CN116642577A - Method and system for monitoring equipment operation time based on vibration sensor - Google Patents
Method and system for monitoring equipment operation time based on vibration sensor Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01H—MEASUREMENT OF MECHANICAL VIBRATIONS OR ULTRASONIC, SONIC OR INFRASONIC WAVES
- G01H17/00—Measuring mechanical vibrations or ultrasonic, sonic or infrasonic waves, not provided for in the preceding groups
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- G—PHYSICS
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- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
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Abstract
The embodiment of the invention discloses a method and a system for monitoring equipment operation time based on a vibration sensor, wherein the method comprises the following steps: the vibration sensor collects vibration signals of equipment, filters and preprocesses data information of the vibration signals to obtain time domain related information of the signals, judges whether the equipment is in a starting-up state or not through classification statistics or machine learning of the vibration time domain information, and then continuously accumulates collection interval time of which two continuous collection are in the starting-up state as starting-up time of the equipment through continuous collection monitoring, so that total starting-up time of the equipment can be obtained. By adopting the invention, a system for monitoring the running time of the equipment based on the vibration sensor can be constructed. The method and the system can acquire the running time of the equipment under the condition of not accessing and interfering the original equipment system.
Description
Technical Field
The invention relates to the technical field of sensor monitoring and measurement, in particular to a method and a system for monitoring equipment working operation time length.
Background
The current sensors are widely applied in industrial environments, a plurality of vibration sensors are assembled for follow-up or are independent into a system for auxiliary monitoring, in order to know and analyze the vibration condition of equipment, the working strength and the operation time of the equipment are required to be known, and the method is used for analyzing the working operation time of the metering equipment from the vibration signal of the method without adding additional equipment.
Disclosure of Invention
The first aspect of the embodiment of the invention provides a method for monitoring equipment operation time based on a vibration sensor, which is characterized in that a vibration sensor is used for collecting vibration signals of equipment, filtering and preprocessing data information of the vibration signals to obtain time domain related information of the signals, classifying and counting or machine learning is carried out on the time domain information of the vibration to judge whether the equipment is in a starting state, then, through continuous collection and monitoring, collection interval time of which the continuous collection is in the starting state is taken as the starting time of the equipment, and continuous accumulation is carried out, so that the total starting time of the equipment can be obtained, and the maximum error of the starting time and the actual starting time of the equipment in a starting and stopping period of the equipment is not more than 2 collection interval times, so that the vibration collection interval time can be shortened to reduce the error, and the available equipment operation time is obtained.
The embodiment of the invention provides a method for monitoring equipment operation time based on a vibration sensor, which can comprise the following steps:
collecting vibration signals of equipment through a vibration sensor;
preprocessing the vibration information and obtaining time domain related information;
whether the equipment is in a starting state or not is analyzed through classification statistics or machine learning of time domain information;
through continuous monitoring analysis, if the two continuous monitoring devices are in a starting state, accumulating and metering the interval duration between the two monitoring devices to obtain the total operation duration of the devices; and the statistical error of the total operation time length can be reduced by shortening the vibration acquisition interval time.
Further, the vibration signal of the device is acquired by the vibration sensor, and the method further comprises the steps of:
collecting vibration signals of the device by the vibration sensor includes: a displacement signal, a velocity signal, and an acceleration signal;
collecting vibration signals of the device by the vibration sensor includes: unidirectional signals, 2-way signals, three-dimensional 3-way signals and multi-way signals;
the acquisition mode of the vibration signal of the vibration sensor acquisition equipment further comprises the following steps: collecting real-time data and offline data;
the real-time acquisition and transmission mode of the vibration signals of the vibration sensor acquisition equipment comprises the following steps: wired acquisition transmission and wireless acquisition transmission;
the device for collecting the device by the vibration sensor comprises: all devices or components that have a vibration feedback difference between start-up and shut-down.
Further, the method includes preprocessing the vibration information and obtaining time domain related parameters, and the method further includes:
filtering noise information in the vibration information;
converting the vibration information after the filtering treatment into digital information from analog data;
and carrying out statistical analysis and time domain analysis on the vibration digital information to obtain a maximum value, a minimum value, an average value, a peak-to-peak value, an absolute average value, a variance, a standard deviation, an effective value, a root mean square, a root amplitude value, a kurtosis value, a pulse value, a margin value, a waveform value and a base line.
Further, when the vibration interval or model is classified by statistical classification or machine learning of the data of the shutdown state, the vibration interval or model is matched with the vibration interval or model to be the shutdown state, otherwise, the vibration interval or model is the startup state, and the method further comprises the following steps:
a threshold value is preset according to data statistics analysis of vibration data of the sensor characteristics in a shutdown state or a static state, wherein the value is larger than or equal to the threshold value and is in a startup state, and the value is smaller than or equal to the threshold value and is in a shutdown state;
counting and analyzing a vibration interval of a shutdown state according to vibration data of the sensor characteristics in the shutdown or static state, wherein the vibration accords with the interval to be the shutdown state, and otherwise, the vibration accords with the startup state;
machine learning is carried out according to vibration data of the sensor characteristics in a shutdown state or a static state to obtain a shutdown model, and the model is suitable for being in the shutdown state, and is in a startup state in the reverse;
further, the method further comprises the following steps:
through the continuous monitoring vibration signal of fixed interval time, if the continuous vibration acquisition analysis equipment is monitored to be in the starting state, the time between the two monitoring, namely the fixed interval time, is added to the total running time of the equipment, and otherwise, the total running time is not added.
The interval time of continuous acquisition is dynamically adjusted according to the actual condition of the site through a sensor intelligent control program, if monitoring is carried out, if the continuous vibration acquisition analysis equipment is monitored to be in a starting state, the time between the two monitoring is added to the total running time of the equipment, and otherwise, the equipment is not added.
Because the error of the total running time is always smaller than the interval of 2 acquisition periods in the start-stop period of single equipment, the statistical error of the total running time can be obviously reduced by shortening the vibration acquisition interval time as much as possible.
A second aspect of the embodiment of the present invention provides a system for monitoring an operation duration of a device based on a vibration sensor, which may include:
the information acquisition device is used for acquiring vibration acceleration signals of the sensor in three directions of the current equipment;
the data preprocessing device is used for preprocessing vibration acceleration information in three directions;
data transmission means for transmitting the vibration information to the data monitoring server;
the data monitoring server is used for carrying out second preprocessing on the vibration data information preprocessed through filtering to obtain corresponding vibration time domain parameter information, then carrying out statistics on the vibration time domain information to classify vibration intervals of vibration acceleration effective values in three directions during shutdown, judging whether the equipment is in an operation state or not beyond the vibration intervals, judging whether the equipment is in the operation state or not if the equipment is in the operation state, and if the equipment is in the operation state, adding all the time from the last monitoring time to the monitoring time as the operation time of the equipment into the operation time of the equipment and displaying the operation time of the equipment in real time.
Further, the data preprocessing device comprises a filter circuit and a microprocessor;
the filter circuit is used for filtering noise information in the vibration acceleration information;
the microprocessor is used for converting the acceleration information after the filtering processing from analog data into digital acceleration information;
and the microprocessor is also used for calculating the distribution coordinates of the digital acceleration information in the XYZ direction of the current three-dimensional coordinate system.
Further, the data preprocessing device further comprises a wireless communication module, which is used for transmitting the output information of the microprocessor based on a wireless communication mode.
Further, when the communication protocol of the wireless communication is a ZigBee communication protocol, the system further includes: and the wireless transmission relay is used for carrying out relay transmission on the output information.
Further, the data monitoring server comprises a time domain analysis preprocessing module, a shutdown state statistical analysis module, an equipment state judging module and a master control module;
the time domain analysis preprocessing module is used for carrying out statistical analysis and time domain analysis on the vibration acceleration digital information in the XYZ directions, and obtaining maximum value, minimum value, average value, peak-to-peak value, absolute average value, variance, standard deviation, effective value, root mean square, square root amplitude, kurtosis value, pulse value, margin value, waveform value and base line of the vibration acceleration in the XYZ directions;
the system comprises a shutdown state statistical analysis module, a time domain analysis preprocessing module and a time domain analysis preprocessing module, wherein the shutdown state statistical analysis module is used for defaulting to be in a shutdown state in a period of time when a user monitors a play interval of vibration acceleration effective values without the shutdown state, and counting and analyzing a fluctuation interval of the vibration acceleration effective values in the shutdown state according to the XYZ three-direction vibration acceleration effective value set obtained by the time domain analysis preprocessing module.
The equipment state judging module is used for judging whether the vibration effective value of the current equipment is in the interval or not according to the fluctuation interval of the vibration acceleration in the shutdown state, wherein the interval is in the shutdown state, and the current equipment is in the startup state.
The equipment operation duration statistics module is used for counting the total operation duration of adding equipment by taking the time interval between two vibration acquisitions as the equipment operation duration when the continuous two vibration monitoring is in a starting-up operation state by a user and displaying the total operation duration on a display screen
And the master control module is used for initializing a user control sensor and displaying a judging result.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below.
FIG. 1 is a schematic flow chart of a method for monitoring the operation time of a device based on a vibration sensor according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a microprocessor and a peripheral circuit thereof according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of an acceleration signal filtering circuit according to an embodiment of the present invention;
fig. 4 is a schematic diagram of a wireless communication module and a peripheral circuit structure thereof according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of a data processing flow of a data acquisition monitoring system according to an embodiment of the present invention;
FIG. 6 is a schematic diagram of a system function structure based on the operation time of a vibration sensor monitoring device according to an embodiment of the present invention;
fig. 7 is a schematic structural diagram of a data preprocessing device at a sensor end according to an embodiment of the present invention;
FIG. 8 is a schematic functional structure diagram of a data monitoring output device according to an embodiment of the present invention;
fig. 9 is a schematic diagram of a system device structure based on operation duration of a vibration sensor monitoring device according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.
The method for monitoring the running time of the equipment based on the vibration sensor provided by the embodiment of the invention can be applied to the application scenes of equipment or components with vibration differences in the shutdown state and the startup state.
A method for monitoring the operation time of the device based on the vibration sensor according to the embodiment of the present invention will be described in detail with reference to fig. 1.
Referring to fig. 1, a flow chart of a method for monitoring an operation duration of a device based on a vibration sensor is provided in an embodiment of the present invention. As shown in fig. 1, the method according to the embodiment of the present invention may include the following steps S101 to S104.
S101, collecting vibration signals of the equipment through a vibration sensor.
Collecting vibration signals of the device by the vibration sensor includes: a displacement signal, a velocity signal, and an acceleration signal;
collecting vibration signals of the device by the vibration sensor includes: unidirectional signals, 2-way signals, three-dimensional 3-way signals and multi-way signals;
the acquisition mode of the vibration signal of the vibration sensor acquisition equipment further comprises the following steps: collecting real-time data and offline data;
the real-time acquisition and transmission mode of the vibration signals of the vibration sensor acquisition equipment comprises the following steps: wired acquisition transmission and wireless acquisition transmission;
the device for collecting the device by the vibration sensor comprises: all devices or components that have a vibration feedback difference between start-up and shut-down.
S102, preprocessing the vibration information and obtaining time domain related parameters.
Filtering noise information in the vibration information;
converting the vibration information after the filtering treatment into digital information from analog data;
and carrying out statistical analysis and time domain analysis on the vibration digital information to obtain a maximum value, a minimum value, an average value, a peak-to-peak value, an absolute average value, a variance, a standard deviation, an effective value, a root mean square, a root amplitude value, a kurtosis value, a pulse value, a margin value, a waveform value and a base line.
S103, judging whether the equipment is in a starting state or not through classification statistics or machine learning of time domain information.
A threshold value is preset according to data statistics analysis of vibration data of the sensor characteristics in a shutdown state or a static state, wherein the value is larger than or equal to the threshold value and is in a startup state, and the value is smaller than or equal to the threshold value and is in a shutdown state;
counting and analyzing a vibration interval of a shutdown state according to vibration data of the sensor characteristics in the shutdown or static state, wherein the vibration accords with the interval to be the shutdown state, and otherwise, the vibration accords with the startup state;
machine learning is carried out according to vibration data of the sensor characteristics in a shutdown state or a static state to obtain a shutdown model, and the model is suitable for being in the shutdown state, and is in a startup state in the reverse;
s104, accumulating the interval time of the continuous two-time acquisition equipment in the starting state through continuous acquisition to obtain the total starting time of the equipment.
According to the continuous monitoring analysis, if the two continuous monitoring devices are in a starting-up state, accumulating and metering the interval duration between the two monitoring devices to obtain the total operation duration of the devices; and the statistical error of the total operation time length can be reduced by shortening the vibration acquisition interval time. The method further comprises the steps of:
according to the continuous monitoring vibration signal with fixed interval time, if the continuous two-time vibration acquisition analysis equipment is monitored to be in a starting state, the time between the two monitoring is the fixed interval time, the total running time of the equipment is added, and the other conditions are not added.
According to the intelligent control program of the sensor, the interval time of continuous acquisition is dynamically adjusted according to the actual condition of the site, if the monitoring is that the continuous vibration acquisition analysis equipment is in a starting state for two times, the time between the two monitoring is added to the total running time of the equipment, and the other conditions are not added.
Because the error of the total running time is always smaller than the interval of 2 acquisition periods in the start-stop period of single equipment, the statistical error of the total running time can be obviously reduced by shortening the vibration acquisition interval time as much as possible.
A system for monitoring the operation time of a device based on a vibration sensor according to an embodiment of the present invention will be described in detail with reference to fig. 2 to 9. It should be noted that the monitoring system shown in fig. 2-9 is used to perform the method of the embodiment of the present invention shown in fig. 1, and only the portions relevant to the embodiment of the present invention are shown for convenience of description.
As shown in fig. 2, the microprocessor and its peripheral circuit diagram in this embodiment may use the latest ultra-low power STM32L432KBKCU6 chip, the 32-bit RISC instruction controller, and the maximum operating frequency 80MHz, and the 10-way 12-bit a/D converter integrated in the chip, so as to support multiple power management modes, and the peripheral circuit of the microprocessor is shown in fig. 2. The microprocessor controls the triaxial acceleration sensor chip, the filter circuit and the wireless communication module to work under a preset instruction, finishes the conversion processing and analysis work of data transmitted from a sensor end, encodes the data according to a specified format and controls the communication module to transmit the data.
The filtering circuit can be as shown in fig. 3, and the signal output by the triaxial acceleration sensor chip is processed by the filtering circuit composed of the AD8629ARMZ chip, and then the processed information is transmitted to the microprocessor. The sensor starts to measure and process acceleration signal information under the control of the microprocessor, and the acceleration signal is transmitted to the microprocessor in a voltage form for A/D conversion and data analysis processing after passing through the signal amplifying circuit.
The communication module can adopt limited or wireless transmission, the wireless ZigBee communication transmission is selected in the embodiment, the circuit layout of the wireless communication module can be as shown in fig. 4, the working frequency is 2.405 GHz-2.4815 GHz, the ZigBee communication protocol is adopted, the wireless transmitting power is +20dBm, and the wireless ZigBee communication module can transmit 2000m under the condition that an external antenna is not shielded. The modular design is provided with a PCB antenna and can be externally connected with the antenna. And the microprocessor is connected with the SPI serial bus. The data is transmitted to the repeater through ZigBee wireless transmission, and then the repeater is transmitted to the data server through Ethernet.
The repeater can be composed of an explosion-proof shell, a power supply module, a wireless communication module and a 232-to-Ethernet module, supports connection of a plurality of wireless vibration temperature sensors, can set a fixed local area network IP and sends data to a fixed IP address. The repeater is arranged in the sight distance range of the vibration temperature sensor (within the distance of 100M under the condition of no shielding), the wireless vibration temperature sensor acquires vibration information, temperature information, battery electric quantity and signal strength information, and the wireless vibration temperature sensor sends out the vibration information, the battery electric quantity and the signal strength information through wireless transmission, and the repeater receives data and forwards the data to the Ethernet and transmits the data to the server for storage.
In a specific implementation manner of the embodiment of the present invention, an implementation process of a data processing flow of a data collection monitoring system may be as shown in fig. 5:
s201, signal data is initially filtered.
S202, time domain analysis processing.
It can be appreciated that by performing statistical analysis and time domain analysis on the vibration digital information, a maximum value, a minimum value, an average value, a peak-to-peak value, an absolute average value, a variance, a standard deviation, an effective value, a root mean square, a root amplitude, a kurtosis value, a pulse value, a margin value, a waveform value, and a base line value can be obtained.
S203, whether the fluctuation interval range of the shutdown state exists.
S204, judging whether the initial data is sufficient.
It will be appreciated that a sufficient amount of data is required to ensure that the range of oscillation effective values for the counted shutdown conditions is accurately valid.
S205, analyzing the fluctuation interval range of the vibration effective value of the shutdown state through statistics.
It will be appreciated that the range of the fluctuation interval of the vibration effective value can be confirmed by the mean and variance.
S206, judging whether the equipment is in a starting-up running state according to the fluctuation interval range.
It is understood that the fluctuation interval range conforming to the shutdown state is the shutdown state, and vice versa is the startup operation state.
S207, judging whether the device is in a starting-up running state when data are acquired last time.
It can be understood that the determination state stored in the last data processing can be directly read, and the determination state can be the shutdown state again according to the fluctuation interval range conforming to the shutdown state, and the startup operation state is the reverse.
And S208, accumulating the monitoring time intervals which are continuously started twice as the running time of the equipment, and displaying the total running time of the equipment.
It should be noted that the steps illustrated in the flowcharts of the figures may be performed in a computer system such as a set of computer executable instructions, and that although a logical order is illustrated in the flowcharts, in some cases the steps illustrated or described may be performed in an order other than that illustrated herein.
Referring to fig. 6, a schematic functional structure diagram of a system based on operation duration of a vibration sensor monitoring device is provided in an embodiment of the present invention. As shown in fig. 6, the monitoring system 1 of the embodiment of the present invention may include: the system comprises an information acquisition device 11, a data preprocessing device 12, a data transmission device 13 and a data monitoring output device 14. The data preprocessing device 12 may include, as shown in fig. 7: a filter circuit 121 and a microprocessor 122. The data monitoring output device 14 may include, as shown in fig. 8: a time domain analysis processing module 141, a shutdown state statistics analysis module 142, an equipment state determination module 143, an equipment operation duration statistics module 144, and a master control module 145.
And the information acquisition device 11 is used for acquiring acceleration information of the sensor in the current three-dimensional coordinate system.
In a specific implementation, the information acquisition device 11 may be a triaxial acceleration sensor chip, and may acquire acceleration information of the sensor in a current three-dimensional coordinate system, where the information may be acceleration information in three directions of the three-dimensional coordinate system XYZ. The triaxial acceleration sensor chip can measure the acceleration information in the XYZ direction of a space, the measuring range is +/-16 g, the bandwidth of acceleration signals can be set by configuring a capacitor, the XY-axis acceleration signals are adjustable from 0.5Hz to 1600Hz, and the Z-axis acceleration signals are adjustable from 0.5Hz to 550 Hz.
And the data preprocessing device 12 is used for preprocessing the acceleration information.
It is understood that the preprocessing may include filtering, a/D conversion, intelligent analysis, and the like. Alternatively, the system 1 may filter noise information in the acceleration information based on the filter circuit 121, and further, the microprocessor 122 may be used to convert the acceleration information from analog data to digital acceleration information after removing the noise information, so as to facilitate subsequent processing by a computer. Alternatively, the system 1 may also use the microprocessor 122 to calculate the distribution coordinates of the digital acceleration information in XYZ directions of the current three-dimensional coordinate system.
It can be understood that the microprocessor 122 may employ the latest ultra-low power STM32L432KBKCU6 chip, a 32-bit RISC instruction controller, a maximum operating frequency of 80MHz, and an on-chip 10-channel 12-bit A/D converter to support multiple power management modes, and the peripheral circuits of the microprocessor 122 are shown in FIG. 2. The microprocessor 122 controls the triaxial acceleration sensor chip, the filter circuit and the wireless communication module to work under a preset instruction, finishes the conversion processing and analysis work of data transmitted from a sensor end, encodes the data according to a specified format, and controls the wireless communication module to transmit the data.
Alternatively, as shown in fig. 3, the signal output by the tri-axis acceleration sensor chip may be processed by a filtering circuit composed of an AD8629ARMZ chip, and then the processed information may be transferred to the microprocessor 122. The sensor starts measuring and processing the acceleration signal information under the control of the microprocessor 122, and the acceleration signal is transmitted to the microprocessor in a voltage form for A/D conversion and data analysis processing after passing through the signal amplifying circuit.
In an alternative embodiment, the system 1 may transmit the preprocessed acceleration information to the data monitoring output device 14 through the transmission relay 13, and may output the information by using a wireless communication module. Optionally, when the system adopts the ZigBee communication protocol, the system may use wireless relay to relay the preprocessed acceleration information. Optionally, when the system adopts WIFI or other wireless communication protocols, relay forwarding may not be required.
It should be noted that, as shown in fig. 4, the circuit layout of the wireless communication module may have a working frequency of 2.405 GHz-2.4815 GHz, a zigbee communication protocol, a wireless transmitting power of +20dbm, and a transmitting power of 2000m without shielding an external antenna. The modular design is provided with a PCB antenna and can be externally connected with the antenna. Is connected to the microprocessor 122 via an SPI serial bus.
The repeater can be composed of an explosion-proof shell, a power supply module, a wireless communication module and a 232-to-Ethernet module, supports connection of a plurality of wireless vibration temperature sensors, can set a fixed local area network IP and sends data to a fixed IP address. The repeater is arranged in the sight distance range of the vibration temperature sensor (within the distance of 100M under the condition of no shielding), the wireless vibration temperature sensor acquires vibration information, temperature information, battery electric quantity and signal strength information, and the wireless vibration temperature sensor sends out the vibration information, the battery electric quantity and the signal strength information through wireless transmission, and the repeater receives data and forwards the data to the Ethernet and transmits the data to the server for storage.
The data monitoring output device 14 is used for preprocessing the upper computer of the vibration signal, judging the equipment state, and accumulating and displaying the running time statistics.
The time domain analysis processing module 141 performs statistical analysis and time domain analysis on the vibration digital information to obtain a maximum value, a minimum value, an average value, a peak-peak value, an absolute average value, a variance, a standard deviation, an effective value, a root mean square, a root amplitude, a kurtosis value, a pulse value, a margin value, a waveform value and a baseline value.
It is understood that the statistical analysis module 142 for the shutdown state may perform statistical analysis according to vibration data collected by the device in the shutdown state during an initial period of time, and determine a fluctuation interval of the vibration effective value in the shutdown state through the mean and the variance.
It will be appreciated that the preparation status determining module 143 performs a matching determination on the vibration effective value received in real time and the fluctuation interval generated by the preprocessing and the vibration effective value 142, and if the vibration effective value is matched with the fluctuation interval, the preparation status determining module is in a shutdown status, otherwise, the preparation status determining module is in a startup status.
It will be appreciated that the device operation duration statistics module 144 adds the monitoring time interval in which the two continuous monitoring determinations are in the power-on operation state to the total operation duration of the device, and outputs the total operation duration on the display.
It will be appreciated that the master control module 145 may need to initialize the control of the monitoring point, i.e., remove the existing inaccurate or invalid fluctuation range of the shutdown state, and then restart the monitoring when the fluctuation range of the effective value of the shutdown state of the statistical device needs to be re-analyzed under special conditions, such as inaccurate or changed fluctuation range of the shutdown state. Or the monitoring time interval is adjusted according to the actual situation so as to ensure that the error of the running time of the equipment obtained by statistics is acceptable.
It should be noted that, the process of determining the on-off state of the device based on the vibration signal may be implemented in the front end of the monitoring system 1, i.e. the sensor terminal, or may be implemented in the rear end of the monitoring system 1, i.e. the data monitoring output device 14, and any implementation manner is within the protection scope of the embodiments of the present invention.
In the embodiment of the invention, the running time of the display equipment is analyzed through preprocessing the collected sensor acceleration data and the data monitoring output device, so that the blank of practical application of monitoring the running time of the equipment through the vibration sensor is filled, and the running time of the equipment can be obtained from the outside on the basis of not accessing and interfering an original system.
Those skilled in the art will appreciate that implementing all or part of the above-described methods in the embodiments may be accomplished by computer programs stored in a computer-readable storage medium, which when executed, may include the steps of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), or the like.
The foregoing disclosure is illustrative of the present invention and is not to be construed as limiting the scope of the invention, which is defined by the appended claims.
Claims (5)
1. A method for monitoring the operational duration of a device based on a vibration sensor, comprising:
collecting vibration signals of equipment through a vibration sensor;
preprocessing the vibration information and obtaining time domain related information;
whether the equipment is in a starting state or not is analyzed through classification statistics or machine learning of time domain information;
through continuous monitoring analysis, if the two continuous monitoring devices are in a starting state, accumulating and metering the interval duration between the two monitoring devices to obtain the total operation duration of the devices; and the statistical error of the total operation time length can be reduced by shortening the vibration acquisition interval time.
2. The method of claim 1, wherein, in acquiring a vibration signal of a device with the vibration sensor, the method further comprises:
collecting vibration signals of the device by the vibration sensor includes: a displacement signal, a velocity signal, and an acceleration signal;
collecting vibration signals of the device by the vibration sensor includes: unidirectional signals, 2-way signals, three-dimensional 3-way signals and multi-way signals.
The acquisition mode of the vibration signal of the vibration sensor acquisition equipment further comprises the following steps: real-time acquisition and offline data acquisition.
The real-time acquisition and transmission mode of the vibration signals of the vibration sensor acquisition equipment comprises the following steps: and (5) wired acquisition transmission and wireless acquisition transmission.
Sensors combined by single or multiple content as described above are within the scope of the claims.
The device for collecting the device by the vibration sensor comprises: all devices or components that have a vibration feedback difference between start-up and shut-down.
3. The method of claim 1, wherein, when preprocessing the vibration information and obtaining time-domain related parameters, the method further comprises:
filtering noise information in the vibration information;
converting the vibration information after the filtering treatment into digital information from analog data;
and carrying out statistical analysis and time domain analysis on the vibration digital information to obtain a maximum value, a minimum value, an average value, a peak-to-peak value, an absolute average value, a variance, a standard deviation, an effective value, a root mean square, a root amplitude value, a kurtosis value, a pulse value, a margin value, a waveform value and a base line.
4. The method of claim 1, wherein the device is in an on state or not is analyzed by classification statistics or machine learning of time domain information. The method further comprises the steps of:
a threshold value is preset according to data statistics analysis of vibration data of the sensor characteristics in a shutdown state or a static state, wherein the value is larger than or equal to the threshold value and is in a startup state, and the value is smaller than or equal to the threshold value and is in a shutdown state;
counting and analyzing a vibration interval of a shutdown state according to vibration data of the sensor characteristics in the shutdown or static state, wherein the vibration accords with the interval to be the shutdown state, and otherwise, the vibration accords with the startup state;
and performing machine learning according to vibration data of the sensor characteristics in a shutdown state or a static state to obtain a shutdown model, wherein the model is suitable for being in the shutdown state, and is otherwise in the startup state.
5. The method according to claim 1, wherein by continuous monitoring analysis, if the continuous monitoring device is in a power-on state for both times, the total operation time of the device is obtained by accumulating and metering the interval time between the two monitoring; and the statistical error of the total operation time length can be reduced by shortening the vibration acquisition interval time. The method further comprises the steps of:
through the continuous monitoring vibration signal of fixed interval time, if the continuous vibration acquisition analysis equipment is monitored to be in the starting state, the time between the two monitoring, namely the fixed interval time, is added to the total running time of the equipment, and otherwise, the total running time is not added.
The interval time of continuous acquisition is dynamically adjusted according to the actual condition of the site through a sensor intelligent control program, if the continuous vibration acquisition analysis equipment is monitored to be in a starting state, the time between the two monitoring is added to the total running time of the equipment, and the other conditions are not added.
Because the error of the total running time is always smaller than the interval of 2 acquisition periods in the start-stop period of single equipment, the statistical error of the total running time can be obviously reduced by shortening the vibration acquisition interval time as much as possible.
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