CN117217593A - Machine tool energy efficiency real-time monitoring and online evaluating method - Google Patents
Machine tool energy efficiency real-time monitoring and online evaluating method Download PDFInfo
- Publication number
- CN117217593A CN117217593A CN202311171804.3A CN202311171804A CN117217593A CN 117217593 A CN117217593 A CN 117217593A CN 202311171804 A CN202311171804 A CN 202311171804A CN 117217593 A CN117217593 A CN 117217593A
- Authority
- CN
- China
- Prior art keywords
- machine tool
- energy efficiency
- energy consumption
- monitoring
- real
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000012544 monitoring process Methods 0.000 title claims abstract description 66
- 238000000034 method Methods 0.000 title claims abstract description 35
- 238000005265 energy consumption Methods 0.000 claims abstract description 64
- 238000011156 evaluation Methods 0.000 claims abstract description 28
- 238000003754 machining Methods 0.000 claims abstract description 20
- 238000004891 communication Methods 0.000 claims abstract description 9
- 230000000007 visual effect Effects 0.000 claims abstract description 6
- 238000005520 cutting process Methods 0.000 claims description 24
- 230000008569 process Effects 0.000 claims description 17
- 239000000463 material Substances 0.000 claims description 13
- 238000012545 processing Methods 0.000 claims description 12
- 238000004519 manufacturing process Methods 0.000 claims description 11
- 230000003993 interaction Effects 0.000 claims description 5
- 230000007246 mechanism Effects 0.000 claims description 4
- 238000011160 research Methods 0.000 abstract 1
- 238000010586 diagram Methods 0.000 description 5
- 230000001133 acceleration Effects 0.000 description 3
- 238000004364 calculation method Methods 0.000 description 3
- 238000002474 experimental method Methods 0.000 description 3
- CURLTUGMZLYLDI-UHFFFAOYSA-N Carbon dioxide Chemical compound O=C=O CURLTUGMZLYLDI-UHFFFAOYSA-N 0.000 description 2
- 230000004075 alteration Effects 0.000 description 2
- 230000005540 biological transmission Effects 0.000 description 2
- 238000010276 construction Methods 0.000 description 2
- 238000013499 data model Methods 0.000 description 2
- 238000007726 management method Methods 0.000 description 2
- 238000003860 storage Methods 0.000 description 2
- 238000006467 substitution reaction Methods 0.000 description 2
- 238000012800 visualization Methods 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 1
- 229910002092 carbon dioxide Inorganic materials 0.000 description 1
- 239000001569 carbon dioxide Substances 0.000 description 1
- 239000000470 constituent Substances 0.000 description 1
- 238000009826 distribution Methods 0.000 description 1
- 238000004134 energy conservation Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000012854 evaluation process Methods 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 239000013307 optical fiber Substances 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
- 230000003071 parasitic effect Effects 0.000 description 1
- 238000012887 quadratic function Methods 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
Landscapes
- General Factory Administration (AREA)
Abstract
The invention discloses a machine tool energy efficiency real-time monitoring and online evaluating method, which comprises the following steps: firstly, a machine tool energy efficiency real-time monitoring system frame is provided; secondly, analyzing the machining energy consumption characteristic of the machine tool according to the acquired machine tool equipment parameters and the machining process parameters, and establishing machine tool energy efficiency monitoring indexes; then, a machine tool energy consumption monitoring visual display interface is manufactured, parameters are processed and called through codes, and real-time data communication of a monitoring system is realized; and finally, constructing a machine tool energy efficiency grade evaluation flow frame based on a research method of clustering and combined weighting, and realizing real-time monitoring and online evaluation of machine tool energy efficiency.
Description
Technical neighborhood:
the invention relates to the technical field of mechanical processing energy management, in particular to a machine tool energy efficiency real-time monitoring and energy efficiency grade evaluation method.
The background technology is as follows:
with the rapid advancement of industrialization, there is an increasing demand for energy. According to statistics, the carbon dioxide emission of the industrial departments in China accounts for more than 80% of the total amount, and the manufacturing industry accounts for more than 85% of the whole industrial field. The machine tool is used as a working master machine in the manufacturing industry, has a large range, and occupies more than 70% of the whole manufacturing industry in energy consumption. Therefore, how to identify the energy consumption points through a proper machine tool energy efficiency monitoring mechanism is a key basis for machine tool energy consumption management and energy efficiency improvement.
Currently, the energy efficiency grade evaluation in the prior art is widely applied to the manufacturing industry neighborhood of air conditioners, electric lamps, motors and the like, and has corresponding national standards. However, the evaluation index system and the evaluation method for the energy efficiency grade of the machine tool are still under study. Because the machine tool has various kinds, various energy consumption components, variable processing working conditions and other dilemmas, the energy efficiency grade evaluation of the machine tool is difficult. Therefore, in order to solve the problems encountered in the machine tool energy efficiency grade evaluation process, it is necessary to establish a machine tool energy efficiency grade evaluation method.
The invention comprises the following steps:
the invention provides a machine tool energy efficiency real-time monitoring and energy efficiency grade evaluation method.
The technical scheme adopted for realizing the purpose of the invention is that the machine tool energy efficiency real-time monitoring and energy efficiency grade evaluation method comprises the following steps:
step 1: constructing a machine tool energy efficiency real-time monitoring system frame;
step 2: analyzing the energy consumption characteristics of the machine tool according to the collected machine tool equipment parameters and the machining process parameters, and formulating energy efficiency monitoring indexes of the machine tool;
step 3: manufacturing a machine tool energy consumption monitoring visual display interface based on the energy consumption data acquired in the step 2, and carrying out real-time data communication of a monitoring system through codes;
step 4: and (3) constructing a machine tool energy efficiency grade evaluation flow frame based on the energy consumption data acquired in the step (2).
Preferably, the specific construction process of the machine tool energy efficiency real-time monitoring system framework in the step 1 is as follows:
(1) As shown in fig. 1, the machine tool energy efficiency real-time monitoring system framework mainly comprises four layers: an internet of things layer (Internet of Things, ioT), a facilities layer (Infrastructure as a Service, iaaS), a middle platform layer (Platform as a Service, paaS), and a business layer (Software as a Service, saaS), wherein:
(1) IoT layer. The IoT layer is an internet of things layer in the energy efficiency monitoring system, and the layer mainly comprises a power sensor, an NC system, a network card, a PLC, a terminal, a workshop energy consumption device and the like, and is responsible for sensing and integrating energy consumption and operation data of production equipment and auxiliary equipment.
(2) IaaS layer. The IaaS layer is an infrastructure layer in the energy efficiency monitoring system, and includes network facilities such as servers, firewalls, databases, routers, and the like. The layer mainly provides a storage database for process data, cutter data, processed energy consumption data and the like acquired by the IoT layer, provides facilities such as routers and optical fibers for data transmission, and provides software and hardware security support for the deployment of the machine tool energy efficiency monitoring system.
(3) PaaS layer. The PaaS layer comprises a data center, a database service center and an energy consumption data model. The data center provides corresponding data support for the service center; the database service center provides data retrieval, access, and storage means. The energy efficiency data model is an algorithm model provided for data structure and energy efficiency monitoring index calculation established for the collected data.
(4) SaaS layer. The SaaS layer is a man-machine interaction service layer facing a workshop manager in the energy efficiency monitoring system. The machine tool energy efficiency monitoring interface is divided into a workshop level and an equipment level, and machine tool energy efficiency monitoring and visualization are realized from a single machine tool and all machine tools in the whole workshop.
Preferably, step 2 analyzes the energy consumption characteristic of the machine tool, and formulates an energy efficiency monitoring index system of the machine tool, wherein the specific process is as follows:
(1) The energy consumption of the machine tool in the machining process is mainly influenced by standby energy consumption, idle cutting energy consumption, cutting energy consumption and worn tool replacement energy consumption, and the same stage is similar in time period characteristics of the machine tool in the machining process, as shown in fig. 2, the machine tool can be divided into a shutdown state, a starting state, a standby state, a spindle acceleration/deceleration state, an idle cutting state, a cutting machining state and the like according to the time period characteristics. However, in the actual machining process, the time of machine tool on/off and main shaft acceleration/deceleration is very short and the frequency is low, the machine tool on/off energy consumption is integrated into standby energy consumption from the monitoring analysis point of view, and the main shaft acceleration/deceleration energy consumption is integrated into idle energy consumption, so the machine tool energy consumption is divided into standby energy consumption Est, idle cutting energy consumption Eac and cutting energy consumption Ec from the time period characteristics, and the total machine tool energy consumption calculation formula is as follows:
E total ＝E st +E ac +E cut
the machine tool power is classified into a standby power Pst, a machining-related auxiliary system power Pau, an idle power Pul, an additional load loss power Padd, and a material removal power Pm according to the constituent characteristics. As can be seen from fig. 3, the cutting power is the sum of the material removal power, the parasitic load loss power and the idle power. The additional load loss power is the electrical and mechanical loss in the motor and transmission system generated by cutting load, and is a quadratic function relation with the material removal power:
P cut ＝P m +P add +P ul
P add ＝c 0 P m +c 1 P m 2
the material removal power can be obtained according to the above two formulas, wherein the formula is as follows:
wherein c0 and c1 are accessory load coefficients, and are obtained through an experimental fitting mode. The auxiliary equipment energy consumption calculation formula is:
wherein P is n equip Representing the power of the nth device, t n equip Indicating the nth device on time.
(2) According to the machine tool machining mechanism characteristics, namely the ratio of the material removal energy consumption to the cutting energy consumption and the ratio of the cutting energy consumption to the total energy consumption in the machine tool machining process, the machine tool energy efficiency monitoring index is constructed, and the index formula is as follows:
in the formula, μmachine represents the machine tool material removal energy utilization rate, and μmachine represents the cutting energy utilization rate.
Preferably, the step 3 machine tool energy consumption monitoring visual display interface is used for making real-time data communication with a monitoring system, and the specific process is as follows:
(1) And designing a data acquisition interface through a Qt Designer interface Designer, writing algorithm codes and logic implementation codes in a Qt Creator code compiler, and triggering UI and logic codes by using a Qt 'signal and slot' mechanism.
(2) Based on a Django framework in Python language, a machine tool energy efficiency monitoring interface is established through CSS and JS language, and the monitoring system displays parameter information of respective equipment on the interface in real time to realize machine tool energy consumption monitoring visualization.
(3) Based on PROFIBUS, MODBUS industrial-level communication protocol, the collected machine tool equipment parameters and the processing technological parameters are stored in a database in real time through a TCP/IP network structure and a wireless and wired communication mode, network assistant software is connected with a monitoring system, and the database is read by utilizing a program to realize real-time data communication of the monitoring system.
Preferably, the machine tool energy efficiency grade evaluation flow frame in step 4 is shown in fig. 3, and the specific flow is as follows:
(1) Task data and process data in the manufacturing execution system and power and time data of the power sensor are acquired through the data acquisition and interaction terminal.
(2) And classifying the energy efficiency evaluation influence element indexes based on the K-means influence element clustering method, and performing energy efficiency index evaluation and grading in the same class.
(3) And (5) comprehensive energy efficiency evaluation based on combination weighting. And calculating the comprehensive score of the evaluation data by using an analytic hierarchy process and an entropy weight process, and classifying the evaluation data according to the influence element index classification result and the comprehensive score result.
(4) And visualizing the evaluation result in an interface of the mechanical processing system energy efficiency monitoring system.
Drawings
Fig. 1: and a machine tool energy efficiency real-time monitoring system frame diagram.
Fig. 2: and analyzing the energy consumption characteristic of the machine tool.
Fig. 3: and a machine tool energy efficiency grade evaluation flow chart.
Fig. 4: ioT layer construction graph.
Fig. 5: and data acquisition and interaction diagram.
Fig. 6: the machine tool monitors the interface map.
Fig. 7: experimental apparatus and field diagram.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are only some, but not all embodiments of the invention. Various substitutions and alterations are made according to the ordinary skill and familiar means of the art without departing from the technical spirit of the invention, and all such substitutions and alterations are intended to be included in the scope of the invention.
The system is applied to hardware devices such as an HC-33C3 power sensor of Huizhou electronics, an industrial intelligent terminal developed by Haidek, an industrial router of Huacheng, a server of Hewlett packard and the like. Taking the VGC1500 vertical gantry machining center as an example, the shop IoT layer setup is shown in fig. 4. The power sensor is deployed on a main shaft of the machine tool equipment to collect main shaft power, on a machine tool bus to collect total power, on an auxiliary equipment bus to collect auxiliary equipment power, and the intelligent terminal and the machine tool are deployed in a one-to-one mode to acquire data of machine tool processing parameters, energy consumption, efficiency and the like. The data acquisition and interaction client function interface used in the intelligent terminal is shown in fig. 5, and the data acquisition acquires information such as operation parameter data, processing time data, power data and the like of data required by the SaaS end energy efficiency monitoring and evaluating process, and stores the data into a database. And extracting monitoring data of a machine tool part from the database, processing the monitoring data into evaluation index data, and comprehensively evaluating energy efficiency in the machining process of the machine tool, wherein the evaluation index data are shown in table 1.
The machine tool energy efficiency monitoring interface is divided into a total interface and a single machine tool interface. The total machine tool interface includes three kinds of information including total energy consumption of machining on the same day, utilization rate of machining time and state of the machine tool, as shown in fig. 6 (a). Clicking the machine tool name in the total interface, and entering a single machine tool monitoring interface. In a single machine tool monitoring interface, the operation information of the machine tool is displayed in more detail, wherein the operation information comprises the basic information of the machine tool, the energy consumption information of the machine tool, the operation power curve, the energy consumption distribution diagram of the machine tool, the machine tool monitoring index diagram and the processing time information, as shown in fig. 6 (b).
Table 1 machine tool index data
Experiments prove that the VGC1500 vertical gantry machining center is used for carrying out experiments, the adopted workpiece materials and the machining tool parameters are shown in table 2, and the machining parameters adopted in the experimental process and the additional load loss coefficients corresponding to the rotating speeds are shown in table 3.
Table 2 experimental workpiece materials and tool parameters
Table 3 table of experimental process parameters
The daily HOKI3390C power analyzer and the Kistler9257B three-way dynamometer are adopted as experimental instruments, and the experimental instruments are synchronously measured with a data acquisition system. Cutting time and material removal energy consumption were obtained by a Kistler9257B three-way dynamometer, spindle idle time and idle energy consumption were obtained by a daily HOKI3390C power analyzer, and the experimental setup is shown in fig. 7.
And (5) carrying out experiment statistics on material removal energy consumption, cutting processing time, blank cutting time and blank cutting energy consumption in the 6-time feeding processing process. And obtaining resultant force in the x and y directions through a Kistler9257B three-way dynamometer, multiplying the resultant force with the cutting speed to obtain material removal power, counting the cutting process time, obtaining the idle cutting time through the Kistler9257B three-way dynamometer and a daily HOKI3390C power analyzer, and obtaining the idle cutting energy consumption through integrating the obtained power with time, wherein the comparison result is shown in a table 4.
Table 4 comparison of experimental results
As can be seen by comparison, in the process of acquiring the material removal energy consumption and the cutting machining state of the machine tool, the relative error between the acquisition software and the measurement result of the standard test instrument is 6.04% at most. According to the state judging method applied by the system, the error meets the application requirement of the production field.
The invention provides a machine tool energy efficiency real-time monitoring and evaluating method, which is characterized in that a workshop machine tool equipment energy efficiency monitoring index system is provided from the angles of energy efficiency and operation according to the machine tool processing energy consumption characteristics, and an industrial Internet is fused to construct a machine tool energy efficiency monitoring system. According to the method of clustering and combined weighting of the collected energy consumption data, a machine tool energy efficiency grade evaluation flow frame is constructed, the energy efficiency optimization of a workshop is researched, and more comprehensive support is provided for workshop energy conservation.
Claims (5)
1. The machine tool energy efficiency real-time monitoring and online evaluating method is characterized by comprising the following steps of:
step 1: constructing a machine tool energy efficiency real-time monitoring system frame;
step 2: analyzing the energy consumption characteristics of the machine tool according to the collected machine tool equipment parameters and the machining process parameters, and formulating energy efficiency monitoring indexes of the machine tool;
step 3: manufacturing a machine tool energy consumption monitoring visual display interface based on the energy consumption data acquired in the step 2, and carrying out real-time data communication of a monitoring system through codes;
step 4: and (3) constructing an online evaluation flow framework of the machine tool energy efficiency based on the energy consumption data acquired in the step (2).
2. The method for monitoring and evaluating energy efficiency of a machine tool in real time and on line according to claim 1, wherein the method comprises the following steps: in the step 1, a machine tool energy efficiency real-time monitoring system framework mainly comprises four layers of an Internet of things layer, a facility layer, a middle platform layer and a service layer.
3. The method for monitoring and evaluating energy efficiency of a machine tool in real time and on line according to claim 1, wherein the method comprises the following steps: in the step 2, analyzing the energy consumption characteristic of the machine tool, making an energy efficiency monitoring index of the machine tool, and making a visual display interface of the energy consumption monitoring of the machine tool, wherein the process is as follows:
(1) The machine tool has the time period characteristics which can be shown in the machining process, the same stage shows a similar rule, and the energy consumption of the machine tool is divided into standby energy consumption Est, idle cutting energy consumption Eac and cutting energy consumption Ec according to the time period characteristics;
(2) And constructing a machine tool energy efficiency monitoring index according to the machine tool machining mechanism characteristics, namely the ratio of the material removal energy consumption to the cutting energy consumption, and the ratio of the cutting energy consumption to the total energy consumption in the machine tool machining process.
4. The method for monitoring and evaluating energy efficiency of a machine tool in real time and on line according to claim 1, wherein the method comprises the following steps: and 3, manufacturing a visual display interface for machine tool energy consumption monitoring and real-time data communication of a monitoring system, wherein the process is as follows:
(1) Designing a data acquisition interface through a Qt Designer interface Designer;
(2) Based on a Django frame in Python language, establishing a machine tool energy efficiency monitoring interface through CSS and JS language;
(3) Acquiring workshop equipment data based on Modbus protocol and data acquisition terminal, transmitting the acquired equipment data to a server by using TCP/IP protocol,
and connecting the network assistant software with the monitoring system, and reading a database by using a program to realize real-time data communication of the monitoring system.
5. The method for monitoring and evaluating energy efficiency of a machine tool in real time and on line according to claim 1, wherein the method comprises the following steps: and 4, constructing an online evaluation flow framework of the machine tool energy efficiency, wherein the flow is as follows:
(1) Task data and process data in a manufacturing execution system and power and time data of a power sensor are acquired through a data acquisition and interaction terminal;
(2) Classifying the energy efficiency evaluation influence element indexes based on a K-means influence element clustering method;
(3) Calculating the comprehensive score of the evaluation data by using an analytic hierarchy process and an entropy weight process, and classifying the evaluation data according to the classification result of the influencing element index and the comprehensive score result;
(4) And visualizing the evaluation result in an interface of the mechanical processing system energy efficiency monitoring system.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311171804.3A CN117217593A (en) | 2023-09-12 | 2023-09-12 | Machine tool energy efficiency real-time monitoring and online evaluating method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311171804.3A CN117217593A (en) | 2023-09-12 | 2023-09-12 | Machine tool energy efficiency real-time monitoring and online evaluating method |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN117217593A true CN117217593A (en) | 2023-12-12 |
Family
ID=89045577
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311171804.3A Pending CN117217593A (en) | 2023-09-12 | 2023-09-12 | Machine tool energy efficiency real-time monitoring and online evaluating method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117217593A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN118277224A (en) * | 2024-05-31 | 2024-07-02 | 苏州元脑智能科技有限公司 | Method for constructing energy efficiency model, computer device, storage medium and program product |
-
2023
- 2023-09-12 CN CN202311171804.3A patent/CN117217593A/en active Pending
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN118277224A (en) * | 2024-05-31 | 2024-07-02 | 苏州元脑智能科技有限公司 | Method for constructing energy efficiency model, computer device, storage medium and program product |
| CN118277224B (en) * | 2024-05-31 | 2024-08-06 | 苏州元脑智能科技有限公司 | Method for constructing energy efficiency model, computer device, storage medium and program product |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111461431B (en) | Optimization method and system based on screw locking process in mobile phone manufacturing | |
| CN117217593A (en) | Machine tool energy efficiency real-time monitoring and online evaluating method | |
| CN111708798B (en) | Wind turbine generator system fault diagnosis and processing method and system | |
| CN105652781B (en) | A kind of PLC method for safety monitoring based on bypass message | |
| CN102262401A (en) | Industrial production line monitoring system | |
| CN104808587A (en) | Utilization statistical approach based on operation states of machining equipment | |
| CN104503362B (en) | Batch workpiece digital control processing progress automatic acquiring method based on Multi-information acquisition | |
| CN110823561B (en) | Method for monitoring fatigue life of key part of rolling mill transmission shaft system under unsteady state load in real time based on material model library | |
| CN111461746A (en) | Quality intelligent tracing method for assembly | |
| CN117932976B (en) | Method and device for acquiring process machine set energy data | |
| CN116703254B (en) | Production information management system for mechanical parts of die | |
| CN114386626A (en) | Equipment state evaluation and operation and maintenance strategy formulation realization system based on digital twinning | |
| CN115563341A (en) | Spatial video field for electric power operation violation identification and intelligent data processing system and method thereof | |
| CN115755758A (en) | Machine tool machining control method based on neural network model | |
| CN118377268A (en) | Numerical control machine tool control method and system based on Internet of things | |
| CN106067142A (en) | A kind of power quality data method for expressing | |
| CN104834787B (en) | Perception and analysis method for energy consumption of bearing grinding machine production workshop | |
| CN110019167B (en) | Method and system for constructing medium-and-long-term new energy resource database | |
| CN115796436B (en) | Production test data management system based on big data | |
| CN111526072A (en) | Intelligent industrial Internet of things terminal detection system | |
| CN108846552B (en) | Distribution network automation terminal defect analysis system and method thereof | |
| CN114905334B (en) | Intelligent real-time clean cutting monitoring system and method | |
| CN115983582A (en) | Data analysis method and energy consumption management system | |
| CN114817863A (en) | Process quality situation control system | |
| CN115221252A (en) | Method and equipment for establishing lightning arrester aging test database and storage medium |
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 |