A manufacturing equipment state analysis method and system based on data analysis

Abstract

The application discloses a kind of manufacturing equipment state analysis method and system based on data analysis, it is related to equipment state analysis technical field, including obtaining the historical operation data of manufacturing equipment;Temperature data of historical operation is analyzed and processed, and the temperature growth rate of manufacturing equipment is determined.The application is first to the historical operation temperature data analysis calculation, determines the temperature growth rate of manufacturing equipment, secondly, again the temperature growth rate of manufacturing equipment is simulated analysis, and then determines the aging rate of manufacturing equipment, then, again the vibration analysis of historical operation vibration data is carried out, determines the abnormality generated in the operation process of manufacturing equipment, finally, the aging rate and abnormal vibration characteristics of manufacturing equipment are analyzed, determine the real-time state of manufacturing equipment, according to the real-time state of manufacturing equipment, replace the aging serious component, repair the abnormal characteristics of manufacturing equipment, ensure that manufacturing equipment does not appear fault when running, shorten production time.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of equipment state analysis, in particular to a manufacturing equipment state analysis method and system based on data analysis. BACKGROUND

[0002] Manufacturing equipment refers to machine equipment used in industrial enterprises for producing materials needed in daily life of human beings, mainly including machinery, power and transmission equipment, etc.

[0003] With the increase of the use time of the manufacturing equipment, some parts of the manufacturing equipment will age, and when the parts of the manufacturing equipment age to a certain extent, the manufacturing equipment will malfunction, the production task of the manufacturing equipment will be interrupted, and the production time will be prolonged. In addition, when the manufacturing equipment abnormally, the production task of the manufacturing equipment will also be affected. SUMMARY

[0004] To solve the above technical problems, the present application provides a manufacturing equipment state analysis method and system based on data analysis, which solves the problems of the background technology, i.e. when the parts of the manufacturing equipment age to a certain extent, the manufacturing equipment will malfunction, the production task of the manufacturing equipment will be interrupted, and the production time will be prolonged. In addition, when the manufacturing equipment abnormally, the production task of the manufacturing equipment will also be affected.

[0005] To achieve the above purposes, the technical scheme adopted by the present application is as follows:

[0006] A manufacturing equipment state analysis method based on data analysis, comprising:

[0007] obtaining historical running data of the manufacturing equipment, wherein the historical running data of the manufacturing equipment is obtained from a database system, and the historical running data of the manufacturing equipment includes historical running temperature data and historical running vibration data;

[0008] It can be understood that the historical running vibration data is audio data, which is collected by a sound sensor, and the historical running temperature data is collected by a temperature sensor. When some parts of the manufacturing equipment are seriously aged, the temperature data will increase rapidly during production. For example, when the circuit is seriously aged, the temperature on the surface of the manufacturing equipment will increase rapidly during operation. Therefore, the aging rate of the manufacturing equipment can be determined by analyzing the historical running temperature data.

[0009] analyzing and processing the historical running temperature data based on a state analysis terminal to determine the temperature growth rate of the manufacturing equipment;

[0010] simulating and analyzing the temperature growth rate of the manufacturing equipment based on the state analysis terminal to determine the aging rate of the manufacturing equipment;

[0011] Based on the state analysis terminal, the historical running vibration data is analyzed and processed to determine the abnormal vibration characteristics;

[0012] Based on the state analysis terminal, the abnormal vibration characteristics and the aging rate of the manufacturing equipment are analyzed to determine the real-time state of the manufacturing equipment.

[0013] Preferably, the historical running temperature data is analyzed and processed by the state analysis terminal to determine the temperature growth rate of the manufacturing equipment, specifically including the following steps:

[0014] Based on the state analysis terminal, the historical running temperature data is preprocessed, and the data preprocessing includes data cleaning, data denoising and data normalization;

[0015] It can be understood that data preprocessing is to remove invalid data, handle missing values and standardize data format;

[0016] Based on the state analysis terminal, the historical running temperature data is classified and processed based on the number of times the manufacturing equipment is run, and is uniquely marked, obtaining a plurality of sets of numbered running temperature data, the specific form of which is (temperature data, running time);

[0017] The unique mark is generated by the number of times the manufacturing equipment is run, and has uniqueness, which is to distinguish the temperature data corresponding to different running times, for example, the first time the manufacturing equipment is run, its number is "1", the second time it is run, its number is "2", making subsequent data analysis more convenient and efficient;

[0018] Based on the state analysis terminal, the plurality of sets of numbered running temperature data are respectively plotted in a two-dimensional rectangular coordinate system to obtain a plurality of numbered temperature curves, the X-axis parameter of the two-dimensional rectangular coordinate system being the running time, and the Y-axis parameter being the temperature data;

[0019] It can be understood that the curve can reflect the trend of data change;

[0020] Based on the state analysis terminal, the running time of the plurality of sets of numbered running temperature data is filtered to determine the shortest running time;

[0021] It can be understood that the running time of the manufacturing equipment may be different each time it is run, in order to obtain the accurate temperature growth rate of the manufacturing equipment, the running time of all the numbered running temperature data is sorted, the shortest running time of the numbered running temperature data is set as the shortest running time, and the remaining numbered temperature curves are intercepted by the shortest running time, and there is the same analysis standard when analyzing the temperature growth rate of the manufacturing equipment;

[0022] The state analysis terminal determines the temperature growth rate of the manufacturing equipment by performing feature analysis on the plurality of numbered temperature curves characterized by the shortest running time.

[0023] The specific calculation formula for determining the shortest running time is as follows:

[0024]

[0025] In the formula, T min is the shortest running time; T i is the running time in the plurality of sets of numbered running temperature data; i is the specific number of running time in the plurality of sets of numbered running temperature data; and min() is the minimum function.

[0026] Preferably, the state analysis terminal determines the temperature growth rate of the manufacturing equipment by performing feature analysis on the plurality of numbered temperature curves characterized by the shortest running time, which specifically includes the following steps:

[0027] The state analysis terminal performs curve intercepting processing on the plurality of numbered temperature curves characterized by the shortest running time to obtain a plurality of partially numbered temperature curves.

[0028] The state analysis terminal performs average calculation processing on the temperature data and the shortest running time in the plurality of partially numbered temperature curves to obtain the temperature growth rates of the plurality of sets of numbered temperature curves.

[0029] It can be understood that, as the running time of the manufacturing equipment increases, the temperature growth rate of the manufacturing equipment changes each time. Because the components of the manufacturing equipment age each time it is used, the temperature data and the shortest running time in each partially numbered temperature curve are calculated to determine the temperature growth rate of the manufacturing equipment each time it is run.

[0030] The state analysis terminal performs difference calculation processing on the temperature growth rates of the plurality of sets of numbered temperature curves characterized by adjacent numbers to obtain a plurality of temperature growth rate difference values.

[0031] It can be understood that, by subtracting the temperature growth rate of the temperature curve numbered "1" from the temperature growth rate of the temperature curve numbered "2", the temperature change of the components of the manufacturing equipment after it is used once can be obtained, which indirectly reflects the aging degree of the components. In this way, the aging degree of the components of the manufacturing equipment after each run can be obtained. Because the aging degree of the manufacturing equipment becomes more severe as the number of runs increases, the temperature growth rate increases. Therefore, in order to obtain an accurate temperature growth rate of the manufacturing equipment, the state analysis terminal performs difference calculation processing on the temperature growth rates of the plurality of sets of numbered temperature curves characterized by adjacent numbers.

[0032] Based on the state analysis terminal, a plurality of sets of temperature rate difference values are averaged to determine the temperature growth rate of the manufacturing equipment;

[0033] The specific calculation formula for determining the temperature growth rate of the manufacturing equipment is:

[0034]

[0035] In the formula, V c is the temperature growth rate of the manufacturing equipment; V j is the temperature rate of a plurality of sets of numbered temperature curves; and j is the specific number of temperature rates of the plurality of sets of numbered temperature curves.

[0036] Preferably, the simulation analysis of the temperature growth rate of the manufacturing equipment by the state analysis terminal to determine the aging rate of the manufacturing equipment specifically includes the following steps:

[0037] Based on the state analysis terminal, a plurality of sets of numbered operating temperature data are selected to obtain target numbered operating temperature data;

[0038] The target numbered operating temperature data is the operating temperature data of the manufacturing equipment just after completing a manufacturing task;

[0039] It can be understood that, in order to obtain the aging rate of the manufacturing equipment, the data of the last operation of the manufacturing equipment need to be analyzed and calculated to obtain the current aging rate of the manufacturing equipment, and the target numbered operating temperature data is the data of the last operation of the manufacturing equipment (i.e., the operating temperature data of the manufacturing equipment just after completing a manufacturing task);

[0040] Based on the state analysis terminal, the temperature data and the operating time of the target numbered operating temperature data are calculated to obtain the average temperature growth rate of the target number;

[0041] The critical temperature of the manufacturing equipment is obtained from the database system;

[0042] It can be understood that, when the manufacturing equipment reaches the critical temperature, continuing to operate is an overload operation, which will accelerate the aging of the manufacturing equipment, and may even cause the manufacturing equipment to malfunction. Therefore, by analyzing the time period during which the manufacturing equipment reaches the critical temperature, the aging rate of the manufacturing equipment is determined;

[0043] Based on the state analysis terminal, the critical temperature of the manufacturing equipment, the average temperature growth rate of the target number, and the temperature growth rate of the manufacturing equipment are calculated to determine the time period during which the critical temperature is reached;

[0044] The state analysis terminal compares and judges the time length of reaching the critical temperature to determine the aging rate of the manufacturing equipment.

[0045] The specific calculation formula of the time length of reaching the critical temperature is as follows:

[0046]

[0047] In the formula, T is the time length of reaching the critical temperature, C1 is the critical temperature of the manufacturing equipment, C2 is the temperature of the manufacturing equipment when completing the manufacturing task in the target number of running temperature data, T is the running time length in the target number of running temperature data, and V is the temperature growth rate of the manufacturing equipment. a b c

[0048] Preferably, the specific steps of determining the aging rate of the manufacturing equipment based on the state analysis terminal and comparing and judging the time length of reaching the critical temperature include the following steps:

[0049] The time length required for the manufacturing equipment to normally reach the critical temperature is obtained from the database system.

[0050] The state analysis terminal calculates the difference between the time length of reaching the critical temperature and the time length required for the manufacturing equipment to normally reach the critical temperature to obtain a time length difference.

[0051] The state analysis terminal calculates the aging rate of the manufacturing equipment based on the time length difference and the time length required for the manufacturing equipment to normally reach the critical temperature.

[0052] Preferably, the specific steps of determining the abnormal vibration characteristics based on the state analysis terminal and analyzing and processing the historical running vibration data include the following steps:

[0053] The state analysis terminal performs denoising processing on the historical running vibration data, and the denoising processing is performed by wavelet transform method.

[0054] The state analysis terminal classifies and processes the historical running vibration data based on the running number of the manufacturing equipment as a feature and marks the historical running vibration data uniquely to obtain a plurality of sets of numbered running vibration data, and the specific form of the numbered running vibration data is (vibration data, running time length).

[0055] Based on the fast Fourier transform algorithm, the vibration data in the plurality of sets of numbered running vibration data is respectively processed by frequency domain conversion to obtain the frequency spectrum information of the plurality of sets of numbered running vibration data.

[0056] ​​​The state analysis terminal extracts and processes the frequency spectrum information of the vibration data of a plurality of groups of numbered operation, and obtains the frequency spectrum information of the vibration data of the target numbered operation.

[0057] The frequency spectrum information of the vibration data of the target numbered operation is the frequency spectrum information of the vibration data when the manufacturing equipment is initially put into use. When the manufacturing equipment is initially put into use, no abnormality occurs, and the operation vibration data of the manufacturing equipment is standard. However, when the manufacturing equipment is subsequently operated, an abnormality may occur. Once the manufacturing equipment is abnormal, different vibration occurs, that is, different operation sound occurs, which means that different frequency spectrum characteristics occur.

[0058] The state analysis terminal compares the frequency spectrum information of the vibration data of a plurality of groups of numbered operation with the frequency spectrum information of the vibration data of the target numbered operation, and determines the abnormal vibration characteristics.

[0059] Preferably, the state analysis terminal compares the frequency spectrum information of the vibration data of a plurality of groups of numbered operation with the frequency spectrum information of the vibration data of the target numbered operation, and determines the abnormal vibration characteristics, specifically including the following steps:

[0060] The state analysis terminal matches the frequency spectrum information of the vibration data of a plurality of groups of numbered operation with the frequency spectrum information of the vibration data of the target numbered operation, and obtains the frequency spectrum information of a plurality of groups of abnormal vibration data.

[0061] The state analysis terminal counts the frequency spectrum information of the abnormal vibration data, and obtains the occurrence frequency of the frequency spectrum information of the abnormal vibration characteristics.

[0062] The state analysis terminal judges the occurrence frequency of the frequency spectrum information of the abnormal vibration characteristics, and determines the abnormal vibration characteristics.

[0063] Preferably, the state analysis terminal judges the occurrence frequency of the frequency spectrum information of the abnormal vibration characteristics, and determines the abnormal vibration characteristics, specifically including the following steps:

[0064] The state analysis terminal judges the occurrence frequency of the frequency spectrum information of the abnormal vibration characteristics and a set occurrence frequency threshold.

[0065] If the occurrence frequency of the frequency spectrum information of the abnormal vibration characteristics is greater than the set occurrence frequency threshold, the vibration data corresponding to the occurrence frequency of the frequency spectrum information of the abnormal vibration characteristics is the abnormal vibration characteristics.

[0066] If the occurrence frequency of the frequency spectrum information of the abnormal vibration characteristics is less than or equal to the set occurrence frequency threshold, the vibration data corresponding to the occurrence frequency of the frequency spectrum information of the abnormal vibration characteristics does not conform to the abnormal vibration characteristics.

[0067] It can be understood that when the foreign matter appears in the interior of the manufacturing equipment, different vibration data can appear, but when the foreign matter falls, the vibration data disappears, so by judging the number of occurrences of the spectrum information of the abnormal vibration, this kind of situation is excluded, and after the manufacturing equipment appears abnormal, no matter how, the vibration data will not disappear, and will exist all the time, unless it is repaired, so by judging the number of occurrences of the spectrum information of the abnormal vibration feature, the abnormal vibration feature is determined.

[0068] Preferably, the state analysis terminal based on the abnormal vibration feature and the aging rate of the manufacturing equipment carries out equipment state analysis to determine the real-time state of the manufacturing equipment, and specifically includes the following steps:

[0069] The state analysis terminal based on the abnormal vibration feature carries out counting processing to obtain the number of abnormal vibration features;

[0070] The state analysis terminal based on the abnormal vibration feature and the aging rate of the manufacturing equipment carries out judgment processing;

[0071] If the number of abnormal vibration features is greater than or equal to the set abnormal vibration feature number threshold, and the aging rate of the manufacturing equipment is greater than or equal to the set aging rate threshold, the real-time state of the manufacturing equipment is poor, etc.

[0072] If the number of abnormal vibration features is greater than or equal to the set abnormal vibration feature number threshold, or the aging rate of the manufacturing equipment is greater than or equal to the set aging rate threshold, the real-time state of the manufacturing equipment is good, etc.

[0073] If the number of abnormal vibration features is less than the set abnormal vibration feature number threshold, and the aging rate of the manufacturing equipment is less than the set aging rate threshold, the real-time state of the manufacturing equipment is excellent.

[0074] Further, a manufacturing equipment state analysis system based on data analysis is proposed, which is used to realize the manufacturing equipment state analysis method based on data analysis as described above, and includes:

[0075] The state analysis terminal is used for aging rate analysis and abnormal vibration feature analysis on the historical running temperature data and the historical running vibration data to determine the real-time state of the manufacturing equipment;

[0076] The database system is used for storing the historical running temperature data, the historical running vibration data, the time required for the manufacturing equipment to normally reach the critical temperature, and the critical temperature of the manufacturing equipment, and the database system is in communication connection with the state analysis terminal;

[0077] The state analysis terminal is internally integrated with:

[0078] A central processing unit is used for controlling data transmission and information interaction among various modules.

[0079] A data reading module is used for data reading of a database system.

[0080] A data preprocessing module is used for data preprocessing of historical running temperature data.

[0081] A temperature growth rate calculation module is used for data classification, data uniqueness marking, drawing of numbered temperature curves, and intercepting of numbered temperature curves of the preprocessed historical running temperature data, so as to determine the temperature growth rate of the manufacturing equipment.

[0082] An aging rate analysis module is used for analog analysis of the temperature growth rate of the manufacturing equipment, so as to determine the aging rate of the manufacturing equipment.

[0083] A data denoising module is used for denoising processing of historical running vibration data by a wavelet transform method.

[0084] An abnormal vibration feature determination module is used for classification processing, data uniqueness marking, frequency domain conversion, and spectrum analysis of the denoised historical running vibration data, so as to determine the abnormal vibration feature.

[0085] A state determination module is used for equipment state analysis of the abnormal vibration feature and the aging rate of the manufacturing equipment, so as to determine the real-time state of the manufacturing equipment.

[0086] Compared with the prior art, the present application provides a manufacturing equipment state analysis method and system based on data analysis, which has the following beneficial effects:

[0087] Firstly, the historical running temperature data is analyzed and calculated to determine the temperature growth rate of the manufacturing equipment; secondly, the temperature growth rate of the manufacturing equipment is analog analyzed to further determine the aging rate of the manufacturing equipment; then, the historical running vibration data is analyzed to determine the abnormal vibration feature generated by the manufacturing equipment during operation; finally, the aging rate and the abnormal vibration feature of the manufacturing equipment are analyzed to determine the real-time state of the manufacturing equipment, the seriously aged parts are replaced according to the real-time state of the manufacturing equipment, the abnormal features of the manufacturing equipment are repaired, the manufacturing equipment is ensured not to fail during operation, and the production time is shortened. BRIEF DESCRIPTION OF DRAWINGS

[0088] Figure 1 A flowchart of steps S100-S500 in a manufacturing equipment state analysis method based on data analysis is provided.

[0089] Figure 2 A flowchart of steps S201-S205 in a manufacturing equipment state analysis method based on data analysis according to the present application is shown in Figure 2;

[0090] Figure 3 A flowchart of steps S2051-S2054 in a manufacturing equipment state analysis method based on data analysis according to the present application is shown in Figure 5;

[0091] Figure 4 A flowchart of steps S301-S305 in a manufacturing equipment state analysis method based on data analysis according to the present application is shown in Figure 6;

[0092] Figure 5 A flowchart of steps S3051-S3053 in a manufacturing equipment state analysis method based on data analysis according to the present application is shown in Figure 7;

[0093] Figure 6 A flowchart of steps S401-S405 in a manufacturing equipment state analysis method based on data analysis according to the present application is shown in Figure 8;

[0094] Figure 7 A flowchart of steps S4051-S4053 in a manufacturing equipment state analysis method based on data analysis according to the present application is shown in Figure 9;

[0095] Figure 8 A flowchart of steps S40531-S40533 in a manufacturing equipment state analysis method based on data analysis according to the present application is shown in Figure 10;

[0096] Figure 9 A flowchart of steps S501-S505 in a manufacturing equipment state analysis method based on data analysis according to the present application is shown in Figure 11;

[0097] Figure 10 A block diagram of a manufacturing equipment state analysis system based on data analysis according to the present application is shown in Figure 12. DETAILED DESCRIPTION

[0098] The following description is presented to enable any person skilled in the art to practice the present application as claimed. The preferred embodiments disclosed herein are only examples of the present application and alternative embodiments will be apparent to those skilled in the art.

[0099] Referring to Figure 1 A manufacturing equipment state analysis method based on data analysis, comprising:

[0100] S100, acquire historical running data of the manufacturing equipment, the historical running data of the manufacturing equipment being acquired from a database system, wherein the historical running data of the manufacturing equipment comprises historical running temperature data and historical running vibration data;

[0101] S200, based on the state analysis terminal, analyze and process the historical running temperature data to determine a temperature growth rate of the manufacturing equipment;

[0102] S300, based on the state analysis terminal, simulate and analyze the temperature growth rate of the manufacturing equipment to determine an aging rate of the manufacturing equipment;

[0103] S400, based on the state analysis terminal, analyze and process the historical running vibration data to determine an abnormal vibration feature;

[0104] S500, based on the state analysis terminal, analyze the equipment state based on the abnormal vibration feature and the aging rate of the manufacturing equipment to determine a real-time state of the manufacturing equipment;

[0105] As can be understood by those skilled in the art, when the manufacturing equipment is aging to a certain extent, the speed of its running temperature increase will be different, and the manufacturing equipment will be aging to a certain extent after each use. The temperature can reflect the aging rate of the manufacturing equipment. For example, if the circuit of the manufacturing equipment is seriously aging, the internal resistance will increase, the circuit temperature will increase too fast, and the power consumption will be serious. If the motor of the manufacturing equipment is seriously aging, the temperature will also increase too fast during running. Therefore, by analyzing the historical running temperature data of the manufacturing equipment, the aging rate of the manufacturing equipment can be determined, the manufacturing equipment can be prevented from malfunctioning during running, and the production time can be prolonged. At the same time, as the manufacturing equipment is used for a long time, some abnormalities may occur in the manufacturing equipment, and if some abnormalities last for a long time, the manufacturing equipment will malfunction. Therefore, by analyzing the historical running vibration data of the manufacturing equipment, the abnormalities of the manufacturing equipment can be determined. Finally, the manufacturing equipment is maintained by the staff according to the aging rate and the abnormal vibration feature, so that the manufacturing equipment can be prevented from malfunctioning during production, and the production time can be shortened.

[0106] Referring to Figure 2 As shown in FIG. 2, the analyzing and processing of the historical running temperature data based on the state analysis terminal to determine the temperature growth rate of the manufacturing equipment specifically comprises the following steps:

[0107] S201, based on the state analysis terminal, data preprocessing is performed on the historical running temperature data, and the data preprocessing comprises data cleaning, data denoising, and data normalization;

[0108] S202. Based on the status analysis terminal, the historical operating temperature data is classified and uniquely marked according to the number of times the manufacturing equipment is run, and several sets of numbered operating temperature data are obtained. The specific form of the numbered operating temperature data is (temperature data, running time).

[0109] S203. Based on the status analysis terminal, several sets of numbered operating temperature data are plotted as curves in a two-dimensional rectangular coordinate system to obtain several numbered temperature curves. The X-axis parameter of the two-dimensional rectangular coordinate system is the operating time, and the Y-axis parameter of the two-dimensional rectangular coordinate system is the temperature data.

[0110] S204. Based on the status analysis terminal, filter the running time in several sets of numbered running temperature data to determine the shortest running time.

[0111] S205. Based on the status analysis terminal, perform feature analysis on several numbered temperature curves with the shortest running time as the feature to determine the temperature growth rate of the manufacturing equipment.

[0112] The specific formula for determining the shortest running time is as follows:

[0113]

[0114] In the formula, T min The shortest runtime; the T i The i represents the runtime of a numbered set of operating temperature data; i is the specific number of runtimes in the numbered set of operating temperature data; min() is the minimum value function.

[0115] In this embodiment, the rate of temperature increase can indirectly reflect the aging rate of the manufacturing equipment. Each time the manufacturing equipment is put into use, it will age a little. Therefore, the rate of temperature increase of the manufacturing equipment will change each time. However, this rate of temperature increase is in line with the aging law of the manufacturing equipment. Because the components of the manufacturing equipment have their own aging law, the rate of temperature increase of the manufacturing equipment is also in line with this law within a certain range. Therefore, by calculating the rate of temperature increase of the manufacturing equipment, the aging rate of the manufacturing equipment can be indirectly obtained.

[0116] Reference Figure 3 As shown, based on the state analysis terminal, the temperature growth rate of the manufacturing equipment is determined by performing feature analysis on several numbered temperature curves with the shortest running time as the characteristic, specifically including the following steps:

[0117] S2051. Based on the state analysis terminal, the shortest running time is used as a feature to perform curve truncation processing on several numbered temperature curves to obtain several partially numbered temperature curves.

[0118] S2052. Based on the state analysis terminal, the temperature data and shortest running time in several partially numbered temperature curves are averaged to obtain the heating rate of several sets of numbered temperature curves.

[0119] S2053. Based on the state analysis terminal, the heating rate of several groups of numbered temperature curves is calculated by difference based on adjacent numbers to obtain the heating rate difference of multiple groups.

[0120] S2054. Based on the state analysis terminal, the average calculation of multiple sets of heating rate differences is performed to determine the temperature growth rate of the manufacturing equipment.

[0121] The specific calculation formula for determining the temperature growth rate of the manufacturing equipment is as follows:

[0122]

[0123] In the formula, V c The temperature growth rate of the manufacturing equipment; the V j The heating rate is a numbered set of temperature curves; j is the specific number of the numbered sets of temperature curves.

[0124] In this embodiment, in order to make the aging rate of the manufacturing equipment more accurate, each numbered temperature curve is truncated using the same standard (i.e., the shortest running time) so that each numbered temperature curve has the same time length. Temperature analysis is performed on it under the same time length, and the results are more accurate.

[0125] Reference Figure 4 As shown, based on the condition analysis terminal, the temperature growth rate of the manufacturing equipment is simulated and analyzed to determine the aging rate of the manufacturing equipment. The specific steps include the following:

[0126] S301. Based on the status analysis terminal, select and process several sets of numbered operating temperature data to obtain the target numbered operating temperature data;

[0127] S302. Based on the status analysis terminal, calculate and process the temperature data and running time of the target number's operating temperature data to obtain the average temperature growth rate of the target number.

[0128] S303. Obtain the critical temperature of the manufacturing equipment, wherein the critical temperature of the manufacturing equipment is obtained from the database system;

[0129] S304. Based on the state analysis terminal, calculate and process the critical temperature of the manufacturing equipment, the average temperature growth rate of the target number, and the temperature growth rate of the manufacturing equipment to determine the time to reach the critical temperature.

[0130] S305. Based on the status analysis terminal, compare and judge the time to reach the critical temperature to determine the aging rate of the manufacturing equipment.

[0131] The specific formula for determining the time to reach the critical temperature is as follows:

[0132]

[0133] In the formula, T a The time to reach the critical temperature; C1 is the critical temperature of the manufacturing equipment; C2 is the temperature at which the manufacturing equipment completes its manufacturing task in the target number operating temperature data; T b The runtime in the running temperature data for the target number; the V c The temperature growth rate of manufacturing equipment;

[0134] In this embodiment, the temperature change of the manufacturing equipment can reflect the aging rate of the manufacturing equipment. This is because the higher the degree of aging of the manufacturing equipment, the faster its temperature rises. In order to obtain the specific aging rate of the manufacturing equipment, the time it takes for the temperature of the manufacturing equipment to reach the critical temperature of the manufacturing equipment is judged. This is because the more severe the aging of the manufacturing equipment, the faster it reaches the critical temperature. Therefore, the aging rate of the manufacturing equipment is determined by comparing the time it takes to reach the critical temperature.

[0135] Reference Figure 5 As shown, based on the condition analysis terminal, the aging rate of the manufacturing equipment is determined by comparing and judging the time taken to reach the critical temperature, specifically including the following steps:

[0136] S3051. Obtain the time required for the manufacturing equipment to normally reach the critical temperature, wherein the time required for the manufacturing equipment to normally reach the critical temperature is obtained from the database system;

[0137] S3052. Based on the state analysis terminal, perform a difference calculation on the time to reach the critical temperature and the time required for the manufacturing equipment to normally reach the critical temperature, and obtain the time difference value.

[0138] S3053. Based on the status analysis terminal, calculate and process the time difference and the time required for the manufacturing equipment to reach the critical temperature normally to determine the aging rate of the manufacturing equipment.

[0139] In this embodiment, the aging rate of the manufacturing equipment can be obtained by calculating the time difference and the time required for the manufacturing equipment to reach the critical temperature. For example, if the time difference is 50 minutes and the time required for the manufacturing equipment to reach the critical temperature is 500 minutes, the aging rate of the manufacturing equipment is 10%. Therefore, the aging rate of the manufacturing equipment can be determined by calculating the time difference and the time required for the manufacturing equipment to reach the critical temperature.

[0140] Referring to Figure 6 As shown, based on the state analysis terminal, the historical running vibration data is analyzed and processed to determine the abnormal vibration characteristics, which specifically includes the following steps:

[0141] S401, based on the state analysis terminal, the historical running vibration data is denoised, and the denoising is performed by wavelet transform method;

[0142] S402, based on the state analysis terminal, the historical running vibration data is classified and processed based on the number of running times of the manufacturing equipment, and is uniquely marked, to obtain a plurality of sets of numbered running vibration data, and the specific form of the numbered running vibration data is (vibration data, running time)

[0143] S403, based on the fast Fourier transform algorithm, the vibration data in the plurality of sets of numbered running vibration data is respectively processed in the frequency domain, to obtain the frequency spectrum information of the plurality of sets of numbered running vibration data;

[0144] S404, based on the state analysis terminal, the frequency spectrum information of the plurality of sets of numbered running vibration data is extracted, to obtain the frequency spectrum information of the target numbered running vibration data;

[0145] S405, based on the state analysis terminal, the frequency spectrum information of the plurality of sets of numbered running vibration data is compared based on the frequency spectrum information of the target numbered running vibration data, to determine the abnormal vibration characteristics;

[0146] In this embodiment, the sound sensor is used to collect the sound of the manufacturing equipment in use. Because when the manufacturing equipment is abnormal, there will be a certain frequency of special vibration, therefore, the historical running vibration data is the sound data. When the sound sensor collects the vibration sound, it may also collect the external sound (such as speaking sound). In order to make the subsequent analysis more accurate, the wavelet transform method is used to denoise. Different vibration sounds have different frequency spectrums in the frequency domain, therefore, the fast Fourier algorithm is used to convert the denoised historical running vibration data to the frequency domain for frequency spectrum analysis, to determine the frequency spectrum information of the abnormal vibration, and further determine the abnormal vibration characteristics.

[0147] Referring to Figure 7 As shown, based on the state analysis terminal, the frequency spectrum information of the plurality of sets of numbered running vibration data is compared based on the frequency spectrum information of the target numbered running vibration data, to determine the abnormal vibration characteristics, which specifically includes the following steps:

[0148] S4051, based on the state analysis terminal, the frequency spectrum information of the plurality of sets of numbered running vibration data is matched based on the frequency spectrum information of the target numbered running vibration data, to obtain the frequency spectrum information of a plurality of sets of abnormal vibration data;

[0149] S4052, based on the state analysis terminal, count processing is performed on the frequency spectrum information of the abnormal vibration data, and the number of occurrences of the frequency spectrum information of the abnormal vibration feature is obtained;

[0150] S4053, based on the state analysis terminal, the number of occurrences of the frequency spectrum information of the abnormal vibration feature is judged and processed, and the abnormal vibration feature is determined;

[0151] In this embodiment, when the historical running vibration data is analyzed abnormally, a reference needs to be set to determine whether it is abnormal. The manufacturing equipment just put into use will not appear abnormal, so the vibration data generated by the manufacturing equipment just put into use is taken as the reference data (i.e. the target number of running vibration data), and then the frequency spectrum analysis is performed to obtain the frequency spectrum information of the vibration data under the normal operation of the manufacturing equipment. Then, the vibration frequency spectrum information generated by the subsequent running manufacturing equipment is screened to determine the abnormal frequency spectrum information.

[0152] Referring to Figure 8 As shown in the figure, based on the state analysis terminal, the number of occurrences of the frequency spectrum information of the abnormal vibration feature is judged and processed, and the abnormal vibration feature is determined. The specific steps include:

[0153] S40531, based on the state analysis terminal, the number of occurrences of the frequency spectrum information of the abnormal vibration feature and the set number of occurrence threshold are judged and processed;

[0154] S40532, if the number of occurrences of the frequency spectrum information of the abnormal vibration feature is greater than the set number of occurrence threshold, the vibration data corresponding to the number of occurrences of the frequency spectrum information of the abnormal vibration feature is the abnormal vibration feature;

[0155] S40533, if the number of occurrences of the frequency spectrum information of the abnormal vibration feature is less than or equal to the set number of occurrence threshold, the vibration data corresponding to the number of occurrences of the frequency spectrum information of the abnormal vibration feature does not conform to the abnormal vibration feature;

[0156] In this embodiment, the manufacturing equipment may generate a certain number of vibrations when foreign matter appears inside during operation. However, when the foreign matter is removed, the type of vibration will not be generated. Therefore, by judging the number of occurrences of the frequency spectrum information of the abnormal vibration feature, some interference factors are removed. If the manufacturing equipment is not repaired after the abnormality, vibration will always be generated. Therefore, the number of occurrences of the frequency spectrum information of the abnormal vibration feature is used to determine which vibration is the abnormal vibration feature and which is the interference factor.

[0157] Referring to Figure 9As shown, based on the state analysis terminal, the abnormal vibration characteristics and the aging rate of the manufacturing equipment are analyzed to determine the real-time state of the manufacturing equipment, which specifically includes the following steps:

[0158] S501, based on the state analysis terminal, the abnormal vibration characteristics are counted to obtain the number of abnormal vibration characteristics;

[0159] S502, based on the state analysis terminal, the number of abnormal vibration characteristics and the aging rate of the manufacturing equipment are judged;

[0160] S503, if the number of abnormal vibration characteristics is greater than or equal to the set abnormal vibration characteristic quantity threshold value, and the aging rate of the manufacturing equipment is greater than or equal to the set aging rate threshold value, the real-time state of the manufacturing equipment is poor, etc.

[0161] S504, if the number of abnormal vibration characteristics is greater than or equal to the set abnormal vibration characteristic quantity threshold value, or the aging rate of the manufacturing equipment is greater than or equal to the set aging rate threshold value, the real-time state of the manufacturing equipment is good, etc.

[0162] S505, if the number of abnormal vibration characteristics is less than the set abnormal vibration characteristic quantity threshold value, and the aging rate of the manufacturing equipment is less than the set aging rate threshold value, the real-time state of the manufacturing equipment is excellent.

[0163] In this embodiment, by analyzing the number of abnormal vibration characteristics and the aging rate of the manufacturing equipment, the real-time state of the manufacturing equipment can be determined, and the staff only needs to repair the manufacturing equipment according to the real-time state of the manufacturing equipment, avoiding the failure of the manufacturing equipment during operation, and prolonging the production time.

[0164] Referring to Figure 10 As shown, a manufacturing equipment state analysis system based on data analysis is used to realize a manufacturing equipment state analysis method based on data analysis, which includes:

[0165] The state analysis terminal is used to analyze the aging rate and abnormal vibration characteristics of the historical running temperature data and the historical running vibration data, and to determine the real-time state of the manufacturing equipment.

[0166] The database system is used to store the historical running temperature data, the historical running vibration data, the time required for the manufacturing equipment to normally reach the critical temperature, and the critical temperature of the manufacturing equipment, and the database system is in communication connection with the state analysis terminal.

[0167] The above shows and describes the basic principles, main features and advantages of the present application. Those skilled in the art should understand that the present application is not limited to the above-mentioned embodiments, and the above-mentioned embodiments and descriptions in the specification are only the principles of the present application. Various changes and improvements can be made without departing from the spirit and scope of the present application, and these changes and improvements all fall within the scope of the claimed present application. The scope of protection of the present application is defined by the appended claims and their equivalents.

Claims

1. A method for manufacturing equipment status analysis based on data analysis, characterized in that, include: Historical operating data of the manufacturing equipment is obtained from a database system, including historical operating temperature data and historical operating vibration data. Based on the status analysis terminal, historical operating temperature data is analyzed and processed to determine the temperature growth rate of the manufacturing equipment. Based on the condition analysis terminal, the temperature growth rate of the manufacturing equipment is simulated and analyzed to determine the aging rate of the manufacturing equipment. Based on the condition analysis terminal, historical operational vibration data is analyzed and processed to determine abnormal vibration characteristics; Based on the condition analysis terminal, the equipment condition analysis is performed on the abnormal vibration characteristics and the aging rate of the manufacturing equipment to determine the real-time condition of the manufacturing equipment. The step of simulating and analyzing the temperature growth rate of the manufacturing equipment based on the condition analysis terminal to determine the aging rate of the manufacturing equipment specifically includes the following steps: Based on the status analysis terminal, several sets of numbered operating temperature data are selected and processed to obtain the target numbered operating temperature data; Based on the status analysis terminal, the temperature data and runtime of the target number's operating temperature data are calculated and processed to obtain the average temperature growth rate of the target number. The critical temperature of the manufacturing equipment is obtained from a database system; Based on the state analysis terminal, the critical temperature of the manufacturing equipment, the average temperature growth rate of the target number, and the temperature growth rate of the manufacturing equipment are calculated and processed to determine the time to reach the critical temperature. Based on the condition analysis terminal, the time to reach the critical temperature is compared and judged to determine the aging rate of the manufacturing equipment. The step of analyzing and processing historical operational vibration data based on the state analysis terminal to determine abnormal vibration characteristics specifically includes the following steps: Based on the state analysis terminal, historical operational vibration data is denoised using wavelet transform. Based on the state analysis terminal, historical operating vibration data is classified and uniquely marked according to the number of times the manufacturing equipment is run, and several sets of numbered operating vibration data are obtained. The numbered operating vibration data includes vibration data and running time. Based on the Fast Fourier Transform algorithm, frequency domain transformation processing is performed on the vibration data in several groups of numbered running vibration data to obtain the spectral information of several groups of numbered running vibration data. Based on the state analysis terminal, the spectral information of several sets of numbered operational vibration data is extracted and processed to obtain the spectral information of the target numbered operational vibration data; Based on the state analysis terminal, the spectral information of several groups of numbered vibration data is compared and processed using the spectral information of target numbered vibration data as a feature to determine abnormal vibration characteristics. The process of comparing and processing the spectral information of several groups of numbered vibration data based on the spectral information of target-numbered vibration data using the state analysis terminal to determine abnormal vibration characteristics specifically includes the following steps: Based on the state analysis terminal, the spectral information of several groups of numbered vibration data is matched and processed using the spectral information of target numbered vibration data as a feature to obtain the spectral information of multiple groups of abnormal vibration data. Based on the state analysis terminal, the spectral information of abnormal vibration data is counted to obtain the number of occurrences of the spectral information of abnormal vibration characteristics; Based on the state analysis terminal, the frequency of occurrence of the spectral information of abnormal vibration characteristics is judged and processed to determine the abnormal vibration characteristics; The process of determining the frequency of occurrence of spectral information of abnormal vibration characteristics based on the state analysis terminal includes the following steps: Based on the state analysis terminal, the frequency of occurrence of the spectral information of abnormal vibration characteristics and the set frequency threshold are judged and processed. If the frequency of occurrence of the spectrum information of the abnormal vibration feature is greater than the set frequency threshold, the vibration data corresponding to the frequency of occurrence of the spectrum information of the abnormal vibration feature is the abnormal vibration feature. If the frequency of occurrence of the spectrum information of the abnormal vibration feature is less than or equal to the set frequency threshold, the vibration data corresponding to the frequency of occurrence of the spectrum information of the abnormal vibration feature does not conform to the abnormal vibration feature.

2. The manufacturing equipment status analysis method based on data analysis according to claim 1, characterized in that, The process of analyzing and processing historical operating temperature data based on the status analysis terminal to determine the temperature growth rate of the manufacturing equipment specifically includes the following steps: Based on the status analysis terminal, historical operating temperature data is preprocessed, including data cleaning, data denoising, and data normalization. Based on the status analysis terminal, the historical operating temperature data is classified and uniquely marked according to the number of times the manufacturing equipment is run, and several sets of numbered operating temperature data are obtained. The specific form of the numbered operating temperature data is (temperature data, running time). Based on the status analysis terminal, several sets of numbered operating temperature data are plotted as curves in a two-dimensional rectangular coordinate system to obtain several numbered temperature curves. The X-axis parameter of the two-dimensional rectangular coordinate system is the operating time, and the Y-axis parameter of the two-dimensional rectangular coordinate system is the temperature data. Based on the status analysis terminal, the running time in several sets of numbered running temperature data is filtered to determine the shortest running time. Based on the state analysis terminal, the shortest running time is used as a feature to perform feature analysis on several numbered temperature curves to determine the temperature growth rate of the manufacturing equipment.

3. The manufacturing equipment status analysis method based on data analysis according to claim 2, characterized in that, The process of using a state analysis terminal to perform feature analysis on several numbered temperature curves, with the shortest runtime as a characteristic, to determine the temperature growth rate of the manufacturing equipment specifically includes the following steps: Based on the state analysis terminal, curve truncation processing is performed on several numbered temperature curves with the shortest running time as the feature to obtain several partial numbered temperature curves. Based on the state analysis terminal, the temperature data and shortest running time in several partially numbered temperature curves are averaged to obtain the heating rate of several sets of numbered temperature curves. Based on the state analysis terminal, the heating rate of several groups of numbered temperature curves is calculated by subtracting adjacent numbers to obtain the heating rate difference values ​​of multiple groups. Based on the state analysis terminal, the average calculation of multiple sets of heating rate differences is performed to determine the temperature growth rate of the manufacturing equipment.

4. The manufacturing equipment status analysis method based on data analysis according to claim 1, characterized in that, The process of comparing and judging the time to reach the critical temperature based on the state analysis terminal to determine the aging rate of the manufacturing equipment includes the following steps: The time required for the manufacturing equipment to normally reach the critical temperature is obtained from the database system. Based on the state analysis terminal, the difference between the time to reach the critical temperature and the time required for the manufacturing equipment to normally reach the critical temperature is calculated to obtain the time difference. Based on the condition analysis terminal, the time difference and the time required for the manufacturing equipment to reach the critical temperature are calculated and processed to determine the aging rate of the manufacturing equipment.

5. The manufacturing equipment status analysis method based on data analysis according to claim 1, characterized in that, The process of analyzing abnormal vibration characteristics and the aging rate of manufacturing equipment based on the condition analysis terminal to determine the real-time status of the manufacturing equipment includes the following steps: Based on the state analysis terminal, the abnormal vibration features are counted to obtain the number of abnormal vibration features. Based on the condition analysis terminal, the number of abnormal vibration characteristics and the aging rate of manufacturing equipment are judged and processed. If the number of abnormal vibration features is greater than or equal to the set threshold for the number of abnormal vibration features, and the aging rate of the manufacturing equipment is greater than or equal to the set threshold for the aging rate, the real-time status of the manufacturing equipment is poor. If the number of abnormal vibration features is greater than or equal to the set threshold for the number of abnormal vibration features, or if the aging rate of the manufacturing equipment is greater than or equal to the set threshold for the aging rate, the real-time status of the manufacturing equipment is good. If the number of abnormal vibration features is less than the set threshold for the number of abnormal vibration features, and the aging rate of the manufacturing equipment is less than the set threshold for the aging rate, the real-time status of the manufacturing equipment is excellent.

6. A manufacturing equipment status analysis system based on data analysis, used to implement the manufacturing equipment status analysis method based on data analysis as described in any one of claims 1-5, characterized in that, include: A status analysis terminal is used to perform aging rate analysis and abnormal vibration characteristic analysis on historical operating temperature data and historical operating vibration data to determine the real-time status of the manufacturing equipment. A database system is provided for storing historical operating temperature data, historical operating vibration data, the time required for the manufacturing equipment to reach the critical temperature, and the critical temperature of the manufacturing equipment. The database system is communicatively connected to the condition analysis terminal.

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