CN116437243B - Remote diagnosis method for natural gas metering analysis equipment - Google Patents
Remote diagnosis method for natural gas metering analysis equipment Download PDFInfo
- Publication number
- CN116437243B CN116437243B CN202211652232.6A CN202211652232A CN116437243B CN 116437243 B CN116437243 B CN 116437243B CN 202211652232 A CN202211652232 A CN 202211652232A CN 116437243 B CN116437243 B CN 116437243B
- Authority
- CN
- China
- Prior art keywords
- value
- alarm
- edge processor
- flow
- flowmeter
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- VNWKTOKETHGBQD-UHFFFAOYSA-N methane Chemical compound C VNWKTOKETHGBQD-UHFFFAOYSA-N 0.000 title claims abstract description 142
- 239000003345 natural gas Substances 0.000 title claims abstract description 71
- 238000000034 method Methods 0.000 title claims abstract description 65
- 238000004171 remote diagnosis Methods 0.000 title claims description 19
- 238000001514 detection method Methods 0.000 claims abstract description 160
- 238000012544 monitoring process Methods 0.000 claims abstract description 55
- 230000004044 response Effects 0.000 claims abstract description 45
- 230000002159 abnormal effect Effects 0.000 claims abstract description 10
- 230000005856 abnormality Effects 0.000 claims abstract description 9
- 230000008859 change Effects 0.000 claims description 42
- 238000012360 testing method Methods 0.000 claims description 25
- 238000004364 calculation method Methods 0.000 claims description 11
- 238000012423 maintenance Methods 0.000 claims description 10
- 230000008569 process Effects 0.000 claims description 9
- 238000002604 ultrasonography Methods 0.000 claims description 7
- 239000012530 fluid Substances 0.000 claims description 6
- 230000007488 abnormal function Effects 0.000 claims description 4
- 238000005259 measurement Methods 0.000 claims description 3
- 238000010438 heat treatment Methods 0.000 claims description 2
- 238000003745 diagnosis Methods 0.000 abstract description 19
- 238000002405 diagnostic procedure Methods 0.000 abstract description 2
- 230000006870 function Effects 0.000 description 6
- 238000010586 diagram Methods 0.000 description 5
- 230000000007 visual effect Effects 0.000 description 5
- 230000003993 interaction Effects 0.000 description 4
- 239000007788 liquid Substances 0.000 description 3
- 230000006978 adaptation Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 2
- 238000004891 communication Methods 0.000 description 2
- 238000012935 Averaging Methods 0.000 description 1
- 238000013475 authorization Methods 0.000 description 1
- 238000011088 calibration curve Methods 0.000 description 1
- 238000004590 computer program Methods 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 238000013500 data storage Methods 0.000 description 1
- 230000009977 dual effect Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000007689 inspection Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04Q—SELECTING
- H04Q9/00—Arrangements in telecontrol or telemetry systems for selectively calling a substation from a main station, in which substation desired apparatus is selected for applying a control signal thereto or for obtaining measured values therefrom
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
Landscapes
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Health & Medical Sciences (AREA)
- Computing Systems (AREA)
- General Health & Medical Sciences (AREA)
- Medical Informatics (AREA)
- Signal Processing (AREA)
- Measuring Volume Flow (AREA)
Abstract
The present disclosure relates to a remote diagnostic method of a natural gas gauge analysis device, comprising: the natural gas metering diagnostic system comprises: one or more monitoring stations interconnected by a network, the monitoring stations including an edge processor, and a detection unit and an alarm unit respectively connected to the edge processor. The method comprises the following steps: the edge processor receives the detection data sent by the detection unit; and the edge processor diagnoses the detection unit according to the detection data, and controls the alarm unit to alarm in response to determining that the detection unit diagnoses abnormality. According to the application, after the edge processor determines that the diagnosis is abnormal, the alarm unit is controlled to alarm, and the edge processor replaces the remote central data acquisition server. The problem that the remote central data acquisition server cannot perform diagnosis work because data cannot be obtained due to network faults is avoided, and the problem that the diagnosis work cannot be performed is avoided.
Description
Technical Field
The disclosure relates to the technical field of natural gas detection, in particular to a remote diagnosis method of natural gas metering analysis equipment.
Background
The natural gas metering and diagnosing system of the related art is provided with a remote data acquisition center server, and data acquisition and diagnosis are carried out on a plurality of monitoring stations through the remote data acquisition center server. If the network communication between the data acquisition center server and each monitoring station is interrupted, the real-time data acquisition, storage and diagnosis functions cannot be realized.
Disclosure of Invention
To overcome the problems in the related art, the present disclosure provides a remote diagnosis method of a natural gas gauge analysis apparatus to solve the above-mentioned problems.
According to a first aspect of embodiments of the present disclosure, there is provided a method of remote diagnosis of a natural gas gauge analysis apparatus, the method comprising:
the natural gas metering diagnostic system comprises: one or more monitoring stations interconnected by a network;
For any one monitoring station, the monitoring station includes: the device comprises an edge processor, and a detection unit and an alarm unit which are respectively connected with the edge processor;
The method comprises the following steps:
the edge processor receives detection data sent by the detection unit;
And the edge processor diagnoses the detection unit according to the detection data, and controls the alarm unit to alarm in response to determining that the detection unit diagnoses abnormality.
In one embodiment, the natural gas gauge diagnostic system further comprises: a flow computer; the flow computer is respectively connected with the detection unit and the edge processor;
the method further comprises the steps of:
the flow computer processes the detection data to obtain a first heat value;
the edge processor receives the first heat value sent by the flow computer;
the edge processor determines a second heat value according to the detection data;
And controlling the alarm unit to alarm in response to the difference between the first heat value and the second heat value being greater than a preset first heat value difference threshold.
The flow computer processes according to the detection data to obtain a first standard condition flow value;
the edge processor receives the first standard condition flow value sent by the flow computer;
The edge processor determines a second standard condition flow value according to the detection data;
and controlling the alarm unit to alarm in response to the difference between the first standard condition flow value and the second standard condition flow value being greater than a preset first standard condition flow value difference threshold.
In one embodiment, the detection unit comprises a chromatographic analyzer;
the edge processor diagnoses the detection unit according to the detection data, and the edge processor comprises:
the edge processor determines a third heating value output by the chromatograph;
and controlling the alarm unit to alarm in response to the difference value between the second heat value and the third heat value being greater than a preset second heat value difference threshold.
In one embodiment, the detection unit comprises a turbine flow meter;
the edge processor diagnoses the detection unit according to the detection data, and the edge processor comprises:
the edge processor receives a first frequency signal and a second frequency signal which are respectively output by the turbine flowmeter according to the flow value;
And controlling the alarm unit to alarm in response to the difference value between the first flow value corresponding to the first frequency signal and the second flow value corresponding to the second frequency signal being greater than a preset turbine flowmeter flow difference value threshold.
In one embodiment, the detection unit comprises an ultrasonic flow meter;
the edge processor diagnoses the detection unit according to the detection data, and the edge processor comprises:
acquiring a theoretical standard instantaneous flow value and an actual instantaneous measurement flow value of the ultrasonic flowmeter in a rated working state;
controlling the alarm unit to alarm in response to the difference value between the actual instantaneous measured flow value of the ultrasonic flowmeter in the rated working state and the theoretical standard instantaneous flow value being greater than a preset ultrasonic flowmeter flow difference value threshold;
Acquiring an actual measured ultrasonic sound velocity value and a theoretical calculated sound velocity value of the ultrasonic flowmeter in a rated working state;
and controlling the alarm unit to alarm in response to the difference value between the actual measured ultrasonic sound velocity value and the theoretical calculated sound velocity value being greater than a preset first ultrasonic sound velocity difference value threshold.
In one embodiment, the detection unit further comprises a vibration sensor disposed on the turbine flow meter;
the edge processor diagnoses the detection unit according to the detection data, and the edge processor comprises:
acquiring a vibration value of the turbine flowmeter detected by the vibration sensor;
And controlling the alarm unit to alarm in response to the vibration value of the turbine flowmeter being greater than a preset vibration threshold value.
In one embodiment, the detection unit comprises a flow meter;
the edge processor diagnoses the detection unit according to the detection data, and the edge processor comprises:
A second comparison test flowmeter is installed on a pipeline where the flowmeter is located in series, so that the detected instantaneous flow of the second comparison test flowmeter is identical to that of the flowmeter;
The edge processor obtains the second comparison test flowmeter flow value;
and controlling the alarm unit to alarm in response to the difference between the second comparison test flowmeter flow value and the detected instantaneous flow value of the flowmeter being greater than a predetermined flowmeter first flow value difference threshold.
In one embodiment, the detection unit comprises an ultrasonic flow meter; the detection data includes: the ultrasonic parameters of the ultrasonic flowmeter and the natural gas parameters;
The relevant parameters of the ultrasound include: sound speed deviation, gain value, single reflection sound channel gain value ratio, double reflection sound gain value ratio, gain value mismatch degree and signal to noise ratio;
The relevant parameters of the natural gas include natural gas flow speed ratio, asymmetry factor, fluid profile coefficient, swirl angle and turbulence;
The edge processor diagnoses the detection unit according to the detection data, and controls the alarm unit to alarm in response to determining that the detection unit diagnoses abnormality, and the edge processor comprises the following steps:
For any one relevant parameter, acquiring a standard value of the relevant parameter;
and controlling the alarm unit to alarm in response to the difference value between the actual measured value of the related parameter and the standard value being larger than a preset difference value threshold.
In one embodiment, the method further comprises:
Determining a first grading value of each ultrasonic according to a preset grading value and a weight of a related parameter of each ultrasonic;
determining a second grading value of the natural gas according to the preset grading value and the weight of the related parameter of each natural gas;
Determining a score total value of the ultrasonic flowmeter according to the first score value of the ultrasonic related parameter and the second score value of the natural gas related parameter;
and controlling the alarm unit to alarm in response to the score total value being smaller than a preset score total value threshold value.
In one embodiment, the detection unit includes: a temperature sensor and a pressure sensor;
the edge processor diagnoses the detection unit according to the detection data, and the edge processor comprises:
Acquiring historical data of the temperature sensor;
determining a threshold value of the temperature sensor and a change rate threshold value according to the historical data;
Calibrating the temperature sensor;
determining a detected temperature value of the calibrated temperature sensor, and a rate of change of the temperature value;
Controlling the alarm unit to alarm in response to the detected temperature value being greater than the temperature threshold value and/or the detected temperature value change rate being greater than the temperature value change rate threshold value;
the edge processor diagnoses the detection unit according to the detection data, and the edge processor comprises:
Acquiring historical data of the pressure sensor;
determining a threshold value of the pressure sensor and a change rate threshold value according to the historical data;
calibrating the pressure sensor;
Determining a detected pressure value of the calibrated pressure sensor, and a rate of change of the pressure value;
And controlling the alarm unit to alarm in response to the detected pressure value being greater than the threshold value and/or the change rate of the pressure value being greater than the change rate threshold value.
According to a second aspect of embodiments of the present disclosure, a remote diagnostic device for a natural gas gauge analysis apparatus is applied to the edge processor described above. The natural gas metering diagnostic system comprises: one or more monitoring stations interconnected by a network; for any one monitoring station, the monitoring station includes: the device comprises an edge processor, and a detection unit and an alarm unit which are respectively connected with the edge processor;
the device comprises: the receiving module is used for receiving the detection data obtained by the detection unit for detecting the natural gas of the monitoring station and sending the detection data;
and the diagnosis module is used for diagnosing the detection unit according to the detection data, and controlling the alarm unit to alarm in response to the determination that the detection unit diagnoses abnormality.
According to a third aspect of the embodiments of the present disclosure, there is provided an electronic device provided in the above-mentioned monitoring station, including: the edge processor described above; a memory for storing the edge processor executable instructions; wherein the edge processor is configured to execute the executable instructions to implement the steps of the method performed by the edge processor provided by the first aspect of the present disclosure.
According to a fourth aspect of embodiments of the present disclosure, there is provided a non-transitory computer readable storage medium having stored thereon computer program instructions which, when executed by a processor, implement the steps of the method provided by the first aspect of the present disclosure as described above.
The technical scheme provided by the embodiment of the disclosure can comprise the following beneficial effects: according to the method, an edge processor is arranged in each monitoring station, the edge processor diagnoses the detection unit according to the detection data, and the alarm unit is controlled to alarm after the detection unit is determined to have abnormal diagnosis. The diagnosis of the remote central data acquisition server in the related art is carried out by putting down the diagnosis work on the edge processor, and the edge processor replaces the work of the remote central data acquisition server. Therefore, the problem that the remote central data acquisition server cannot perform diagnosis work because the remote central data acquisition server cannot acquire data due to network faults can be avoided.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the disclosure and together with the description, serve to explain the principles of the disclosure.
FIG. 1 is a schematic diagram of a remote diagnostic system of a natural gas liquids analysis facility, according to an exemplary embodiment;
FIG. 2 is a flow chart illustrating a method of remote diagnosis of a natural gas liquids analysis facility, according to an exemplary embodiment;
FIG. 3 is a schematic diagram of a specific flowmeter arrangement according to an exemplary embodiment;
FIG. 4 is a graph illustrating a dry-standard versus real-flow calibration state relative sound speed deviation plot according to an example embodiment;
FIG. 5 is a schematic diagram of a remote diagnostic device of a natural gas liquids analysis facility, according to an exemplary embodiment;
fig. 6 is a schematic diagram illustrating the construction of an alarm circuit according to an exemplary embodiment.
Detailed Description
Reference will now be made in detail to exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numbers in different drawings refer to the same or similar elements, unless otherwise indicated. The implementations described in the following exemplary examples are not representative of all implementations consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with some aspects of the present disclosure as detailed in the accompanying claims.
It should be noted that, all actions of acquiring signals, information or data in the present application are performed under the condition of conforming to the corresponding data protection rule policy of the country of the location and obtaining the authorization given by the owner of the corresponding device.
The application provides a remote diagnosis method of natural gas metering and analyzing equipment, and a remote diagnosis system of the natural gas metering and analyzing equipment comprises the following steps: one or more monitoring stations interconnected by a network; for any one monitoring station, the monitoring station includes: the device comprises an edge processor, and a detection unit and an alarm unit which are respectively connected with the edge processor. In each monitoring station, the number of the flow computers and the detection units can be one or more, and when the number is more, the flow computers and the detection units in each group are divided into a plurality of groups, and the flow computers and the detection units in each group are in one-to-one correspondence.
Exemplary, referring to the schematic structural diagram of a remote diagnostic system for a natural gas gauge analysis device shown in FIG. 1; the system includes a plurality of monitoring stations, which in turn are first monitoring station 100 through nth monitoring station N00. Wherein N is a positive integer greater than 1. The structure of each monitoring station is the same, and for any one monitoring station, the monitoring station comprises: and the edge processor is connected with the detection unit and the alarm unit respectively. Taking the first monitoring station 100 as an example, the first monitoring station 100 includes a first edge processor 13, and a first detecting unit 11 and a first alarm unit 15 connected to the first edge processor 13. Wherein the number of the first detecting units 11 may be set to one or more.
Taking an nth monitoring station N00 as an example, the nth monitoring station N00 includes an nth edge processor N3, and an nth detecting unit N1 and an nth alarm unit N5 respectively connected to the nth edge processor N3. Wherein the number of the nth detecting units N1 may be set to one or more.
Referring to the flow chart of a remote diagnostic method for a natural gas meter analysis facility shown in figure 2,
The method can be applied to an edge processor in each monitoring station, and comprises the following steps:
In step S202, the edge processor receives the detection data sent by the detection unit.
The detection unit detects the natural gas of the monitoring station to obtain detection data, and sends the detection data to the edge processor.
In step S204, the edge processor diagnoses the detecting unit according to the detection data, and controls the alarm unit to alarm in response to determining that the detecting unit diagnoses abnormality.
In this embodiment, the alarm unit may alarm in multiple modes, and one mode is that the alarm unit may alarm in a field alarm circuit, and a buzzer, a light emitting diode, and an audible and visual alarm may be implemented in the alarm circuit. Alternatively, the alarm can be sent by communication, and the alarm information can be sent to the client of the user by a wired or wireless network to give an alarm, and the user can be an operation and maintenance person, an administrator or the like.
According to the method, an edge processor is arranged in each monitoring station, the edge processor diagnoses the detection unit according to the detection data, and the alarm unit is controlled to alarm after the detection unit is determined to have abnormal diagnosis. The diagnosis of the remote central data acquisition server in the related art is carried out by putting down the diagnosis work on the edge processor, and the edge processor replaces the work of the remote central data acquisition server. Therefore, the problem that the remote central data acquisition server cannot perform diagnosis work because the remote central data acquisition server cannot acquire data due to network faults can be avoided.
In one embodiment, the natural gas gauge diagnostic system further comprises a flow computer connected to the detection unit and the edge processor, respectively.
In this embodiment, referring to fig. 1, the first monitoring station 100 includes a plurality of first flow computers 12, which are divided into a plurality of groups, wherein in each group, the first flow computers 12 in the group are respectively connected to the first detection units 11 and the first edge processors 13 in the group.
An nth monitoring station 100 includes a plurality of nth flow computers 12, each of which is connected to an nth detection unit 11 and an nth edge processor 13 of the group.
In order to perform diagnostics on the flow computer described above, the method may further comprise the steps of:
The edge processor receives the first heat value sent by the flow computer.
Specifically, the flow computer processes according to the detection data to obtain a first heat value, and sends the first heat value to the edge processor.
The edge processor determines a second heat value according to the detection data;
And controlling the alarm unit to alarm in response to the difference between the first heat value and the second heat value being greater than a preset first heat value difference threshold.
In this embodiment, when the edge processor determines the second heat value according to the detection data, the same heat value calculation method as that of the flow computer may be used, and the second heat value may be calculated according to the detection data. And the edge processor compares the first heat value calculated by the received flow computer with the second heat value, if the difference of the second heat values is larger than the preset first heat value difference value, the second heat value which is possibly calculated by the flow computer is indicated to be abnormal, and further the second heat value is determined to possibly have abnormal functions, and the alarm unit is controlled to alarm so as to remind an operation and maintenance person to perform important checking work on the flow computer. The first heat value difference threshold value can be flexibly set, and the application is not limited. The method is beneficial to improving the function of the flow computer in the aspect of heat value calculation and improving the accuracy of heat value calculation.
In some embodiments, the method may further comprise the steps of: the flow computer processes according to the detection data to obtain a first standard condition flow value; the edge processor receives the first standard condition flow value sent by the flow computer; the edge processor determines a second standard condition flow value according to the detection data; and controlling the alarm unit to alarm in response to the difference between the first standard condition flow value and the second standard condition flow value being greater than a preset first standard condition flow value difference threshold.
In this embodiment, the flow computer processes the received detection data to obtain the first standard condition flow value, and when the edge processor determines the second standard condition flow value according to the detection data, the same standard condition flow value calculation method as that of the flow computer may be adopted for calculation. And the edge processor compares the first standard condition flow value obtained by calculation of the received flow computer with the second standard condition flow value, if the difference of the standard condition flow values is larger than a preset first standard condition flow value difference threshold value, the second standard condition flow value which is possibly calculated by the flow computer is indicated to be abnormal, further the second flow computer is determined to possibly have abnormal functions, and the alarm unit is controlled to alarm so as to remind an operation and maintenance person to carry out important checking work on the flow computer. The first standard flow difference threshold can be flexibly set.
In one embodiment, the detection unit comprises a chromatographic analyzer; the chromatographic analyzer is connected with the edge processor and is used for calculating the heat value of the natural gas in the pipeline to obtain a third heat value and sending the third heat value to the edge processor.
In the present embodiment, referring to fig. 1, the first detection unit 11 includes a first chromatograph 113. The nth detection unit includes an nth chromatograph N13.
The edge processor may diagnose the detection unit according to the detection data, and further include the following steps:
The edge processor determines a third heat value output by the chromatographic analyzer, and controls the alarm unit to alarm in response to the difference value between the second heat value and the third heat value being greater than a preset second heat value difference threshold.
In this embodiment, after receiving the third heat value sent by the chromatograph, the edge processor may compare the third heat value with the second heat value to determine a difference between the third heat value and the second heat value. If the difference is greater than the preset second heat value difference threshold, it can be determined that the computing function of the chromatograph is abnormal, and the alarm unit is controlled to alarm so as to remind the user to perform further important inspection on the chromatograph. The second heat value difference threshold may be flexibly set, which is not limited by the present application. According to the method, the edge processor is used for carrying out diagnosis work on the heat value calculation of the chromatographic analyzer, so that the diagnosis effect on the chromatographic analyzer is improved, whether the chromatographic analyzer has potential faults or not is found in time, and the accuracy of the heat value calculation function of the chromatographic analyzer is improved.
In one embodiment, the detection unit comprises a turbine flow meter.
In this embodiment, referring to fig. 1, the first detecting unit 11 includes a first flowmeter 112, and the first flowmeter 112 may be a turbine flowmeter. The nth detection unit N1 includes an nth flow meter N12.
The edge processor may diagnose the detection unit according to the detection data, and may further include the steps of:
The edge processor receives a first frequency signal and a second frequency signal which are respectively output by the turbine flowmeter according to the flow value.
And controlling the alarm unit to alarm in response to the difference value between the first flow value corresponding to the first frequency signal and the second flow value corresponding to the second frequency signal being greater than a preset turbine flowmeter difference value threshold.
In this embodiment, the turbine flow differential threshold described above may be set to five parts per million. The turbine flowmeter can output a corresponding frequency signal to the edge processor according to the flow value, so that the edge processor determines the flowmeter according to the frequency signal. The turbine flow meter may output a corresponding first frequency signal based on the first flow value and a corresponding second frequency signal based on the second flow value.
The edge processor determines a corresponding first flow value according to the received first frequency signal, determines a corresponding second flow value according to the second frequency signal, and determines a difference between the first flow value and the second flow value. If the difference is larger than a preset first flow difference threshold value of the turbine flowmeter, the turbine flowmeter can be determined to have faults possibly, the turbine flowmeter can be determined to need to be subjected to important maintenance, and the alarm unit can be controlled to alarm.
In one embodiment, the detection unit comprises an ultrasonic flow meter.
The edge processor diagnosing the detection unit according to the detection data may further include the steps of:
And acquiring a theoretical standard instantaneous flow value and an actual instantaneous measurement flow value of the ultrasonic flowmeter in a rated working state. And controlling the alarm unit to alarm in response to the difference value between the actual instantaneous measured flow value of the ultrasonic flowmeter in the rated working state and the theoretical standard instantaneous flow value being larger than a preset ultrasonic flowmeter flow difference value threshold.
In this embodiment, the flow rate difference threshold of the ultrasonic flowmeter may be flexibly set. The above method of the present application can realize diagnosis of ultrasonic flowmeter in flow parameters, and because flow is a very important parameter of ultrasonic flowmeter, an independent diagnosis scheme is formed separately. And if the difference value between the actual instantaneous measured flow value of the ultrasonic flowmeter in the rated working state and the theoretical standard instantaneous flow value is larger than a preset ultrasonic flowmeter flow difference value threshold value, indicating that the ultrasonic flowmeter has abnormal functions in terms of flow parameters, and controlling the alarm unit to alarm so as to remind a user of overhauling the ultrasonic flowmeter. The alarm may indicate traffic anomalies in voice or text.
In some embodiments, the edge processor diagnosing the detection unit according to the detection data may further include the steps of: and acquiring an actual measured ultrasonic sound velocity value and a theoretical calculated sound velocity value of the ultrasonic flowmeter in a rated working state. And controlling the alarm unit to alarm in response to the difference value between the actual measured ultrasonic sound velocity value and the theoretical calculated sound velocity value being greater than a preset first ultrasonic sound velocity difference value threshold.
In this embodiment, the first ultrasonic sound speed difference threshold may be flexibly set. The theoretical calculation sound velocity value can be calculated in advance by a server and an edge processor. Because ultrasonic sound velocity is a very important parameter of an ultrasonic flow meter, an independent diagnostic protocol is formed separately. And responding to the fact that the difference value between the actual measured ultrasonic sound velocity value and the theoretical calculated sound velocity value is larger than a preset first ultrasonic sound velocity difference value threshold value, wherein the ultrasonic flowmeter is abnormal in the aspect of ultrasonic sound velocity and needs to be overhauled. The alarm may indicate the sound speed anomaly in voice or text.
In one embodiment, the detection unit further includes a vibration sensor disposed on the turbine flow meter, and the vibration sensor is connected to the edge processor and is used for detecting a vibration value of the turbine flow meter.
The edge processor diagnosing the detection unit according to the detection data may further include the steps of: the edge processor acquires a vibration value of the turbine flowmeter detected by the vibration sensor; and controlling the alarm unit to alarm in response to the vibration value of the turbine flowmeter being greater than a preset vibration threshold value.
In this embodiment, the edge processor may acquire the vibration value detected by the vibration sensor connected thereto. Comparing the vibration value of the turbine flowmeter with a preset vibration threshold value, if the vibration value of the turbine flowmeter is larger than the vibration threshold value, determining that the vibration of the turbine flowmeter exceeds the standard, and further maintenance work is needed, and controlling the alarm unit to alarm so as to enable related personnel to maintain the turbine flowmeter.
In one embodiment, the detection unit comprises a flow meter. The flow meter may be an ultrasonic flow meter, and/or a turbine flow meter.
The edge processor diagnosing the detection unit according to the detection data may further include the steps of:
and a second comparison test flowmeter is installed on the pipeline where the flowmeter is located in series, so that the detected instantaneous flow of the second comparison test flowmeter is the same as that of the flowmeter.
In this embodiment, in order to diagnose the flowmeter, a second comparison test flowmeter may be disposed on the pipeline where the flowmeter is located, where the flow rates measured by the flowmeter and the second comparison test flowmeter are the same in theory. The number of the second comparison test flow meters can be one or more, and if the number of the second comparison test flow meters is more than one, the average value of the second comparison test flow meters can be calculated and used as a reference comparison value. The second comparison test flow meter may be an ultrasonic flow meter or a turbine flow meter.
Preferably, when the flowmeter is an ultrasonic flowmeter, the second comparison test flowmeter is a turbine flowmeter; when the flowmeter is an eddy current flowmeter, the second comparison test flowmeter is an ultrasonic flowmeter.
Illustratively, referring to fig. 3, a flow meter 1, which is a working flow meter, is provided on the pipeline; a pressure transmitter and a temperature transmitter may be respectively provided at both ends of the flowmeter 1; for testing the flowmeter 1, a flowmeter 2 can be connected in series with the pipeline as a comparison flowmeter. A pressure transmitter and a temperature transmitter may be provided at both ends of the flowmeter 2, respectively.
The edge processor obtains the second comparison test flow meter flow value. And controlling the alarm unit to alarm in response to the difference between the second comparison test flowmeter flow value and the flowmeter flow value being greater than a predetermined flowmeter first flow difference value threshold.
In this embodiment, after the above-mentioned edge processor obtains the flow value of the flowmeter and the flow value of the second comparison test flowmeter, the flow value of the flowmeter and the flow value of the second comparison test flowmeter may be compared, and a difference value between the two may be calculated. If the difference is larger than a preset second flow difference threshold value of the flowmeter, the flow metering function of the flowmeter can be determined to be abnormal, and the alarm unit is controlled to alarm so as to remind related personnel of further overhauling the flowmeter. The second flow rate difference threshold of the ultrasonic flowmeter can be flexibly set, and the method is not limited.
In some embodiments, when the above-mentioned flowmeter is plural, for example, including an ultrasonic flowmeter and a vortex flowmeter connected in series, it may not be necessary to separately provide the second comparison test flowmeter. The ultrasonic flowmeter and the vortex flowmeter can be used as a second comparison test flowmeter, and the comparison can be performed by adopting the method.
In one embodiment, the detection unit comprises an ultrasonic flow meter; the detection data includes: ultrasonic related parameters of the ultrasonic flowmeter and natural gas related parameters.
The relevant parameters of the ultrasound include: sound speed deviation, gain value, mono-reflected channel gain value ratio, dual-reflected sound gain value ratio, gain value mismatch, and signal-to-noise ratio. Relevant parameters of the natural gas include natural gas flow ratio, asymmetry factor, fluid profile coefficient, swirl angle and turbulence.
The edge processor diagnoses the detection unit according to the detection data, and controls the alarm unit to alarm in response to determining that the detection unit diagnoses abnormality, and the method can further comprise the following steps:
For any one relevant parameter, acquiring a standard value of the relevant parameter; and controlling the alarm unit to alarm in response to the difference value between the actual measured value of the related parameter and the standard value being larger than a preset difference value threshold.
In this embodiment, the acquisition of the standard value of the relevant parameter may be performed in various ways. For example, the ultrasonic flowmeter may be sent to a calibration unit for calibration, and in the process of calibration, a standard value of the relevant parameter of the ultrasonic flowmeter is obtained. The standard values of the relevant parameters mentioned above are also referred to as "fingerprint" data, or "footprint" data. For another example, a historical relevant parameter of the ultrasonic flowmeter may be obtained, and a standard value of the relevant parameter may be determined according to the historical relevant parameter. For example, the standard value of the relevant parameter can be determined by averaging the historical relevant parameter. For another example, the standard value of the relevant parameter of the ultrasonic flowmeter can be obtained through the manufacturer of the ultrasonic flowmeter.
For any relevant parameter, if the difference between the actual measured value of the relevant parameter and the standard value of the relevant parameter is smaller than or equal to a preset difference threshold, the alarm unit is controlled to alarm if the difference between the actual measured value of the relevant parameter and the standard value of the relevant parameter is larger than the preset difference threshold, and the alarm unit is controlled to alarm if the difference between the actual measured value of the relevant parameter and the standard value of the relevant parameter is smaller than or equal to the preset difference threshold. When in alarming, the related parameter is prompted to be abnormal in a voice or text mode, so that a user can check the ultrasonic flowmeter with emphasis according to the related parameter.
The method realizes the alarm according to the actual measured value of each relevant parameter. There is a case that each of the above-mentioned related parameters alone does not meet the alarm condition, if the parameter values of a part of the plurality of related parameters are not ideal, the overall performance of the related parameters is low, in which case the alarm processing should be performed, and the ultrasonic flowmeter should be further overhauled, if not, the detection is missed.
In one embodiment, if none of the above related parameters is alerted or one or more related parameters have been alerted, the method may further comprise the steps of: determining a first grading value of each ultrasonic according to a preset grading value and a weight of a related parameter of each ultrasonic; determining a second grading value of the natural gas according to the preset grading value and the weight of the related parameter of each natural gas; determining a score total value of the ultrasonic flowmeter according to the first score value of the ultrasonic related parameter and the second score value of the natural gas related parameter; and controlling the alarm unit to alarm in response to the score total value being smaller than a preset score total value threshold value.
In this embodiment, the first scoring value of each ultrasound may be determined according to the score and the weight of the relevant parameter of the ultrasound.
And setting corresponding weights for relevant parameters of each ultrasonic wave. The weight may be set according to the priority importance of each relevant parameter. The priority ranking of each relevant parameter may be preset, for example, the order of priority from large to small is as follows: sound speed deviation, gain value, mono-reflected channel gain value ratio, dual-reflected sound gain value ratio, gain value mismatch, and signal-to-noise ratio. The weight values are sequentially from big to small: sound speed deviation, gain value, mono-reflected channel gain value ratio, dual-reflected sound gain value ratio, gain value mismatch, and signal-to-noise ratio. The weights may be set to be the same if the priorities are the same.
In determining the score for each ultrasound-related parameter, the following steps may be employed: determining a fraction coefficient according to the actual measured value of the relevant parameter of each ultrasonic and the standard value of the parameter; the score of the relevant parameter for each ultrasound is determined based on the predetermined score of the parameter and the score coefficient.
The score coefficient is determined according to the actual measured value of the relevant parameter of each ultrasonic and the standard value of the parameter, and the following steps can be adopted: the absolute value of the difference between the actual measured value and the standard value of the parameter is determined, and the fractional coefficient of the parameter is determined according to the absolute value of the difference and a preset difference threshold.
Illustratively, the score coefficient is a first score coefficient if the absolute value of the difference is greater than a nominal difference threshold. And if the absolute value of the difference is smaller than or equal to the rated difference threshold value, the score coefficient is a second score coefficient. For example, if the difference is 0.3 and the rated difference is 0.2, the fractional coefficient is set to 0.5. For another example, if the difference is 0.1 and the nominal difference is 0.2, the fractional coefficient should be set to 0.9. In order to improve the accuracy of the score, it is preferable that in the case where the difference is smaller than the rated difference, the score coefficient is set to be inversely related to the difference. That is, the larger the absolute value of the difference value, the smaller the fractional coefficient, the larger the fractional coefficient, and the maximum value of the fractional coefficient is set to 1.
The first scoring value described above is determined from the sum of the scores of each parameter.
See Table 1
| Parameters (parameters) | Predetermined score | Fractional coefficient | Weight value | Score of |
| Deviation of sound velocity | 100 | 0.8 | 0.8 | 64 |
| Gain value | 100 | 0.9 | 0.9 | 81 |
| Gain value ratio of single reflection sound channel | 100 | 0.7 | 0.7 | 49 |
| Dual reflected acoustic gain value ratio | 100 | 0.6 | 0.6 | 36 |
| Degree of gain value mismatch | 100 | 0.5 | 0.6 | 30 |
| Signal to noise ratio | 100 | 0.5 | 0.5 | 25 |
| First score value | 285 |
TABLE 1
According to the method, the weight is set according to the importance degree of each ultrasonic parameter, the score coefficient is set according to the degree of deviation of each ultrasonic from the standard value, and the finally obtained first score value can reflect the overall performance of the ultrasonic related parameters of the ultrasonic flowmeter more comprehensively and scientifically.
In some embodiments, the above method may further comprise the steps of: the comparison may be performed according to the first score value and the first score value threshold, and if the first score value is smaller than the first score value threshold, an alarm is given. The first scoring value threshold can be flexibly set. The method can realize the independent detection and alarm of ultrasonic parameters in the ultrasonic flowmeter.
The relevant parameters of the natural gas include: natural gas flow velocity ratio, asymmetry factor, fluid profile coefficient, swirl angle, and turbulence.
Determining a second scoring value for the relevant parameter of the natural gas may comprise the steps of: and determining a second grading value of the natural gas according to the grading value and the weight value of the related parameter of each natural gas.
In this embodiment, a corresponding weight is set for each natural gas related parameter. The weight may be set according to the priority importance of each relevant parameter. The priority ranking of each relevant parameter may be preset, for example, the order of priority from large to small is as follows: natural gas flow velocity ratio, asymmetry factor, fluid profile coefficient, swirl angle, and turbulence. The weight values are sequentially from big to small: natural gas flow velocity ratio, asymmetry factor, fluid profile coefficient, swirl angle, and turbulence.
The method for determining the score of each relevant parameter of the natural gas is the same as the method for determining the score of the relevant parameter of the ultrasonic wave. The fractional coefficient is determined from the actual measured value of each natural gas related parameter and the standard value of the parameter. The score of each natural gas is determined based on a predetermined score of the parameter and the score coefficient. The score coefficient is determined according to the actual measured value of each natural gas related parameter and the standard value of the parameter, and the following steps can be adopted: the absolute value of the difference between the actual measured value and the standard value of the parameter is determined, and the fractional coefficient of the parameter is determined according to the absolute value of the difference and a preset difference threshold.
In some embodiments, the above method may further comprise the steps of: the comparison may be performed according to the second score value and the second score value threshold, and if the second score value is smaller than the second score value threshold, an alarm is given. The second score threshold value can be flexibly set. The method can realize independent detection and alarm of the natural gas related parameters in the ultrasonic flowmeter.
The method of the application can alarm according to the actual measured value of each relevant parameter of the ultrasonic flowmeter, and can alarm according to the score total value of all relevant parameters. The missing detection of the ultrasonic flowmeter caused by the fact that each parameter is not alarmed independently can be avoided, and the overall diagnostic performance of the ultrasonic flowmeter parameters is improved.
In some embodiments, in the process of calibrating the ultrasonic flowmeter by sending it to the calibration unit, a two-dimensional graph of the parameter may be generated, so as to facilitate observation. The method may further comprise the steps of: and acquiring a first parameter in a first calibration state and a second parameter in a second calibration state of the ultrasonic flowmeter. And respectively generating a first parameter curve and a second parameter curve according to the first parameter value and the second parameter value in the same coordinate system.
The first calibration state is that the air in the pipeline where the ultrasonic flowmeter is located is air, and the flowmeter is calibrated or calibrated in the first calibration state, namely, the dry calibration state. And the second working state is that natural gas is conveyed in a pipeline where the ultrasonic flowmeter is located, namely, a real-flow calibration state, and flowmeter calibration or calibration is carried out in the state. When the parameter is the sound velocity deviation, see the graph of the relative sound velocity deviation between the dry standard and the real flow calibration state shown in fig. 3. The graph shows two sound speed deviation curves. Wherein curve 1 represents a dry standard curve and curve 2 represents a real flow calibration curve.
In one embodiment, the detection unit includes: a temperature sensor.
In the present embodiment, in the first monitoring station 100, a first temperature sensor 111. In the nth monitoring station N00, an nth temperature sensor N11 is provided.
The edge processor diagnosing the detection unit according to the detection data may further include the steps of:
And acquiring historical data of the temperature sensor. And determining a temperature threshold value and a temperature change rate threshold value of the temperature sensor according to the historical data. And calibrating the temperature sensor. A detected temperature value of the calibrated temperature sensor, and a rate of change of the temperature value are determined. And controlling the alarm unit to alarm in response to the detected temperature value being greater than the temperature threshold value and/or the detected temperature value change rate being greater than the temperature value change rate threshold value.
In this embodiment, when the temperature sensor is calibrated, a multi-point calibration method may be used to calibrate a plurality of temperature points. After calibration, it is put into use. After the edge processor acquires the temperature value detected by the calibrated temperature sensor, the temperature value can be compared with a temperature threshold according to the temperature value, if the temperature value is larger than the temperature threshold, the temperature sensor is determined to need further maintenance, and the alarm unit can be controlled to alarm.
The temperature value threshold can be flexibly set, and the application is not limited.
In this embodiment, after the edge processor obtains the temperature value change rate detected by the calibrated temperature sensor, the edge processor may compare the temperature value change rate with the temperature value change rate threshold, and if the temperature value change rate is greater than the temperature value change rate threshold, determine that the temperature sensor needs further maintenance, and may control the alarm unit to alarm.
The temperature value change rate threshold can be flexibly set, and the application is not limited.
In this embodiment, the edge processor may also alarm according to the condition that the temperature value and the rate of change of the temperature value both satisfy the threshold, that is, the detected temperature value is greater than the temperature threshold, and the detected rate of change of the temperature value is greater than the predetermined rate of change of the temperature value, and control the alarm unit to alarm when both conditions satisfy.
In one embodiment, the detection unit includes: a pressure sensor.
In the present embodiment, in the first monitoring station 100, a first pressure sensor 114 is provided. In the nth monitoring station N00, an nth pressure sensor N14 is provided.
The edge processor diagnosing the detection unit according to the detection data may further include the steps of:
And acquiring historical data of the pressure sensor. And determining a threshold value of the pressure sensor and a change rate threshold value according to the historical data. And calibrating the pressure sensor. A sensed pressure value of the calibrated pressure sensor, and a rate of change of the pressure value, are determined. And controlling the alarm unit to alarm in response to the detected pressure value being greater than the pressure threshold value and/or the pressure value change rate being greater than the pressure change rate threshold value.
In this embodiment, when the pressure sensor is calibrated, a multi-point calibration method may be used to calibrate a plurality of pressure points. After calibration, it is put into use. After the edge processor acquires the pressure value detected by the calibrated pressure sensor, the pressure value can be compared with a pressure threshold value according to the pressure value, if the pressure value is larger than the pressure threshold value, the pressure sensor is determined to need further maintenance, and the alarm unit can be controlled to alarm.
The pressure value threshold can be flexibly set, and the application is not limited.
In this embodiment, after the edge processor obtains the pressure value change rate detected by the calibrated pressure sensor, the edge processor may compare the pressure value change rate with the pressure value change rate threshold, and if the pressure value change rate is greater than the pressure value change rate threshold, determine that the pressure sensor needs further maintenance, and may control the alarm unit to alarm.
The pressure value change rate threshold can be flexibly set, and the application is not limited.
In this embodiment, the edge processor may also alarm according to the condition that the pressure value and the rate of change of the pressure value both satisfy the threshold, that is, the detected pressure value is greater than the pressure threshold, and the detected rate of change of the pressure value is greater than the predetermined rate of change of the pressure value, and control the alarm unit to alarm when both conditions satisfy.
In a second aspect, the present application provides a remote diagnosis device for a natural gas metering analysis apparatus, which is applied to the edge processor. Referring to fig. 4, the apparatus 300 includes:
The natural gas metering diagnostic system comprises: one or more monitoring stations interconnected by a network; for any one monitoring station, the monitoring station includes: the device comprises an edge processor, and a detection unit and an alarm unit which are respectively connected with the edge processor;
The device comprises a receiving module 31, a detecting unit and a control module, wherein the receiving module 31 is used for receiving the detection data obtained by detecting the natural gas of the monitoring station by the detecting unit and sending the detection data;
and the diagnosis module 32 is used for diagnosing the detection unit according to the detection data, and controlling the alarm unit to alarm in response to determining that the detection unit diagnoses abnormality.
The specific manner in which the various modules perform the operations in the apparatus of the above embodiments have been described in detail in connection with the embodiments of the method, and will not be described in detail herein.
In a fourth aspect, the present application further provides an electronic device, applied to each of the above monitoring stations, including: the edge processor described above; a memory for storing the edge processor executable instructions; wherein the edge processor is configured to execute the executable instructions to implement the method of any of the above.
Referring to fig. 1, a first monitor station 100 is illustrated in which a first memory 16 is disposed; the first memory 16 is configured to store executable instructions of the first edge processor 13; wherein the first edge processor 13 is configured to execute the executable instructions to implement the method of any of the above. The first edge processor 13 is connected to the first flow computer 12, the first detection unit 11 and the first human interaction device 17, respectively. Wherein the first human interaction device 17 may be used for displaying parameters and inputting instructions.
An N6 and an N man-machine interaction device are arranged in the N monitoring station. The nth memory N6 and the nth man-machine interaction device are respectively connected with the nth edge processor N3.
In some embodiments, the alarm unit may be implemented by an audible and visual alarm, where the audible and visual alarm is electrically connected to the edge processor, and the audible and visual alarm alarms under the control of the edge processor. The voice alarm device can be realized by adopting a touch screen with a sounding device, the touch screen is electrically connected with the edge processor, the alarm is carried out under the control of the edge processor, the voice alarm can be realized in the touch screen, and the text prompt alarm content can be displayed on the touch screen at the same time. When in voice alarm, the voice of the alarm can be preset to carry out voice alarm.
In one embodiment, the alarm unit may further include: a triode and a buzzer. And the base electrode of the triode is connected with the edge processor. The collector electrode of the triode is connected with the first end of the buzzer, and the second end of the buzzer is connected with a power supply. The emitter of the triode is connected with the first end of the resistor, and the second end of the resistor is grounded.
In this embodiment, referring to fig. 6, taking the first monitoring station 100 as an example, the first alarm unit 15 may further include a first triode 152 and a first buzzer 151. The base of the first transistor 152 is connected to the first edge processor 13. The collector of the first triode 152 is connected to the first end of the first buzzer 151, and the second end of the first buzzer 151 is connected to a power supply. The emitter of the first triode 152 is connected to a first end of a resistor 153, and a second end of the resistor 153 is grounded.
In a state that the first edge processor 13 controls the first transistor 152 to be turned on, the buzzer 151 sounds to alarm. In a state where the first edge processor 13 controls the first transistor 152 to be turned off, the buzzer 151 does not sound.
Of course, the first alarm unit may also be provided with a light emitting diode, for example, a light emitting diode is connected in series to the position of the buzzer, and the light emitting diode emits light to play a role of alarm when the first triode 152 is turned on. The LED is combined with the buzzer, so that the audible and visual alarm function can be realized.
The alarm unit N00 in the other monitoring stations may be provided with the same structure as the alarm unit 15 in the first monitoring station 100 described above.
In one embodiment, each monitoring station further comprises a station access terminal; the station access terminal is connected with the edge processor through a network and is used for receiving alarm information and sending a control instruction to the edge processor so as to control the detection unit.
In the present embodiment, in the first monitoring station 100, a first station access terminal 14 is provided, and a first edge processor 12 and a first force computer 12 are connected, respectively. The nth monitoring station is provided with an nth station access terminal N4 which is respectively connected with the nth edge processor and the nth flow computer.
In one embodiment, referring to fig. 1, the system further comprises a server 2 and a remote workstation 3. The server 2 and the remote workstation 3 are connected to the plurality of monitoring stations via a network.
In this embodiment, the server 2 and the remote workstation 3 are connected to each of the monitoring stations via a network, and are configured to send working instructions to the monitoring stations and receive feedback data of each of the monitoring stations.
In an exemplary embodiment, a non-transitory computer readable storage medium comprising instructions executable to perform the above-described method is also provided. For example, the non-transitory computer readable storage medium may be ROM, random Access Memory (RAM), CD-ROM, magnetic tape, floppy disk, optical data storage device, etc.
Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure. This application is intended to cover any adaptations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
It is to be understood that the present disclosure is not limited to the precise arrangements and instrumentalities shown in the drawings, and that various modifications and changes may be effected without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.
Claims (10)
1. A remote diagnosis method for natural gas metering analysis equipment is characterized in that,
The natural gas metering diagnostic system comprises: one or more monitoring stations interconnected by a network;
For any one monitoring station, the monitoring station includes: the device comprises an edge processor, and a detection unit and an alarm unit which are respectively connected with the edge processor;
The method comprises the following steps:
the edge processor receives detection data sent by the detection unit;
The edge processor diagnoses the detection unit according to the detection data, and controls the alarm unit to alarm in response to determining that the detection unit diagnoses abnormality;
the natural gas gauge diagnostic system further comprises: a flow computer; the flow computer is respectively connected with the detection unit and the edge processor;
the method further comprises the steps of:
the flow computer processes the detection data to obtain a first heat value;
the edge processor receives the first heat value sent by the flow computer;
the edge processor determines a second heat value according to the detection data;
controlling the alarm unit to alarm in response to the difference between the first heat value and the second heat value being greater than a predetermined first heat value difference threshold;
When the edge processor determines the second heat value according to the detection data, the edge processor calculates the second heat value according to the detection data by adopting a heat value calculation method which is the same as that of the flow computer;
And the edge processor compares the first heat value obtained by calculation of the received flow computer with the second heat value, if the difference between the first heat value and the second heat value is larger than a preset first heat value difference value, the second heat value calculated by the flow computer is abnormal, and further, the second heat value is determined to have abnormal functions, and the alarm unit is controlled to alarm so as to remind an operation and maintenance person to perform important checking work on the flow computer.
2. A method of remote diagnosis of a natural gas meter analysis facility according to claim 1,
The flow computer processes according to the detection data to obtain a first standard condition flow value;
the edge processor receives the first standard condition flow value sent by the flow computer;
The edge processor determines a second standard condition flow value according to the detection data;
and controlling the alarm unit to alarm in response to the difference between the first standard condition flow value and the second standard condition flow value being greater than a preset first standard condition flow value difference threshold.
3. A method of remote diagnosis of a natural gas meter analysis facility according to claim 2,
The detection unit comprises a chromatographic analyzer;
the edge processor diagnoses the detection unit according to the detection data, and the edge processor comprises:
the edge processor determines a third heating value output by the chromatograph;
and controlling the alarm unit to alarm in response to the difference value between the second heat value and the third heat value being greater than a preset second heat value difference threshold.
4. A method of remote diagnosis of a natural gas meter analysis facility according to claim 1,
The detection unit comprises a turbine flowmeter;
the edge processor diagnoses the detection unit according to the detection data, and the edge processor comprises:
the edge processor receives a first frequency signal and a second frequency signal which are respectively output by the turbine flowmeter according to the flow value;
And controlling the alarm unit to alarm in response to the difference value between the first flow value corresponding to the first frequency signal and the second flow value corresponding to the second frequency signal being greater than a preset turbine flowmeter flow difference value threshold.
5. A method of remote diagnosis of a natural gas meter analysis facility according to claim 1,
The detection unit comprises an ultrasonic flowmeter;
the edge processor diagnoses the detection unit according to the detection data, and the edge processor comprises:
acquiring a theoretical standard instantaneous flow value and an actual instantaneous measurement flow value of the ultrasonic flowmeter in a rated working state;
controlling the alarm unit to alarm in response to the difference value between the actual instantaneous measured flow value of the ultrasonic flowmeter in the rated working state and the theoretical standard instantaneous flow value being greater than a preset ultrasonic flowmeter flow difference value threshold;
Acquiring an actual measured ultrasonic sound velocity value and a theoretical calculated sound velocity value of the ultrasonic flowmeter in a rated working state;
and controlling the alarm unit to alarm in response to the difference value between the actual measured ultrasonic sound velocity value and the theoretical calculated sound velocity value being greater than a preset first ultrasonic sound velocity difference value threshold.
6. A method of remote diagnosis of a natural gas meter analysis facility according to claim 4,
The detection unit further comprises a vibration sensor arranged on the turbine flowmeter;
the edge processor diagnoses the detection unit according to the detection data, and the edge processor comprises:
acquiring a vibration value of the turbine flowmeter detected by the vibration sensor;
And controlling the alarm unit to alarm in response to the vibration value of the turbine flowmeter being greater than a preset vibration threshold value.
7. A method of remote diagnosis of a natural gas meter analysis facility according to claim 1,
The detection unit comprises a flowmeter;
the edge processor diagnoses the detection unit according to the detection data, and the edge processor comprises:
A second comparison test flowmeter is installed on a pipeline where the flowmeter is located in series, so that the detected instantaneous flow of the second comparison test flowmeter is identical to that of the flowmeter;
the edge processor obtains the instantaneous flow value of the second comparison test flowmeter;
and controlling the alarm unit to alarm in response to the difference between the second comparison test flowmeter instantaneous flow value and the flowmeter detection instantaneous flow value being greater than a preset flowmeter first flow value difference threshold.
8. A method of remote diagnosis of a natural gas meter analysis facility according to claim 1,
The detection unit comprises an ultrasonic flowmeter;
The detection data includes: the ultrasonic parameters of the ultrasonic flowmeter and the natural gas parameters;
The relevant parameters of the ultrasound include: sound speed deviation, gain value, single reflection sound channel gain value ratio, double reflection sound gain value ratio, gain value mismatch degree and signal to noise ratio;
The relevant parameters of the natural gas include natural gas flow speed ratio, asymmetry factor, fluid profile coefficient, swirl angle and turbulence;
The edge processor diagnoses the detection unit according to the detection data, and controls the alarm unit to alarm in response to determining that the detection unit diagnoses abnormality, and the edge processor comprises the following steps:
For any one relevant parameter, acquiring a standard value of the relevant parameter;
and controlling the alarm unit to alarm in response to the difference value between the actual measured value of the related parameter and the standard value being larger than a preset difference value threshold.
9. A method of remote diagnosis of a natural gas meter analysis facility according to claim 8,
The method further comprises the steps of:
Determining a first grading value of each ultrasonic according to a preset grading value and a weight of a related parameter of each ultrasonic;
determining a second grading value of the natural gas according to the preset grading value and the weight of the related parameter of each natural gas;
Determining a score total value of the ultrasonic flowmeter according to the first score value of the ultrasonic related parameter and the second score value of the natural gas related parameter;
and controlling the alarm unit to alarm in response to the score total value being smaller than a preset score total value threshold value.
10. A method of remote diagnosis of a natural gas meter analysis facility according to claim 1,
The detection unit includes: a temperature sensor and a pressure sensor;
the edge processor diagnoses the detection unit according to the detection data, and the edge processor comprises:
Acquiring historical data of the temperature sensor;
determining a threshold value of the temperature sensor and a change rate threshold value according to the historical data;
Calibrating the temperature sensor;
determining a detected temperature value of the calibrated temperature sensor, and a rate of change of the temperature value;
Controlling the alarm unit to alarm in response to the detected temperature value being greater than the temperature threshold value and/or the detected temperature value change rate being greater than the temperature value change rate threshold value;
the edge processor diagnoses the detection unit according to the detection data, and the edge processor comprises:
Acquiring historical data of the pressure sensor;
determining a threshold value of the pressure sensor and a change rate threshold value according to the historical data;
calibrating the pressure sensor;
Determining a detected pressure value of the calibrated pressure sensor, and a rate of change of the pressure value;
And controlling the alarm unit to alarm in response to the detected pressure value being greater than the threshold value and/or the change rate of the pressure value being greater than the change rate threshold value.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211652232.6A CN116437243B (en) | 2022-12-22 | 2022-12-22 | Remote diagnosis method for natural gas metering analysis equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211652232.6A CN116437243B (en) | 2022-12-22 | 2022-12-22 | Remote diagnosis method for natural gas metering analysis equipment |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN116437243A CN116437243A (en) | 2023-07-14 |
| CN116437243B true CN116437243B (en) | 2024-04-19 |
Family
ID=87089605
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211652232.6A Active CN116437243B (en) | 2022-12-22 | 2022-12-22 | Remote diagnosis method for natural gas metering analysis equipment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116437243B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN118243200B (en) * | 2024-05-28 | 2024-08-23 | 上海真兰仪表科技股份有限公司 | Gas turbine flowmeter fault diagnosis method and system |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112565409A (en) * | 2020-12-02 | 2021-03-26 | 杭州谐云科技有限公司 | Industrial equipment monitoring method and system based on cloud edge cooperation |
| CN114338760A (en) * | 2022-03-14 | 2022-04-12 | 湖南易净环保科技有限公司 | Management control system for small and medium-sized water treatment equipment based on MQTT protocol |
| CN115186883A (en) * | 2022-06-29 | 2022-10-14 | 成都航天科工大数据研究院有限公司 | Industrial equipment health state monitoring system and method based on Bian Yun collaborative computing |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US11796368B2 (en) * | 2021-02-04 | 2023-10-24 | Chengdu Qinchuan Iot Technology Co., Ltd. | Methods and systems for measuring energy of natural gas based on Internet of Things |
-
2022
- 2022-12-22 CN CN202211652232.6A patent/CN116437243B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112565409A (en) * | 2020-12-02 | 2021-03-26 | 杭州谐云科技有限公司 | Industrial equipment monitoring method and system based on cloud edge cooperation |
| CN114338760A (en) * | 2022-03-14 | 2022-04-12 | 湖南易净环保科技有限公司 | Management control system for small and medium-sized water treatment equipment based on MQTT protocol |
| CN115186883A (en) * | 2022-06-29 | 2022-10-14 | 成都航天科工大数据研究院有限公司 | Industrial equipment health state monitoring system and method based on Bian Yun collaborative computing |
Also Published As
| Publication number | Publication date |
|---|---|
| CN116437243A (en) | 2023-07-14 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US7254520B2 (en) | Testing of wire systems and end devices installed in industrial processes | |
| CN116437243B (en) | Remote diagnosis method for natural gas metering analysis equipment | |
| CN117664281B (en) | Ultrasonic water meter fault detection and automatic calibration method and system based on Internet of Things | |
| CN111060267A (en) | Oil level early warning method based on multi-parameter liquid level meter | |
| EP3783320A1 (en) | Detecting and identifying a change in a vibratory meter | |
| US20230084562A1 (en) | Non-destructive inspection method and system based on artificial intelligence | |
| US20240036011A1 (en) | System and method for corrosion and erosion monitoring of pipes and vessels | |
| CN111562037B (en) | Thermometer fault detection method and device | |
| CN113625133A (en) | Online monitoring feedback system and method for partial discharge of power distribution equipment | |
| JP2023552461A (en) | Systems and methods for corrosion and erosion monitoring of pipes and vessels | |
| CN117171366A (en) | Knowledge graph construction method and system for power grid dispatching operation situation | |
| CN104568438A (en) | Engine bearing fault detection system and method | |
| JPH0484754A (en) | Method for evaluating soundness of material | |
| EP3857176A1 (en) | Flowmeter as an asset | |
| US20060085102A1 (en) | Methods for establishing alerts and/or alert limits for monitoring mechanical devices | |
| CN115728695A (en) | Transformer comprehensive monitoring intelligent diagnostic instrument inspection device and method | |
| CN108536777A (en) | A kind of data processing method, server cluster and data processing equipment | |
| CN213843857U (en) | Ventilator fault remote diagnosis device | |
| CN114730409A (en) | System and method for automated wet stock management | |
| US12123850B1 (en) | System and method for testing inhomogeneities in a fluid within a conduit | |
| CN109491373A (en) | A kind of Practical training equipment fault diagnosis system | |
| CN117590022B (en) | Anemometer control method, device, equipment and storage medium for roadway | |
| KR20180093351A (en) | Apparatus and Method for Detecting Sensing Error at the Sensing Point for the Thermal Efficiency of Facility | |
| CN218037981U (en) | Automatic test system for terminal equipment of Internet of things | |
| CN113763679B (en) | Method and device for monitoring abnormal sound of gas insulated enclosed type combined electrical apparatus |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |