CN113791727B - Edge acquisition equipment applied to industrial acoustic intelligent sensing - Google Patents
Edge acquisition equipment applied to industrial acoustic intelligent sensing Download PDFInfo
- Publication number
- CN113791727B CN113791727B CN202110913539.6A CN202110913539A CN113791727B CN 113791727 B CN113791727 B CN 113791727B CN 202110913539 A CN202110913539 A CN 202110913539A CN 113791727 B CN113791727 B CN 113791727B
- Authority
- CN
- China
- Prior art keywords
- data
- processor
- acquisition
- sampling
- digital input
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/05—Digital input using the sampling of an analogue quantity at regular intervals of time, input from a/d converter or output to d/a converter
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01H—MEASUREMENT OF MECHANICAL VIBRATIONS OR ULTRASONIC, SONIC OR INFRASONIC WAVES
- G01H17/00—Measuring mechanical vibrations or ultrasonic, sonic or infrasonic waves, not provided for in the preceding groups
-
- H—ELECTRICITY
- H03—ELECTRONIC CIRCUITRY
- H03M—CODING; DECODING; CODE CONVERSION IN GENERAL
- H03M1/00—Analogue/digital conversion; Digital/analogue conversion
- H03M1/12—Analogue/digital converters
- H03M1/1205—Multiplexed conversion systems
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Human Computer Interaction (AREA)
- General Engineering & Computer Science (AREA)
- Measurement Of Mechanical Vibrations Or Ultrasonic Waves (AREA)
Abstract
The invention discloses edge acquisition equipment applied to industrial acoustic intelligent sensing, which comprises at least one sensor, an acquisition part, an acquisition controller, a data processor and an edge AI processor, wherein the acquisition part comprises a first acquisition part and a second acquisition part; the acquisition part comprises at least one AD acquisition chip; the acquisition part samples acoustic signals obtained by the sensor; the acquisition controller controls each AD sampling chip to synchronously sample according to the same sampling frequency, and continuously and uninterruptedly send sampled data to the data processor according to the sampling frequency; the data processor preprocesses the AD sampling data and then sends the AD sampling data to the edge terminal AI processor; the side-end AI processor inputs the preprocessed AD sampling data into various mathematical models, trained AI models or mathematical formulas, and analyzes to obtain results. The invention can analyze acoustic information of the product carrier which produces sound actively or passively, and obtain the analysis results of the product quality, fault, differentiation, defect, classification and the like, and the detection result is accurate, safe and reliable.
Description
Technical Field
The invention relates to the technical field of acoustic detection, in particular to edge-end acquisition equipment applied to industrial acoustic intelligent sensing.
Background
The integration of the new generation artificial intelligence and the technology in the manufacturing field can quickly improve the intelligence level of the manufacturing industry and accelerate the progress of the country from the manufacturing big country to the manufacturing strong country. At present, technologies such as big data, chips, GPU and the like are rapidly developed, conditions and environments where artificial intelligence AI is developed are greatly changed, artificial intelligence is being converted from academic traction to demand traction, and the artificial intelligence is developed towards an intelligent system with cloud, side and end integration.
The acoustic detection is a nondestructive detection method for realizing fault identification by acquiring and analyzing sound signals containing information such as the state, process, size, defects and the like of an object to be detected; therefore, the acoustic detection has a wide development prospect in industrial fault diagnosis. The faults of refrigeration products, parts of five-axis numerical control cutter grinder equipment, automatic assembly lines and the like are mainly detected and checked by human hearing. And the accuracy, efficiency, result consistency and reliability of the human hearing detection are low. The present invention is intended to solve the above problems by means of an acoustic image intelligent perception technique.
Disclosure of Invention
In view of the above, in order to solve the above problems in the prior art, the present invention provides an edge side acquisition device applied to industrial acoustic intelligent sensing.
The invention solves the problems through the following technical means:
an edge acquisition device applied to industrial acoustic intelligent sensing comprises at least one sensor, an acquisition part, an acquisition controller, a data processor and an edge AI processor; the acquisition part comprises at least one AD acquisition chip;
each sensor is connected with an AD acquisition chip;
the sensor is used for collecting acoustic signals;
the acquisition section samples an acoustic signal obtained by a sensor;
the acquisition controller controls each AD sampling chip to synchronously sample according to the same sampling frequency, and continuously and uninterruptedly transmits sampled data to the data processor according to the sampling frequency;
after the data processor receives the AD sampling data, the AD sampling data are preprocessed and then sent to an edge-end AI processor;
and the side-end AI processor inputs the preprocessed AD sampling data into various mathematical models, trained AI models or mathematical formulas, and analyzes to obtain a result.
Furthermore, the acquisition part also comprises a digital input port, an IO output port and a bus interface.
Furthermore, the acquisition controller also acquires information through a bus interface and sends the information to the data processor for processing, and the result is obtained after the processing of the side-end AI processor; and the adopted controller also continuously samples the digital input signal of the digital input port according to the sampling frequency and sends the digital input signal to the data processor, and the side-end AI processor processes the digital input signal to obtain a result.
Further, the result information of the edge AI processor is displayed by a display, or output to other systems through the ethernet, or transmitted to the acquisition controller, and output to other systems from the IO output port or the bus interface through the acquisition controller.
Furthermore, the bus interface and the edge-side AI processor are used for the communication between the equipment and other systems, the bus interface receives the instruction of the equipment, and the edge-side AI processor transmits the result of the equipment processing; the instructions to the device include the start of acquisition, the end, the specified time length t1 for the transmitted data, the sampling frequency, the amplification factor of the AD, the current sound object data tag q, the specified time interval t2, and the data processing specification requirement format.
Furthermore, the acquisition controller controls each AD acquisition chip to control the amplification factor of the AD sampling chips, so that the gains of the AD sampling chips are independently adjustable.
Further, the data processor starts according to the digital input triggering time point of the digital input port and sends data with the specified time length t1 to the edge terminal AI processor; starting at the point in time when the bus interface receives the command, data of a specified time length t1 is sent to the edge AI processor.
Further, in the preprocessing of the data processor, the tag is marked for the AD data according to the digital input signal of the digital input port or the command information received by the bus interface, so that the automatic marking of the AI model data is realized, and the digital input signal or the command information is the current sound object data tag q.
Further, when receiving digital input trigger of the digital input port, the acquisition controller outputs signals to the digital analog IO port according to a specified time interval t2, and if the analysis result of the edge-side AI processor received within the specified time interval t2 is that no signal is output, the acquisition controller cancels the output of the digital analog IO port, so that accurate digital analog IO output control is realized.
Furthermore, the edge-end acquisition equipment applied to industrial acoustic intelligent sensing further comprises a reference source, the acquisition controller closes the sensor input, the reference source is started, the reference source inputs reference voltage to each AD acquisition chip, and then the voltage value obtained by the data processor from the acquisition controller is compared with the reference voltage value to obtain the deviation value of each AD acquisition chip; and during the subsequent data preprocessing, the data acquired by the AD acquisition chip is corrected by using the deviation value, so that the automatic calibration function of the acquisition equipment is realized.
Compared with the prior art, the invention has the beneficial effects that at least:
the edge-end acquisition equipment can acquire acoustic information, process data and analyze the acoustic information of the actively-sounding or passively-sounding product carrier, then obtain analysis results of the quality, faults, differentiation, defects, classification and the like of the product, and output the analysis results in real time, so that the detection result is accurate, safe and reliable.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a schematic structural diagram of an edge-end acquisition device applied to industrial acoustic intelligent sensing.
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. It should be noted that the described embodiments are only a part of the embodiments of the present invention, and not all embodiments, and all other embodiments obtained by those skilled in the art without any inventive work based on the embodiments of the present invention belong to the protection scope of the present invention.
As shown in fig. 1, the present invention provides an edge acquisition device applied to industrial acoustic intelligent sensing, which includes at least one sensor, an acquisition part, an acquisition controller, a data processor and an edge AI processor; the acquisition part comprises at least one AD acquisition chip and a digital input port, and can be provided with an IO output port and a bus interface.
The sensor is used for collecting acoustic signals, the AD acquisition chip samples the acoustic signals obtained by the sensor and sends the acoustic signals to the data processor through the acquisition controller, the data processor processes the data and then sends the data to the side terminal AI processor, and the side terminal AI processor analyzes the data to obtain a result; in addition, the acquisition controller can also acquire information through a digital input port or a bus interface and send the information to the data processor for processing; and the result is obtained after the side AI processor processes the data.
The result information of the edge AI processor can be displayed by a display, output to other systems through ethernet, or transmitted to the acquisition controller, and output to other systems through the acquisition controller from an IO output port or a bus interface.
The bus interface and the side AI processor can be used for the communication between the equipment and other systems, the bus interface can receive the instruction of the equipment, and the side AI processor can transmit the result of the equipment processing; the instructions to the device may include start of acquisition, end, transfer of data for a specified length of time t1, sampling frequency, amplification of the AD, current sound object data tag q, specified time interval t2, data processing specification requirements format, and the like.
The acquisition equipment has an automatic calibration function; the acquisition controller closes the sensor input, the reference source is started, the reference source inputs reference voltage to each AD sampling chip, and then the data processor calculates and compares the voltage value obtained from the acquisition controller with the reference voltage value to obtain the deviation value of each AD sampling chip; and correcting the data acquired by the AD chip by using the deviation value during the subsequent data preprocessing.
Each AD sampling gain is independently adjustable: each sensor is connected with an AD chip; the acquisition controller can control each AD sampling chip to control the amplification factor (gain) of AD.
The acquisition controller controls each AD sampling chip to synchronously sample according to the same sampling frequency, and continuously and uninterruptedly transmits sampled data to the data processor according to the sampling frequency; the digital input signal of the digital input port is sampled continuously and uninterruptedly at the sampling frequency and sent to the data processor.
After receiving the data, the data processor preprocesses the data and sends the data to the side AI processor; all AD sampling data can be sent to the side-end AI processor continuously; the data with the specified time length t1 can be sent to the side end AI processor by starting from the digital input triggering time point of the digital input port; data for a prescribed time period t1 may be sent to the edge AI processor starting at the point in time when the bus interface receives the command.
After receiving the data, the data processor preprocesses the data and sends the data to the side AI processor; in the preprocessing, the AD data can be labeled according to the digital input signal of the digital input port or the command information (current sound object data label q) received by the bus interface, so that the automatic marking of the AI model data is realized.
Accurate IO output control can be realized, when the acquisition controller receives digital input trigger of the digital input port, signals are output to the digital analog IO port according to the specified time interval t2, and if the analysis result received by the side-end AI processor within the specified time interval t2 is that no signal is output, the digital analog IO port output is cancelled.
The side-end AI processor analyzes the data to obtain a result, wherein the result can be obtained by inputting the data into various mathematical models, trained AI models or mathematical formulas; the AI model can be a machine learning model such as SVM, CNN, MLP, RNN, DNN, etc.
The sensor may be a set of N >6 microphones, which may be arranged in an array, matrix, queue, or deployed in some geometric pattern in space or plane.
The acquisition controller can be an FPGA, an ARM, a single chip microcomputer and the like.
The data processor can be an FPGA, an ARM, a singlechip, a PC and the like.
The edge AI processor can be FPGA, ARM, ASIC, GPU, PC, etc.
The bus interface may be RS232, RS485, ethernet, etc.
The connection between the data processor and the edge AI processor can be bus, USB, ethernet.
The connection between the acquisition controller and the data processor can be a bus, a USB and an Ethernet.
The communication between the edge AI processor and other systems can be bus, USB, ethernet, wifi, etc.
The sampling frequency may be 40-192K.
The data processor preprocesses the data, namely processing the received data into a format with specified requirements.
The acquisition controller and the data processor are processed by 2 processors, so that the real-time performance of data can be guaranteed.
1. Refrigeration product quality detection industry application
After the final assembly of the air-conditioning products (refrigeration products) is finished, the air-conditioning products need to be electrified and started to detect the noise of the whole machine so as to check the operation faults. At present, in the process, air-conditioning products may have 20 kinds of faults and cause fault sound, wherein the faults include that a cross-flow fan blade touches a bottom shell, an evaporator pipe, pipeline touch, an axial-flow fan blade touches a flow guide ring, a steel shaft of the cross-flow fan blade is separated from a bearing, a centrifugal fan blade touches a volute, a capillary tube part touches a rear side plate, an air suction pipe touches a front side plate and the like. The invention aims at the general assembly detection of the air-conditioning product, carries out the application of the sound image perception technology and realizes the intelligent diagnosis of the fault of the air-conditioning product.
2. Equipment part state monitoring industry application
The state of the parts of the processing equipment is monitored in real time, so that the faults of the parts or the equipment can be found and checked in time, and high processing precision, stable processing quality and the like are guaranteed. A five-axis numerical control cutter grinder is selected as an object, and the application of the sound image perception technology in the field of monitoring the state of equipment parts is developed. The five-axis numerical control cutter grinding machine is used for grinding various end cutters, round nose cutters, ball cutters, drill bits, forming cutters and the like, and has the advantages of high efficiency, high precision, stable performance and the like. The produced cutter is widely applied to industries such as mobile phones, steel rails and the like. In the machining of a tool, core components such as a main shaft, a feed shaft, a grinding wheel, a milling liquid supply system, and a machine table of a grinding machine have more than 10 kinds of failures such as poor operation, lead screw abrasion, abrasion/damage, excessive or insufficient milling liquid, poor lubrication/aging, and the like.
3. Automatic assembly state monitoring industry application
The automatic assembly line mainly comprises a conveying line, a sensing detection device and various industrial robots, is used for the processes of assembly, detection, marking, packaging and the like of product manufacturing, and is widely applied to the industries of automobile manufacturing, hardware, equipment manufacturing, food/medicine packaging and the like. In the assembly production, the chain of the conveying line loosens, rusts, various bearing rolling bodies break, wear and damage, impurities invade bearing lubricating grease, the carrier roller does not rotate and is stuck, and the gear wear and the crack of the industrial robot can cause more than 10 faults and are accompanied with fault sound. The invention develops the application of an industrial multi-mode intelligent diagnosis system aiming at the state monitoring of the automatic assembly line and realizes the real-time perception and intelligent diagnosis of the faults of the automatic assembly line.
The edge-end acquisition equipment can acquire acoustic information, process data and analyze the acoustic information of the actively-sounding or passively-sounding product carrier, then obtain analysis results of the quality, faults, differentiation, defects, classification and the like of the product, and output the analysis results in real time, so that the detection result is accurate, safe and reliable.
The above-mentioned embodiments only express several embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (5)
1. The utility model provides an edge collection equipment who is applied to industry acoustics intelligence perception which characterized in that includes at least one sensor, collection part, collection controller, data processor and edge AI treater; the acquisition part comprises at least one AD acquisition chip;
each sensor is connected with an AD acquisition chip;
the sensor is used for collecting acoustic signals;
the acquisition section samples an acoustic signal obtained by a sensor;
the acquisition controller controls each AD sampling chip to synchronously sample according to the same sampling frequency, and continuously and uninterruptedly send sampled data to the data processor according to the sampling frequency;
after receiving the AD sampling data, the data processor preprocesses the AD sampling data and then sends the AD sampling data to the side-end AI processor;
the side-end AI processor inputs the preprocessed AD sampling data into various mathematical models, trained AI models or mathematical formulas, and analyzes to obtain a result;
the acquisition part also comprises a digital input port, an IO output port and a bus interface;
the bus interface and the side AI processor are used for communicating the equipment with other systems, the bus interface receives an instruction to the equipment, and the side AI processor transmits a result processed by the equipment; the instructions to the equipment comprise the start and the end of acquisition, the specified time length t1 of the transmitted data, the sampling frequency, the amplification factor of AD, the current sound object data label q, the specified time interval t2 and the specified required format of data processing;
the data processor starts according to the digital input triggering time point of the digital input port and sends data with the specified time length t1 to the side end AI processor; starting from the time point when the bus interface receives the command, sending data with a specified time length t1 to the AI processor at the side end;
in the preprocessing of the data processor, the AD data is labeled according to the digital input signal of a digital input port or the command information received by a bus interface, so that the automatic marking of the AI model data is realized, and the digital input signal or the command information is the current sound object data label q;
when the acquisition controller receives digital input trigger of the digital input port, signals are output to the digital analog IO port according to the specified time interval t2, if the analysis result received by the side end AI processor in the specified time interval t2 is that no signal is output, the output of the digital analog IO port is cancelled, and therefore accurate digital analog IO output control is achieved.
2. The frontend acquisition device applied to industrial acoustic intelligent sensing according to claim 1, wherein the acquisition controller further acquires information through a bus interface and sends the information to a data processor for processing, and the frontend AI processor obtains a result after processing; and the acquisition controller also continuously samples the digital input signal of the digital input port according to the sampling frequency and sends the digital input signal to the data processor, and the side-end AI processor processes the digital input signal to obtain a result.
3. The edge-side acquisition device applied to industrial acoustic intelligent sensing according to claim 1, wherein the result information of the edge-side AI processor is displayed by a display, or output to other systems through Ethernet, or transmitted to the acquisition controller, and output to other systems through an IO output port or a bus interface through the acquisition controller.
4. The edge-end acquisition device applied to industrial acoustic intelligent sensing according to claim 1, wherein the acquisition controller controls each AD acquisition chip to control the amplification factor of the AD sampling chip, so that the gain of each AD sampling chip can be independently adjusted.
5. The edge collecting device applied to industrial acoustic intelligent sensing according to claim 1, further comprising a reference source, wherein the collecting controller turns off the sensor input and turns on the reference source, the reference source inputs a reference voltage to each AD collecting chip, and the voltage value obtained by the data processor from the collecting controller is compared with the reference voltage value to obtain a deviation value of each AD collecting chip; and during the subsequent data preprocessing, the data acquired by the AD acquisition chip is corrected by using the deviation value, so that the automatic calibration function of the acquisition equipment is realized.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110913539.6A CN113791727B (en) | 2021-08-10 | 2021-08-10 | Edge acquisition equipment applied to industrial acoustic intelligent sensing |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110913539.6A CN113791727B (en) | 2021-08-10 | 2021-08-10 | Edge acquisition equipment applied to industrial acoustic intelligent sensing |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113791727A CN113791727A (en) | 2021-12-14 |
| CN113791727B true CN113791727B (en) | 2023-03-24 |
Family
ID=78875808
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110913539.6A Active CN113791727B (en) | 2021-08-10 | 2021-08-10 | Edge acquisition equipment applied to industrial acoustic intelligent sensing |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113791727B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115730475B (en) * | 2023-01-09 | 2023-05-19 | 广东省科学院智能制造研究所 | Cloud edge end cooperative flexible production line robot learning system and method |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2008129028A (en) * | 2006-11-16 | 2008-06-05 | Nippon Telegr & Teleph Corp <Ntt> | Acoustic model adaptation processing method, acoustic model adaptation processing device, acoustic model adaptation processing program, and recordng medium |
| CN109473120A (en) * | 2018-11-14 | 2019-03-15 | 辽宁工程技术大学 | A kind of abnormal sound signal recognition method based on convolutional neural networks |
Family Cites Families (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN201772263U (en) * | 2010-08-23 | 2011-03-23 | 雷神能源技术(山东)有限公司 | Acoustic wave pipeline safety detection system |
| JP6573838B2 (en) * | 2016-02-10 | 2019-09-11 | 株式会社神戸製鋼所 | Anomaly detection system for rotating machines |
| CN106441555A (en) * | 2016-11-04 | 2017-02-22 | 恒信大友（北京）科技有限公司 | High-performance dynamic characteristic tester for high-speed motion member |
| CN108089154B (en) * | 2017-11-29 | 2021-06-11 | 西北工业大学 | Distributed sound source detection method and sound detection robot based on same |
| US11715284B2 (en) * | 2018-05-18 | 2023-08-01 | Nec Corporation | Anomaly detection apparatus, anomaly detection method, and program |
| KR20200075133A (en) * | 2018-12-12 | 2020-06-26 | 현대자동차주식회사 | A device and method for detecting noise source based big data |
| US20200233397A1 (en) * | 2019-01-23 | 2020-07-23 | New York University | System, method and computer-accessible medium for machine condition monitoring |
| JP7253721B2 (en) * | 2019-05-08 | 2023-04-07 | パナソニックＩｐマネジメント株式会社 | Abnormal noise determination device, abnormal noise determination method, and abnormal noise determination system |
| US11531100B2 (en) * | 2019-06-13 | 2022-12-20 | The Boeing Company | Methods and systems for acoustic machine perception for an aircraft |
| JP2021022311A (en) * | 2019-07-30 | 2021-02-18 | 株式会社リコー | Abnormality detecting device, abnormality detecting system, and program |
| CN112177865B (en) * | 2020-12-02 | 2021-02-26 | 南京智谷人工智能研究院有限公司 | Method for solving marking noise and insufficient marks in fan fault detection |
-
2021
- 2021-08-10 CN CN202110913539.6A patent/CN113791727B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2008129028A (en) * | 2006-11-16 | 2008-06-05 | Nippon Telegr & Teleph Corp <Ntt> | Acoustic model adaptation processing method, acoustic model adaptation processing device, acoustic model adaptation processing program, and recordng medium |
| CN109473120A (en) * | 2018-11-14 | 2019-03-15 | 辽宁工程技术大学 | A kind of abnormal sound signal recognition method based on convolutional neural networks |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113791727A (en) | 2021-12-14 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN103808734B (en) | Auto-parts fully-automated synthesis equipment | |
| CN103823409B (en) | Digit Control Machine Tool machining state multiparameter online actively monitoring system and its implementation | |
| CN110355608A (en) | Based on the tool abrasion prediction technique from attention mechanism and deep learning | |
| CN113791727B (en) | Edge acquisition equipment applied to industrial acoustic intelligent sensing | |
| CN110059442A (en) | A kind of turnery processing cutter replacing method based on Part Surface Roughness and power information | |
| CN201446458U (en) | Online real-time detection system for detecting machining precision of numerical control punching equipment of automobile girder | |
| CN202317881U (en) | On-line anti-collision monitoring device for centerless internal grinder | |
| CN107270852A (en) | Automatic shaft length detection and wear shaft device | |
| CN213998767U (en) | Vertical machining center for machining airplane parts | |
| CN113617852B (en) | Cross wedge rolling intelligent control system based on data driving | |
| CN112598651A (en) | Intelligent robot processing production detecting system | |
| CN108776457A (en) | A kind of numerically-controlled machine tool cutter head fault diagnosis system | |
| CN110728655A (en) | Machine vision-based numerical control machine tool workpiece abnormity detection method and device | |
| CN204007531U (en) | A kind of piston ring intelligent comprehensive checking system | |
| CN115993366A (en) | Workpiece surface detection method and system based on sensing equipment | |
| CN106425453A (en) | Device and method for automatically eliminating bearing assembling clearance | |
| CN204330330U (en) | A kind of test unit with compound sensor intelligent bearing | |
| CN113791728B (en) | Industrial acoustic intelligent sensing system | |
| CN204247546U (en) | A kind of on-line checkingi falls bottle and treating apparatus | |
| CN206919863U (en) | Automatic shaft length detection and shaft crossing device | |
| CN114354633B (en) | Ceramic bathroom appearance quality detection system and detection method | |
| CN115599016A (en) | Cooperative positioning control system used in multi-stage transmission process of fragile workpiece | |
| CN113752084A (en) | Intelligent monitoring method and system for performance of numerical control machine tool cutter | |
| CN202316544U (en) | Automatic cold-rolled surface quality rating system | |
| CN109271948B (en) | Multi-channel remote vibration signal monitoring system and method based on clustering algorithm |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |