CN111693135A - Power equipment anomaly detection method based on acoustic array edge calculation - Google Patents
Power equipment anomaly detection method based on acoustic array edge calculation Download PDFInfo
- Publication number
- CN111693135A CN111693135A CN202010495890.3A CN202010495890A CN111693135A CN 111693135 A CN111693135 A CN 111693135A CN 202010495890 A CN202010495890 A CN 202010495890A CN 111693135 A CN111693135 A CN 111693135A
- Authority
- CN
- China
- Prior art keywords
- module
- sound
- power equipment
- data
- monitoring
- 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.)
- Pending
Links
- 238000001514 detection method Methods 0.000 title claims abstract description 27
- 238000004364 calculation method Methods 0.000 title claims abstract description 16
- 230000002159 abnormal effect Effects 0.000 claims abstract description 34
- 238000012544 monitoring process Methods 0.000 claims abstract description 29
- 230000005540 biological transmission Effects 0.000 claims abstract description 19
- 230000003321 amplification Effects 0.000 claims abstract description 17
- 238000003199 nucleic acid amplification method Methods 0.000 claims abstract description 17
- 230000005856 abnormality Effects 0.000 claims description 15
- 238000004891 communication Methods 0.000 claims description 7
- 239000013078 crystal Substances 0.000 claims description 5
- 238000013500 data storage Methods 0.000 claims description 3
- 238000005516 engineering process Methods 0.000 claims description 3
- 238000012546 transfer Methods 0.000 claims description 2
- 238000000034 method Methods 0.000 claims 6
- 238000012545 processing Methods 0.000 abstract description 8
- 230000009466 transformation Effects 0.000 description 6
- 238000003745 diagnosis Methods 0.000 description 3
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 238000013507 mapping Methods 0.000 description 1
- 238000005065 mining Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 208000024891 symptom Diseases 0.000 description 1
- 238000013024 troubleshooting Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01H—MEASUREMENT OF MECHANICAL VIBRATIONS OR ULTRASONIC, SONIC OR INFRASONIC WAVES
- G01H11/00—Measuring mechanical vibrations or ultrasonic, sonic or infrasonic waves by detecting changes in electric or magnetic properties
- G01H11/06—Measuring mechanical vibrations or ultrasonic, sonic or infrasonic waves by detecting changes in electric or magnetic properties by electric means
- G01H11/08—Measuring mechanical vibrations or ultrasonic, sonic or infrasonic waves by detecting changes in electric or magnetic properties by electric means using piezoelectric devices
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
Abstract
The invention discloses a power equipment abnormity detection method based on sound array edge calculation, which adopts a power equipment abnormity detection device, wherein the power equipment abnormity detection device comprises a main control module, a sound array sensor module, a data amplification module, an information transmission module and a monitoring module, and the sound array sensor module, the data amplification module, the information transmission module and the monitoring module are all coupled with the main control module. The acoustic array sensor module is arranged to monitor the abnormal sound in the power equipment in an all-around manner, so that the fault sound source is accurately positioned, and the monitoring accuracy is improved; by amplifying the abnormal sound of the fault and defining a sensitive area, the reporting mode of the abnormal sound is effectively improved, and the processing efficiency is improved; by arranging the camera module, the angle adjusting module and the height adjusting module, the omnibearing shooting and recording of the power equipment are realized, a mode is further provided for determining an abnormal detection result, personnel does not need to check on site, and the processing efficiency is further improved.
Description
Technical Field
The invention relates to the technical field of transmission equipment running state abnormity detection methods, in particular to an electric power equipment abnormity detection method based on acoustic array edge calculation.
Background
With the ever-increasing demand for electrical power, power systems have increasingly demanding economic and reliability requirements for electrical equipment. As an electric power device with the characteristics of small occupied area, high operation reliability, flexible configuration, simple maintenance, long overhaul period and the like, the closed gas insulated switchgear GIS is widely applied to high-voltage power transmission and transformation systems such as urban power supply, power plants, large industrial and mining enterprises and the like with the technical advancement and the economy of life cycle cost, but the operation faults of the electric power device are increased, and particularly the large-scale power transmission and transformation device runs for a long time; once the power transmission and transformation equipment fails, the equipment can be damaged and even large-area power failure can occur, and huge economic loss and social influence are caused.
At present, troubleshooting of power transmission and transformation equipment is also a difficult point, because the power transmission and transformation equipment has a complex structure, a plurality of factors of equipment operation faults are caused, the fault characteristics of the equipment are often different, even if the same equipment has the same fault at different time and places, the fault characteristics are not necessarily completely the same, and the fault symptoms and the faults of the equipment do not have one-to-one mapping relation, so that the fault diagnosis of the power transmission and transformation equipment is carried out, and if the fault diagnosis is carried out only by depending on the functional relation between the equipment operation rules and the equipment operation parameters determined in advance, the equipment is difficult to carry out effective and accurate fault diagnosis.
The patent CN201910516444.3 has been published, which monitors the power equipment through the acoustic array sensor, the data receiving module, the control module, the storage module, the edge computing module, the communication module, and the cloud server platform, but the technical means proposed in the patent needs to manually check the result of the anomaly detection, and the efficiency is low.
Disclosure of Invention
The invention aims to solve the defects in the prior art, and provides an electrical equipment abnormity detection method based on acoustic array edge calculation, which monitors all-around abnormal sound in electrical equipment by arranging an acoustic array sensor module, realizes accurate positioning of a fault sound source and improves the monitoring accuracy; by amplifying the abnormal sound of the fault and defining a sensitive area, the reporting mode of the abnormal sound is effectively improved, and the processing efficiency is improved; by arranging the camera module, the angle adjusting module and the height adjusting module, the omnibearing shooting and recording of the power equipment are realized, a mode is further provided for determining an abnormal detection result, personnel does not need to check on site, and the processing efficiency is further improved.
In order to achieve the purpose, the invention adopts the following technical scheme:
a power equipment abnormity detection method based on sound array edge calculation adopts a power equipment abnormity detection device, wherein the power equipment abnormity detection device comprises a main control module, a sound array sensor module, a data amplification module, an information transmission module and a monitoring module, and the sound array sensor module, the data amplification module, the information transmission module and the monitoring module are all coupled with the main control module;
the acoustic array sensor module is used for receiving sound in the power equipment;
the data amplification module is used for amplifying the sound received by the sound array sensor module and converting the sound into an electric signal;
the information transmission module is used for transmitting the electric signal converted by the data amplification module to the cloud server platform;
the cloud server platform is used for denoising and storing the received original signal and sending the denoised original signal to the edge computer;
the edge computer is used for receiving data from the cloud server platform, realizing edge calculation, extracting characteristic values and other related information of original data, accurately positioning a fault sound source, and determining whether to start the monitoring module for further checking equipment abnormality by a monitoring person operating the edge computer;
the abnormality detection method includes the steps of:
s1, recording sound data of equipment operation through a plurality of groups of sound array sensors;
s2, amplifying the sound data recorded by the multiple groups of sound array sensors through a data amplification module, and entering the next step when the amplified sound meets the requirement;
s3, transmitting the amplified sound data to a cloud server platform through data to compare with normal sound data;
s4, carrying out grade judgment according to a preset sound threshold value to obtain an area where the abnormal sound is located, judging whether the abnormal sound is greater than a set value or not, and entering the next step if the abnormal sound is greater than the set value;
s5, outputting initial abnormal sound, and determining whether to start the monitoring module to further check the equipment abnormality by monitoring personnel;
and S6, after the abnormal sound is output, the algorithm cycle is ended, and the sound is collected again through the sound array sensor.
Preferably, the acoustic array sensor is composed of 4-200 piezoelectric crystals, and the piezoelectric crystals are closely arranged at equal intervals and are arranged in an L shape.
Preferably, in the step S2, if the amplified sound does not meet the requirement, the step S2 is continued until the amplified sound meets the requirement.
Preferably, in step S4, if the abnormal noise is not greater than the set value, the algorithm cycle is ended, reset, and restarted from S1 for the next cycle.
Preferably, the monitoring module includes a camera module, an angle adjustment module and a height adjustment module, the camera module is used for recording the power equipment under the control of an operator, the angle adjustment module is used for adjusting the angle of the camera module to realize omnibearing recording of the power equipment, and the height adjustment module is used for adjusting the height of the camera module.
Preferably, the main control module is composed of an embedded microprocessor and a data storage card, and the information transfer module comprises a wireless communication device based on a zigbee technology and is used for realizing data communication with the cloud server platform.
Preferably, the angle adjustment module comprises a micro motor, a gear box, a driving wheel and a free steering wheel, wherein the micro motor is connected with the driving wheel through the gear box and a chain, and transmits power to the camera module to drive the camera module to rotate.
The invention has the following beneficial effects:
1. by arranging the acoustic array sensor module, the comprehensive abnormal sound monitoring is carried out in the power equipment, the fault sound source is accurately positioned, and the monitoring accuracy is improved;
2. by amplifying the abnormal sound of the fault and defining a sensitive area, the reporting mode of the abnormal sound is effectively improved, and the processing efficiency is improved;
3. by arranging the camera module, the angle adjusting module and the height adjusting module, the omnibearing shooting and recording of the power equipment are realized, a mode is further provided for determining an abnormal detection result, personnel does not need to check on site, and the processing efficiency is further improved.
Drawings
Fig. 1 is a system block diagram of an electrical equipment anomaly detection method based on acoustic array edge calculation according to the present invention;
fig. 2 is a monitoring flowchart of an electrical equipment abnormality detection method based on acoustic array edge calculation according to the present invention.
Detailed Description
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in detail below. In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention. This invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein, but rather should be construed as broadly as the present invention is capable of modification in various respects, all without departing from the spirit and scope of the present invention.
It will be understood that when an element is referred to as being "secured to" another element, it can be directly on the other element or intervening elements may also be present. When an element is referred to as being "connected" to another element, it can be directly connected to the other element or intervening elements may also be present. The terms "vertical," "horizontal," "left," "right," and the like as used herein are for illustrative purposes only and do not represent the only embodiments.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items.
Referring to fig. 1-2, a power equipment anomaly detection method based on acoustic array edge computing adopts a power equipment anomaly detection device, the power equipment anomaly detection device comprises a main control module, an acoustic array sensor module, a data amplification module, an information transmission module and a monitoring module, the acoustic array sensor module, the data amplification module, the information transmission module and the monitoring module are all coupled with the main control module, the main control module is composed of an embedded microprocessor and a data storage card, and the information transmission module comprises a wireless communication device based on a zigbee technology and is used for realizing data communication with a cloud server platform;
the acoustic array sensor module is used for receiving sound in the power equipment, and the acoustic array sensor consists of 4-200 piezoelectric crystals which are closely arranged at equal intervals and are arranged in an L shape;
the data amplification module is used for amplifying the sound received by the sound array sensor module and converting the sound into an electric signal;
the information transmission module is used for transmitting the electric signal converted by the data amplification module to the cloud server platform;
the cloud server platform is used for denoising and storing the received original signal and sending the denoised original signal to the edge computer;
the edge computer is used for receiving data from the cloud server platform, realizing edge calculation, extracting characteristic values and other related information of original data, accurately positioning a fault sound source, and determining whether to start the monitoring module for further checking equipment abnormality by a monitoring person operating the edge computer;
the monitoring module comprises a camera module, an angle adjusting module and a height adjusting module, the camera module is used for shooting and recording the power equipment under the control of an operator, the angle adjusting module is used for adjusting the angle of the camera module to realize omnibearing shooting and recording of the power equipment, and the height adjusting module is used for adjusting the height of the camera module.
The abnormality detection method includes the steps of:
s1, recording sound data of equipment operation through a plurality of groups of sound array sensors;
s2, amplifying the sound data recorded by the multiple groups of sound array sensors through the data amplification module, entering the next step when the amplified sound meets the requirement, and continuing to execute the step S2 if the amplified sound does not meet the requirement in the step S2 until the amplified sound meets the requirement;
s3, transmitting the amplified sound data to a cloud server platform through data to compare with normal sound data;
s4, carrying out grade judgment according to a preset sound threshold value to obtain an area where the abnormal sound is located, judging whether the abnormal sound is larger than a set value or not, if the abnormal sound is larger than the set value, entering the next step, in step S4, if the abnormal sound is not larger than the set value, ending the algorithm period, resetting, restarting from S1, and carrying out the next cycle;
s5, outputting initial abnormal sound, and determining whether to start the monitoring module to further check the equipment abnormality by monitoring personnel;
and S6, after the abnormal sound is output, the algorithm cycle is ended, and the sound is collected again through the sound array sensor.
The acoustic array sensor module is arranged to monitor the abnormal sound in the power equipment in an all-around manner, so that the fault sound source is accurately positioned, and the monitoring accuracy is improved; by amplifying the abnormal sound of the fault and defining a sensitive area, the reporting mode of the abnormal sound is effectively improved, and the processing efficiency is improved; by arranging the camera module, the angle adjusting module and the height adjusting module, the omnibearing shooting and recording of the power equipment are realized, a mode is further provided for determining an abnormal detection result, personnel does not need to check on site, and the processing efficiency is further improved.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should be considered to be within the technical scope of the present invention, and the technical solutions and the inventive concepts thereof according to the present invention should be equivalent or changed within the scope of the present invention.
Claims (7)
1. A power equipment abnormity detection method based on sound array edge calculation is characterized in that a power equipment abnormity detection device is adopted, the power equipment abnormity detection device comprises a main control module, a sound array sensor module, a data amplification module, an information transmission module and a monitoring module, and the sound array sensor module, the data amplification module, the information transmission module and the monitoring module are all coupled with the main control module;
the acoustic array sensor module is used for receiving sound in the power equipment;
the data amplification module is used for amplifying the sound received by the sound array sensor module and converting the sound into an electric signal;
the information transmission module is used for transmitting the electric signal converted by the data amplification module to the cloud server platform;
the cloud server platform is used for denoising and storing the received original signal and sending the denoised original signal to the edge computer;
the edge computer is used for receiving data from the cloud server platform, realizing edge calculation, extracting characteristic values and other related information of original data, accurately positioning a fault sound source, and determining whether to start the monitoring module for further checking equipment abnormality by a monitoring person operating the edge computer;
the abnormality detection method includes the steps of:
s1, recording sound data of equipment operation through a plurality of groups of sound array sensors;
s2, amplifying the sound data recorded by the multiple groups of sound array sensors through a data amplification module, and entering the next step when the amplified sound meets the requirement;
s3, transmitting the amplified sound data to a cloud server platform through data to compare with normal sound data;
s4, carrying out grade judgment according to a preset sound threshold value to obtain an area where the abnormal sound is located, judging whether the abnormal sound is greater than a set value or not, and entering the next step if the abnormal sound is greater than the set value;
s5, outputting initial abnormal sound, and determining whether to start the monitoring module to further check the equipment abnormality by monitoring personnel;
and S6, after the abnormal sound is output, the algorithm cycle is ended, and the sound is collected again through the sound array sensor.
2. The method for detecting the abnormality of the electric power equipment based on the acoustic array edge calculation as claimed in claim 1, wherein the acoustic array sensor is composed of 4-200 piezoelectric crystals, and the piezoelectric crystals are closely arranged at equal intervals in an L-shaped arrangement.
3. The method as claimed in claim 1, wherein in step S2, if the amplified sound does not meet the requirement, the step S2 is continued until the amplified sound meets the requirement.
4. The method for detecting abnormality of electric power equipment based on acoustic array edge calculation as claimed in claim 1, wherein in step S4, if the abnormal sound is not larger than the set value, the algorithm cycle is ended, reset, and restart from S1 for the next cycle.
5. The method for detecting the abnormality of the electric power equipment based on the acoustic array edge calculation according to claim 1, wherein the monitoring module includes a camera module, an angle adjustment module and a height adjustment module, the camera module is used for shooting and recording the electric power equipment under the control of an operator, the angle adjustment module is used for adjusting the angle of the camera module to realize omnibearing shooting and recording of the electric power equipment, and the height adjustment module is used for adjusting the height of the camera module.
6. The method for detecting the abnormality of the electric power equipment based on the acoustic array edge computing as claimed in claim 1, wherein the main control module is composed of an embedded microprocessor and a data storage card, and the information transfer module includes a wireless communication device based on a zigbee technology, and is used for realizing data communication with a cloud server platform.
7. The method for detecting the abnormality of the electrical equipment based on the acoustic array edge calculation as claimed in claim 5, wherein the angle adjustment module comprises a micro motor, a gear box, a driving wheel and a free steering wheel, the micro motor is connected with the driving wheel through the gear box and a chain, and transmits power to the camera module for driving the camera module to rotate.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010495890.3A CN111693135A (en) | 2020-06-03 | 2020-06-03 | Power equipment anomaly detection method based on acoustic array edge calculation |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010495890.3A CN111693135A (en) | 2020-06-03 | 2020-06-03 | Power equipment anomaly detection method based on acoustic array edge calculation |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN111693135A true CN111693135A (en) | 2020-09-22 |
Family
ID=72479427
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010495890.3A Pending CN111693135A (en) | 2020-06-03 | 2020-06-03 | Power equipment anomaly detection method based on acoustic array edge calculation |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111693135A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113365200A (en) * | 2021-06-07 | 2021-09-07 | 杭州纳奇思科技有限公司 | Self-adaptive abnormal sound source detection device and detection method |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP0342597B1 (en) * | 1988-05-16 | 1994-12-28 | Hitachi, Ltd. | Abnormality system for a high voltage power supply apparatus |
| CN201549049U (en) * | 2009-11-18 | 2010-08-11 | 吉林省电力有限公司长春供电公司 | Intelligent transformer substation audio-video alarm device |
| US20140216157A1 (en) * | 2013-02-05 | 2014-08-07 | Tzu-Feng Wang-Lee | Method for Determining Arc Discharge as well as Failure of Mechanical Vibration and Abnormal Displacement in Power Equipment Using Acoustic Energy Feature |
| CN105867366A (en) * | 2016-03-28 | 2016-08-17 | 国网福建省电力有限公司 | Method for full-automatic smart routing inspection of electrical equipment in substation |
| CN109406965A (en) * | 2018-11-16 | 2019-03-01 | 国网江苏省电力有限公司盐城供电分公司 | A kind of partial discharge detecting system and its detection method based on sound signal collecting |
| CN110146764A (en) * | 2019-06-14 | 2019-08-20 | 国网新疆电力有限公司电力科学研究院 | A kind of power equipment method for detecting abnormality based on acoustic array edge calculations |
-
2020
- 2020-06-03 CN CN202010495890.3A patent/CN111693135A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP0342597B1 (en) * | 1988-05-16 | 1994-12-28 | Hitachi, Ltd. | Abnormality system for a high voltage power supply apparatus |
| CN201549049U (en) * | 2009-11-18 | 2010-08-11 | 吉林省电力有限公司长春供电公司 | Intelligent transformer substation audio-video alarm device |
| US20140216157A1 (en) * | 2013-02-05 | 2014-08-07 | Tzu-Feng Wang-Lee | Method for Determining Arc Discharge as well as Failure of Mechanical Vibration and Abnormal Displacement in Power Equipment Using Acoustic Energy Feature |
| CN105867366A (en) * | 2016-03-28 | 2016-08-17 | 国网福建省电力有限公司 | Method for full-automatic smart routing inspection of electrical equipment in substation |
| CN109406965A (en) * | 2018-11-16 | 2019-03-01 | 国网江苏省电力有限公司盐城供电分公司 | A kind of partial discharge detecting system and its detection method based on sound signal collecting |
| CN110146764A (en) * | 2019-06-14 | 2019-08-20 | 国网新疆电力有限公司电力科学研究院 | A kind of power equipment method for detecting abnormality based on acoustic array edge calculations |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113365200A (en) * | 2021-06-07 | 2021-09-07 | 杭州纳奇思科技有限公司 | Self-adaptive abnormal sound source detection device and detection method |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US10288043B2 (en) | Wind turbine condition monitoring method and system | |
| CN204439797U (en) | A kind of Diagnostic system of motor fault | |
| CN103245912B (en) | A kind of running of wind generating set state analysis diagnostic method and system | |
| CN102494894A (en) | Audio monitoring and fault diagnosis system for wind generating set and audio monitoring and fault diagnosis method for same | |
| CN103115667B (en) | A kind of sensor-based vibration monitoring device | |
| CN101719309A (en) | System and method for monitoring running state of intelligent LED display | |
| CN201666248U (en) | Natural gas compressor state detection and failure predication system | |
| CN201523223U (en) | Intelligent monitoring system for surge protector | |
| CN103513180A (en) | Motor operation state monitoring and fault detecting system | |
| CN104730081A (en) | Failure detection system for wind power blade | |
| CN101086513A (en) | Transmission line real-time on-line monitoring method based on acoustic emission principle and the device | |
| CN106706241B (en) | Active self-checking device and method for damage of wind turbine blade | |
| CN111693135A (en) | Power equipment anomaly detection method based on acoustic array edge calculation | |
| CN104280683A (en) | Mechanical fault monitoring device for power transformer motor and fan | |
| US11308408B2 (en) | Fault signal recovery system and method | |
| CN103310389A (en) | Method for overhauling fault of overhead transmission line built on basis of fault mode and fault tree | |
| CN202091172U (en) | Device for monitoring state and analyzing reliability of gas compressor | |
| CN104297686A (en) | Electromobile motor data monitoring system based on LabVIEW | |
| CN103969331A (en) | Wind driven generator blade detection device | |
| CN116667783A (en) | Distributed photovoltaic power station maintenance system | |
| CN106195247A (en) | A kind of control system of speed variator based on big Db Management Model | |
| CN101930037A (en) | Intelligent monitoring system for surge protector | |
| CN202916000U (en) | Electronic vibration switch | |
| CN212007343U (en) | Remote diagnosis and analysis system for stone crushing and screening equipment | |
| CN102914360A (en) | Monitoring device and monitoring method for vibration of redundancy type wind turbine generator |
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 | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20200922 |
|
| RJ01 | Rejection of invention patent application after publication |