CN109459500A - The online high speed acquisition processing system of acoustic emission signal - Google Patents

The online high speed acquisition processing system of acoustic emission signal Download PDF

Info

Publication number
CN109459500A
CN109459500A CN201811287165.6A CN201811287165A CN109459500A CN 109459500 A CN109459500 A CN 109459500A CN 201811287165 A CN201811287165 A CN 201811287165A CN 109459500 A CN109459500 A CN 109459500A
Authority
CN
China
Prior art keywords
data
acoustic emission
signal
arm processor
processor
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
Application number
CN201811287165.6A
Other languages
Chinese (zh)
Inventor
何鹏举
于子江
袁伟标
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Shenzhen Institute Northwestern Polytechnical University
Original Assignee
Shenzhen Institute Northwestern Polytechnical University
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Shenzhen Institute Northwestern Polytechnical University filed Critical Shenzhen Institute Northwestern Polytechnical University
Priority to CN201811287165.6A priority Critical patent/CN109459500A/en
Publication of CN109459500A publication Critical patent/CN109459500A/en
Pending legal-status Critical Current

Links

Classifications

    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N29/00Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
    • G01N29/14Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object using acoustic emission techniques
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N29/00Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
    • G01N29/44Processing the detected response signal, e.g. electronic circuits specially adapted therefor

Abstract

The invention discloses the online high speed acquisition processing systems of acoustic emission signal, it is related to signal processing technology field, including the heterogeneous polynuclear embedded signal acquisition being made of FPGA, DSP and ARM and processing platform, and pass through the calculating and storage capacity of privately owned cloud computing remote server expansion embedded system;On-line checking based on Implementation of Embedded System equipment operation base state, equipment key part health status, the remote server based on privately owned cloud computing realize that unified management and signal collaboration to distributed embedded test node fault data are handled.

Description

The online high speed acquisition processing system of acoustic emission signal
Technical field
The present invention relates to signal processing technology fields, more particularly to the online high speed acquisition processing system of acoustic emission signal System.
Background technique
With the progress of Mechanical Industry Technology, mechanical equipment intelligence degree, in terms of achieve length Foot development.On the one hand the development of modern machinery and equipment is conducive to improve productivity, reduces cost;On the other hand due to the rule of equipment Mould is huge, and distributional region is wide, and composed structure is complicated, and each section connection is close, once it is lost caused by breaking down also substantially Increase.In petroleum, metallurgy, electric power, in the fields such as chemical industry, some mechanical equipments once break down, and will seriously endanger the public's The person and property safety.Traditional mechanical equipment detection method is the health status of regular offline inspection equipment, but to some sides Edge area and unattended equipment are since the variation of environment can usually break down in detection cycle and then lead to safe thing Therefore.
Traditional mechanical equipment state detection system is generally basede on the acquisition of vibration signal and equipment state inspection is realized in analysis It surveys, acoustic emission testing technology has following advantage relative to vibration detection as a kind of non-destructive testing new technology: characteristic frequency is obvious, Acoustic emission signal is wider compared to vibration signals spectrograph, and the high frequency characteristics based on sound emission can inhibit to interfere;When forecasting failure Between it is early, such as in bearing and gear testing, be not easy to detect in failure initial stage vibrating sensor, and acoustic emission signal can be examined Measure significant change;Therefore acoustic emission is easier to detect initial failure;Acoustic emission testing technology is especially suitable to be surveyed on site Examination, detection device is simple, high reliablity, and anti-interference is good.
Current AE detection system is based primarily upon the data collecting card data acquisition of the companies such as NI, PAC, based on upper Machine completes the various real-time analyses such as Data Analysis Services, such as completion acoustic emission source positioning and ex-post analysis function.This detection System is on the one hand expensive, is not on the other hand suitable for long-range unattended application scenarios, can not achieve on-line testing.One As long-range unattended test all realize that signal acquires and online processing in real time by embedded testing instrument system.However, In AE detection system, the AE signal that metal structure generates is generally between 50KHz-950KHz, according to sampling thheorem, system signal Sample rate is 2MS/s.Such as to realize on-line checking mechanical equipment, embedded system just needs to handle 2MS/s real-time stream, this It is a challenging problem, there is presently no effective high speed acquisition processing systems.
Summary of the invention
The embodiment of the invention provides the online high speed acquisition processing systems of acoustic emission signal, can solve in the prior art There are the problem of.
The present invention provides the online high speed acquisition processing system of acoustic emission signal, which includes the sound being sequentially connected electrically Emission sensor, signal conditioning circuit, analog-digital converter, fpga chip, dual core processors and privately owned cloud computing remote service Device, the acoustic emission sensor are mounted on equipment under test, for acquiring the acoustic emission signal of equipment under test generation, and sound are sent out It penetrates signal and is sent to the signal conditioning circuit, the signal conditioning circuit is filtered and amplifies to received acoustic emission signal The analog-digital converter is sent to after processing, the acoustic emission signal after received conditioning is converted to number by the analog-digital converter Signal, and it is sent to the fpga chip;
The fpga chip reads the digital signal latter aspect that the analog-digital converter is sent and is written by A D interface Asynchronous FIFO, and back-end logic data acquisition function is combined, the on the other hand input as RMS computing module is complete in real time At the calculating of RMS value;
The dual core processors include model arm processor and dsp processor, at the fpga chip and DSP It manages between device using EMIF interface as data/address bus, handshake procedure, the DSP is completed using Handshake Protocol before data transmission Processor uses a part of L2RAM as shared section key to carry out data transmission using with the arm processor, described Dsp processor realizes internuclear synchronous, the dsp processor configuration EDMA control with arm processor using Notify component, by EDMA controller driving EMIF interface reads data from the fpga chip, and the arm processor reads institute using SysLink The data in the shared section key of dsp processor are stated, then the data of reading are transmitted through the network to institute by the arm processor State privately owned cloud computing remote server;
Transplanting has mobile Agent in the dual core processors, and the data of acquisition are transmitted to private in the arm processor After having cloud computing remote server, the privately owned cloud computing remote server carries out batch processing and storage to received data, Then it is long-range to be moved to the privately owned cloud computing for the real-time blind separation study phase algorithm of the parallel single channel of the mobile Agent carrying Server carries out the distributed parallel batch processing of big data.
The online high speed acquisition processing system of acoustic emission signal in the embodiment of the present invention, including by FPGA, DSP and ARM The heterogeneous polynuclear embedded signal of composition acquires and processing platform, and expands embedded system by privately owned cloud computing remote server The calculating and storage capacity of system;Based on Implementation of Embedded System equipment operation base state, equipment key part health status On-line checking is realized based on privately owned cloud computing remote server and is managed to the unified of distributed embedded test node fault data Reason.
Detailed description of the invention
In order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, to embodiment or will show below There is attached drawing needed in technical description to be briefly described, it should be apparent that, the accompanying drawings in the following description is only this Some embodiments of invention for those of ordinary skill in the art without creative efforts, can be with It obtains other drawings based on these drawings.
Fig. 1 is the structural block diagram of the online high speed acquisition processing system of acoustic emission signal of the embodiment of the present invention.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete Site preparation description, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.It is based on Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts every other Embodiment shall fall within the protection scope of the present invention.
Referring to Fig.1, the embodiment of the invention provides the online high speed acquisition processing system of acoustic emission signal, which includes Sound emission (AE) sensor for being sequentially connected electrically, signal conditioning circuit, analog-digital converter, fpga chip, dual core processors and Privately owned cloud computing remote server, the acoustic emission sensor are mounted on equipment under test, for acquiring equipment under test generation Acoustic emission signal, and acoustic emission signal is sent to the signal conditioning circuit, the signal conditioning circuit sends out received sound Signal is penetrated to be filtered and be sent to the analog-digital converter after enhanced processing.The analog-digital converter will be after received conditioning Acoustic emission signal is converted to digital signal, and is sent to the fpga chip.Analog-digital converter described in the present embodiment is AD7622 modulus conversion chip.
The fpga chip reads the digital signal latter aspect that the analog-digital converter is sent and is written by A D interface Asynchronous FIFO (i.e. DCFIFO), and back-end logic data acquisition function is combined, on the other hand as the defeated of RMS computing module Enter, completes the calculating of RMS value in real time.
The dual core processors model OMAPL138, the processor include the arm processor of model 926EJ_S with And the dsp processor of model C674X.Using EMIF interface as data/address bus between the fpga chip and dsp processor, Handshake procedure is completed using Handshake Protocol before data transmission.The dsp processor uses a part of L2RAM as shared interior Arm processor described in Qu Yiyu is deposited to carry out data transmission using dsp processor and arm processor are realized using Notify component Internuclear synchronization.The dsp processor configuration EDMA control, is read from the fpga chip by EDMA controller driving EMIF interface Access evidence, the arm processor directly read the data in the shared section key of the dsp processor using SysLink, then The data of reading are transmitted through the network to the privately owned cloud computing remote server by the arm processor.
Acoustic emission sensor, signal conditioning circuit, analog-digital converter, fpga chip and double-core processing in above system Device is known as detection node, and a detection node is respectively mounted on each equipment under test.Arm processor obtains in multiple detection nodes Data are sent in the privately owned cloud computing remote server being arranged in a region.Ethernet is described in Network Abnormal Arm processor can not normally send data, and the data that can be will acquire at this time are stored in the SD card of detection node.The ARM The starting that processor also controls data receives, and after the data receiver for completing preset times, the data of storage are passed through TCP/IP Agreement is transmitted to the privately owned cloud computing remote server.
Data sampling rate is controlled by the frequency division module of the fpga chip, can support the sample rate of 2MS/s, acquires data Amount determined by preset receive number, to adapt to the demand of different duration collections.
Carried out data transmission between the dsp processor and arm processor using double-core flowing water parallel scheme, it is specific next Say, the dsp processor be used to complete to take a long time it is suitable determine signal reconstruction tasks, the arm processor is used to complete SOBI And power Spectral Estimation task.Since the dsp processor time-consuming is longer than the arm processor, there is no need to between double-core Shared section key carry out exclusive reference setting, i.e., the dsp processor complete a frame data it is suitable determine signal reconstruction after be not necessarily to It waits the arm processor to complete and directly starts the processing of next frame data.Therefore, although the processing time-consuming of every frame data not It reduces, but the optimization design based on double-core flowing water parallel scheme improves the throughput (number handled in the unit time of system Increase according to frame number).
In above-mentioned double-core flowing water parallel scheme, a complete process flow is divided into according to data flow without preceding Xiang Yi 3 bad subtasks, are denoted as Task0, Task1 and Task2 respectively, this 3 subtasks be respectively divided to the fpga chip, In the core of this 3 processors of dsp processor and arm processor.After 0th processor core completes the calculating of Task0, by result It exports to the 1st processor core, and continues to complete the part Task1 of new task, the 1st processor core is completed result after calculating Output to the 2nd processor core completes Task2, and so on, although this parallel mode fails to provide the execution of entire task Efficiency, but improve the data throughput of system.
User can access the privately owned cloud computing remote server by browser, and then access each detection section The testing result of point, multiple detection nodes use distributed arrangement.High speed acquisition processing system i.e. in this law invention can Detection node data acquisition and processing to be divided into client layer and data acquisition and process layer, in data acquisition and procession layer Task, and service is provided to client layer by the privately owned cloud computing remote server.
It includes: cycle data acquisition transmission module, equipment key portion that each detection node is divided from functional module Position health status identification module, equipment running status detect FIR-RMS module, remote testing module.
(1) cycle data acquisition transmission module is the data for being 2MS/s based on the OMAPL138 and FPGA sample rate realized The characteristics of acquisition module has configuration convenient, and sample rate is high, supports a variety of data storage methods.According to data flow, the mould For number converter after completing analog-to-digital conversion, the dsp processor configures EDMA controller, drives EMIF interface by EDMA controller Data are read from the fpga chip, the arm processor is communicated by SysLink component with the dsp processor, directly The L2RAM for reading the dsp processor is met, by reading data to the memory of the arm processor, the arm processor will be counted It is also configurable under network abnormal situation by data according to the privately owned cloud computing remote server is transmitted through the network to It is stored in SD card.
(2) working condition of equipment key position health status identification module is divided into study stage and working stage.It is learning The habit stage, need to complete signal sources number detection separated with each road signal AR spectrum determine rank and AR Power estimation.In working stage, directly It connects the information source number reconstruct obtained according to the study stage and fits and determine signal, and the order obtained when AR Power estimation using the study stage, After completing Power estimation, is compared by power spectrum and determine operating status.Start the cycle data acquisition transmission module if abnormal Transmission mode is acquired into cycle data, one cycle data transfer of acquisition to the privately owned cloud computing remote server establishes ' event Hinder dictionary '.In working stage, the signal of resume module is the frame data acquired in real time, and a frame data are 1024 in the present invention Point.
(3) equipment running status detection FIR-RMS module passes through the RMS calculated in real time as characteristic value, in the study stage It finds out RMS to change most significant frequency range and generate threshold value, judges state using the RMS value of this frequency range as foundation in working stage. Compared to being completed in the fpga chip in the dsp processor or arm processor realization, timely with detection, delay is low Advantage.
(4) in order to improve efficiency, more easily equipment under test state is detected convenient for staff, described Flush type WEB server BOA is transplanted on arm processor, and develops web page program and shows equipment state and operation data, referred to as The remote testing module.
It includes: real-time detection mode and cycle data acquisition transmission mould that each detection node is divided from operating mode Formula.After the detection node powers on, the arm processor is started and carried out self-starting script, into real-time detection mode, in reality When detection pattern under, complete the study stage after, into working stage.When working stage detects abnormal state, or execution time After number reaches the upper limit value of setting, then enters cycle data and acquire transmission mode.
The switching of operating mode is real by the program under arm processor operating mode corresponding with dsp processor calling Existing, i.e., cycle data acquisition transmission module, equipment key position health status identification module realize part on OMAPL138 Program switching (equipment running status detection algorithm FIR-RMS is realized in fpga chip).In the present invention, set OMAPL138's Arm processor is master control core, starts the dsp processor by SLAVELOADER and executes specific program, and can be stopped described The operation of dsp processor.The program entry of the detection node is the SHELL script of arm processor.
The privately owned cloud computing remote server stores after receiving data, and data and the status information of particular device are closed Connection, establishes Mishap Database.
The privately owned cloud computing remote server develops connecing for multithreading by pthread (POSIX thread) thread library Receive program.For each request, generation data receiver thread is gone to the data for receiving detection node transmission, and main thread continues to hold Row ACCEPT system call waiting, which is newly connected to, to be come.Data receiver thread establishes the Connection Time to data according to detection node IP+ It is named, is stored in server hard disc, complete reception task backed off after random.
Clock scheme between heretofore described detection node realizes high-precision based on OMAPL138 and DP83640 on hardware PTP ordinary clock node;Linux kernel is transplanted in the arm processor on software, IEEE1588 protocol stack uses out The LinuxPTP software in source.
In the present invention, remote collaborative processing is carried out using mobile Agent.Specifically, the mobile Agent is implanted in In OMAPL138, after the data of acquisition are transmitted to privately owned cloud computing remote server by arm processor, privately owned cloud computing is long-range Server carries out batch processing, data storage and single channel mixed signal data flow to these data and handles in real time, batch processing It is handled including single channel blind separation and state space modeling.Mobile Agent carries the real-time blind separation of parallel single channel according to setting Learn phase algorithm by OMAPL138 autonomous to privately owned cloud computing remote server, carries out the distributed parallel batch of big data Processing, is calculated state-space model by the study stage.Then the data flow sent from arm processor is received, is utilized State-space model separates data stream in real time, and then detects and obtain the real-time status of equipment under test.
Although preferred embodiments of the present invention have been described, it is created once a person skilled in the art knows basic Property concept, then additional changes and modifications may be made to these embodiments.So it includes excellent that the following claims are intended to be interpreted as It selects embodiment and falls into all change and modification of the scope of the invention.
Obviously, various changes and modifications can be made to the invention without departing from essence of the invention by those skilled in the art Mind and range.In this way, if these modifications and changes of the present invention belongs to the range of the claims in the present invention and its equivalent technologies Within, then the present invention is also intended to include these modifications and variations.

Claims (6)

1. the online high speed acquisition processing system of acoustic emission signal, which is characterized in that the system includes the sound hair being sequentially connected electrically Sensor, signal conditioning circuit, analog-digital converter, fpga chip, dual core processors and privately owned cloud computing remote server are penetrated, The acoustic emission sensor is mounted on equipment under test, for acquiring the acoustic emission signal of equipment under test generation, and by sound emission Signal is sent to the signal conditioning circuit, the signal conditioning circuit to received acoustic emission signal be filtered and amplification at The analog-digital converter is sent to after reason, the acoustic emission signal after received conditioning is converted to digital letter by the analog-digital converter Number, and it is sent to the fpga chip;
The digital signal latter aspect that the fpga chip reads the analog-digital converter transmission is written asynchronous by A D interface FIFO, and back-end logic data acquisition function is combined, on the other hand the input as RMS computing module, completes RMS in real time The calculating of value;
The dual core processors include model arm processor and dsp processor, the fpga chip and dsp processor Between data/address bus is used as using EMIF interface, handshake procedure is completed using Handshake Protocol before data transmission, the DSP is handled Device uses a part of L2RAM as shared section key to carry out data transmission using with the arm processor, at the DSP It is internuclear synchronous using the realization of Notify component with arm processor to manage device, the dsp processor configuration EDMA control is controlled by EDMA Device driving EMIF interface processed reads data from the fpga chip, and the arm processor reads the DSP using SysLink Data in the shared section key of processor, then the data of reading are transmitted through the network to the private by the arm processor There is cloud computing remote server;
Transplanting has mobile Agent in the dual core processors, and the data of acquisition are transmitted to private clound in the arm processor After calculating remote server, the privately owned cloud computing remote server carries out batch processing and storage to received data, then The mobile Agent carries the real-time blind separation study phase algorithm of parallel single channel and is moved to the privately owned cloud computing remote service Device carries out the distributed parallel batch processing of big data.
2. such as the online high speed acquisition processing system of claim 1 acoustic emission signal, which is characterized in that the analog-digital converter is AD7622 modulus conversion chip, the dual core processors model OMAPL138, the model 926EJ_ of the arm processor S, the model C674X of the dsp processor.
3. such as the online high speed acquisition processing system of claim 1 acoustic emission signal, which is characterized in that the voice sending sensor Device, signal conditioning circuit, analog-digital converter, fpga chip and dual core processors are known as detection node, on each equipment under test It is respectively mounted a detection node, in ethernet network exception, the data that the arm processor will acquire are stored in detection node SD card in, the starting of arm processor control data receives, after the data receiver for completing preset times, by storage Data are transmitted to the privately owned cloud computing remote server by ICP/IP protocol.
4. as claim 1 acoustic emission signal online high speed acquisition processing system, which is characterized in that the dsp processor and Carried out data transmission between arm processor using double-core flowing water parallel scheme, the double-core flowing water parallel scheme is at the DSP Reason device, which is completed to fit, determines signal reconstruction tasks, and the arm processor completes SOBI and power Spectral Estimation task.
5. such as the online high speed acquisition processing system of claim 1 acoustic emission signal, which is characterized in that the privately owned cloud computing is remote Journey server stores after receiving data, and data are associated with the status information of particular device, establishes Mishap Database.
6. such as the online high speed acquisition processing system of claim 1 acoustic emission signal, which is characterized in that for each request, institute The reception program for stating the multithreading that privately owned cloud computing remote server is developed by pthread thread library will generate data receiver line Journey goes to receive the data of detection node transmission, and main thread continues to execute the call waiting of ACCEPT system and be newly connected to, data Receiving thread is established the Connection Time according to detection node IP+ and is named to data, and server hard disc is stored in, and completes to receive and appoint Business backed off after random.
CN201811287165.6A 2018-10-31 2018-10-31 The online high speed acquisition processing system of acoustic emission signal Pending CN109459500A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201811287165.6A CN109459500A (en) 2018-10-31 2018-10-31 The online high speed acquisition processing system of acoustic emission signal

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201811287165.6A CN109459500A (en) 2018-10-31 2018-10-31 The online high speed acquisition processing system of acoustic emission signal

Publications (1)

Publication Number Publication Date
CN109459500A true CN109459500A (en) 2019-03-12

Family

ID=65609087

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201811287165.6A Pending CN109459500A (en) 2018-10-31 2018-10-31 The online high speed acquisition processing system of acoustic emission signal

Country Status (1)

Country Link
CN (1) CN109459500A (en)

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110708513A (en) * 2019-10-18 2020-01-17 中国科学院长春光学精密机械与物理研究所 8K video multi-core heterogeneous processing device
CN111272401A (en) * 2020-03-04 2020-06-12 云南电网有限责任公司电力科学研究院 GIS mechanical fault diagnosis method and system based on acoustic emission signals
CN111855817A (en) * 2020-07-28 2020-10-30 西北工业大学 Method for cooperatively detecting fatigue crack by cloud edge end of complex structural member

Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101606848A (en) * 2008-06-20 2009-12-23 Ge医疗系统环球技术有限公司 Data entry device and supersonic imaging device
CN102506994A (en) * 2011-11-21 2012-06-20 嘉兴中科声学科技有限公司 Digitized acoustic detection system
WO2012125296A2 (en) * 2011-03-16 2012-09-20 Microscan Systems, Inc. Multi-core distributed processing for machine vision applications
CN103169495A (en) * 2012-12-06 2013-06-26 广州丰谱信息技术有限公司 Monitoring method and monitoring device of movable ultrasonic image with high resolution
CN104978744A (en) * 2015-06-16 2015-10-14 谢维波 Smog detection system based on heterogeneous dual cores
CN105415191A (en) * 2015-11-26 2016-03-23 西北工业大学 Grinding state detecting and controlling method and device based on sound emission
CN105678727A (en) * 2016-01-12 2016-06-15 四川大学 Infrared and visible light image real-time fusion system based on heterogeneous multi-core architecture
CN107742004A (en) * 2016-09-23 2018-02-27 华中科技大学 A kind of main shaft of numerical control machine tool data simulation method based on historical data

Patent Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101606848A (en) * 2008-06-20 2009-12-23 Ge医疗系统环球技术有限公司 Data entry device and supersonic imaging device
WO2012125296A2 (en) * 2011-03-16 2012-09-20 Microscan Systems, Inc. Multi-core distributed processing for machine vision applications
CN102506994A (en) * 2011-11-21 2012-06-20 嘉兴中科声学科技有限公司 Digitized acoustic detection system
CN103169495A (en) * 2012-12-06 2013-06-26 广州丰谱信息技术有限公司 Monitoring method and monitoring device of movable ultrasonic image with high resolution
CN104978744A (en) * 2015-06-16 2015-10-14 谢维波 Smog detection system based on heterogeneous dual cores
CN105415191A (en) * 2015-11-26 2016-03-23 西北工业大学 Grinding state detecting and controlling method and device based on sound emission
CN105678727A (en) * 2016-01-12 2016-06-15 四川大学 Infrared and visible light image real-time fusion system based on heterogeneous multi-core architecture
CN107742004A (en) * 2016-09-23 2018-02-27 华中科技大学 A kind of main shaft of numerical control machine tool data simulation method based on historical data

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
何鹏举 等: ""单通道AE信号盲分离的飞机构件监测方法研究"", 《仪器仪表学报》 *
山东省科学技术协会 主编: "《2007-2008山东省学科发展报告》", 30 September 2008 *
陈泰红 等: "《手把手教你学DSP》", 31 January 2016 *

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110708513A (en) * 2019-10-18 2020-01-17 中国科学院长春光学精密机械与物理研究所 8K video multi-core heterogeneous processing device
CN111272401A (en) * 2020-03-04 2020-06-12 云南电网有限责任公司电力科学研究院 GIS mechanical fault diagnosis method and system based on acoustic emission signals
CN111855817A (en) * 2020-07-28 2020-10-30 西北工业大学 Method for cooperatively detecting fatigue crack by cloud edge end of complex structural member

Similar Documents

Publication Publication Date Title
Moreno et al. Proactive self-adaptation under uncertainty: a probabilistic model checking approach
CN108353090B (en) Method for improving processing of sensor stream data in a distributed network
Lorincz et al. Resource aware programming in the pixie os
Wang et al. A wireless structural health monitoring system with multithreaded sensing devices: design and validation
Zimmerman et al. Automated modal parameter estimation by parallel processing within wireless monitoring systems
Beneventi et al. Continuous learning of HPC infrastructure models using big data analytics and in-memory processing tools
AU2016380302B2 (en) Computer storage medium, computer program product, method for monitoring fault of wind power generator set, and device
US9519571B2 (en) Method for analyzing transaction traces to enable process testing
CN101577426B (en) Power system state estimator applicable to wide area measurement system
Tikir et al. PSINS: An open source event tracer and execution simulator for MPI applications
CN101084488B (en) Method and system for debugging multithreading procedure in a multicore architecture
Grimaldi et al. Java-based distributed measurement systems
EP2882141A1 (en) Network test system
Rossigneux et al. A generic and extensible framework for monitoring energy consumption of OpenStack clouds
CN103713281B (en) Based on radar signal unit performance test and the fault diagnosis system of general-utility test platform
Zhong et al. Power system frequency monitoring network (FNET) implementation
CN104242447A (en) Integrated measuring and controlling device and system of intelligent transformer substation
CN105338061B (en) A kind of implementation method and system of lightweight messages middleware
CN201742158U (en) Online monitoring device for power transformer
US20090198383A1 (en) Location determination of power system disturbances based on frequency responses of the system
CN102841835B (en) The method and system of hardware performance evaluation and test
Li et al. CAPES: Unsupervised storage performance tuning using neural network-based deep reinforcement learning
CN103294579A (en) Method for testing high-performance computing cluster application performance
EP2741450B1 (en) Systems for synchrophasor data management
CN101874229B (en) Method and system for registering events in wind turbines of a wind power system

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