TWI682276B - Intelligent machinery monitoring equipment with customized tolerance value - Google Patents

Abstract

A smart mechanical monitoring device with a customized tolerance value includes a vibration detection device, which is installed on a machine and connected to a host computer. The host computer includes an acquisition unit and a Fourier conversion unit for Fourier transforming the cutting vibration data into A conversion data and an analysis unit are used to cut the conversion data and read the peak value for analysis to obtain a tolerance value. A database unit stores a tolerance value and creates an operation behavior model according to the tolerance value, so that This case can effectively distinguish the normal operation of the component from other failures. The mechanical equipment determines whether to return the information to the remote monitoring platform based on the tolerance value, to solve the problem that the periodic large amount of data return leads to the inability to update the information and waste network bandwidth. .

Description

Intelligent machinery monitoring equipment with customized tolerance value

The invention relates to a mechanical device, especially a mechanical device with intelligent monitoring function.

Smart manufacturing is a development trend in the field of industrial manufacturing and an important means to improve the production efficiency and management level of manufacturing enterprises. In the past, enterprises used manual or simple systems to monitor processing equipment in manufacturing systems. These monitoring methods can only meet the needs of simple field equipment monitoring. With the expansion of the enterprise scale and the increase of production departments and peripheral subsidiaries, how to use a more efficient remote monitoring system and at the same time to remotely monitor, detect and control the production line is a top priority.

As a carrier of information transmission and information sharing, the Internet network provides a strong basic support for the application and development of advanced manufacturing technologies, especially breaking the geographical restrictions, laying a platform for the realization of remote monitoring, and integrating the manufacturing process with technology Pushed to a higher stage. However, although the conventional mechanical equipment can return the information to the cloud storage, most of it is normal production data. The conventional monitoring method cannot choose to only periodically upload information. This monitoring technology will only cause the system to process and store. Burden.

The reason is that the conventional mechanical equipment cannot distinguish the cause of the failure, and it cannot automatically choose which data to upload. Taking the bearing as an example, if the traditional modeling method will not be used to divide the normal operation of the bearing or inner bearing, ball damage What is the difference with the frequency of the outer bearing damage, etc., can not achieve the purpose of timely and effective monitoring.

In addition, in the process of production, it is most likely to cause human error to cause production errors. Once the mechanical equipment is in operation, it is unlikely to temporarily suspend its operation. Therefore, inspection of production components and materials before production operation is very important. However, the conventional mechanical equipment also lacks the methods and functions of controlling the materials used before production. If the materials are neglected, it will not be able to find the stop in time, which will increase the cost of the enterprise. On the other hand, when the original equipment engineer needs to be repaired when the mechanical equipment fails, it is often impossible to confirm the actual maintenance hours of the engineer, and the production cost cannot be effectively calculated to achieve the monitoring purpose.

In view of the above-mentioned deficiencies, the inventor of this case collected relevant information, evaluated and considered by many parties, and based on the years of experience accumulated in this industry, through continuous trial work and modification, he designed the invention patent.

According to the above problems in the prior art, the present invention proposes a smart mechanical device with a customized tolerance value, which has a real-time information return function. The user can set the trigger of the return event according to the characteristics of the information change of the mechanical device, according to the parameters of each mechanical device Customize the numerical value tolerate the value to adjust the return frequency, fill the data in the method of internal difference method, average method, equal width division method, equal depth division method and boxing method to facilitate cloud storage. Modeling with the highest frequency (and its surroundings) at the time of failure, effectively distinguishing the normal operation of the component from other failures, can effectively solve the problem that traditional methods cannot distinguish similar groups.

Another object of the present invention is to generate QR Code (work order) for the required production components and materials and let the computer on the machine scan and input the relevant values to monitor the produced components and materials (RFID) to avoid human negligence and misplanting. The related property losses caused.

Another object of the present invention is to set the allowable distance value between the engineer and the mechanical equipment by satellite positioning. Within the allowable distance value, the handheld device application will only perform the timing action. When the engineer must leave for a period of time or take a rest trip, the system can manually Or it can automatically perform timing and pause timing, and automatically calculate the precise maintenance time.

In order to achieve the above purpose, the technical means adopted by the present invention include installing a vibration detection device on a machine for detecting vibration data of the machine; and a host with a signal connected to the vibration detection Device, the host includes an acquisition unit for receiving the vibration data, and cutting the vibration data to send a cutting vibration data; a Fourier transform unit connected to the acquisition unit, the Fourier transform unit for the cutting vibration Fourier transform the data into a converted data; an analysis unit connected to the Fourier transform unit, the analysis unit is used to cut the converted data and then read the peak value to analyze to obtain a tolerance value; and a database unit connected to the An analysis unit. The database unit is used to store at least one tolerance value and create a failure model according to the at least one tolerance value.

In a preferred embodiment, the vibration detection device may be a vibration sensor or a torque sensor, used to collect and detect vibration frequency or rotational speed data generated during the production process of the machine.

In a preferred embodiment, the failure model includes tolerance values for temperature, vibration, sound or production parameters.

In a preferred embodiment, the host determines whether the converted data exceeds the tolerance value, and if so, adds the time-receiving word and returns it to the cloud database; if not, it continues to monitor the vibration data.

In a preferred embodiment, the host further includes a pre-stored continuous parameter, which may be temperature, vibration, sound, and speed.

In a preferred embodiment, the host receives the vibration data and compares it with the continuous parameter. If it is, then the vibration data is stored in the cloud database in chronological order. If not, interpolation, Organize and analyze the data by the method of equal division, equal ratio or average.

In a preferred embodiment, the failure model is generated by the acquisition unit taking the peak value of the same type of failure per unit time and transmitting it to the analysis unit for judgment.

In a preferred embodiment, the machine is connected to a material monitoring system and is connected to a machine-side computer. The machine-side computer scans and inputs a component to generate a work order. The work order is compared with the database system. If the information is correct, the production process is executed. If not, the material monitoring system displays an error and instructs the computer at the machine to re-execute the scan-in work order and reconfirm the action.

In a preferred embodiment, the material monitoring system has three sets of identification IDs (RFID tags), which respectively monitor a production mold or a production tool or at least one production material installed in the machine.

In a preferred embodiment, the machine is connected to a satellite positioning system. The satellite positioning system includes a timing unit and a distance detection unit. The distance detection unit is signal-connected to a handheld device to determine the machine and the handheld. Is there a reasonable distance between the devices? If yes, the timing unit starts timing. If not, does the timing unit stop timing.

In detail, the present invention has the following effects: 1. Cloud storage is performed only when necessary to reduce database load and network traffic burden. 2. Establish a judgment model based on the peak value of the failure, effectively determine the cause of the failure, and accurately classify the cause of the failure. 3. QR Code control of materials and components before production to avoid human error due to production errors or wrong materials. 4. Use satellite positioning technology to accurately calculate the maintenance time of maintenance engineers to facilitate customer computer utilization and cost.

The technical solutions in the embodiments of the present invention will be described clearly and completely in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by a person of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

It should be noted that the embodiments of the present invention and the features in the embodiments can be combined with each other without conflict.

The present invention discloses a smart mechanical monitoring device with a customized tolerance value, please refer to FIG. 1, including a vibration detection device 1 installed on a machine 2, the vibration detection device 1 can be used to collect and detect the machine The vibration frequency, rotation speed and other data generated in the production process of the stage 2 can be vibration sensors or torque sensors. When the vibration detection device 1 intercepts certain known faults and known normal vibration data, the data will be transmitted To a host 3, the host 3 then processes and models the abnormal data. The host 3 includes: an extraction unit 31, a Fourier transform unit 32, an analysis unit 33, and a database unit 34. The database unit 34 can Cloud storage technology.

The invention discloses a fault detection method, which includes a fault model 4 and a fault detection monitor 5. The first time the machine is used, the fault model 4 is pre-executed. The steps are as follows: 401 data detection: vibration detection device 1 Collect known fault and vibration data during production; 402 Data extraction: The vibration detection device 1 transmits the data to the acquisition unit 31 in the host 2; 403 Fourier transform: After the acquisition unit 31 receives the data, it first uses Fourier Unit 32 performs the time domain conversion of the intercepted vibration data in the frequency domain, and cuts the result into multiple pieces of converted data in units of per second and then transmits it to the analysis unit 33; 404 Data analysis: the analysis unit 33 receives and reads its The converted data is analyzed, and the analysis unit 33 compares the abnormal and normal data after multiple analyses are completed, cuts the converted data and then reads the peak value for analysis to obtain a tolerance value, and transmits it to the database unit 34; 405 fault detection Test model creation: The database unit 34 stores at least one tolerance value and creates a failure model based on the at least one tolerance value. The failure model includes tolerance values for each production parameter.

The second and subsequent productions perform fault detection monitoring 5, the steps are as follows: 501 data extraction: the acquisition unit 31 receives the data of the vibration detection device 1; 502 data cutting: cutting the unknown data intercepted from the spindle into each The size in seconds; 503 Fourier transform: Fourier transform unit 32 performs Fourier reading of its peak value and judges with the established fault model (tolerance value); 504 fault detection: if the production parameters are abnormally larger than the values in the fault model ( Tolerance value) then outputs its failure type to the database unit 34.

In actual operation in the preferred embodiment, the database unit 34 is a cloud database. The mechanical equipment end (machine 2) is equipped with a vibration detection device 1, which will detect user-defined values, including normal values and tolerance values (tolerance value creation, refer to the aforementioned fault detection method ), these values can be temperature, vibration, sound or any parameters related to production. The host 2 judges whether these parameters exceed the tolerance value, if it is, it will be returned to the cloud database after adding the time acceptance word; otherwise, continue to monitor and use Custom parameters.

In the cloud database, after receiving the normal value and the tolerance value, the database unit 34 determines whether continuous data is received within a unit time, if it is, it is sorted and stored according to time, if not, interpolation, equal division, equal ratio or average is used. Number and other methods to organize the data.

Taking the fault detection of the bearing as an example, the user can set the trigger of the return event according to the changing characteristics of the mechanical equipment information. Figure 2 is the calculated peak table. It can be observed that different types of fault peaks fall at different points. Find the maximum and minimum values of various types of data from the peak table to establish a fault model.

The tolerance value can also be deduced by the receiving end. Taking temperature detection as an example, for example, when the temperature of the machine 2 is produced, the change of each unit time exceeds the change of the set temperature (normal value), an abnormal event will be triggered. pass. 1 sec 2 sec 3sec 4 sec 5 sec 2℃ 3℃ 4℃ 5℃ 10℃ 0℃~2℃ (trigger return) - - - 5℃~10℃ (trigger return) Taking the above table as an example, the database unit 34 can be restored based on two abnormal data.

The setting of the data acquisition time period of the present invention is to set the data of 12000 records equal to 1 second, and take the peak value of the same type of failure of “1” seconds as the judgment. The analysis unit 32 combines the two data back and forth to perform calculations. Since the failure model is established on the basis of 1 second, and the greater the number of data read by the database unit 34, the success rate of the type of failure is determined. The higher.

Please refer to FIG. 3, a smart machine monitoring device with a customized tolerance value according to the present invention further includes a material monitoring system 6, which is used on the machine 2, and the material monitoring system 6 has a radio frequency identification function, which can identify production components and materials. Three sets of identification ID (RFID Tag), respectively monitor the production mold 61, production material 62 and production tool 63, the three sets of identification ID (RFID Tag) are connected to a machine-side computer 64 via Ethernet, the machine-side computer 64 will The QR code (work order) of the production component and material information needs to be generated for the computer-side computer 64 to scan and input. During operation, the computer-side computer 64 enters the work order in advance. After input, it is obtained from the cloud or database (ERP) system 65. All the production materials (such as material name, production quantity, other information, etc.), compare the data after obtaining the data, and confirm whether all the production materials are correctly matched. If so, execute the production process. If otherwise, the system displays an error and instructs to rescan. Work orders and reconfirmed work procedures.

Please refer to FIG. 5, a smart machine monitoring device with a customized tolerance value according to the present invention further includes a satellite positioning system 7 for the machine 2. The satellite positioning system 7 includes a timing unit 71 and a distance detection unit 72, During operation, the distance detection unit 72 is signal-connected to a handheld device 73. During operation, after the handheld device 73 installs the maintenance APP, the distance information (GPS) can be compared with the cloud database, continuously via the distance detection unit 72 Compare the distance with the machine 2 to determine whether it is within a preset reasonable range. If it is, the timing unit 71 starts to calculate the maintenance time; after the timing is turned on, if the distance detection unit 72 detects an unreasonable distance, the timing unit pauses the timing. Until the distance detection unit 72 detects a reasonable distance, it will continue to count continuously.

The global satellite positioning information of the handheld device 73 and the machine 2 must be quite close to the allowable range, and the application installed in the handheld device 73 of the maintenance timing can perform the timing action. When the maintenance personnel must leave for a period of time or take a rest trip At this time, the satellite positioning system 7 can manually or automatically time the timer to pause the timer, otherwise, it will resume the timing operation.

1 Vibration detection device 2 machine 3 host 31 acquisition unit 32 Fourier conversion unit 33 analysis unit 34 database unit 4 fault model steps 401~405 5 fault detection monitoring steps 501~504 6 material monitoring system 61 production mold 62 production Material 63 production tool 64 machine side computer 65 database (ERP) system 7 satellite positioning system 71 timing unit 72 distance detection unit 73 handheld device

1 is a flowchart of the system of the present invention; FIG. 2 is a schematic diagram of the peak table of the present invention; FIG. 3 is a schematic diagram of the material monitoring system and machine of the present invention; FIG. 4 is a schematic diagram of the identification ID of the material monitoring system of the present invention; Schematic diagram of the positioning system.

1 Vibration detection device 2 units 3 host 31 acquisition unit 32 Fourier conversion unit 33 analysis unit 34 database unit

Claims (9)

Intelligent machinery monitoring equipment with customized tolerance values, including: a vibration detection device, installed on a machine, used to detect a known fault vibration data of the machine; and a host, the signal is connected to the The vibration detection device receives the fault vibration data, and includes: an acquisition unit for receiving the fault vibration data, cutting the fault vibration data, and transmitting a cutting vibration data; a Fourier transform unit, connected to The acquisition unit, the Fourier conversion unit is used to Fourier transform the cutting vibration data into a conversion data; an analysis unit is connected to the Fourier conversion unit, the analysis unit is used to cut the conversion data and then read its peak value Analyze a tolerance value of temperature, vibration, sound or production parameters with fault data; and a database unit connected to the analysis unit, the database unit is used to store at least one tolerance value and establish a tolerance value based on the tolerance value A failure model that accumulates units on the basis of aperiodic backhaul, and when the change in the unit time exceeds the set change, an abnormal event return is triggered, where the failure model includes the tolerance value. The intelligent machinery monitoring equipment with a customized tolerance value as described in claim 1, wherein the vibration detection device may be a vibration sensor or a torque sensor to collect and detect the vibration frequency or rotation speed generated during the production process of the machine data. The intelligent machine monitoring device with a customized tolerance value as described in claim 1, wherein the host judges whether the conversion data exceeds the tolerance value, and if so, adds the time-receiving word and returns it to the cloud database; if not, continue to monitor the Shock data. As described in claim 1, a smart machine monitoring device with a customized tolerance value, wherein the host further includes a pre-stored continuous parameter, which may be temperature, vibration, sound, and speed. The intelligent machinery monitoring device with a customized tolerance value as described in claim 4, wherein the host receives the vibration data and compares with the continuous parameter whether it is consistent, and if so, sorts the vibration data into the cloud data in chronological order The library, if not, then use interpolation, equalization, equal ratio, average method to organize and analyze the data. The intelligent machine monitoring device with a customized tolerance value as described in claim 1, wherein the failure model is generated by the acquisition unit taking the peak value of the same type of failure in a unit time and transmitting it to the analysis unit for judgment. The intelligent machinery monitoring equipment with a customized tolerance value as described in claim 1, wherein the machine is connected to a material monitoring system and connected to a machine-side computer, and the machine-side computer scans and inputs a component to generate a work order, and the work order Compare the data with the database system. If the data is correct, the production process is executed. If not, the material monitoring system displays an error and instructs the computer on the machine to re-execute the scan-in work order and reconfirm the action. The intelligent machinery monitoring equipment with customized tolerance value as described in claim 7, wherein the material monitoring system has three sets of identification IDs (RFID tags) to monitor a production mold or a production tool installed in the machine respectively Or at least one production material. The intelligent mechanical monitoring device with a customized tolerance value according to claim 1, wherein the machine is connected to a satellite positioning system, the satellite positioning system includes a timing unit and a distance detection unit, the distance detection unit and a handheld The signal connection of the device determines whether the machine is within a reasonable distance from the handheld device. If so, the timing unit starts timing. If not, the timing unit stops timing.

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