CN107414600A - The process monitoring method of internal thread low frequency exciting cold extrusion lathe based on multiple sensor signals - Google Patents

The process monitoring method of internal thread low frequency exciting cold extrusion lathe based on multiple sensor signals Download PDF

Info

Publication number
CN107414600A
CN107414600A CN201710309037.6A CN201710309037A CN107414600A CN 107414600 A CN107414600 A CN 107414600A CN 201710309037 A CN201710309037 A CN 201710309037A CN 107414600 A CN107414600 A CN 107414600A
Authority
CN
China
Prior art keywords
internal thread
screw tap
signal
low frequency
abrasion
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
CN201710309037.6A
Other languages
Chinese (zh)
Inventor
崔晓飞
廖泽南
侯源君
左敦稳
孙玉利
徐洋
汤苏扬
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.)
Nanjing University of Aeronautics and Astronautics
Original Assignee
Nanjing University of Aeronautics and Astronautics
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 Nanjing University of Aeronautics and Astronautics filed Critical Nanjing University of Aeronautics and Astronautics
Priority to CN201710309037.6A priority Critical patent/CN107414600A/en
Publication of CN107414600A publication Critical patent/CN107414600A/en
Pending legal-status Critical Current

Links

Classifications

    • BPERFORMING OPERATIONS; TRANSPORTING
    • B23MACHINE TOOLS; METAL-WORKING NOT OTHERWISE PROVIDED FOR
    • B23QDETAILS, COMPONENTS, OR ACCESSORIES FOR MACHINE TOOLS, e.g. ARRANGEMENTS FOR COPYING OR CONTROLLING; MACHINE TOOLS IN GENERAL CHARACTERISED BY THE CONSTRUCTION OF PARTICULAR DETAILS OR COMPONENTS; COMBINATIONS OR ASSOCIATIONS OF METAL-WORKING MACHINES, NOT DIRECTED TO A PARTICULAR RESULT
    • B23Q17/00Arrangements for observing, indicating or measuring on machine tools
    • B23Q17/09Arrangements for observing, indicating or measuring on machine tools for indicating or measuring cutting pressure or for determining cutting-tool condition, e.g. cutting ability, load on tool
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B23MACHINE TOOLS; METAL-WORKING NOT OTHERWISE PROVIDED FOR
    • B23GTHREAD CUTTING; WORKING OF SCREWS, BOLT HEADS, OR NUTS, IN CONJUNCTION THEREWITH
    • B23G1/00Thread cutting; Automatic machines specially designed therefor
    • B23G1/44Equipment or accessories specially designed for machines or devices for thread cutting
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B23MACHINE TOOLS; METAL-WORKING NOT OTHERWISE PROVIDED FOR
    • B23QDETAILS, COMPONENTS, OR ACCESSORIES FOR MACHINE TOOLS, e.g. ARRANGEMENTS FOR COPYING OR CONTROLLING; MACHINE TOOLS IN GENERAL CHARACTERISED BY THE CONSTRUCTION OF PARTICULAR DETAILS OR COMPONENTS; COMBINATIONS OR ASSOCIATIONS OF METAL-WORKING MACHINES, NOT DIRECTED TO A PARTICULAR RESULT
    • B23Q17/00Arrangements for observing, indicating or measuring on machine tools
    • B23Q17/20Arrangements for observing, indicating or measuring on machine tools for indicating or measuring workpiece characteristics, e.g. contour, dimension, hardness

Landscapes

  • Engineering & Computer Science (AREA)
  • Mechanical Engineering (AREA)
  • Automatic Control Of Machine Tools (AREA)
  • Measurement Of Mechanical Vibrations Or Ultrasonic Waves (AREA)

Abstract

A kind of process monitoring method of the internal thread low frequency exciting cold extrusion lathe based on multiple sensor signals, it is characterized in that:First with vibration amplitude and extrusion torque, temperature, the acoustic information of multi-sensor collection exciting device;Secondly the signal collected is analyzed, feature extraction, screw tap abrasion, internal thread quality is detected;Then build based on this under different technical parameters, multiple sensor signals and thread forming tap abrasion, the mapping model of internal thread quality;Realize and the lathe is monitored on-line, finally realize to screw tap abrasion condition and the on-line prediction of internal thread quality.Not only internal threads low frequency exciting cold extrusion special purpose machine tool has preferable applicability to the present invention, and can be widely applied to realize the lathe on-line monitoring field of processing using vibration principle.

Description

The process of internal thread low frequency exciting cold extrusion lathe based on multiple sensor signals Monitoring method
Technical field
It is particularly a kind of low suitable for internal thread the present invention relates to a kind of lathe and its on-line monitoring system of process The special on-line monitoring system of frequency exciting cold extrusion lathe, specifically a kind of internal thread low frequency based on multiple sensor signals The process monitoring method of exciting cold extrusion lathe.
Background technology
Class part is threadedly coupled as one of most important connection and structural member, has been widely used for heavy duty, high speed etc. Under the conditions of in the industrial circle such as shipbuilding, Aero-Space.At present, the internal thread that the cold extrusion of low frequency exciting shapes has more High case hardness and intensity, higher thread surface quality, lower production cost and higher production efficiency, are thus protected Mechanical performance and its fatigue life of important feature threaded connector are demonstrate,proved.
The core exciting device of internal thread low frequency exciting cold extrusion special purpose machine tool is under a kind of state based on balance Mechanical exciting device, extrusion torque, temperature, voice signal in the vibration amplitude and process of the exciting device The prediction of selection, thread forming tap wear extent and internal thread quality for machined parameters has important researching value.Thus adopt During with multi-sensor monitoring low frequency exciting Cold Extrusion Process, the monitoring signals of the reflection extrusion process of acquisition necessarily include screw tap The relevant information of abrasion condition, screw processing quality, similarly help to the optimum option of machined parameters.
But related on-line monitoring system is not high for the applicability of this lathe, is in particular in:1. add for vibration Amplitude monitoring in work all directly monitors the output amplitude of exciting device, and the screw tap of extrusion process is directly acted on without paying close attention to The vibration amplitude of working portion;2. the signal acquisition approach of most monitoring system is single, not according to itself spy of signal Point uses different acquisition methods.3. prediction screw tap abrasion condition and screw processing quality are only analyzed single signal, it is such One-sidedness be present in analysis method.
The content of the invention
The purpose of the present invention can not be reacted comprehensively for existing internal thread low frequency exciting cold extrusion lathe signal monitoring The problem of Cold Extrusion Process, invent a kind of process of the internal thread low frequency exciting cold extrusion lathe based on multiple sensor signals Monitoring method, each process information is directly gathered so as to more accurate, and distinguished by the transmission means suitable for each signal Preservation is transmitted, the purpose to low frequency exciting cold extrusion process on-line monitoring can be realized, so as to low frequency exciting cold-extruded Screw tap abrasion and internal thread quality in pressure processing carry out on-line prediction, by the optimization of machined parameters, and then effectively drop The abrasion of low screw tap and the machining accuracy for improving internal thread.
The technical scheme is that:
A kind of process monitoring method of the internal thread low frequency exciting cold extrusion lathe based on multiple sensor signals, its feature It is:First with vibration amplitude and extrusion torque, temperature, the acoustic information of multi-sensor collection exciting device;Secondly to adopting The signal collected is analyzed, feature extraction, and screw tap abrasion, internal thread quality are detected;Then build based on this Under different technical parameters, multiple sensor signals and thread forming tap abrasion, the mapping model of internal thread quality;Realization exists to the lathe Line monitors, and finally realizes to screw tap abrasion condition and the on-line prediction of internal thread quality.
The sensor of use includes:Piezoelectric acceleration transducer, torque sensor, infrared temperature sensor harmony hair Penetrate sensor.
The measurement of exciting amplitude uses the feeding acceleration of piezoelectric acceleration transducer direct measurement screw tap axial direction, according to Kinematic geometry relation calculates screw tap circumference angular displacement, the i.e. vibration amplitude of screw tap.
Acceleration, moment of torsion, voice signal are gathered by capture card, and temperature signal can not be neglected by capture card internal interference Slightly, so becoming warp let-off serial acquisition by secondary meter.
A variety of different characteristics of multiple sensor signals under different technical parameters in low frequency exciting cold extrusion are identified, Analysis;To different screw tap abrasion conditions, internal thread quality is tested and analyzed;Monitoring signals and screw tap are established on this basis Wear extent, the mapping relations of thread quality, to realize to screw tap wear extent, the on-line prediction of thread quality.
The beneficial effects of the invention are as follows:
(1)A kind of process monitoring system of internal thread low frequency exciting cold extrusion lathe based on multiple sensor signals of the present invention System, it uses different acquisition methods by different signal characteristics, so both ensure that the sample rate of signal, and reduced again dry The influence disturbed so that the acquisition collection of signal is more accurate.
(2)A kind of process prison of internal thread low frequency exciting cold extrusion lathe based on multiple sensor signals of the present invention Examining system, its multiple sensor signals feature established and screw tap abrasion, the mapping model of internal thread quality, not only from the more of signal Sample angle ensure that the accuracy of model, and more screw tap abrasion, the prediction of internal thread quality provides more accurate experiment Foundation.
(3)A kind of process prison of internal thread low frequency exciting cold extrusion lathe based on multiple sensor signals of the present invention Examining system, its screw tap established abrasion, forecast model of internal thread quality, not only have recorded substantial amounts of test data and is available for looking into Ask, can also constantly take in the accuracy that new test data improves amendment forecast model.
(4)A kind of process prison of internal thread low frequency exciting cold extrusion lathe based on multiple sensor signals of the present invention It examining system, can not only optimize low frequency exciting cold-extrusion technology parameter, reduce screw tap wear extent, improve the quality of internal thread, also It can be improved for the further design of internal thread low frequency exciting cold extrusion lathe and test basis is provided.
Brief description of the drawings
Fig. 1 is the functional-block diagram of the present invention.
Fig. 2 is the overview flow chart of the multiple sensor signals collection of the present invention.
Fig. 3 is screw tap-workpiece motion s schematic diagram of the present invention.
Fig. 4 is the schematic view of the mounting position of the vibration amplitude monitoring device of the present invention.1 is that piezoelectric type acceleration senses in figure Device, 2 be exciting device.
Fig. 5 is the moment of torsion, sound, the acquisition module of vibration signal of the present invention.
Fig. 6 is the acquisition module of the temperature signal of the present invention.
Fig. 7-1 is a kind of sound emission primary signal figure of the present invention.
Fig. 7-2 is a kind of power spectrum chart of acoustic emission signal of the present invention.
Fig. 7-3 is a kind of frequency domain character distribution map of acoustic emission signal of the present invention.
Fig. 8 is the partial enlarged drawing of the screw tap state of wear of the present invention.Wherein a is the mild wear state of screw tap, and b is silk The heavy wear state of cone, c are the breaking state of screw tap, and d is the slipping state of screw tap.
Fig. 9 is the internal thread hardness and hardened case distribution figure of the present invention.Including at root of the tooth, at tooth side, at crest Hardness and hardened case distribution.
Figure 10 is each signal characteristic and screw tap abrasion, the mapping of internal thread quality under the different technical parameters of the present invention Model flow figure.
Figure 11 is each signal characteristic and screw tap abrasion, the prediction of internal thread quality under the different technical parameters of the present invention Model flow figure.
Embodiment
The present invention is further described embodiment below in conjunction with the accompanying drawings.
As shown in figs. 1-11.
A kind of process monitoring method of the internal thread low frequency exciting cold extrusion lathe based on multiple sensor signals, first with Vibration amplitude and extrusion torque, temperature, the acoustic information of multi-sensor collection exciting device;Secondly the signal collected is entered Row analysis, feature extraction, screw tap abrasion, internal thread quality are detected;Then different technical parameters are built based on this Under, multiple sensor signals and thread forming tap abrasion, the mapping model of internal thread quality;Realize and the lathe is monitored on-line, finally Realize as follows to screw tap abrasion condition and the on-line prediction of internal thread quality, specific embodiment:
(1)Signal acquisition:Process signal is acquired using multisensor, and basis signal feature selects different adopt Diversity method.
1)The exciting amplitude of acceleration transducer measurement core exciting device, because the vibration amplitude of exciting device output exists It can decay in transmittance process, so answering the vibration amplitude of direct measurement screw tap working portion, therefore use acceleration transducer The acceleration of screw tap axial feed motion is measured, the rotational vibration amplitude of screw tap working portion is calculated.
2)Frequency acquisition required by vibration, moment of torsion and acoustic emission signal is higher, therefore uses data collecting card to simulate and believe Number being converted into data signal is acquired.
3) collection of temperature signal is easily by transmitting and capture card internal interference is influenceed, and not high in temperature In the case of disturb and can not ignore, therefore use secondary meter to become warp let-off serial acquisition into computer.
(2)Interpretation of result is handled:On the one hand, more sensings for being gathered in internal thread low frequency exciting cold extrusion process Device signal, according to the difference of signal characteristic, signal is subjected to different processing and extracts the characteristic information of correlation.On the other hand, Signature analysis record is carried out to the thread forming tap abrasion after the completion of process and internal thread quality.
1)Extrusion torque, temperature signal are the curve of change in process, so carrying out time-domain analysis.
2)Voice signal in process engineering will not only consider temporal signatures, it is also contemplated that its frequency change in process Change is frequency domain character, therefore to carry out time domain and the comprehensive analysis of time-frequency domain to acoustic emission signal.
3)The measurement of exciting amplitude is completed by acceleration transducer, only focuses on the circumferential amplitude of screw tap, so using preposition Acceleration signal is converted to displacement signal and is acquired by the double integrator function of amplifier.
4)The abrasion condition of thread forming tap is divided into normal operating conditions, mild wear state, heavy wear state, disconnected Split state and workpiece slipping state.
5)The crudy of internal thread is weighed using the surface hardness at internal thread root of the tooth, at tooth side and at crest.
(3)Establish mapping model:Establish under different technical parameters, exciting amplitude and extrusion torque, temperature, voice signal are special Sign and thread forming tap wear extent, the mapping model of internal thread machining quality.
(4)Establish forecast model:Realize and sensed according to the amplitude and moment of torsion of Metal Cutting Machine Tool Stimulated Vibration device, temperature, sound emission more Device signal wears to screw tap, the prediction of internal thread machining quality.For the reduction of the thread forming tap abrasion of the special purpose machine tool, internal thread Quality provides important practical guided significance, and provides experiment for the optimum option of the machined parameters of the lathe and refer to Lead.
Details are as follows:
As shown in Figure 1, this figure is the internal thread low frequency exciting cold extrusion lathe process monitoring based on multiple sensor signals The functional-block diagram of system.Pass through screw tap axial vibration signal, acoustic emission signal, the moment of torsion in multi-sensor collection process Signal and temperature signal;According to the characteristics of signal using correlation method extraction signal characteristic;Analyze thread forming tap state of wear and The crudy of internal thread;The multiple sensor signals feature established under different technical parameters and screw tap abrasion, internal thread quality Mapping model;Based on this, screw tap abrasion, the forecast model of internal thread quality are established.So as to realize to machine tooling process On-line monitoring and screw tap abrasion, the prediction of internal thread quality.
As shown in Figure 2, this figure is the overview flow chart of multiple sensor signals collection.Temperature is less than 100 degrees Celsius at it When, voltage signal is more faint, is vulnerable to the interference of capture card, therefore using the method for secondary meter pick-up serial acquisition;Moment of torsion, Sound emission and the sample rate needed for vibration signal are higher, therefore use data collecting card to gather.So diversified acquisition mode, protect The accuracy of signal is demonstrate,proved.
As shown in Figure 3, this figure is screw tap-workpiece motion s schematic diagram.Screw tap does low-frequency vibration, workpiece along hand of helix Along the circumferential direction do gyration, the motion of screw tap can be analyzed to the vibration of vertical axial direction and the vibration of horizontal axis, therefore can be with Axial vibration is measured, rotational vibration amplitude is calculated.And non-measured exciting device output amplitude, but direct measurement screw tap work Make the vibration amplitude of part, it is contemplated that vibrate the amplitude attenuation problem of transmission, improve accuracy.
As shown in Figure 4, this figure is the schematic view of the mounting position of vibration amplitude monitoring device.1 is that piezoelectric type accelerates in figure Sensor is spent, 2 be exciting device.This mode and non-measured exciting device output amplitude, but direct measurement screw tap work department The vibration amplitude divided, it is contemplated that vibrate the amplitude attenuation problem of transmission, improve measurement accuracy.
As shown in Figure 5, this figure is the acquisition module of moment of torsion, sound, vibration signal.Number is gathered using data collecting card According to sample rate height ensure that the accuracy of signal, and simple to operate.
As shown in Figure 6, this figure is the acquisition module of temperature signal.Using serial communication gathered data, collection is eliminated The interference of the internal signal to temperature when relatively low of card.
As shown in accompanying drawing 7-1, this figure is a kind of sound emission primary signal figure.Gatherer process is believed under different technical parameters Number, the oscillogram of the data point and magnitude of voltage similar to the figure can be drawn, wherein just contain machining information i.e. screw tap abrasion with The information of internal thread quality.
As shown in accompanying drawing 7-2, this figure is a kind of power spectrum chart of acoustic emission signal.Because Welch methods have data overlap Part, so power spectrum curve is more smooth, variance performance is more preferable, therefore uses this method to carry out the primary signal in Fig. 7-1 Power spectrumanalysis.
As shown in accompanying drawing 7-3, this figure is a kind of frequency domain character distribution map of acoustic emission signal.By to acoustic emission signal Power spectrumanalysis, it is possible to substantially obtain which frequency components the vibration signal mainly has, analyze the distribution feelings of dominant frequency therein Condition and its peak value size, make further Fusion Features and processing, just obtained frequency domain character distribution map.Other signals also do phase Close similar process, it is possible to obtain the signal characteristic of multisensor.
As shown in Figure 8, this figure is the partial enlarged drawing of screw tap state of wear.The wear condition of thread forming tap passes through processing After the completion of using tool microscope measurement obtain, state of wear is divided into substantially five kinds of situations, sorted out according to abrasion condition Arrange.
As shown in Figure 9, this figure is internal thread hardness and hardened case distribution figure.Including at root of the tooth, at tooth side, crest The hardness and hardened case distribution at place.The internal thread sample machined extracts a fritter and carried out after decontamination, polishing using digital Intelligent microhardness testers carry out hardness test, characterize the crudy of internal thread with this.
As shown in Figure 10, this figure is that each signal characteristic wears with screw tap under different technical parameters, internal thread quality Mapping model flow chart.In a specific application example, multiple sensor signals feature is obtained with Fig. 7 methods, with figure 8th, 9 methods can obtain screw tap wear information and internal thread quality information, is corresponded to storage, that is, forms the mapping model, Experiment preparation has been done for the forecast model of next step.
As shown in Figure 11, under the different technical parameters that this figure is, each signal characteristic and screw tap abrasion, internal thread quality Forecast model flow chart.In process, by each sensor signal input prediction model, in the mapping that Figure 10 is introduced It is special further according to signal using prior art and related ripe model under the experiment of extensive application example in model is supported Sign, realize the crudy of the abrasion condition and this internal thread of more accurately predicting thread forming tap.
Part that the present invention does not relate to is same as the prior art or can be realized using prior art.

Claims (5)

1. a kind of process monitoring method of the internal thread low frequency exciting cold extrusion lathe based on multiple sensor signals, its feature It is:First with vibration amplitude and extrusion torque, temperature, the acoustic information of multi-sensor collection exciting device;Secondly to adopting The signal collected is analyzed, feature extraction, and screw tap abrasion, internal thread quality are detected;Then build based on this Under different technical parameters, multiple sensor signals and thread forming tap abrasion, the mapping model of internal thread quality;Realization exists to the lathe Line monitors, and finally realizes to screw tap abrasion condition and the on-line prediction of internal thread quality.
2. the method according to claim 11, it is characterized in that:The sensor of use includes:Piezoelectric acceleration transducer, torsion Square sensor, infrared temperature sensor and acoustic emission sensor.
3. the method according to claim 11, it is characterized in that:The measurement of exciting amplitude is straight using piezoelectric acceleration transducer The feeding acceleration of measurement screw tap axial direction is connect, screw tap circumference angular displacement, the i.e. vibration of screw tap are calculated according to kinematic geometry relation Amplitude.
4. the method according to claim 11, it is characterized in that:Acceleration, moment of torsion, voice signal are gathered by capture card, and Temperature signal be can not ignore by capture card internal interference, so becoming warp let-off serial acquisition by secondary meter.
5. the method according to claim 11, it is characterized in that:To more biographies under different technical parameters in low frequency exciting cold extrusion A variety of different characteristics of sensor signal are identified, analyzed;To different screw tap abrasion conditions, internal thread quality carries out detection point Analysis;Establish monitoring signals and screw tap wear extent, the mapping relations of thread quality on this basis, with realize to screw tap wear extent, The on-line prediction of thread quality.
CN201710309037.6A 2017-05-04 2017-05-04 The process monitoring method of internal thread low frequency exciting cold extrusion lathe based on multiple sensor signals Pending CN107414600A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201710309037.6A CN107414600A (en) 2017-05-04 2017-05-04 The process monitoring method of internal thread low frequency exciting cold extrusion lathe based on multiple sensor signals

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201710309037.6A CN107414600A (en) 2017-05-04 2017-05-04 The process monitoring method of internal thread low frequency exciting cold extrusion lathe based on multiple sensor signals

Publications (1)

Publication Number Publication Date
CN107414600A true CN107414600A (en) 2017-12-01

Family

ID=60425799

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201710309037.6A Pending CN107414600A (en) 2017-05-04 2017-05-04 The process monitoring method of internal thread low frequency exciting cold extrusion lathe based on multiple sensor signals

Country Status (1)

Country Link
CN (1) CN107414600A (en)

Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111195740A (en) * 2020-01-03 2020-05-26 西北工业大学 Method and apparatus for machining parts
CN111795817A (en) * 2020-07-27 2020-10-20 西安交通大学 RV reduction gear capability test device based on many sensing fuse
CN114346762A (en) * 2022-02-22 2022-04-15 南京航空航天大学 Flutter monitoring method and system in high-speed milling process and storable medium
CN114571285A (en) * 2022-03-07 2022-06-03 博世华域转向***有限公司 Method for intelligently identifying micro-tipping of extrusion tap
WO2023110576A1 (en) * 2021-12-14 2023-06-22 Sms Group Gmbh Apparatus for machining workpieces and method for controlling a machine tool
CN116415434A (en) * 2023-04-07 2023-07-11 平湖市山特螺纹工具有限公司 Screw tap processing technique and system for high-strength steel

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101780488A (en) * 2010-03-01 2010-07-21 南京航空航天大学 Internal thread cold-extrusion processing quality on-line forecasting method
CN205016055U (en) * 2015-09-23 2016-02-03 桂林电子科技大学 Lathe data acquisition system based on zigbee
CN106077843A (en) * 2016-06-20 2016-11-09 南京航空航天大学 Female thread low frequency exciting cold extrusion Special Purpose Machine for Processing

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101780488A (en) * 2010-03-01 2010-07-21 南京航空航天大学 Internal thread cold-extrusion processing quality on-line forecasting method
CN205016055U (en) * 2015-09-23 2016-02-03 桂林电子科技大学 Lathe data acquisition system based on zigbee
CN106077843A (en) * 2016-06-20 2016-11-09 南京航空航天大学 Female thread low frequency exciting cold extrusion Special Purpose Machine for Processing

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
张敏: "基于多传感器信息融合的冷挤压内螺纹成形质量预测研究", 《工程科技I辑》 *
缪宏: "基于冷挤压的高强度钢内螺纹抗疲劳加工工艺研究", 《工程科技I辑》 *

Cited By (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111195740A (en) * 2020-01-03 2020-05-26 西北工业大学 Method and apparatus for machining parts
CN111795817A (en) * 2020-07-27 2020-10-20 西安交通大学 RV reduction gear capability test device based on many sensing fuse
WO2023110576A1 (en) * 2021-12-14 2023-06-22 Sms Group Gmbh Apparatus for machining workpieces and method for controlling a machine tool
CN114346762A (en) * 2022-02-22 2022-04-15 南京航空航天大学 Flutter monitoring method and system in high-speed milling process and storable medium
CN114571285A (en) * 2022-03-07 2022-06-03 博世华域转向***有限公司 Method for intelligently identifying micro-tipping of extrusion tap
CN114571285B (en) * 2022-03-07 2024-01-19 博世华域转向***有限公司 Method for intelligently identifying micro-tipping of extrusion tap
CN116415434A (en) * 2023-04-07 2023-07-11 平湖市山特螺纹工具有限公司 Screw tap processing technique and system for high-strength steel
CN116415434B (en) * 2023-04-07 2024-05-24 平湖市山特螺纹工具有限公司 Screw tap processing technique and system for high-strength steel

Similar Documents

Publication Publication Date Title
CN107414600A (en) The process monitoring method of internal thread low frequency exciting cold extrusion lathe based on multiple sensor signals
Chen et al. Acoustic emission method for tool condition monitoring based on wavelet analysis
US7341410B2 (en) Dynamical instrument for machining
JP5512691B2 (en) Vibration analysis method, vibration analysis apparatus, sample database for vibration analysis, and use thereof
CN107350900B (en) A kind of tool condition monitoring method extracted based on the chip breaking time
CN110576335B (en) Cutting force-based tool wear online monitoring method
CA2098943A1 (en) System and method for dectecting cutting tool failure
Fu et al. On-line breakage monitoring of small drills with input impedance of driving motor
CN112781820B (en) Hob performance degradation trend evaluation method
CN109894925B (en) Thin-wall part milling vibration monitoring method based on embedded piezoelectric sensor
Zhang et al. Cutting tool wear monitoring based on a smart toolholder with embedded force and vibration sensors and an improved residual network
Du et al. Intelligent turning tool monitoring with neural network adaptive learning
CN116871978A (en) Drilling tool state monitoring method based on multi-sensor fusion
Mary et al. Monitoring of drill runout using least square support vector machine classifier
Wang et al. Condition monitoring on grease lubrication of rolling bearing using AE technology
Yin et al. Multi-information fusion recognition model and experimental study of grinding wheel wear status
CN211783846U (en) Portable engine abnormal sound identification and positioning system
Suprock et al. A low cost wireless high bandwidth transmitter for sensor-integrated metal cutting tools and process monitoring
CN201953977U (en) On-line fault diagnosis system of decelerating clutch
CN101769785A (en) Vibration state spot check method for water injection machines and detection device
Boud et al. Application of multi-sensor signals for monitoring tool/workpiece condition in broaching
CN206073967U (en) A kind of gap detection device between compressor drum and stator
CN202735778U (en) Numerical control machine tool cutting performance and cutting power testing device
CN114091544A (en) TBM disc cutter abrasion identification system based on vibration signal and neural network
CN104197869B (en) System and method used for automatically detecting drilling rod length stress waves

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
RJ01 Rejection of invention patent application after publication
RJ01 Rejection of invention patent application after publication

Application publication date: 20171201