TW201732238A - Enhanced-FFT online machine vibration measurement system and method - Google Patents

Abstract

The invention provides enhanced-FFT online machine vibration measurement system and method, which at least comprising acceleration sensor unit, control processor, enhanced-FFT operating model, data acquisition module, database server, webpage data managing module and APP that downloaded on a mobile device. The acceleration sensor unit correspondingly mounting on the machine that about to be detected for monitoring steadiness and abnormal phenomenon of the machine during operation, the control processor proceeding to spectrum analysis in accordance with the enhanced-FFT operating model and further transmitting the detecting analysis data to the data acquisition module, which will decide whether the vibrating spectrum data has exceeded the forewarning value and further transmitting and storing the data in the database server. The webpage data managing module then connecting with the database server, which is capable of reading displayed detecting data instantly and further providing the linkage to the APP that downloaded on a mobile device for Inquiry. Accordingly, the maintenance costs of the machine can be considerably reduced and enhance industrial competitiveness thereof via applying networking-technology to all types of machines or devices in order to construct far end mechanisms of sensing, diagnosing, forewarning and maintaining.

Description

Enhanced-FFT online machine vibration measurement system and method

The invention relates to a vibration measuring system and method for establishing an enhanced-FFT online machine, in particular to a vibration measuring system for a machine capable of constructing a mechanism for remote sensing, diagnosis, early warning and maintenance, thereby achieving a reduction of the machine platform. Maintenance costs, effectively improve the competitiveness of the industry for its innovative application inventors.

Pressing, rolling element bearings are the most commonly used devices for industrial rotating machines. The state of vibration is often regarded as the main characteristic of measuring quality. It is also used as an important indicator for predictive maintenance before the machine fails. Based on such reasons, vibration Analysis is the most critical condition tool for rotating machine fault detection, diagnosis and prediction.

There are many different methods that can be used for the analysis and diagnosis of bearing faults, such as vibration, sound, temperature and deformation, among which frequency analysis is the most effective way to reveal the source and magnitude of vibration. In general, the range of vibration high frequency and low frequency is the place we are most interested in. The most commonly used measurement method is the DFT algorithm. When the vibration is in steady state, the FFT algorithm even provides faster calculation time without affecting its accuracy. In practice, when the rolling element bearing is deformed or faulty, the vibration signal will have transient and aperiodic characteristics, so that neither DFT nor FFT can obtain accurate results, innate The limitation is mainly due to the problem of spectrum leakage. Although the Fast Fourier Transform (FFT) is still the most widely used method to this day, the direct use of FFT analysis can not achieve accurate targets for defective bearings due to their non-fixed signal characteristics.

However, in recent years, the Internet and communication technologies have flourished, which has led to the rapid expansion of the Internet of Things (IOT) and its widespread application to various things management. The Internet of Things can use electronic tags to connect real objects to the Internet. All devices can find their specific location and use the computer to centrally manage and control the devices. Based on such a development trend, the technology using the Internet of Things can be applied to various types of machines or devices to construct a mechanism for remote sensing, diagnosis, early warning, and maintenance, which can greatly reduce the maintenance cost of the machine and effectively enhance the industrial competitiveness. .

Today, the inventor has long been rich in design and development and practical production experience of the relevant industry, and has been researched and improved by using Internet of Things technology. It provides a system and method for establishing vibration-measurement of enhanced-FFT online machine in order to achieve better practical value. The purpose of sex.

The main object of the present invention is to provide a system and method for establishing vibration measurement of an enhanced-FFT line machine, in particular to develop an enhanced-FFT (e-FFT) operation model for realizing detection and analysis of on-line instantaneous bearing vibration. Using the collapse energy generated by the fast Fourier transform (FFT) to establish the numerical relationship between it and the main vibration frequency, and at the same time, the recovery of the collapsed energy around the main frequency point can effectively restore the amplitude of the original vibration signal (ie, gravity). Acceleration), because the established model is an algebraic relationship, the calculation time is extremely short, which is suitable for the execution of real-time systems. In practice, the model calculus uses a single-chip program to perform operations and immediately transmits the spectrum results to (MySQL). ) The database is then instantly observed and recorded via PHP and APP. The historical data of abnormal conditions can also be queried online to achieve remote sensing, diagnosis, early warning, maintenance of the machine and other mechanisms, thereby reducing the maintenance cost of the machine. Effectively enhance the competitiveness of the industry for its purpose.

The invention aims to establish the main purpose and effect of the vibration measurement system of the enhanced-FFT online machine, which is achieved by the following specific technical means:

The utility model mainly comprises at least one acceleration sensing component, a control processor, an enhanced-FFT operation model, a data acquisition module, a database server, a webpage data management module and an APP application downloaded from the mobile device, wherein The acceleration sensing component can be correspondingly mounted on the device to be tested to detect the smoothness and abnormality of the operation of the machine, and then the control processor performs spectrum analysis based on the enhanced-FFT operation model, and the detection data is detected. Transfer to the data capture module, the data capture module determines whether the vibration spectrum data exceeds the warning value, and the judgment data result is transmitted and stored in the database server, and the web data management module connects the database servo The application can be read and displayed immediately, and the APP application on the mobile device can be used to link the inquirer; thereby, the technology of the Internet of Things can be applied to various types of machines or devices to construct remote sensing and diagnosis. The mechanism of early warning and maintenance can greatly reduce the maintenance cost of the machine and effectively enhance the industrial competitiveness.

The enhanced-FFT online machine vibration measurement system is established as described above, wherein the acceleration sensing component is an acceleration gauge using a measurement acceleration, and the acceleration gauge is installed on the machine platform to detect the smooth operation of the machine platform. Degree, and then to detect whether the accuracy of the machine is abnormal.

The enhanced-FFT online machine vibration measurement system is established as described above, wherein the control processor uses a single chip to construct an enhanced-FFT (E-FFT) operation model for realizing detection and analysis of on-line instantaneous bearing vibration. The recovery of the collapsed energy around the main frequency point can effectively restore the amplitude of the original vibration signal (ie, the acceleration of gravity); since the established model is an algebraic relationship, the calculation time is extremely short, which is suitable for the execution of the real-time system.

The enhanced-FFT online machine vibration measurement system is established as described above, wherein the control processor 1 communicates with the computer through RS232/RS4853. 2. Receive commands from the computer. 3. Capture the signal of the sensor circuit voltage. 4. Transfer the test data (sensor circuit and other signals) to the computer.

As described above, the enhanced-FFT online machine vibration measurement system is established, wherein the data acquisition module is respectively connected with the control processor and the database server, and mainly performs data transmission and reception to be transmitted by the control processor. The vibration spectrum data is judged whether the warning value is exceeded, and the detected detection data is transmitted to the database server.

As described above, the enhanced-FFT online machine vibration measurement system is established, wherein the database server is respectively connected with the data acquisition module and the webpage data management module, and is mainly responsible for recording the record of the detected detection data. Management, further the database server includes a display interface, which can display the detection data on the display interface to provide monitoring machine/device, historical data query and early warning function.

The above-mentioned enhanced-FFT online machine vibration measurement system is established as described above, wherein the webpage data management module is linked with the database server, and mainly provides instant display, management and query analysis of the data.

The enhanced-FFT online machine vibration measurement system is established as described above, wherein the APP application is downloaded to the mobile device, and the user can link the webpage data management module to provide real-time display of the chart and query analysis.

As described above, the enhanced-FFT online machine vibration measurement system is established, wherein the data acquisition module, the database server and the webpage data management module can be independent of individual computers according to actual needs, and through the network (TCP/ IP) is linked and can be integrated into the same computer.

The main purpose and effect of the vibration measuring method of the enhanced-FFT online machine in the invention are achieved by the following specific technical means:

It mainly uses the enhanced-FFT operation model to detect and analyze the instantaneous bearing vibration on the line; first set the sampling frequency ( ), sampling points (N), bandwidth ( ), simultaneously sample the signal; perform the FFT; then determine the number of main spectra (M); then find the maximum amplitude ( ) with the second largest amplitude ( The frequency of the drop; then, the bandwidth of the energy will be recovered ( Set a certain value, and then check whether the distance between the maximum amplitude and the sub-large amplitude drop frequency and the multiple Fourier fundamental frequency ( Relationship; recalculate the frequency drift ( And the amplitude of the response (RA); finally, exclude the frequency point of the largest amplitude found , set M=M-1; check if M=0, if yes, the step stops, if not, then return to find the maximum amplitude ( ) with the second largest amplitude ( The frequency of landing.

It can be seen from the above components and implementation description that the present invention has the following advantages as compared with the prior art:

1. The invention establishes an enhanced-FFT online machine vibration measurement system and method, and establishes a real-time machine vibration detection system by using a single wafer, and performs spectrum analysis of the vibration signal of the machine by an enhanced-FFT model method.

2. The invention establishes an enhanced-FFT online machine vibration measurement system and method, and has a human-machine interface operating system.

3. The invention establishes an enhanced-FFT online machine vibration measurement system and method, and has a data acquisition end and a display interface system.

4. The invention establishes an enhanced-FFT online machine vibration measurement system and method, and provides a cloud database management system.

5. The invention establishes an enhanced-FFT online machine vibration measurement system and method, and provides an APP online timely display and query program; thereby, the technology of the Internet of Things can be applied to various types of machines or devices to construct a remote end. The mechanism of sensing, diagnosis, early warning and maintenance can greatly reduce the maintenance cost of the machine and effectively enhance the industrial competitiveness.

For a more complete and clear disclosure of the technical content, the purpose of the invention and the effects thereof achieved by the present invention, it is explained in detail below, and please refer to the drawings and drawings:

First, please refer to the first figure of the present invention for establishing an enhanced-FFT online machine vibration measurement system architecture diagram, which mainly includes:

At least one acceleration sensing component (1) is mounted on the machine to be tested (A), can detect the smoothness of the operation of the machine (A), and whether the accuracy of the detection machine (A) is generated. An abnormal phenomenon; further the acceleration sensing element (1) can adopt an acceleration gauge for measuring acceleration.

A control processor (2) is coupled to the acceleration sensing component (1) and receives the vibration frequency sensed by the acceleration sensing component (1). The control processor (2) is constructed with an enhanced-FFT (E- FFT) operation model, which is used to realize the detection and spectrum analysis of the instantaneous bearing vibration on the line;

a data capture module (3), coupled to the control processor and connected to receive the vibration spectrum data transmitted by the control processor (2), and determine whether the warning value is exceeded, and then transmit the determined detection data. Further, the data capture module (3) includes a display interface (31) for displaying the detection data to provide monitoring machine/device, historical data query and early warning functions;

a database server (4) is coupled to the data capture module (3) and receives the test data transmitted by the data capture module (3), and is responsible for recording and management;

A webpage data management module (5) is linked to the database server (4). The webpage data management module (5) further comprises a display interface (51) for providing instant display, management and query analysis of the data; and

An APP application (6) is downloaded from the mobile device (B) and corresponds to the linked web data management module (5) for the user to link the webpage through the APP application (6) in the mobile device (B). Data management module (5), and provide information to display charts and query analysis instantly.

The following describes the techniques and preferred use specifications of the present invention:

First, the accelerating sensing component (1) in the system of the present invention adopts an accelerometer of PCB352A25/NC, and the signal processing circuit of the accelerometer is mainly divided into buffering, filtering amplification, clamp amplification, and second-order filtering (such as the second diagram). Show), the signal is processed by the oscilloscope to confirm and confirm whether the accelerometer is working normally. First, when the measuring machine (A) is not vibrating, the signal is not changed (as shown in the third figure), on the measuring machine ( A) At startup, the signal will change according to the vibration of the machine (A) (as shown in the fourth figure). Finally, when the measuring machine (A) is started, the change caused by the appropriate amount of tapping is used to test the acceleration. Whether the maximum limit of the regulation meets the specifications required by the control processor (single chip) (as shown in the fifth figure); through the above, the smoothness and detection machine of the acceleration gauge detection machine (A) can be obtained. Whether the accuracy of the stage (A) produces an abnormal frequency of vibration frequency, and the vibration frequency is transmitted to the control processor (2).

Next, the control processor (2) adopts a PIC 18F4520 single chip [the wafer used in the actual application of the present invention], and the control processor (2) performs spectrum analysis based on the E-FFT operation model, and adopts an E-FFT operation model. It is used to realize the detection and analysis of online real-time bearing vibration. The main function is 1. Communication connection with data acquisition module (3) [computer] through RS232/RS485 converter. 2. Receive the command from the data capture module (3) [computer]. 3. Capture the voltage signal of the signal processing circuit of the acceleration gauge and perform an E-FFT operation model. 4. Transfer the detection data (the vibration frequency signal detected by the signal processing circuit) to the data acquisition module (3) [computer] end.

Next, explain the principle and analysis of the E-FFT operation model used:

System signal according to Fourier Series It can be simply expressed as a finite sequence of sinusoidal harmonics, as shown in the following equation:

(3)

among them , versus .

Take Interval sampling signals, equation (3) can be presented in discrete ways, as shown in the following equation:

(4)

Where n is the discrete sampling ordinal, and the time variable .

Cycle is , its Fourier base angular frequency ( )defined as

(5)

Suppose the waveform samples p ( p > 1) cycles, Can be expressed as

(6)

among them .

Fourier base frequency ( ) can be defined as follows:

(7)

among them , as well as . Note: The waveform is The sampling frequency is sampled by N points.

With the discrete form of the Parseval relation, the power P of the waveform can be expressed as follows: (8)

At frequency The energy at the place can be expressed as (9)

Where k = 0, 1, 2, ..., N / 2-1.

By the above formula The amplitude of the main harmonics is at the discrete frequency The location is as follows:

(10)

Where m =1, 2,..., M .

The energy of the harmonics may collapse due to problems with spectral leakage. Harmonic around, therefore, harmonic energy The vicinity of the harmonics can be restored to "group power". Each group of energy Can be collected versus The energy between them is as follows:

(11)

among them Is a positive integer representing the bandwidth of the group.

Each harmonic amplitude can be written as follows:

(12)

Further consider the case of two kinds of inter-level harmonics in small frequency offset and large frequency offset, according to the effect of using FFT signal spectrum analysis; and the overall complete model-based FFT leakage energy distribution rule develops accurate and fast The time-varying inter-harmonic measurement and tracking model is shown in the sixth diagram. The process steps are as follows:

Step (1) setting (sampling frequency), N (sampling points), (Bandwidth) and signal sampling.

Step (2) Perform FFT.

Step (3) determines the number of primary spectrums (M).

Step (4) versus Defined as the frequency of the maximum amplitude and the second largest amplitude drop point, respectively.

Step (5) check if If yes, set =1 then to step (10), otherwise, to the next step. Further notes: That is, the distance between the maximum amplitude and the sub-large amplitude drop frequency is less than 4 times the Fourier fundamental frequency ( ), =1 means that the bandwidth of the recovered energy is set to 1.

Step (6) Check if If yes, set =2 then to step (10), otherwise, to the next step. Further notes: That is, the distance between the maximum amplitude and the sub-large amplitude drop frequency is less than 6 times greater than 4 times the Fourier fundamental frequency ( ), = 2 means that the bandwidth of the recovered energy is set to 2.

Step (7) check if If yes, set =3 then to step (10), otherwise, to the next step. Further notes: That is, the distance between the maximum amplitude and the sub-large amplitude drop frequency is less than 8 times greater than 6 times the Fourier fundamental frequency ( ), =3 means that the bandwidth of the recovered energy is set to 3.

Step (8) check if If yes, set =4 then to step (10), otherwise, to the next step. Further notes: That is, the distance between the maximum amplitude and the sub-large amplitude drop frequency is less than 10 times greater than 8 times the Fourier fundamental frequency ( ), = 4 means that the bandwidth of the recovered energy is set to 4.

Step (9) setting =5. annotation: = 4 means that the bandwidth of the recovered energy is set to 4.

Step (10) Calculate the amount of frequency drift ( ), the amplitude of the response (RA). annotation: , RA = .

Step (11) excludes the frequency point of the largest amplitude found , set M=M-1.

Step (12) checks if M=0. If yes, the step is stopped, and if not, return to step (4).

The above is the analysis step performed by the E-FFT operation model during system execution, and the obtained detection data is transmitted to the data acquisition module (3) [computer] end.

After the data acquisition module (3) receives the detection data transmitted by the control processor (2), it is displayed on the display interface (31), and the display interface (31) is provided for the machine monitoring interface and the warning value setting. Manipulation [as shown in Figure 7]:

a. Open the communication port: Select the communication port of the connected data capture module (3) [computer].

b. Machine number selection: Select the machine (A) number to be monitored. The current system default is a machine number.

c. Warning value setting: Various machine (A) have different kinds of abnormal value judgments, which can be monitored by setting the abnormal value of each machine.

d. Manual and automatic mode selection: Manually can be used for local monitoring of the user's needs.

e. Instant display of test results (machine table, spectrum pattern): Real-time monitoring is performed by the vibration amount generated by the current machine (A). Here, the machine of the present invention performs abnormal vibration and is located at 1.2KHz~1.5. Between KHz.

f. Data upload database selection and interval setting: as the basis for storage, the interval can specify how long (in seconds) the data interval is to be stored.

g. System time display: displays the current time.

h. The test result is linked to the database server (4) for enquiry.

Further, the detection result may be linked to the database server (4) for query, historical data and early warning data display interface (31) [as shown in the eighth figure], the main functions are as follows:

a. Historical data query: By browsing historical data, it is judged whether the machine (A) needs to be replaced or corrected.

b. Abnormal value data query: When the abnormal value is exceeded, the correction and adjustment machine (A) can be done immediately.

c. Select the number of displayed data: based on the amount of data the user needs to monitor.

d. Perform conditional query display on the machine (A), acceleration sensing component (1) or time.

e. Database data display form: Quickly identify the machine number, sensor number, time, value range, and fast compounding leaf value range as the basis for the user to judge. f. Close the program.

The above test data is loaded into the database server (4) by the data capture module (3) for storage. Then, the webpage data management module (5) is linked with the database server (4) to provide instant display, management and query analysis of the data. When entering the webpage data management module (5) display interface (51), Select the real-time detection data display, which is currently displayed as an E-FFT chart [as shown in Figure 9]. This chart shows that the vibration level of this vibrating object is close to 750 Hz, so that it can monitor whether the machine (A) is out of the normal range, and if there is an abnormal phenomenon, it can stop the detection immediately. If you select the historical data query screen, you can retrieve the machine vibration data for a specific time period (year, month, and day) according to the needs of the registrant. If you want to query the machine (A) more quickly, you can turn it. Go to the warning message page to check if there is any abnormality in this machine (A) at the most recent time.

Please refer to Figure 10 to Figure 11. Further, when the user is monitoring remotely, the APP application (6) can be downloaded via the mobile device (B), mainly for the user to access the APP application in the mobile device (6). ) Link the web page data management module (5) and provide information to display charts and query analysis in real time [as shown in Figure 11]. The user only needs to open the data query program, first enter the user page, after logging in the user's account password, immediately go to the abnormal data query page, the user can immediately query the recent abnormal state of the machine, if you want to monitor The current status of this machine, press the LIVE CHART button, you can switch to the instant chart display, if you want to check whether this machine (A) is to be repaired or replaced, press the HISTORY CHART button, you can switch to Historical data charts for analysis and comparison.

However, the above-described embodiments or drawings are not intended to limit the structure or the use of the present invention, and any suitable variations or modifications of the invention will be apparent to those skilled in the art.

It can be seen from the above components and implementation description that the present invention has the following advantages as compared with the prior art:

1. The invention establishes an enhanced-FFT online machine vibration measuring system, establishes a real-time machine vibration detecting system by using a single chip, and performs spectrum analysis of the machine vibration signal by an enhanced-Fast Fourier Transform (E-FFT) method.

2. The invention establishes an enhanced-FFT online machine vibration measuring system with a human-machine interface operating system.

3. The invention establishes an enhanced-FFT online machine vibration measuring system, which has a data capturing end and a display interface system.

4. The invention establishes an enhanced-FFT online machine vibration measurement system, and provides a cloud database management system.

5. The invention establishes an enhanced-FFT online machine vibration measurement system, and provides an on-line display and query program on the APP line; thereby, the technology of the Internet of Things can be applied to various types of machines or devices to construct remote sensing. The mechanism of diagnosis, early warning and maintenance can greatly reduce the maintenance cost of the machine and effectively enhance the industrial competitiveness.

In summary, the embodiments of the present invention can achieve the expected use efficiency, and the specific structure disclosed therein has not been seen in similar products, nor has it been disclosed before the application, and has completely complied with the provisions of the Patent Law. And the request, the application for the invention of a patent in accordance with the law, please forgive the review, and grant the patent, it is really sensible.

(1) ‧‧‧Accelerated sensing components

(2) ‧‧‧Control Processor

(3) ‧‧‧Data Capture Module

(31)‧‧‧Display interface

(4) ‧‧‧Database Server

(5) ‧‧‧Web data management module

(51)‧‧‧Display interface

(6) ‧‧‧APP application

(A)‧‧‧ Machines

(B) ‧‧‧ mobile devices

First: Schematic diagram of the system architecture of the present invention

Second picture: schematic diagram of the signal processing circuit of the present invention

Third figure: Schematic diagram of the unvibrated waveform of the machine of the present invention

Figure 4: Schematic diagram of the starting vibration waveform of the machine of the present invention

Figure 5: Schematic diagram of vibration and tapping waveform of the machine of the present invention

Figure 6 is a flow chart of the e-FFT operation model of the present invention

Figure 7: Schematic diagram of the vibration warning monitoring interface of the present invention

Figure 8: Schematic diagram of the database history and warning data query interface of the present invention

Ninth diagram: vibration spectrum analysis chart of the e-FFT operation model of the present invention

Figure 10: Schematic diagram of the abnormal data query page of the present invention

Figure 11: Schematic diagram of the APP instant chart display of the present invention

(1) ‧‧‧Accelerated sensing components

(2) ‧‧‧Control Processor

(3) ‧‧‧Data Capture Module

(31)‧‧‧Display interface

(4) ‧‧‧Database Server

(5) ‧‧‧Web data management module

(51)‧‧‧Display interface

(6) ‧‧‧APP application

(A)‧‧‧ Machines

(B) ‧‧‧ mobile devices

Claims (8)

A vibration measuring system for establishing an enhanced-FFT online machine, comprising: at least one acceleration sensing component, correspondingly mounted on the machine to be tested, capable of detecting the smoothness of the operation of the machine, and the detecting machine Whether the accuracy of the stage produces an abnormal phenomenon; a control processor is coupled to the acceleration sensing element and receives the vibration frequency sensed by the acceleration sensing element, and the enhanced-FFT (E-FFT) is constructed in the control processor The calculation model is used to realize the detection and spectrum analysis of the instantaneous bearing vibration on the line; a data capture module, which is connected to the control processor and connected to receive the vibration spectrum data transmitted by the control processor, and judge Whether the warning value is exceeded or not, and then the detected detection data is transmitted. Further, the data acquisition module includes a display interface, and the display interface is used to display the detection data to provide a monitoring machine/device, historical data query and early warning function; A database server is connected to the data capture module, and receives the detection data transmitted by the data capture module, and is responsible for the Recording and management; A web page data management module is linked to a database server. The web page data management module includes a display interface for providing instant display, management and query analysis. Establishing an enhanced-FFT online machine vibration measurement system as described in claim 1, wherein the system further includes an APP application for downloading in the mobile device and wirelessly connecting the webpage data management The module allows users to link to the web data management module through the APP application in the mobile device, and provides information to display charts and query analysis in real time. The enhanced-FFT online machine vibration measuring system is established as described in claim 1 or 2, wherein the acceleration sensing element can adopt an acceleration gauge for measuring acceleration. Establishing an enhanced-FFT online machine vibration measurement system as described in claim 1 or 2, wherein the data acquisition module, the database server, and the web data management module are respectively independent individual computers, and One way to connect through the Internet or integrate it on the same computer. An enhanced-FFT online machine vibration measurement method, which mainly uses the enhanced-FFT operation model to perform on-line instantaneous bearing vibration detection and spectrum analysis; the steps are as follows: Step (1) Set the sampling frequency ( ), sampling points (N), bandwidth ( ), and perform signal sampling; step (2) performs FFT; step (3) determines the number of main spectrums (M); step (4) versus Defined as the frequency of the maximum amplitude and the second largest amplitude drop point respectively; Step (5) Check if If yes, set =1 then to step (10), otherwise, to the next step; this step defines That is, the distance between the maximum amplitude and the sub-large amplitude drop frequency is less than 4 times the Fourier fundamental frequency ( ), =1 means that the bandwidth of the recovered energy is set to 1; Step (6) Check if If yes, set =2 then to step (10), otherwise, to the next step; this step defines That is, the distance between the maximum amplitude and the sub-large amplitude drop frequency is less than 6 times greater than 4 times the Fourier fundamental frequency ( ), =2 means that the bandwidth of the recovered energy is set to 2; step (7) checks if If yes, set =3 then to step (10), otherwise, to the next step; this step defines That is, the distance between the maximum amplitude and the sub-large amplitude drop frequency is less than 8 times greater than 6 times the Fourier fundamental frequency ( ), =3 means that the bandwidth of the recovered energy is set to 3; Step (8) Check if If yes, set =4 then to step (10), otherwise, to the next step; this step defines That is, the distance between the maximum amplitude and the sub-large amplitude drop frequency is less than 10 times greater than 8 times the Fourier fundamental frequency ( ), =4 means that the bandwidth of the recovered energy is set to 4; Step (9) =5, =5 means that the bandwidth of the recovered energy is set to 5; Step (10) Calculate the amount of frequency drift ( ), the magnitude of the amplitude of the response (RA); step (11) excludes the frequency point of the largest amplitude found , set M=M-1; Step (12) to check if M=0, if yes, the step stops, and if not, return to step (4). The method for measuring vibration of an on-line machine according to the fifth aspect of the patent application, wherein the sampling signal of the bearing vibration obtained by the method is obtained by an acceleration sensing component mounted on the machine to be tested. . The invention relates to an enhanced-FFT online machine vibration measurement method as described in claim 6, wherein the result measured by the method is transmitted to the remote end, and the data display, management and query analyst can be provided. For example, the enhanced-FFT online machine vibration measurement method described in claim 6 can further provide an instant display of a chart and a query analyst by downloading an APP application via a mobile device via a wireless connection remote end.