CN111980902B - Monitoring system and monitoring method for reciprocating compressor - Google Patents
Monitoring system and monitoring method for reciprocating compressor Download PDFInfo
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- CN111980902B CN111980902B CN201910433980.7A CN201910433980A CN111980902B CN 111980902 B CN111980902 B CN 111980902B CN 201910433980 A CN201910433980 A CN 201910433980A CN 111980902 B CN111980902 B CN 111980902B
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F04—POSITIVE - DISPLACEMENT MACHINES FOR LIQUIDS; PUMPS FOR LIQUIDS OR ELASTIC FLUIDS
- F04B—POSITIVE-DISPLACEMENT MACHINES FOR LIQUIDS; PUMPS
- F04B51/00—Testing machines, pumps, or pumping installations
Abstract
The invention provides a monitoring system and a monitoring method of a reciprocating compressor, wherein the monitoring system of the reciprocating compressor comprises a sensor and an analysis controller, wherein the sensor acquires an action signal when the reciprocating compressor runs; the analysis controller receives the action signal, converts the action signal into an angle signal and matches the action signal with the angle signal to form state information; the analysis controller compares the status information with a template information through an operation program to determine whether the status information conforms to the template information, so as to obtain the operating condition of the reciprocating compressor; therefore, the detection can be performed without process information, and the working condition of the reciprocating compressor can be accurately controlled.
Description
Technical Field
The present invention relates to a monitoring system and method, and more particularly, to a monitoring system and method for a reciprocating compressor.
Background
The reciprocating compressor is a compressor driven by a crankshaft driving a piston, when the crankshaft reciprocates, an air inlet valve is firstly opened, an exhaust valve is closed, the inlet air enters a compression cylinder through the air inlet valve, then the air valve is closed, the volume of the compression cylinder is reduced by the motion of the piston, the air is compressed, and then the exhaust valve is opened to discharge high-pressure air.
In the operation process of the reciprocating compressor, each moving part can make rhythmic normal sounds consistent with the rotating speed, and experienced diagnostic personnel can judge whether the operation of the compressor is normal or not from different sounds. When the sound has harsh noise, impact sound and irregular rhythm, they can immediately judge that the machine is not working normally, and can even judge the approximate part of the fault.
However, the judgment is carried out manually in a sound mode, the accuracy is not high, and the judgment error is easy to occur; therefore, in order to improve the manual judgment method, an intelligent system judgment method is developed, for example: chinese patent No. CN102797671 discloses a method and apparatus for detecting a fault of a reciprocating compressor, which needs to obtain a vibration signal parameter characteristic of the reciprocating compressor and a thermal parameter characteristic including an air intake temperature, an exhaust temperature, an air intake pressure and an exhaust pressure of a cylinder, generate a state characteristic index set according to the vibration signal parameter, generate a working condition characteristic index set according to the vibration signal parameter characteristic and the thermal parameter characteristic, and generate a fault detection result according to the state characteristic index set and an industrial and mining characteristic index set.
However, in the aforementioned patent, the vibration signal parameters must be combined with a large amount of data such as process data (thermal parameter characteristics including cylinder intake temperature, exhaust temperature, intake pressure and exhaust pressure) to break the machine state of the reciprocating compressor, so that if one of the parameter characteristics is abnormal, an accurate fault detection result cannot be obtained.
Further, as disclosed in the above patent specification, it is necessary to install acceleration sensors in a crankshaft bearing seat, an outer surface of a cylinder liner and an air valve seat of a reciprocating compressor, to measure the vibration signal parameters, and to utilize the temperature sensor and the pressure sensor to measure the air intake temperature, the air exhaust temperature, the air intake pressure and the air exhaust pressure of the cylinder of the reciprocating compressor respectively, to obtain the process data (thermal parameters characteristics including cylinder inlet temperature, exhaust temperature, inlet pressure and exhaust pressure), that is, the aforesaid patent requires at least 5 sensors to obtain the information for determining the condition of the reciprocating compressor, therefore, when the fault detection of the reciprocating compressor is performed according to the above patent, the installation cost is too high, and it takes a lot of time to process data generated by each sensor, which is relatively long time to obtain the fault detection result.
Disclosure of Invention
In order to solve the above problems, the present invention provides a monitoring system and a monitoring method for a reciprocating compressor, wherein a single sensor is used to obtain an operation signal during the operation of the reciprocating compressor, so as to perform a detection and determination of the reciprocating compressor, thereby accurately controlling the status of the machine of the reciprocating compressor.
An embodiment of the present invention provides a monitoring system of a reciprocating compressor, including: a sensor for generating an operation signal when the reciprocating compressor is operated; the analysis controller is connected with the sensor through signals and receives the action signal, and is provided with a processing module and a judging module, wherein the processing module converts the action signal into an angle signal and matches the action signal with the angle signal to form state information; the judging module compares the status information with a template information by an operation program to judge whether the status information conforms to the template information, so as to obtain the operating condition of the reciprocating compressor.
In one embodiment, the sensor is mounted to a cylinder of the reciprocating compressor; the sensor is an acceleration gauge; the action signal is an acceleration signal when the reciprocating compressor runs; the operation program is a supervised neural network learning, and the determination module determines whether the status information matches the template information through the operation program.
In one embodiment, the processing module integrates the motion signal into a motion speed signal, and the processing module converts the motion speed signal into an angle signal.
In one embodiment, the template information has an angle corresponding to each component of the reciprocating compressor and an operation signal corresponding to each component; the analysis controller has a memory module, and the memory module stores the template information.
In one embodiment, the template information is state information processed by capturing an operation signal when the reciprocating compressor operates, and the state information is established and stored in the memory module.
In one embodiment, the operating program determines a degree of difference between the state information and the template information to generate a degree of difference information.
Another embodiment of the present invention provides a monitoring method of a reciprocating compressor, which includes the steps of: a measurement step: generating an operation signal when the reciprocating compressor operates through a sensor; and (3) an analysis step: receiving the action signal generated by the sensor through an analysis controller, converting the action signal into an angle signal by the analysis controller, and matching the action signal with the angle signal to form state information; and a judging step: the analysis controller compares the status information with a template information by an operation program to determine whether the status information matches the template information, so as to obtain the operation condition of the reciprocating compressor.
In one embodiment, the analysis controller integrates the motion signal into a motion speed signal, and converts the motion speed signal into an angle signal.
In one embodiment, the present invention further comprises a learning step: the sensor generates an operation signal when the reciprocating compressor is initially operated or an abnormality occurs for the first time, processes the operation signal through the analysis controller to generate state information, and establishes the state information as template information and stores the template information in the analysis controller.
In one embodiment, the analysis controller determines a difference between the state information and the template information by the operation program to generate a difference degree information to obtain an abnormal degree of the reciprocating compressor.
Through the above, the invention can detect and judge only through the action signal obtained by the single sensor, and can accurately grasp the working condition of the reciprocating compressor; the method can improve the inaccuracy of the existing manual judgment method, or can judge the abnormal condition of the reciprocating compressor by installing various sensors and detecting parameter signals.
Drawings
FIG. 1 is a block diagram of a detection system architecture according to the present invention.
FIG. 2 is a block diagram of a monitoring method according to the present invention.
FIG. 3 is a schematic diagram of the determination module learning the travel template information calculation formula from the status information by the calculation program according to the present invention.
FIG. 4 is a schematic diagram illustrating the comparison of the status information and the template information by the determining module according to the present invention.
FIG. 5 is a schematic view of an embodiment of the present invention.
FIG. 6 is a schematic diagram (one) of the template information of the present invention, showing the normal state of the reciprocating compressor.
FIG. 7 is a schematic diagram of template information of the present invention (II) showing crosshead damage of a reciprocating compressor.
FIG. 8 is a schematic diagram (III) of the template information of the present invention, showing the top and bottom dead center abnormality of the piston of the reciprocating compressor.
Description of the reference numerals
Reciprocating compressor 1
Monitoring system 100 for reciprocating compressor
Processing module 21
Angle signal 211'
Measuring step S1
Analysis step S2
Judgment step S3
Step S4 is learned.
Detailed Description
The technical solution in the embodiments of the present invention is clearly and completely described below with reference to the drawings in the embodiments of the present invention. In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, but the present invention may be practiced in other ways than those specifically described and will be readily apparent to those of ordinary skill in the art without departing from the spirit of the present invention, and therefore the present invention is not limited to the specific embodiments disclosed below.
To facilitate the explanation of the present invention, the central ideas shown in the above summary are shown in the following embodiments. Various objects in the embodiments are depicted in terms of scale, dimensions, deformation, or displacement suitable for illustration, rather than in terms of actual component proportions, as previously described.
Referring to fig. 1 to 8, the present invention provides a monitoring system 100 for a reciprocating compressor, including:
a sensor 10 for generating an operation signal 11 when the reciprocating compressor 1 is operated; in the embodiment of the present invention, the sensor 10 is erected on the cylinder of the reciprocating compressor 1, as shown in fig. 5, but the erection position of the sensor 10 is not limited thereto, and the sensor 10 only needs to be capable of generating the operation signal 11 when the reciprocating compressor 1 operates; the sensor 10 is an accelerometer and the motion signal 11 is an acceleration signal generated when the reciprocating compressor 1 is running.
An analysis controller 20 connected to the sensor 10 for receiving the motion signal 11, the analysis controller 20 having a processing module 21, the processing module 21 for converting the motion signal 11 into an angle signal 211; the processing module 21 can directly process the motion 0 signal 11 as the acceleration into the angle signal 211, or the processing module 21 integrates the motion signal 11 into a motion velocity signal, and the processing module 21 converts the motion velocity signal into the angle signal 211'.
Further by way of example, when the motion signal 11 is 10Hz, indicating that 10 cycles occur in the 1 second motion signal 11 (one cycle indicates 360 degrees), and the cycle time is 0.1 second, the 0.1 second motion signal 11 is converted to be indicated by 360 degrees, so that the 1 second motion signal 11 indicates 10 rotations of 360 degrees, and thus the motion signal 11 can be converted to the angle signal 211; moreover, the operation stroke of the reciprocating compressor 1 is fixed, and each angle or angle interval represents each element of the reciprocating compressor 1 in terms of 360 degrees of rotation, that is, the action signal 11 generated by each angle or angle interval can be represented as the state of each element.
Meanwhile, the processing module 21 matches the operation signal 11 with the angle signal 211 to form a status information, where the status information includes the angle corresponding to each component of the reciprocating compressor 1 and the operation signal 11 corresponding to each component, that is, the status information is the information corresponding to the operation signal 11 generated by the reciprocating compressor 1 at each angle; as shown in fig. 6, status information indicating that each component of the reciprocating compressor 1 is in a normal state.
The analysis controller 20 further has a determination module 22, the determination module 22 compares the status information with a template information 23 through an operation program to determine whether the status information matches the template information 23, so as to obtain the operation status of the reciprocating compressor 1, as shown in fig. 4; wherein the operation program is a supervised neural network learning.
The analysis controller 20 has a memory module 24, the memory module 24 is used to store the template information 23, the template information 23 is the status information processed by the action signal 11 generated when the reciprocating compressor 1 is operated for the first time or abnormal for the first time, the processing module 21 of the analysis controller 20 will learn by the operation program, and establish the learned status information as the template information 23 to be stored in the memory module 24, as shown in fig. 1 and fig. 3.
The template information 23 has the angle corresponding to each component of the reciprocating compressor 1, the action signal 11 corresponding to each component and the angle signal 211 corresponding to the action signal 11; and the operating signal 11 as acceleration processes the angle signal 211 and the state information formed by matching the operating signal 11 to judge whether the crosshead of the reciprocating compressor 1 is worn out, whether the intake and exhaust operations are abnormal or whether the cylinder is collided; converting the operating speed signal into an angle signal 211' and state information formed by matching the operating signal 11, so as to determine whether the crankshaft of the reciprocating compressor 1 is balanced, whether the crankshaft is eccentric or whether the piston rod is abnormal; referring to FIG. 7, template information 23 of crosshead wear is shown; FIG. 8 shows template information 23 indicating the abnormality of the top and bottom dead centers of the piston.
In addition, the judging module 22 judges the difference between the state information and the template information 23 through the operation program to generate a difference information, that is, the judging module 22 can first judge whether the state information matches the template information 23 to confirm whether the reciprocating compressor 1 is abnormal, and when the reciprocating compressor 1 is abnormal, the judging module 22 can calculate the abnormal severity of the reciprocating compressor 1 through the operation program, that is, the abnormal degree information, for example: the wear of the crosshead was about 10%.
By using the above-mentioned monitoring system 100 of the reciprocating compressor of the present invention, in practical applications, it can be determined whether the reciprocating compressor 1 is abnormal or not by using the monitoring method of the reciprocating compressor.
The monitoring method of the reciprocating compressor of the present invention comprises the steps of:
measurement step S1: a sensor 10 is mounted on the cylinder of the reciprocating compressor 1, and when the reciprocating compressor 1 is operated, the sensor 10 generates an operation signal 11 when the reciprocating compressor 1 is operated.
Analysis step S2: the sensor 10 transmits the motion signal 11 to the analysis controller 20, and the analysis controller 20 receives the motion signal 11 and converts the motion signal 11 into the angle signal 211, or the analysis controller 20 integrates the motion signal 11 into a motion speed signal and converts the motion speed signal into the angle signal 211'; then, the analysis controller 20 matches the operation signal 11 with the angle signal 211 (angle signal 211') to form status information.
Determination step S3: the analysis controller 20 compares the status information with the template information 23 by the operation program to determine whether the status information matches the template information 23, so as to obtain the operation condition of the reciprocating compressor 1, as shown in fig. 1 and 4; wherein, when the analysis controller 20 determines that the reciprocating compressor 1 is abnormal, the analysis controller 20 will determine the difference between the status information and the template information 23 through the operation program to generate the difference information, so as to obtain the abnormal degree of the condition of the reciprocating compressor 1, and the user can determine whether to replace or maintain the components in time according to the abnormal degree of the condition.
Learning step S4: when the reciprocating compressor 1 initially operates or initially generates an abnormality, the operation signal 11 generated when the reciprocating compressor 1 initially operates or initially generates an abnormality can be obtained through the measuring step S1; next, the angle signal 211 is obtained through calculation in the analyzing step S2, and the state information is learned and established as the template information 23 through the calculation program and stored in the analyzing controller 20, as shown in fig. 1 and 3.
After the template information 23 for determination is established in the reciprocating compressor 1, the state information can be obtained through the measuring step S1 and the analyzing step S2 each time the reciprocating compressor 1 is operated, and the condition of the reciprocating compressor 1 can be obtained through the determining step S3.
Through the foregoing, the effects that the present invention can achieve are as follows:
firstly, the monitoring system 100 of the reciprocating compressor of the present invention can perform detection and judgment only by the action signal 11 obtained by the single sensor 10, so as to accurately grasp the operating condition of the reciprocating compressor 1; therefore, it is able to improve the need of installing various sensors 10 to determine the abnormal condition of the reciprocating compressor 1 by various detection parameter signals, thereby achieving the purpose of simply and rapidly obtaining the detection result.
Secondly, the analysis controller 20 of the monitoring system 100 of the reciprocating compressor of the present invention can obtain the abnormal degree of the machine condition of the reciprocating compressor 1 through the operation program, so as to provide the user with the ability to judge whether to replace or maintain the components in time according to the abnormal degree of the machine condition, thereby providing the flexible scheduling performance in the actual industry.
It is to be understood that the described embodiments are merely a few embodiments of the invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Claims (10)
1. A monitoring system of a reciprocating compressor, characterized in that it comprises:
a sensor for generating an operation signal when the reciprocating compressor is operated; and
the analysis controller is connected with the sensor through signals and receives the action signal, and is provided with a processing module and a judging module, wherein the processing module converts the action signal into an angle signal and matches the action signal with the angle signal to form state information; the judging module compares the status information with a template information through an operation program to judge whether the status information conforms to the template information, so as to obtain the operating condition of the reciprocating compressor;
wherein, the state information has the angle corresponding to each element of the reciprocating compressor and the action signal corresponding to each element; the template information has angles corresponding to the elements of the reciprocating compressor, action signals corresponding to the elements and angle signals corresponding to the action signals.
2. The monitoring system of a reciprocating compressor according to claim 1, wherein the sensor is mounted to a cylinder of the reciprocating compressor; the sensor is an accelerometer; the action signal is an acceleration signal when the reciprocating compressor runs; the operation program is a supervised neural network learning, and the determination module determines whether the status information matches the template information through the operation program.
3. The monitoring system of reciprocating compressor of claim 2, wherein the processing module integrates the motion signal into a motion speed signal, and the processing module converts the motion speed signal into an angle signal.
4. The monitoring system of reciprocating compressor of claim 1, wherein the analysis controller has a memory module storing the template information.
5. The monitoring system for reciprocating compressor according to claim 4, wherein the template information is a status information processed by capturing an operation signal when the reciprocating compressor is operated or an abnormality occurs for the first time, and the status information is set up and stored in the memory module.
6. The monitoring system of reciprocating compressor of claim 1 or 2, wherein the operation program judges a degree of difference between the state information and the template information to generate a degree of difference information.
7. A method for monitoring a reciprocating compressor, characterized in that it comprises the following steps:
the measurement step comprises: generating an operation signal when the reciprocating compressor operates through a sensor;
and (3) an analysis step: receiving the action signal generated by the sensor through an analysis controller, converting the action signal into an angle signal by the analysis controller, and matching the action signal with the angle signal to form state information; and
a judging step: the analysis controller compares the status information with a template information through an operation program to determine whether the status information conforms to the template information, so as to obtain the operating condition of the reciprocating compressor;
wherein, the state information comprises angles corresponding to each element of the reciprocating compressor and action signals corresponding to each element; the template information has angles corresponding to the elements of the reciprocating compressor, action signals corresponding to the elements and angle signals corresponding to the action signals.
8. The method of claim 7, wherein the analysis controller integrates the motion signal into a motion speed signal and converts the motion speed signal into an angle signal.
9. The monitoring method of a reciprocating compressor according to claim 7, further comprising a learning step of: the sensor generates the action signal when the reciprocating compressor is initially operated or an abnormality occurs for the first time, the analysis controller processes the action signal to generate the state information, and the state information is established as the template information and stored in the analysis controller.
10. The method of claim 7, wherein the analysis controller determines a difference between the state information and the template information by the operation program to generate a difference degree information to obtain a degree of abnormality of the reciprocating compressor.
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| CN201910433980.7A CN111980902B (en) | 2019-05-23 | 2019-05-23 | Monitoring system and monitoring method for reciprocating compressor |
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102913432A (en) * | 2012-11-08 | 2013-02-06 | 北京化工大学 | Reciprocating compressor fault diagnosis method based on dimensionless indexes |
| CN107756139A (en) * | 2016-08-18 | 2018-03-06 | 王智中 | Tool state detection system and method |
| CN109707615A (en) * | 2019-02-26 | 2019-05-03 | 东北石油大学 | Reciprocating compressor method for diagnosing faults based on fine multi-fractal |
| CN109779894A (en) * | 2018-12-29 | 2019-05-21 | 西安交通大学 | A kind of reciprocating compressor fault diagnosis system and method based on neural network algorithm |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| US20180283368A1 (en) * | 2017-03-28 | 2018-10-04 | Uop Llc | Determining quality of gas for rotating equipment in a petrochemical plant or refinery |
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Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102913432A (en) * | 2012-11-08 | 2013-02-06 | 北京化工大学 | Reciprocating compressor fault diagnosis method based on dimensionless indexes |
| CN107756139A (en) * | 2016-08-18 | 2018-03-06 | 王智中 | Tool state detection system and method |
| CN109779894A (en) * | 2018-12-29 | 2019-05-21 | 西安交通大学 | A kind of reciprocating compressor fault diagnosis system and method based on neural network algorithm |
| CN109707615A (en) * | 2019-02-26 | 2019-05-03 | 东北石油大学 | Reciprocating compressor method for diagnosing faults based on fine multi-fractal |
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