Equipment fault prediction method and equipment fault prediction system for press line

Abstract

The invention relates to the technical field of equipment detection and maintenance, in particular to an equipment fault prediction method and system for a press line. The equipment fault prediction method comprises the following steps: collecting current vibration data of all preset measurement points in press line equipment; preprocessing the current vibration data to form current vibration indication data and a vibration trend chart of corresponding equipment; judging whether the current vibration indication data meets a preset judgment standard or not; and if the current vibration indication data does not meet the preset judgment standard, performing fault prediction on the equipment according to the vibration trend chart of the equipment corresponding to the current vibration indication data. According to the method, the conventional vibration indication data and the trend graph are combined to carry out equipment trend analysis, so that the influence of data mutation caused by individual special case data and temporary environment mutation in a normal production process on a prediction result is reduced.

Description

Technical Field

[0001] The present application relates to the technical field of equipment detection and maintenance, and in particular to an equipment failure prediction method and an equipment failure prediction system for a stamping line. Background Art

[0002] As an important application carrier of stamping equipment, stamping automation production line plays an extremely important role in my country's automobile industry system. However, with the improvement of production efficiency, stamping automation production line is increasingly facing the risk of downtime and line stoppage. How to efficiently control the health status of equipment and reduce the downtime rate is imminent. Mastering the health status of equipment usually includes two categories: predictive maintenance and preventive maintenance. Preventive maintenance is to organize maintenance plans according to fixed cycles. At present, the maintenance plan of stamping production line is mostly preventive maintenance, but the maintenance plan method is not targeted. The early preventive maintenance may not produce much value and significance for most maintenance investment. With the increase of equipment service life and the aging of equipment parts, the fixed cycle of preventive maintenance should be appropriately adjusted. If it is not adjusted in time, the equipment may fail between two maintenance cycles. Predictive maintenance is to arrange maintenance plans in a targeted manner based on the actual deterioration of equipment or components on the basis of status inspection. This maintenance can keep the equipment in use to the maintenance limit, which is obviously economical. At the same time, we can also maintain, correct or replace the equipment in time according to the working status of the equipment. Therefore, the implementation of predictive maintenance is more in line with production reality and deserves to be widely promoted.

[0003] In the related technology, intelligent control is introduced into modern mechanical equipment, and the fault signals of the mechanical equipment are mostly captured to determine that the mechanical equipment has failed. However, on the one hand, the detection is set based on the existence of a clear fault, and it is impossible to predict the fault trend of the production line. On the other hand, the fault signals currently introduced are often relatively simple, which may be individual special data in the normal production process, or data mutations caused by temporary changes in the environment. The above special data or data mutations do not represent that there is a fault in the equipment. It is obviously not very economical and undesirable to carry out equipment inspection and maintenance on special data caused by various emergencies in production, especially for stamping production lines with complex and numerous equipment. Summary of the invention

[0004] Regarding the related technologies, the fault signals introduced by the equipment fault prediction of the stamping line are often relatively simple. Conventional fault detection can easily detect data mutations caused by individual exceptions in the normal production process or temporary mutations in the environment, resulting in misjudgment of the faults of the stamping line equipment.

[0005] The present application provides a method, device / system, equipment and computer-readable storage medium for predicting equipment failure of a stamping line, which can solve xx technical problems existing in the prior art.

[0006] In a first aspect, an embodiment of the present application provides a method for predicting equipment failure of a stamping line, the method comprising:

[0007] Collect current vibration data at all preset measuring points in the press line equipment;

[0008] Preprocessing the current vibration data to form current vibration indication data and a vibration trend diagram of the corresponding equipment;

[0009] Determine whether the current vibration indication data meets the preset judgment criteria;

[0010] If the preset judgment criteria are not met, the equipment fault prediction is performed based on the vibration trend diagram of the equipment corresponding to the current vibration indication data.

[0011] In combination with the first aspect, in one implementation, before determining whether the current vibration indication data meets a preset judgment standard, the method further includes:

[0012] Collect standard vibration data of all preset measuring points during normal operation of the press line equipment;

[0013] Preprocessing the standard vibration data to obtain standard indicator vibration data;

[0014] Formulate preset judgment criteria for press line equipment based on standard indicator vibration data of press line equipment.

[0015] In combination with the first aspect, in one embodiment, the preset judgment criteria for different parts are formulated based on the standard vibration data set, including: calculating the average value of each standard indication vibration data, and setting the alarm threshold and danger threshold of each vibration data based on the average value of the standard indication vibration data as a reference value.

[0016] In combination with the first aspect, in one implementation, the setting of the alarm threshold and the danger threshold of each vibration data using the average value of the standard indication vibration data as a reference value includes:

[0017] The alarm threshold is set to 2 times the reference value, and the danger threshold is set to 5 times the reference value.

[0018] In combination with the first aspect, in one implementation, the preprocessing of the current vibration data includes:

[0019] The current vibration data is calculated according to the time domain waveform or the spectrum diagram to form the current vibration indication data, and the current vibration indication data includes a vibration acceleration value, a vibration velocity value, a vibration displacement value, a bearing damage value, a broadband energy value and a narrowband energy value.

[0020] In combination with the first aspect, in one implementation, the preprocessing of the current vibration data further includes: creating a trend graph of the current vibration indication data according to the current vibration indication data.

[0021] In combination with the first aspect, in one implementation, predicting a fault of a device according to a vibration trend graph of the device corresponding to the current vibration indication data includes:

[0022] Conduct an overall analysis of the vibration trend graph corresponding to the current vibration indication data;

[0023] If the corresponding trend graph shows that the working trend is stable and the working trend does not exceed the alarm threshold, it is determined that there is no abnormality in the equipment part corresponding to the current vibration indication data;

[0024] If the corresponding trend graph shows an upward trend, and the trend rises and exceeds the alarm threshold line, it is determined that the equipment part corresponding to the current vibration indication data has hidden dangers.

[0025] In combination with the first aspect, in one implementation, the performing fault prediction on the equipment according to the vibration trend graph of the equipment corresponding to the current vibration indication data further includes:

[0026] Fault prediction of equipment is performed based on the time domain waveform or spectrum diagram corresponding to the current vibration indication data.

[0027] In combination with the first aspect, in one embodiment, the collecting current vibration data of all preset measurement points in the press line equipment includes:

[0028] Vibration acceleration sensors are installed at preset measuring points in the collection and stamping line equipment, and the vibration acceleration sensors are used to perform real-time detection of the stamping line equipment.

[0029] In a second aspect, an embodiment of the present application provides a system for predicting equipment failures of a stamping line, which includes:

[0030] A data collection module, which is used to collect current vibration data of all preset measurement points in the press line equipment;

[0031] A data processing module, which is used to pre-process the vibration data set to form current vibration indication data and a trend diagram of the corresponding equipment;

[0032] The data judgment module is used to make a preliminary judgment on the current vibration indication data according to the preset judgment criteria; wherein,

[0033] If the current vibration indicator data in the current vibration indicator data set does not meet the preset judgment criteria, the equipment fault prediction is performed based on the trend chart of the equipment corresponding to the current vibration indicator data.

[0034] The beneficial effects brought by the technical solution provided in the embodiments of the present application include:

[0035] After the equipment failure prediction method of the present application collects the vibration data of the stamping line equipment, it pre-processes it to form vibration indicators and trend graphs of vibration data. In real-time monitoring, the conventional vibration indicator data is first used for preliminary judgment. If the vibration indicator data shows abnormalities, the trend graph of the vibration data is further analyzed to obtain accurate fault prediction results, thereby reducing the impact of data mutations caused by temporary mutations of individual special case data and the environment during normal production on the prediction results. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 A schematic diagram of a flow chart of a method for predicting equipment failure of a stamping line in an embodiment of the present application;

[0037] Figure 2 This is a layout diagram of the vibration measurement points of the press bearing in the embodiment of the present application;

[0038] Figure 3 A schematic diagram of the preset judgment criteria in the embodiment of the present application;

[0039] Figure 4 This is a vibration trend diagram of the normal working state of the equipment in the embodiment of the present application;

[0040] Figure 5 This is a vibration trend diagram of the equipment in the embodiment of the present application when there is a potential fault.

[0041] Figure 6 It is a time domain waveform diagram of the current vibration indication data in the embodiment of the present application;

[0042] Figure 7 is a spectrum diagram of the current vibration indication data in the embodiment of the present application;

[0043] Figure 8 This is a schematic diagram of the hardware structure of the equipment failure prediction device for the stamping line involved in the embodiment of the present application. DETAILED DESCRIPTION

[0044] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0045] Regarding the related technologies, the fault signals introduced by the equipment fault prediction of the stamping line are often relatively simple. Conventional fault detection can easily detect data mutations caused by individual exceptions in the normal production process or temporary mutations in the environment, resulting in misjudgment of the faults of the stamping line equipment.

[0046] First, as Figure 1 As shown, an embodiment of the present application provides a method for predicting equipment failure of a stamping line, and the method for predicting equipment failure includes:

[0047] Step S1, collecting current vibration data of all preset measurement points in the press line equipment.

[0048] It should be noted that the current vibration data collection of the press line equipment includes data collection of the press process, data collection of the automated transmission device process, and data collection of the high-speed press line press.

[0049] The above step S1 includes: installing a vibration acceleration sensor at a preset measuring point in the collection and pressing line equipment, and using the vibration acceleration sensor to perform real-time detection on the pressing line equipment.

[0050] Furthermore, the above step S1a process includes monitoring of press process data, data collection of automated transmission device process, and data collection of high-speed linear presses, and the collected data includes vibration acceleration value, vibration velocity value, and indicator values ​​such as bearing damage, and each monitoring point is connected to a multi-channel online monitoring collector through a dedicated low-noise shielded signal cable for raw signal processing and analysis. When in use, MODBUS, OPC and other protocols can be used to interact with industrial control systems, such as PLC, DCS and MES systems and other industrial control systems or equipment management platforms.

[0051] In some specific implementations, the key main transmission components of the stamping high-speed linear press can be monitored in real time. The key main transmission components include main motor bearings, flywheel bearings, and high-speed shaft bearings.

[0052] It should be noted that these key parts are located inside the equipment, and manual inspection is relatively complicated. In addition, manual inspection cannot accurately determine the degree of deterioration of key components such as bearings, and cannot predict potential mechanical failures in advance. When key main transmission components such as high-speed shafts and main motors fail, the high-speed line will be shut down. However, by using sensors to detect bearing vibration values ​​in real time, collect data, and conduct trend analysis and management, potential mechanical failures can be discovered in advance, achieving the purpose of predictive maintenance and avoiding major shutdowns caused by failures in the main transmission components of the press.

[0053] Furthermore, if Figure 2As shown, for key measurement locations A1-A10 such as press bearings, the present application provides a sensor layout solution to obtain accurate measurement data.

[0054] Step S2: preprocess the vibration data set to form current vibration indication data and a vibration trend diagram of the corresponding equipment.

[0055] The above step S2 comprises:

[0056] Step S2a, calculating the current vibration data according to the time domain waveform or the spectrum to form current vibration indication data, wherein the current vibration indication data includes vibration acceleration value, vibration velocity value, vibration displacement value, bearing damage value, broadband energy value and narrowband energy value.

[0057] It is worth mentioning that the current vibration indicator data is not limited to vibration acceleration values, vibration velocity values, vibration displacement values, bearing damage values ​​and various broadband / narrowband energy values. All these indicator values ​​are calculated from time domain waveforms or spectrum diagrams using specific algorithms. Among them, vibration acceleration values ​​and vibration velocity values ​​are the two most commonly used and most recognized vibration indicator values.

[0058] Step S2b: creating a trend graph of the current vibration indication data according to the current vibration indication data.

[0059] Specifically, a trend chart is produced by predicting the trends of various indicator values ​​calculated from the edges of the current vibration data.

[0060] It is worth noting that the present application processes the vibration data into current vibration indication data and vibration trend graphs, and the combination of the two can obtain more accurate analysis results. As the most intuitive data embodiment, the current vibration indication data can display every data abnormality. However, during the normal production process, due to the differences in the products produced, individual special case data will also appear, causing the vibration indication data of parts to deviate from the normal value. In addition, when the working environment of the equipment changes, it will also cause data mutations. However, the above-mentioned special case data or data mutations do not mean that there are hidden dangers of equipment failure. Therefore, the trend analysis of this application not only needs to monitor the current vibration indication data, but also needs to make a trend graph for it for overall analysis.

[0061] Step S3: determine whether the current vibration indication data meets the preset judgment standard.

[0062] It is worth noting that the current vibration indicator data can intuitively show the working value of the equipment, but as mentioned above, it is greatly affected by other factors, and it is impossible for the staff to shut down the equipment for maintenance every time the data is abnormal. In order to eliminate errors as much as possible, this application needs to combine the trend chart with the current vibration indicator data to judge the trend of the equipment.

[0063] The above step S3 specifically includes:

[0064] Step S3a, setting a preset judgment standard.

[0065] In the first specific embodiment provided in the present application, the setting scheme of the preset judgment standard includes: using the ISO10816-3 standard as the preset judgment standard.

[0066] It is understood that the three main factors that affect the indicator value status are whether the equipment installation foundation is rigid or flexible, motor power and motor center height.

[0067] It is understandable that when the ISO standard, G / B national standard, industry standard or equipment manufacturer standard does not include or is not applicable to the type of equipment being monitored, the industry experience formula can be used to set the indicator value alarm threshold. The setting process can refer to the second specific embodiment provided in the present application below.

[0068] In the second specific embodiment provided in the present application, the setting scheme of the preset judgment criteria includes:

[0069] Step a: Collect standard vibration data of all preset measurement points during the normal operation of the press line equipment.

[0070] Step b: preprocessing the standard vibration data to obtain standard indication vibration data.

[0071] Step c: formulating preset judgment standards for the press line equipment according to the standard indication vibration data of the press line equipment.

[0072] Specifically, step c includes calculating the average value of each standard indicator vibration data, and setting the alarm threshold and danger threshold of each vibration data with the average value of the standard indicator vibration data as a reference value.

[0073] In some optional implementations, such as Figure 3 As shown, the alarm threshold is set to 2 times the reference value, and the danger threshold is set to 5 times the reference value.

[0074] Step S3b: make a preliminary judgment on the current vibration indication data according to a preset judgment standard.

[0075] Specifically, if the current vibration indicator data does not exceed the alarm threshold, it is preliminarily determined that the equipment has no hidden danger of failure; if the current vibration indicator data exceeds the alarm threshold, the subsequent step S4 is executed.

[0076] Step S4: predicting equipment failure according to the vibration trend diagram of the equipment corresponding to the current vibration indication data.

[0077] Specifically, an overall analysis is performed on the vibration trend graph corresponding to the current vibration indication data.

[0078] in,

[0079] Scenario 1: If Figure 4 As shown in the figure, if the corresponding trend chart shows that the working trend is stable and the working trend does not exceed the alarm threshold, it is determined that the equipment part corresponding to the current vibration indication data has no abnormality

[0080] Scenario 2: If Figure 5 As shown, if the corresponding trend graph shows an upward trend, and the trend rises and exceeds the alarm threshold line, it is determined that the equipment part corresponding to the current vibration indication data has hidden dangers.

[0081] In some optional implementations, fault prediction is performed based on a time domain waveform corresponding to the current vibration indication data.

[0082] Specifically, Figure 6 As shown, if the time domain waveform diagram shows that there are regular, equally spaced, obvious, and periodic impact signals in the waveform, it is predicted that the mechanical parts may be damaged.

[0083] In some other optional implementations, fault prediction of the equipment is performed based on the frequency spectrum corresponding to the current vibration indication data.

[0084] Specifically, Figure 7 As shown in the figure, if there are equally spaced, periodic impact signals of about 11.7 Hz in the spectrum diagram, and the harmonic signals are extremely rich, it is predicted that the mechanical parts may be damaged.

[0085] In a second aspect, the present application provides a press line equipment failure prediction system, which includes: a data collection module, a data processing module and a data judgment module; wherein:

[0086] The data collection module is used to collect the current vibration data of all preset measurement points in the press line equipment. The data processing module is used to pre-process the vibration data set to form the current vibration indication data and the trend diagram of the corresponding equipment; the data judgment module is used to make a preliminary judgment on the current vibration indication data according to the preset judgment criteria; wherein,

[0087] If the current vibration indicator data in the current vibration indicator data set does not meet the preset judgment criteria, the equipment fault prediction is performed based on the trend chart of the equipment corresponding to the current vibration indicator data.

[0088] In combination with the above second aspect, in one embodiment, the data collection module includes: a vibration sensor, a vibration data collector and a vibration sensor cable. The data collection module can arrange monitoring points at the support positions of various key components according to the structural characteristics and process characteristics of the stamping machine. All key components use vibration acceleration sensors, which can monitor multiple indicator values ​​such as the vibration acceleration value, vibration velocity value and bearing damage of the equipment, and realize real-time monitoring of the operating status of the equipment.

[0089] Furthermore, each of the above monitoring points is connected to a multi-channel online monitoring collector through a dedicated low-noise shielded signal cable for raw signal processing and analysis.

[0090] In some preferred implementations, the equipment fault prediction system further includes: a data transmission module, which transmits the data of the vibration data collector to the intelligent monitoring software via Ethernet or optical cable. The equipment status data includes multiple types of parameters such as vibration values, time domain waveforms and spectrograms, and the data volume is large. The data acquisition layer and the data application layer communicate via Ethernet.

[0091] Specifically, the data judgment module includes a server and intelligent monitoring software, and does not limit the increase in the number of collectors connected. The data judgment module is used for multi-channel online monitoring of vibration indicators, waveforms, alarm indicators and other data processed by the collector, and displays them in real time on the intelligent monitoring platform, so as to achieve the purpose of real-time monitoring of the operating status of the monitored equipment and intelligent diagnosis.

[0092] It is worth mentioning that the above-mentioned intelligent monitoring platform can provide standard OPC protocol and CMMS interface to share data with third-party platforms.

[0093] Among them, the functional implementation of each module in the above-mentioned equipment failure prediction method for the stamping line corresponds to the steps in the above-mentioned equipment failure prediction method embodiment for the stamping line, and its functions and implementation processes will not be repeated here one by one.

[0094] In a third aspect, an embodiment of the present application provides an equipment failure prediction device for a stamping line. The equipment failure prediction device for a stamping line may be a personal computer (PC), a laptop computer, a server, or other device with data processing capabilities.

[0095] Reference Figure 8 , Figure 8 The hardware structure diagram of the equipment failure prediction device of the stamping line involved in the embodiment of the present application is shown in FIG. In the embodiment of the present application, the equipment failure prediction device of the stamping line may include a processor, a memory, a communication interface and a communication bus.

[0096] The communication bus may be of any type and is used to interconnect the processor, the memory, and the communication interface.

[0097] The communication interface includes input / output (I / O) interface, physical interface and logical interface, etc., which are used to realize the interconnection of devices inside the equipment failure prediction device of the stamping line, and the interface used to realize the interconnection between the equipment failure prediction device of the stamping line and other devices (such as other computing devices or user devices). The physical interface can be an Ethernet interface, a fiber optic interface, an ATM interface, etc.; the user device can be a display, a keyboard, etc.

[0098] The memory can be various types of storage media, such as random access memory (RAM), read-only memory (ROM), non-volatile RAM (NVRAM), flash memory, optical storage, hard disk, programmable ROM (PROM), erasable PROM (EPROM), electrically erasable PROM (EEPROM), etc.

[0099] The processor may be a general-purpose processor, which may call the equipment failure prediction program of the stamping line stored in the memory and execute the equipment failure prediction method of the stamping line provided in the embodiment of the present application. For example, the general-purpose processor may be a central processing unit (CPU). The method executed when the equipment failure prediction program of the stamping line is called may refer to the various embodiments of the equipment failure prediction method of the stamping line of the present application, which will not be repeated here.

[0100] Those skilled in the art will understand that Figure 8 The hardware structure shown in the figure does not constitute a limitation on the present application, and may include more or less components than shown in the figure, or combine certain components, or arrange the components differently.

[0101] In a fourth aspect, an embodiment of the present application also provides a readable storage medium.

[0102] The readable storage medium of the present application stores a device failure prediction program for a stamping line, wherein when the device failure prediction program for a stamping line is executed by a processor, the steps of the device failure prediction method for a stamping line as described above are implemented.

[0103] Among them, the method implemented when the equipment failure prediction program of the stamping line is executed can refer to the various embodiments of the equipment failure prediction method of the stamping line of the present application, and will not be repeated here.

[0104] It should be noted that the serial numbers of the above-mentioned embodiments of the present application are only for description and do not represent the advantages or disadvantages of the embodiments.

[0105] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, disk, CD) as described above, and includes a number of instructions for a terminal device to execute the methods described in each embodiment of the present application.

[0106] The terms "including" and "having" and any variations thereof in the specification and claims of this application and the above-mentioned drawings are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or devices. The terms "first", "second" and "third" are used to distinguish different objects, etc., and do not represent a sequence, nor do they limit "first", "second" and "third" to different types.

[0107] In the description of the embodiments of the present application, "exemplary", "for example" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary", "for example" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary", "for example" or "for example" is intended to present related concepts in a specific way.

[0108] In the description of the embodiments of the present application, unless otherwise specified, “ / ” means or, for example, A / B can mean A or B; the “and / or” in the text is merely a description of the association relationship of associated objects, indicating that three relationships may exist, for example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, in the description of the embodiments of the present application, “multiple” refers to two or more than two.

[0109] In some processes described in the embodiments of the present application, multiple operations or steps that appear in a specific order are included, but it should be understood that these operations or steps may not be executed in the order in which they appear in the embodiments of the present application or in parallel, and the sequence number of the operation is only used to distinguish the different operations, and the sequence number itself does not represent any execution order. In addition, these processes may include more or fewer operations, and these operations or steps may be executed in sequence or in parallel, and these operations or steps may be combined.

[0110] The above are only preferred embodiments of the present application, and are not intended to limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. A method for predicting equipment failure of a stamping line, characterized in that: The equipment failure prediction method comprises: Collect current vibration data at all preset measuring points in the press line equipment; Preprocessing the current vibration data to form current vibration indication data and a vibration trend diagram of the corresponding equipment; Determine whether the current vibration indication data meets the preset judgment criteria; If the preset judgment criteria are not met, the equipment fault prediction is performed based on the vibration trend diagram of the equipment corresponding to the current vibration indication data.

2. The equipment failure prediction method according to claim 1, characterized in that: Before judging whether the current vibration indicator data meets the preset judgment standard, the method further includes: Collect standard vibration data of all preset measuring points during normal operation of the press line equipment; Preprocessing the standard vibration data to obtain standard indicator vibration data; Formulate preset judgment criteria for press line equipment based on standard indicator vibration data of press line equipment.

3. The equipment failure prediction method according to claim 2, characterized in that: The preset judgment standards for different parts are formulated according to the standard vibration data set, including: calculating the average value of each standard indication vibration data, and setting the alarm threshold and danger threshold of each vibration data with the average value of the standard indication vibration data as a reference value.

4. The equipment failure prediction method according to claim 3, characterized in that: The method of setting the alarm threshold and danger threshold of each vibration data by taking the average value of the standard indication vibration data as a reference value includes: The alarm threshold is set to 2 times the reference value, and the danger threshold is set to 5 times the reference value.

5. The equipment failure prediction method according to claim 4, characterized in that: The preprocessing of the current vibration data includes: The current vibration data is calculated according to the time domain waveform or the spectrum diagram to form the current vibration indication data, and the current vibration indication data includes a vibration acceleration value, a vibration velocity value, a vibration displacement value, a bearing damage value, a broadband energy value and a narrowband energy value.

6. The equipment failure prediction method according to claim 5, characterized in that: The preprocessing of the current vibration data also includes: making a trend graph of the current vibration indication data according to the current vibration indication data.

7. The equipment failure prediction method according to claim 6, characterized in that: The method of predicting a fault of the equipment according to the vibration trend diagram of the equipment corresponding to the current vibration indication data includes: Conduct an overall analysis of the vibration trend graph corresponding to the current vibration indication data; If the corresponding trend graph shows that the working trend is stable and the working trend does not exceed the alarm threshold, it is determined that there is no abnormality in the equipment part corresponding to the current vibration indication data; If the corresponding trend graph shows an upward trend, and the trend rises and exceeds the alarm threshold line, it is determined that the equipment part corresponding to the current vibration indication data has hidden dangers.

8. The equipment failure prediction method according to claim 6, characterized in that: The method of predicting a fault of the equipment according to the vibration trend diagram of the equipment corresponding to the current vibration indication data also includes: Fault prediction of equipment is performed based on the time domain waveform or spectrum diagram corresponding to the current vibration indication data.

9. The equipment failure prediction method according to claim 1, characterized in that: The current vibration data of all preset measuring points in the press line equipment are collected, including: Vibration acceleration sensors are installed at preset measuring points in the collection and stamping line equipment, and the vibration acceleration sensors are used to perform real-time detection of the stamping line equipment.

10. A system for predicting equipment failures of a stamping line, characterized in that: include: A data collection module, which is used to collect current vibration data of all preset measurement points in the press line equipment; A data processing module, which is used to pre-process the vibration data set to form current vibration indication data and a trend diagram of the corresponding equipment; The data judgment module is used to make a preliminary judgment on the current vibration indication data according to the preset judgment criteria; wherein, If the current vibration indication data in the current vibration indication data set does not meet the preset judgment standard, the fault prediction of the equipment is performed according to the trend diagram of the equipment corresponding to the current vibration indication data.

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