CN113295445A - Vibration signal acquisition and fault real-time monitoring system and method for rotary machine - Google Patents
Vibration signal acquisition and fault real-time monitoring system and method for rotary machine Download PDFInfo
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- CN113295445A CN113295445A CN202110554569.2A CN202110554569A CN113295445A CN 113295445 A CN113295445 A CN 113295445A CN 202110554569 A CN202110554569 A CN 202110554569A CN 113295445 A CN113295445 A CN 113295445A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
- G01M99/00—Subject matter not provided for in other groups of this subclass
- G01M99/005—Testing of complete machines, e.g. washing-machines or mobile phones
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- G01H—MEASUREMENT OF MECHANICAL VIBRATIONS OR ULTRASONIC, SONIC OR INFRASONIC WAVES
- G01H11/00—Measuring mechanical vibrations or ultrasonic, sonic or infrasonic waves by detecting changes in electric or magnetic properties
- G01H11/06—Measuring mechanical vibrations or ultrasonic, sonic or infrasonic waves by detecting changes in electric or magnetic properties by electric means
Abstract
The invention discloses a vibration signal acquisition and fault real-time monitoring system and a method of a rotary machine, belonging to the technical field of fault monitoring of rotary machines; the monitoring system comprises an acceleration sensor, collectors and an upper computer which is in communication connection with the collectors through a base station; the acceleration sensor adopts an ICP sensor and is correspondingly connected with a sensor interface arranged on the collector; the signal conditioning module and the AD conversion module in the collector process the vibration signals in advance, the signal real-time processing module simply diagnoses the digital signals and transmits fault signals to the microprocessor, and the microprocessor transmits the fault signals to the upper computer through the communication module to perform precise diagnosis. The system of the invention realizes a monitoring method combining simple diagnosis and precise diagnosis by matching the collector and the upper computer, combines the advantages of edge computing and cloud computing, can greatly reduce the data uploading amount under the condition of not influencing the monitoring effect, and reduces the data storage burden of the cloud server.
Description
Technical Field
The invention relates to a fault monitoring system of a rotary machine, in particular to a vibration signal acquisition and fault real-time monitoring system and method of the rotary machine, and belongs to the technical field of fault monitoring of the rotary machine.
Background
With the increase of automation degree, mechanical equipment tends to be complicated, and the connection among the equipment is more and more compact. The large-scale equipment consists of a plurality of parts, the failure of one part can cause the failure of the whole equipment, even the breakdown of the whole production line, the production halt caused by the equipment failure can bring huge economic loss to enterprises, and serious people can also cause serious safety accidents. Therefore, the method has important engineering significance for fault diagnosis and condition monitoring of equipment.
The fault diagnosis of the rotating machinery generally adopts vibration signals of equipment to analyze fault characteristics, and the equipment commonly used for data acquisition comprises a data acquisition card and distributed data acquisition equipment:
1) the data acquisition card is suitable for signal acquisition of a single device, the data acquisition card is matched with a constant current adapter and a computer for use when in use, the data acquisition card is used for acquiring a plurality of devices one by one, and if the number of the tested devices is large, the time and labor are wasted; and are also unsuitable for monitoring the state of the device.
2) The distributed data acquisition equipment uploads the acquired data to the cloud end with a certain delay; however, the mechanical equipment is in a normal operation state most of the time, most of the collected signals are normal state signals of the equipment, so that a large number of normal state signals occupy storage resources, and the processing burden of the upper computer is increased.
Disclosure of Invention
The purpose of the invention is: the system and the method have the advantages that the monitoring method combining simple diagnosis and precise diagnosis is realized through the cooperation of the collector and the upper computer, the advantages of edge calculation and cloud calculation are combined, the data uploading amount can be greatly reduced under the condition that the monitoring effect is not influenced, and the data storage burden of a cloud server is reduced.
In order to achieve the purpose, the invention adopts the following technical scheme: a vibration signal acquisition and fault real-time monitoring system of a rotary machine comprises acceleration sensors and collectors which are arranged at acquisition nodes of a plurality of rotary devices, and an upper computer which is in communication connection with the plurality of collectors through a base station; the acceleration sensor adopts an ICP sensor to collect vibration signals on the rotating equipment and is correspondingly connected with a sensor interface arranged on the collector; the collector comprises a power supply module, a signal conditioning module, an AD conversion module, a signal real-time processing module, a microprocessor, a communication module and an SD card; the input end of the power supply module is connected with an external input power supply, and the output end of the power supply module is connected with a power supply module in the collector and is connected with an ICP sensor to provide a constant current source; the input end of the signal conditioning module is connected with an ICP sensor to receive the collected vibration signal, and the vibration signal is transmitted to the AD conversion module after being subjected to voltage regulation and filtering; the AD conversion module converts the vibration signal from an analog signal into a digital signal and transmits the digital signal to the signal real-time processing module; the signal real-time processing module simply diagnoses the digital signal and transmits the judged fault signal to the microprocessor; the microprocessor transmits the fault signal to the upper computer through the communication module for precise diagnosis, receives the set parameters of the threshold value and the acquisition time interval and the acquisition data instruction sent by the upper computer through the communication module, and stores the acquisition data into the SD card when network communication is interrupted and field manual acquisition is carried out.
An FIFO memory and a signal time domain characteristic calculation submodule are arranged in the signal real-time processing module; the FIFO memory buffers the received digital signals, calculates the relevant time domain characteristics of the signals, and judges the fault signals larger than a set threshold value according to the time domain characteristic values.
And the threshold value in the signal real-time processing module is set by the microprocessor.
The signal real-time processing module is provided with a timing acquisition mode in the simple diagnosis process of the digital signals, and the microprocessor controls the acquisition time interval; the signal real-time processing module provides a clock signal for the AD conversion module through a timing acquisition mode, and the microprocessor adjusts the sampling frequency of the AD conversion module by controlling a frequency division signal of the signal real-time processing module.
The signal real-time processing module adopts an FPGA chip, the model of the microprocessor is STM32F103, and the model of the communication module is an NB-IoT module.
The monitoring method using the monitoring system comprises the following steps:
s0, correspondingly distributing the ICP sensor and the collectors at collection nodes of a plurality of pieces of rotating equipment to be monitored, wherein a power supply is a 24V direct-current power supply, and the power supply is battery power or is connected with a power adapter;
s1, the ICP sensor collects vibration signals of the rotating equipment and transmits the vibration signals to a collector which is correspondingly connected;
s2, the signal conditioning module in the collector adjusts the voltage range of the received vibration signal to 0-2V through the attenuation circuit, then the low-pass filter circuit filters out the frequency components larger than the sampling frequency, and the filtered vibration signal is transmitted to the AD conversion module;
s3, the AD conversion module converts the received analog signal into a digital signal with the bit width of 8 and transmits the digital signal to the signal real-time processing module for simple diagnosis;
s4, the signal real-time processing module buffers the received digital signal through the FIFO memory and calculates the relevant time domain characteristics of the signal, the relevant time domain characteristics comprise a kurtosis index, a pulse index and a margin index, and the fault signal of which the calculated data is larger than a set threshold value outputs a high level signal to the microprocessor through a corresponding pin; meanwhile, the signal real-time processing module gates a data channel at fixed time according to set time in a fixed-time acquisition mode;
the kurtosis index, the pulse index and the margin index are parameter indexes with dimension as one, and the calculation formula is as follows:
kurtosis index:
pulse index:
margin indexes are as follows:
wherein K is a kurtosis index, I is a pulse index, and L is a margin index; xiIs a single data value of the vibration signal sequence;
is the average value of the data and the calculation formula is
And n is the number of acquisition points.
S5, the microprocessor transmits the received fault signal and the vibration signal collected at regular time to the upper computer through the communication module for precise diagnosis; and storing the collected data to the SD card when the network communication is interrupted and the field manual collection is carried out.
In step S4, if any one of the calculated kurtosis index, pulse index and margin index is greater than a set threshold, sending an acquisition signal to a precision diagnosis link; and if all the indexes do not exceed the set threshold, interrupting the data channel.
In step S4, the threshold value may be set according to specific equipment and conditions: during installation, a threshold value is debugged according to the normal running condition of the machine, a fault signal which is 1.5 times higher than the average value of the peak values of normal signals is preliminarily set, and the threshold value setting can be remotely adjusted through an upper computer according to the actual running condition.
The invention has the beneficial effects that:
1) the monitoring method of the system disclosed by the invention realizes the combination of simple diagnosis and precise diagnosis by the cooperation of the collector and the upper computer, combines the advantages of edge computing and cloud computing, can greatly reduce the data uploading amount under the condition of not influencing the monitoring effect, and reduces the data storage burden of the cloud server.
2) The collector in the system can be directly arranged beside the mechanical equipment, and compared with a data acquisition card, the system has the characteristics of small volume and convenient acquisition; and the internal signal real-time processing module adopts an FPGA chip to analyze and calculate the time domain characteristics of the signal, so that the real-time processing of the acquisition equipment has the characteristics of data parallel processing and low time delay, the fault can be found in time, the high accuracy is realized by combining with cloud analysis, and the fault type can be accurately judged.
3) The collector in the system is internally provided with a timing collection mode, and reads data of the SD card or sends a data collection command through the cloud when the data is required to be collected; compared with common distributed data acquisition equipment, the equipment can process data in real time, filter normal state signals of the equipment and select fault signal data to upload.
4) Compared with other transmission modes, the communication module in the system has the advantages of strong signal, low power consumption, low cost and multiple connections by adopting the NB-IoT module; and the system works with a microprocessor and an upper computer in a cooperative manner, so that the communication efficiency and the signal stability of the system are improved.
Drawings
FIG. 1 is a schematic diagram of the overall structure of the system of the present invention;
FIG. 2 is a schematic diagram of the internal structure of the collector in FIG. 1;
FIG. 3 is a diagnostic flow chart of a method of the system of the present invention.
Detailed Description
The invention is further explained below with reference to the figures and the embodiments.
Example (b): as shown in fig. 1-3, the vibration signal acquisition and fault real-time monitoring system for a rotary machine according to the present invention includes an acceleration sensor and a collector arranged at a plurality of acquisition nodes of a rotary device, and an upper computer in communication connection with the plurality of collectors through a base station; the acceleration sensor adopts an ICP sensor to collect vibration signals on the rotating equipment and is correspondingly connected with a sensor interface arranged on the collector; the collector comprises a power supply module, a signal conditioning module, an AD conversion module, a signal real-time processing module, a microprocessor, a communication module and an SD card; the input end of the power supply module is connected with an external input power supply, and the output end of the power supply module is connected with a power supply module in the collector and is connected with an ICP sensor to provide a constant current source; the input end of the signal conditioning module is connected with the ICP sensor to receive the collected vibration signal, and the vibration signal is transmitted to the AD conversion module after being subjected to voltage regulation and filtering; the AD conversion module converts the vibration signal from an analog signal into a digital signal and transmits the digital signal to the signal real-time processing module; the signal real-time processing module simply diagnoses the digital signal and transmits the judged fault signal to the microprocessor; the microprocessor transmits the fault signal to the upper computer through the communication module for precise diagnosis, receives the set parameters of the threshold value and the acquisition time interval and the acquisition data instruction sent by the upper computer through the communication module, and stores the acquisition data into the SD card when the network communication is interrupted and the field manual acquisition is carried out.
An FIFO memory and a signal time domain characteristic calculation submodule are arranged in the signal real-time processing module; the FIFO memory caches the received digital signals, calculates the relevant time domain characteristics of the signals, and judges the fault signals larger than a set threshold value according to the time domain characteristic values; the threshold value in the signal real-time processing module is set by the microprocessor.
A timing acquisition mode is set in the simple diagnosis process of the digital signals by the signal real-time processing module, and the acquisition time interval is controlled by the microprocessor; the signal real-time processing module provides a clock signal for the AD conversion module through a timing acquisition mode, and the microprocessor adjusts the sampling frequency of the AD conversion module by controlling a frequency division signal of the signal real-time processing module.
The signal real-time processing module adopts an FPGA chip, the model of the microprocessor is STM32F103, and the model of the communication module is an NB-IoT module.
A monitoring method utilizing a vibration signal acquisition and fault real-time monitoring system of a rotating machine comprises the following steps:
and S0, correspondingly distributing the ICP sensor and the collectors at the collection nodes of the plurality of pieces of rotating equipment to be monitored, wherein the power supply is a 24V direct-current power supply, and the power supply mode is battery power supply or is connected with a power adapter.
And S1, acquiring the vibration signal of the rotating equipment by the ICP sensor, and transmitting the vibration signal to the corresponding connected acquisition device.
S2, the signal conditioning module in the collector adjusts the voltage range of the received vibration signal to 0-2V through the attenuation circuit, then the low-pass filter circuit filters out the frequency components larger than the sampling frequency, and the filtered vibration signal is transmitted to the AD conversion module.
And S3, the AD conversion module converts the received analog signal into a digital signal with the bit width of 8 and transmits the digital signal to the signal real-time processing module for simple diagnosis.
S4, the signal real-time processing module buffers the received digital signal through the FIFO memory and calculates the relevant time domain characteristics of the signal, the relevant time domain characteristics comprise a kurtosis index, a pulse index and a margin index, and the fault signal of which the calculated data is larger than a set threshold value outputs a high level signal to the microprocessor through a corresponding pin; meanwhile, the signal real-time processing module gates the data channel at fixed time according to the set time in the fixed-time acquisition mode.
The kurtosis index, the pulse index and the margin index are parameter indexes with dimension as one, and the calculation formula is as follows:
kurtosis index:
pulse index:
margin indexes are as follows:
wherein K is a kurtosis index, I is a pulse index, and L is a margin index; xiIs a single data value of the vibration signal sequence;
is the average value of the data and the calculation formula is
And n is the number of acquisition points.
If one of the calculated kurtosis index, pulse index and margin index is larger than a set threshold value, sending an acquired signal to a precision diagnosis link; and if all the indexes do not exceed the set threshold, interrupting the data channel.
S5, the microprocessor transmits the received fault signal and the vibration signal collected at regular time to the upper computer through the communication module for precise diagnosis; and storing the collected data to the SD card when the network communication is interrupted and the field manual collection is carried out.
The threshold value can be set according to specific equipment and working conditions: during installation, a threshold value is debugged according to the normal running condition of the machine, a fault signal which is 1.5 times higher than the average value of the peak values of normal signals is preliminarily set, and the threshold value setting can be remotely adjusted through an upper computer according to the actual running condition.
The whole detection system adopts a method combining simple diagnosis and precise diagnosis, the simple diagnosis judges whether a fault exists, and the precise diagnosis determines the specific fault type. The input acquisition signals are analyzed in real time through a simple diagnosis module arranged at an acquisition node, and then whether precise diagnosis is needed or not is judged.
The method comprises the following steps that collected signals are often accompanied with noise interference, a timing collection mode is specially set for preventing misjudgment of simple diagnosis, a data channel can be gated at regular time according to set time in the timing collection mode, and the time interval can be set to be one day or several days; most normal working signals can be effectively filtered through simple diagnosis, and the uploaded signals are subjected to precision diagnosis through an upper computer; the precision diagnosis can be used for carrying out professional analysis such as time domain analysis, frequency domain analysis, time frequency analysis and the like on the acquired signals, and can also be used for diagnosing abnormal signals by combining with expert diagnosis experience.
The monitoring method of the system disclosed by the invention realizes the combination of simple diagnosis and precise diagnosis by the cooperation of the collector and the upper computer, combines the advantages of edge computing and cloud computing, can greatly reduce the data uploading amount under the condition of not influencing the monitoring effect, and reduces the data storage burden of the cloud server.
The above description is only for the purpose of illustrating the technical solutions of the present invention and not for the purpose of limiting the same, and other modifications or equivalent substitutions made by those skilled in the art to the technical solutions of the present invention should be covered within the scope of the claims of the present invention without departing from the spirit and scope of the technical solutions of the present invention.
Claims (9)
1. The utility model provides a rotary machine's vibration signal acquisition and trouble real-time monitoring system which characterized in that: the device comprises acceleration sensors and collectors which are arranged at the collection nodes of a plurality of pieces of rotating equipment, and an upper computer which is in communication connection with the collectors through a base station; the acceleration sensor adopts an ICP sensor to collect vibration signals on the rotating equipment and is correspondingly connected with a sensor interface arranged on the collector; the collector comprises a power supply module, a signal conditioning module, an AD conversion module, a signal real-time processing module, a microprocessor, a communication module and an SD card; the input end of the power supply module is connected with an external input power supply, and the output end of the power supply module is connected with a power supply module in the collector and is connected with an ICP sensor to provide a constant current source; the input end of the signal conditioning module is connected with an ICP sensor to receive the collected vibration signal, and the vibration signal is transmitted to the AD conversion module after being subjected to voltage regulation and filtering; the AD conversion module converts the vibration signal from an analog signal into a digital signal and transmits the digital signal to the signal real-time processing module; the signal real-time processing module simply diagnoses the digital signal and transmits the judged fault signal to the microprocessor; the microprocessor transmits the fault signal to the upper computer through the communication module for precise diagnosis, receives the set parameters of the threshold value and the acquisition time interval and the acquisition data instruction sent by the upper computer through the communication module, and stores the acquisition data into the SD card when network communication is interrupted and field manual acquisition is carried out.
2. The system according to claim 1, wherein the system comprises: an FIFO memory and a signal time domain characteristic calculation submodule are arranged in the signal real-time processing module; the FIFO memory buffers the received digital signals, calculates the relevant time domain characteristics of the signals, and judges the fault signals larger than a set threshold value according to the time domain characteristic values.
3. The system according to claim 2, wherein the system comprises: and the threshold value in the signal real-time processing module is set by the microprocessor.
4. The system according to claim 1, wherein the system comprises: the signal real-time processing module is provided with a timing acquisition mode in the simple diagnosis process of the digital signals, and the microprocessor controls the acquisition time interval; the signal real-time processing module provides a clock signal for the AD conversion module through a timing acquisition mode, and the microprocessor adjusts the sampling frequency of the AD conversion module by controlling a frequency division signal of the signal real-time processing module.
5. The system according to claim 1, wherein the system comprises: the signal real-time processing module adopts an FPGA chip, the model of the microprocessor is STM32F103, and the model of the communication module is an NB-IoT module.
6. A monitoring method using a vibration signal acquisition and fault real-time monitoring system of a rotary machine according to any one of the preceding claims, characterized in that: the method comprises the following steps:
s0, correspondingly distributing the ICP sensor and the collectors at collection nodes of a plurality of pieces of rotating equipment to be monitored, wherein a power supply is a 24V direct-current power supply, and the power supply is battery power or is connected with a power adapter;
s1, the ICP sensor collects vibration signals of the rotating equipment and transmits the vibration signals to a collector which is correspondingly connected;
s2, the signal conditioning module in the collector adjusts the voltage range of the received vibration signal to 0-2V through the attenuation circuit, then the low-pass filter circuit filters out the frequency components larger than the sampling frequency, and the filtered vibration signal is transmitted to the AD conversion module;
s3, the AD conversion module converts the received analog signal into a digital signal with the bit width of 8 and transmits the digital signal to the signal real-time processing module for simple diagnosis;
s4, the signal real-time processing module buffers the received digital signal through the FIFO memory and calculates the relevant time domain characteristics of the signal, the relevant time domain characteristics comprise a kurtosis index, a pulse index and a margin index, and the fault signal of which the calculated data is larger than a set threshold value outputs a high level signal to the microprocessor through a corresponding pin;
meanwhile, the signal real-time processing module gates a data channel at fixed time according to set time in a fixed-time acquisition mode;
s5, the microprocessor transmits the received fault signal and the vibration signal collected at regular time to the upper computer through the communication module for precise diagnosis; and storing the collected data to the SD card when the network communication is interrupted and the field manual collection is carried out.
7. The system and method for real-time vibration signal acquisition and fault monitoring of rotating machinery as claimed in claim 6, wherein: in step S4, the kurtosis index, the pulse index, and the margin index are all parameter indexes with a dimension of one, and the calculation formula is:
kurtosis index:
pulse index:
margin indexes are as follows:
wherein K is a kurtosis index, I is a pulse index, and L is a margin index; xiIs a single data value of the vibration signal sequence;
is the average value of the data and the calculation formula is
And n is the number of acquisition points.
8. The system and method for real-time vibration signal acquisition and fault monitoring of rotating machinery as claimed in claim 6, wherein: in step S4, if any one of the calculated kurtosis index, pulse index and margin index is greater than a set threshold, sending an acquisition signal to a precision diagnosis link; and if all the indexes do not exceed the set threshold, interrupting the data channel.
9. The system and method for real-time vibration signal acquisition and fault monitoring of rotating machinery as claimed in claim 6, wherein: in step S4, the threshold value may be set according to specific equipment and conditions: during installation, a threshold value is debugged according to the normal running condition of the machine, a fault signal which is 1.5 times higher than the average value of the peak values of normal signals is preliminarily set, and the threshold value setting can be remotely adjusted through an upper computer according to the actual running condition.
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