretization processing and a statistical analysis method, and the suspected impact position point is used as a fault detection basis to determine a fault detection result.
S1: and acquiring original vibration time domain waveform data of the mechanical equipment, and performing signal enhancement processing to obtain enhanced vibration time domain waveform data.
Preferably, the specific method for acquiring the original vibration time domain waveform data of the mechanical device is as follows: the method comprises the steps of collecting original vibration signals of the mechanical equipment through a vibration sensor arranged on a preset part of the mechanical equipment, and obtaining original vibration time domain waveform data of the mechanical equipment according to the original vibration signals of the mechanical equipment.
Preferably, the preset parts comprise a rolling bearing and/or a reduction gearbox gear, and the original vibration signal comprises a speed signal and/or an acceleration signal.
Preferably, the specific method for performing signal enhancement processing includes: and squaring the original vibration time domain waveform data of the mechanical equipment so as to amplify the impact energy.
S2: and carrying out preset standardization processing on the enhanced vibration time domain waveform data to obtain vibration time domain waveform data.
Preferably, the normalization process includes two processes of normalization and precision consistency.
Preferably, the specific method for obtaining the vibration time domain waveform data by performing preset normalization processing on the enhanced vibration time domain waveform data is as follows:
normalizing the enhanced vibration time-domain waveform data by:
wherein, amplitude _ vib _ arr is the enhanced vibration time domain waveform data, i is 0,1,2,3, … n-1, and amplitude _ vib _ arriThe data is ith vibration enhancement time domain waveform data, and n is the number of the vibration enhancement time domain waveform data; the amplitude _ vib _ arr is normalized enhanced vibration time domain waveform data;
performing precision consistency processing on the normalized enhanced vibration time domain waveform data, specifically: and rounding the normalized enhanced vibration time domain waveform data and reserving one decimal number to provide convenience and consistency for subsequent processing to obtain the vibration time domain waveform data.
S3: dividing the vibration time domain waveform data according to a preset time interval to obtain a plurality of parts of sub-vibration time domain waveform data, obtaining the maximum value of each sub-vibration time domain waveform data, and combining to obtain a peak value sequence.
Preferably, the preset time interval delta _ T is determined according to the running speed of the mechanical equipment, and is 1/10-1/2 of the time of one week of the mechanical equipment. The smaller the preset time interval delta _ T, the higher the accuracy of the final estimated impact interval. And calculating the maximum value of each part of the sub-vibration time domain waveform data, and finally forming a peak value sequence by all the calculated maximum values.
S4: obtaining a mode and a maximum value of the peak sequence, dividing the maximum value of the peak sequence by the mode of the peak sequence to obtain a comparison value, and obtaining subscripts corresponding to elements, of which the results of dividing the mode of the peak sequence are larger than or equal to a second threshold value, in the peak sequence when the comparison value is larger than a preset first threshold value to obtain a suspected impact position sequence; otherwise, the analysis is directly finished, no suspected impact exists in the vibration time domain waveform data, and the detection result is no fault.
Wherein the subscript is associated with time, and the product of the subscript and the time interval is the length of time. In essence, the peak sequences are formed at certain time intervals, and the subscripts to some extent are the expression of time. For example: the [1, 2,3, 4] peak value sequence is obtained by taking 2 seconds as a time interval, and the actual corresponding time of the peak value sequence can be approximate to [ 0s, 2s, 4s, 6s ], namely the product value of the subscript value and the time interval corresponding to the peak value array.
Preferably, the first threshold is generally equal to or greater than 2, which indicates that the difference between the maximum value and the mode in the vibration time-domain waveform data is large, and the multiple is equal to or greater than 2. The second threshold needs to be lower than the first threshold, while it needs to satisfy more than 1, i.e. 1< second threshold < first threshold.
S5: acquiring the number of elements in the suspected impact position sequence, wherein when the number of elements in the suspected impact position sequence is less than or equal to 1, the detection result is no fault; otherwise, obtaining a periodic impact interval according to the suspected impact position sequence, obtaining the rotating shaft running period of the mechanical equipment, and when the error between the periodic impact interval and the rotating shaft running period of the mechanical equipment is within a preset error, determining that a fault exists in the detection result; otherwise, the detection result is no fault.
Specifically, the number of elements in the suspected impact position sequence is obtained, when the number of elements in the suspected impact position sequence is less than or equal to 1, the analysis is directly finished, the vibration time domain waveform data only contains a single impact, and the detection result is no fault.
When the number of elements in the suspected impact position sequence is larger than 1, obtaining a periodic impact interval according to the suspected impact position sequence, and obtaining the rotating shaft running period of the mechanical equipment, wherein when the error between the periodic impact interval and the rotating shaft running period of the mechanical equipment is within a preset error, the detection result is that a fault exists; otherwise, the detection result is no fault.
The specific method for obtaining the periodic impact interval according to the suspected impact position sequence comprises the following steps: obtaining a sequence of suspected impact locationsAnd calculating the median of the differential sequence result; periodic impingement interval shk is obtained bycycle：
shockcycle＝delta_T×idx_median
Wherein, delta _ T is a preset time interval, and idx _ mean is a median of the differential sequence result.
The invention relates to a mechanical equipment rotation impact fault detection method based on time domain analysis, which realizes accurate detection of low-speed mechanical equipment fault detection, and comprises the steps of dividing signals through a preset time interval, carrying out first-step dispersion and carrying out second-step dispersion on the signals through preset standardized treatment by utilizing obvious impact characteristics expressed in vibration time domain waveform data and carrying out discretization analysis on the vibration time domain waveform data after impact amplification and enhancement; and extracting a suspected impact position sequence by judging the ratio of each discrete value to the whole mode in the vibration time domain waveform data, and finally realizing fault detection through the suspected impact position sequence. The method is based on time domain analysis and does not depend on frequency domain analysis, so that the method has universality in an application scene compared with the traditional envelope demodulation analysis and other methods, and the reason is that the vibration signals collected aiming at low-speed mechanical equipment are difficult to ensure to contain enough running periods (usually, impact periods) in the practical application scene, and the traditional frequency domain method finally needs to obtain periodic components through FFT (fast Fourier transform), so that the FFT is difficult to obtain effective and accurate results under the condition of insufficient period number according to a sampling principle. In conclusion, the method has stronger universality and particularly has advantages in low-speed operation scenes, and a stable and efficient method is provided for impact fault detection and diagnosis of low-speed mechanical equipment.
Further, a periodic impact interval is obtained through the suspected impact position sequence and a preset time interval, whether the rotation period of the mechanical equipment is within a preset error or not is judged based on the periodic impact interval, if the rotation period of the mechanical equipment is within the preset error, the equipment can be determined to have an impact fault, and if the rotation period of the mechanical equipment is not within the preset error, no fault exists.
Referring to fig. 2, for the time domain waveform corresponding to the vibration acceleration data collected on a certain low-speed device, obvious periodic impact can be observed from the graph, the impact period interval is 5.56Hz, and the impact is from the broken teeth of the low-speed shaft gear through the verification of the machine halt. Therefore, the detection of periodic impacts can provide an important means for impact-type fault diagnosis.
Referring to fig. 3, the result of the spectrum demodulation for vibration acceleration envelope of a certain low-speed mechanical device is shown in the same manner as fig. 2. The apparent periodic impulse in the time domain is not apparent in the spectrum after envelope demodulation when the spectrum is demodulated, and the impulse interval obtained by using the spectrum peak value searching method is not accurate, and some situations even can be wrong. The main reason is that the number of impulse cycles contained in the time domain waveform is small, and the FFT analysis after envelope demodulation is more effective in the case of a large number of cycles (more than 10 cycles). Therefore, for low-speed vibration, the accuracy of extracting the periodic impact by using the traditional envelope demodulation or other frequency domain analysis methods is not sufficient, and the periodic impact interval needs to be obtained by directly processing and analyzing the time domain waveform.
Referring to fig. 4, the data is the same as fig. 2 for the periodic impact interval extraction result based on time domain analysis. The dot-dash line in the figure is the result of the mechanical equipment rotation fault detection method based on time domain analysis, 5 suspected impact positions are extracted, the statistical result of the periodic impact interval is obtained by carrying out differential processing on the suspected impact positions, the periodic impact interval obtained by final calculation is 5.5Hz, and the error is lower than 1% compared with the real periodic impact interval. It can be seen that the present invention accurately estimates the periodic impact intervals of low speed mechanical devices.
The following are embodiments of the apparatus of the present invention that may be used to perform embodiments of the method of the present invention. For details of non-careless mistakes in the embodiment of the apparatus, please refer to the embodiment of the method of the present invention.
In another embodiment of the present invention, a mechanical device rotational impact fault detection system based on time domain analysis is provided, which can be used to implement the mechanical device rotational impact fault detection method based on time domain analysis described above.
The acquisition module is used for acquiring original vibration time domain waveform data of mechanical equipment and performing signal enhancement processing to obtain enhanced vibration time domain waveform data; the preprocessing module is used for carrying out preset standardization processing on the enhanced vibration time domain waveform data to obtain vibration time domain waveform data; the peak processing module is used for dividing the vibration time domain waveform data according to a preset time interval to obtain a plurality of sub-vibration time domain waveform data, obtaining the maximum value of each sub-vibration time domain waveform data, and combining to obtain a peak sequence; the first detection module is used for acquiring the mode and the maximum value of the peak sequence, dividing the maximum value of the peak sequence by the mode of the peak sequence to obtain a comparison value, and acquiring subscripts corresponding to elements, of which the results of dividing the mode of the peak sequence are larger than or equal to a second threshold value, in the peak sequence to obtain a suspected impact position sequence when the comparison value is larger than a preset first threshold value; otherwise, the detection result is no fault; the second detection module is used for acquiring the number of elements in the suspected impact position sequence, and when the number of elements in the suspected impact position sequence is less than or equal to 1, the detection result is no fault; otherwise, obtaining a periodic impact interval according to the suspected impact position sequence, obtaining the rotating shaft running period of the mechanical equipment, and when the error between the periodic impact interval and the rotating shaft running period of the mechanical equipment is within a preset error, determining that a fault exists in the detection result; otherwise, the detection result is no fault.
Preferably, an interval determination module is arranged in the second detection module, and the interval determination module is used for acquiring a differential sequence result of the suspected impact position sequence and calculating a median of the differential sequence result; periodic impingement interval shk is obtained bycycle：
shockcycle＝delta_T×idx_median
Wherein, delta _ T is a preset time interval, and idx _ mean is a median of the differential sequence result.
In yet another embodiment of the present invention, a computer device is provided that includes a processor and a memory for storing a computer program comprising program instructions, the processor for executing the program instructions stored by the computer storage medium. The Processor may be a Central Processing Unit (CPU), or may be other general-purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable gate array (FPGA) or other Programmable logic device, a discrete gate or transistor logic device, a discrete hardware component, etc., which is a computing core and a control core of the terminal, and is adapted to implement one or more instructions, and to load and execute one or more instructions in a computer storage medium to implement a corresponding method flow or a corresponding function; the processor provided by the embodiment of the invention can be used for detecting the rotation impact fault of the mechanical equipment based on time domain analysis.
In yet another embodiment of the present invention, the present invention further provides a storage medium, specifically a computer-readable storage medium (Memory), which is a Memory device in a computer device and is used for storing programs and data. It is understood that the computer readable storage medium herein can include both built-in storage media in the computer device and, of course, extended storage media supported by the computer device. The computer-readable storage medium provides a storage space storing an operating system of the terminal. Also, one or more instructions, which may be one or more computer programs (including program code), are stored in the memory space and are adapted to be loaded and executed by the processor. It should be noted that the computer-readable storage medium may be a high-speed RAM memory, or may be a non-volatile memory (non-volatile memory), such as at least one disk memory. One or more instructions stored in a computer-readable storage medium may be loaded and executed by a processor to perform the corresponding steps in the above embodiments with respect to mechanical device rotational impact fault detection based on time domain analysis.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting the same, and although the present invention is described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: modifications and equivalents may be made to the embodiments of the invention without departing from the spirit and scope of the invention, which is to be covered by the claims.
Claims (10)
1. A mechanical equipment rotation impact fault detection method based on time domain analysis is characterized by comprising the following steps:
acquiring original vibration time domain waveform data of mechanical equipment, and performing signal enhancement processing to obtain enhanced vibration time domain waveform data;
carrying out preset standardization processing on the enhanced vibration time domain waveform data to obtain vibration time domain waveform data;
dividing the vibration time domain waveform data according to a preset time interval to obtain a plurality of sub-vibration time domain waveform data, obtaining the maximum value of each sub-vibration time domain waveform data, and combining to obtain a peak value sequence;
obtaining a mode and a maximum value of the peak sequence, dividing the maximum value of the peak sequence by the mode of the peak sequence to obtain a comparison value, and obtaining subscripts corresponding to elements, of which the results of dividing the mode of the peak sequence are larger than or equal to a second threshold value, in the peak sequence when the comparison value is larger than a preset first threshold value to obtain a suspected impact position sequence; otherwise, the detection result is no fault;
acquiring the number of elements in the suspected impact position sequence, wherein when the number of elements in the suspected impact position sequence is less than or equal to 1, the detection result is no fault;
otherwise, obtaining a periodic impact interval according to the suspected impact position sequence, obtaining the rotating shaft running period of the mechanical equipment, and when the error between the periodic impact interval and the rotating shaft running period of the mechanical equipment is within a preset error, determining that a fault exists in the detection result; otherwise, the detection result is no fault.
2. The method for detecting the rotating impact fault of the mechanical equipment based on the time domain analysis as claimed in claim 1, wherein the specific method for acquiring the original vibration time domain waveform data of the mechanical equipment is as follows:
the method comprises the steps of collecting original vibration signals of the mechanical equipment through a vibration sensor arranged on a preset part of the mechanical equipment, and obtaining original vibration time domain waveform data of the mechanical equipment according to the original vibration signals of the mechanical equipment.
3. The mechanical equipment rotating impact fault detection method based on time domain analysis as claimed in claim 2, wherein the preset parts comprise rolling bearings and/or reduction gearbox gears, and the original vibration signal comprises a speed signal and/or an acceleration signal.
4. The method for detecting the rotating impact fault of the mechanical equipment based on the time domain analysis as claimed in claim 1, wherein the specific method for performing the signal enhancement processing is as follows:
and squaring the original vibration time domain waveform data of the mechanical equipment.
5. The method for detecting the rotating impact fault of the mechanical equipment based on the time domain analysis as claimed in claim 1, wherein the specific method for obtaining the vibration time domain waveform data by performing the preset normalization processing on the enhanced vibration time domain waveform data is as follows:
normalizing the enhanced vibration time-domain waveform data by:
wherein, amplitude _ vib _ arr is enhanced vibration time domain waveform data, i is 0,1,2,3, … n-1, amplitude _ vib _ arri is the ith enhanced vibration time domain waveform data, and n is the number of the enhanced vibration time domain waveform data; the amplitude _ vib _ arr is normalized enhanced vibration time domain waveform data;
and rounding the normalized enhanced vibration time domain waveform data and keeping one decimal to obtain the vibration time domain waveform data.
6. The method for detecting the rotating impact fault of the mechanical equipment based on the time domain analysis as claimed in claim 1, wherein the preset time interval is 1/10-1/2 of the time of one week of the operation of the mechanical equipment.
7. The mechanical equipment rotation impact fault detection method based on time domain analysis as claimed in claim 1, wherein the first threshold is greater than or equal to 2, and the 1< second threshold < first threshold.
8. The method for detecting the rotating impact fault of the mechanical equipment based on the time domain analysis according to claim 1, wherein the specific method for obtaining the periodic impact interval according to the suspected impact position sequence comprises:
obtaining a differential sequence result of the suspected impact position sequence, and calculating a median of the differential sequence result;
the periodic shock interval shock is obtained bycycle：
shockcycle＝delta_T×idx_median
Wherein, delta _ T is a preset time interval, and idx _ mean is a median of the differential sequence result.
9. The time domain analysis-based mechanical device rotational impact fault detection method of claim 1, wherein the preset error is 10%.
10. A mechanical equipment rotation impact fault detection system based on time domain analysis is characterized by comprising:
the acquisition module is used for acquiring original vibration time domain waveform data of the mechanical equipment and performing signal enhancement processing to obtain enhanced vibration time domain waveform data;
the preprocessing module is used for carrying out preset standardization processing on the enhanced vibration time domain waveform data to obtain vibration time domain waveform data;
the peak processing module is used for dividing the vibration time domain waveform data according to a preset time interval to obtain a plurality of sub-vibration time domain waveform data, obtaining the maximum value of each sub-vibration time domain waveform data and combining the sub-vibration time domain waveform data to obtain a peak sequence;
the first detection module is used for acquiring the mode and the maximum value of the peak sequence, dividing the maximum value of the peak sequence by the mode of the peak sequence to obtain a comparison value, and acquiring subscripts corresponding to elements, of which the results of dividing the mode of the peak sequence are larger than or equal to a second threshold value, in the peak sequence to obtain a suspected impact position sequence when the comparison value is larger than a preset first threshold value; otherwise, the detection result is no fault;
the second detection module is used for acquiring the number of elements in the suspected impact position sequence, and when the number of elements in the suspected impact position sequence is less than or equal to 1, the detection result is no fault;
otherwise, obtaining a periodic impact interval according to the suspected impact position sequence, obtaining the rotating shaft running period of the mechanical equipment, and when the error between the periodic impact interval and the rotating shaft running period of the mechanical equipment is within a preset error, determining that a fault exists in the detection result; otherwise, the detection result is no fault.
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