State monitoring method and system for numerical control cutting equipment
Through dynamic sub-sequence segmentation and multi-dimensional abnormality screening mechanism, combined with adaptive data division and dual-threshold coordinated judgment, the problem of insufficient potential fault identification in CNC cutting equipment status monitoring is solved, accurate monitoring and active prediction and maintenance are achieved, and the stability and detection capabilities of the equipment are improved.
Patent Information
- Application Number
- CN202510587511.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-05-08
- Publication Date
- 2025-08-08
- Estimated Expiration
- Not applicable · inactive patent
AI Technical Summary
In the prior art, the status monitoring of CNC cutting equipment is often caused by the failure of the data to break through the critical value, resulting in the potential failure risk not being identified in time, and there is a lack of effective monitoring of potential failures.
Dynamic subsequence segmentation and multi-dimensional anomaly screening mechanism are adopted, combined with adaptive data division strategies and statistics-machine learning dual-mode screening, and through a dual-threshold collaborative judgment system, accurate monitoring and active prediction and maintenance of CNC cutting equipment status are achieved.
It significantly improves the accuracy of abnormal detection, reduces the false alarm rate, improves the detection ability of intermittent faults, shifts from passive alarm to active prediction and maintenance, and ensures the stable operation of CNC cutting equipment.
Smart Images
Figure CN120447470A_ABST
Abstract
Description
Technical Field
[0001] The present invention belongs to the technical field of cutting equipment management, and in particular relates to a state monitoring method and system for numerically controlled cutting equipment. Background Art
[0002] In recent years, with the development of artificial intelligence and big data technologies, the monitoring of CNC cutting equipment has gradually evolved towards intelligence, entering the stage of intelligent monitoring and predictive maintenance. Predictive maintenance is condition-based maintenance. Through continuous online condition monitoring and data analysis of equipment, it diagnoses and predicts the development trend of equipment failures, formulates predictive maintenance plans in advance, and implements inspections and repairs. Intelligent monitoring systems use different types of sensors, such as temperature, pressure, vibration, and ultrasound, to obtain various operating status information of the equipment. Through the collaborative operation and functional complementarity of multi-sensor data, more accurate condition monitoring is achieved. At the same time, fault diagnosis methods such as time-domain signal diagnosis, frequency-domain signal diagnosis, and comprehensive diagnosis using artificial neural networks and expert systems provide guidance for equipment condition prediction and maintenance decisions.
[0003] However, when monitoring the status of CNC cutting equipment in the existing technology, no warning is often given because the data does not exceed the critical value. In fact, the CNC cutting equipment may have potential failure risks at this time, and the existing technology cannot monitor the potential failure risks well. Summary of the Invention
[0004] The present invention provides a state monitoring method and system for numerical control cutting equipment, which are used to solve the technical problem that the state of existing numerical control cutting equipment may be misreported.
[0005] In a first aspect, the present invention provides a condition monitoring method for a CNC cutting device, comprising:
[0006] Acquire at least one piece of operating status data within a preset time period, and sort the at least one piece of operating status data based on chronological order to obtain an operating status data sequence;
[0007] Segmenting the operating status data sequence according to a preset data segmentation strategy to obtain at least one operating status data subsequence, and selecting each operating status data in the at least one operating status data subsequence according to a preset data screening strategy to obtain abnormal operating status data corresponding to the at least one operating status data subsequence;
[0008] Determine whether each abnormal operation status data is greater than a first preset threshold;
[0009] If each abnormal operating status data is not greater than a first preset threshold, determining first abnormal operating status data and second abnormal operating status data from the each abnormal operating status data, defining an operating status data subsequence corresponding to the first abnormal operating status data as a first operating status data subsequence, and defining an operating status data subsequence corresponding to the second abnormal operating status data as a second operating status data subsequence;
[0010] Sliding a preset sliding window over the aligned first operating status data subsequence and the second operating status data subsequence, and determining whether the number of differences between the first operating status data and the second operating status data in the sliding window that exceeds a second preset threshold during each sliding operation is greater than a preset number threshold;
[0011] If the number is not greater than the preset threshold, the state of the numerically controlled cutting device within a preset time period is determined according to the first operating status data subsequence and the second operating status data subsequence.
[0012] In a second aspect, the present invention provides a condition monitoring system for a CNC cutting device, comprising:
[0013] an acquisition module configured to acquire at least one piece of operating status data within a preset time period, and sort the at least one piece of operating status data based on chronological order to obtain an operating status data sequence;
[0014] a processing module configured to segment the operating status data sequence according to a preset data segmentation strategy to obtain at least one operating status data subsequence, and select each operating status data in the at least one operating status data subsequence according to a preset data screening strategy to obtain abnormal operating status data corresponding to the at least one operating status data subsequence;
[0015] A first judgment module is configured to judge whether each abnormal operation status data is greater than a first preset threshold;
[0016] a selection module configured to, if each abnormal operating status data is not greater than a first preset threshold, determine first abnormal operating status data and second abnormal operating status data from the each abnormal operating status data, define a subsequence of operating status data corresponding to the first abnormal operating status data as a first operating status data subsequence, and define a subsequence of operating status data corresponding to the second abnormal operating status data as a second operating status data subsequence;
[0017] a second judgment module configured to slide on the aligned first operating status data subsequence and the second operating status data subsequence based on a preset sliding window, and determine whether the number of differences between the first operating status data and the second operating status data in the sliding window that exceeds a second preset threshold during each sliding is greater than a preset number threshold;
[0018] The determination module is configured to determine the state of the CNC cutting device within a preset time period according to the first operating status data subsequence and the second operating status data subsequence if the number is not greater than a preset number threshold.
[0019] In a third aspect, an electronic device is provided, comprising: at least one processor, and a memory communicatively connected to the at least one processor, wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the steps of the condition monitoring method for CNC cutting equipment of any embodiment of the present invention.
[0020] In a fourth aspect, the present invention further provides a computer-readable storage medium having a computer program stored thereon, wherein when the program instructions are executed by a processor, the processor executes the steps of the condition monitoring method for CNC cutting equipment of any embodiment of the present invention.
[0021] The state monitoring method and system for CNC cutting equipment of the present application realize accurate monitoring and active predictive maintenance of the state of CNC cutting equipment through dynamic subsequence segmentation and multi-dimensional anomaly screening mechanism. The scheme adopts an adaptive data partitioning strategy combined with statistical-machine learning dual-mode screening, which significantly improves the accuracy of anomaly detection and reduces the false alarm rate. At the same time, a dual-threshold collaborative judgment system is adopted, and a two-level filtering mechanism is used to achieve more accurate fault identification, especially the detection capability of intermittent faults is greatly improved, realizing the transition from passive alarm to active predictive maintenance, and providing a strong guarantee for the stable operation of CNC cutting equipment. BRIEF DESCRIPTION OF THE DRAWINGS
[0022] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following is a brief introduction to the drawings required for use in the description of the embodiments. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.
[0023] Figure 1 A flow chart of a method for monitoring the state of a numerically controlled cutting device provided in one embodiment of the present invention;
[0024] Figure 2A structural block diagram of a condition monitoring system for CNC cutting equipment provided by one embodiment of the present invention;
[0025] Figure 3 It is a structural diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION
[0026] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.
[0027] See also Figure 1 , which shows a flow chart of a condition monitoring method for CNC cutting equipment of the present application.
[0028] like Figure 1 As shown, the condition monitoring method for CNC cutting equipment specifically includes the following steps:
[0029] Step S101 : obtaining at least one piece of operating status data within a preset time period, and sorting the at least one piece of operating status data based on chronological order to obtain an operating status data sequence.
[0030] Step S102: segment the operating status data sequence according to a preset data partitioning strategy to obtain at least one operating status data subsequence, and select each operating status data in the at least one operating status data subsequence according to a preset data screening strategy to obtain abnormal operating status data corresponding to the at least one operating status data subsequence.
[0031] In this step, the operating status data sequence is divided into equal parts based on a preset number of equal parts to obtain at least one operating status data subsequence. The operating status data with the largest value in each operating status data subsequence is then selected and defined as abnormal operating status data, thereby obtaining abnormal operating status data corresponding to the at least one operating status data subsequence.
[0032] Step S103: determine whether each abnormal operation status data is greater than a first preset threshold.
[0033] In a specific embodiment, after determining whether each abnormal operation status data is greater than a first preset threshold, if a certain abnormal operation status data is greater than the first preset threshold, it is directly determined that the state of the CNC cutting equipment within the preset time period is abnormal.
[0034] Step S104: If each abnormal operating status data is not greater than the first preset threshold, first abnormal operating status data and second abnormal operating status data are determined in the each abnormal operating status data, and the operating status data subsequence corresponding to the first abnormal operating status data is defined as a first operating status data subsequence, and the operating status data subsequence corresponding to the second abnormal operating status data is defined as a second operating status data subsequence.
[0035] In this step, the difference between any two abnormal operating status data among the abnormal operating status data is calculated, and two abnormal operating status data corresponding to the maximum difference are selected and defined as the first abnormal operating status data and the second abnormal operating status data respectively.
[0036] Step S105: Slide the aligned first operating status data subsequence and the second operating status data subsequence based on a preset sliding window, and determine whether the number of differences between the first operating status data and the second operating status data in the sliding window that is greater than a second preset threshold during each sliding is greater than a preset number threshold.
[0037] In a specific embodiment, after determining whether the difference between the first operating status data and the second operating status data in the sliding window is greater than a second preset threshold value each time it slides, if it is greater than the preset threshold value, it is directly determined that the state of the CNC cutting equipment within the preset time period is abnormal.
[0038] Step S106: If the number is not greater than the preset threshold, determining the state of the numerically controlled cutting device within a preset time period according to the first operating status data subsequence and the second operating status data subsequence.
[0039] In this step, the first difference in the first operating status data subsequence and the second difference in the second operating status data subsequence are obtained, and it is determined whether the first difference and the second difference are greater than a second preset threshold; if both the first difference and the second difference are not greater than the second preset threshold, it is determined that the state of the CNC cutting equipment within the preset time period is normal; if the first difference or the second difference is greater than the second preset threshold, it is determined that the state of the CNC cutting equipment within the preset time period is abnormal.
[0040] In summary, the method of the present application realizes accurate monitoring and active predictive maintenance of the status of CNC cutting equipment through dynamic subsequence segmentation and multi-dimensional anomaly screening mechanism. The scheme adopts an adaptive data partitioning strategy combined with statistical-machine learning dual-mode screening, which significantly improves the accuracy of anomaly detection and reduces the false alarm rate. At the same time, a dual-threshold collaborative judgment system is adopted, and a two-level filtering mechanism is used to achieve more accurate fault identification, especially the detection capability of intermittent faults is greatly improved, realizing the transition from passive alarm to active predictive maintenance, and providing a strong guarantee for the stable operation of CNC cutting equipment.
[0041] See also Figure 2 , which shows a structural block diagram of a condition monitoring system for CNC cutting equipment of the present application.
[0042] like Figure 2 As shown, the state monitoring system 200 includes an acquisition module 210 , a processing module 220 , a first judgment module 230 , a selection module 240 , a second judgment module 250 and a determination module 260 .
[0043] Among them, the acquisition module 210 is configured to acquire at least one operating status data within a preset time period, and sort the at least one operating status data based on the chronological order to obtain an operating status data sequence; the processing module 220 is configured to divide the operating status data sequence according to a preset data partitioning strategy to obtain at least one operating status data subsequence, and select each operating status data in the at least one operating status data subsequence according to a preset data screening strategy to obtain abnormal operating status data corresponding to the at least one operating status data subsequence; the first judgment module 230 is configured to judge whether each abnormal operating status data is greater than a first preset threshold value; the selection module 240 is configured to determine the first abnormal operating status data in the each abnormal operating status data if the each abnormal operating status data is not greater than the first preset threshold value. state data and second abnormal operation state data, and defining the operation state data subsequence corresponding to the first abnormal operation state data as a first operation state data subsequence, and defining the operation state data subsequence corresponding to the second abnormal operation state data as a second operation state data subsequence; a second judgment module 250 is configured to slide on the aligned first operation state data subsequence and the second operation state data subsequence based on a preset sliding window, and judge whether the number of differences between the first operation state data and the second operation state data in the sliding window during each sliding is greater than a second preset threshold; a determination module 260 is configured to determine the state of the CNC cutting equipment within a preset time period based on the first operation state data subsequence and the second operation state data subsequence if it is not greater than the preset threshold.
[0044] It should be understood that Figure 2 Modules and references documented in Figure 1 Therefore, the operations and features described above for the method and the corresponding technical effects also apply to Figure 2 The modules in it will not be described in detail here.
[0045] In other embodiments, embodiments of the present invention further provide a computer-readable storage medium having a computer program stored thereon, wherein when the program instructions are executed by a processor, the processor is caused to execute the condition monitoring method for CNC cutting equipment in any of the above method embodiments;
[0046] As an embodiment, the computer-readable storage medium of the present invention stores computer-executable instructions, and the computer-executable instructions are configured as follows:
[0047] Acquire at least one piece of operating status data within a preset time period, and sort the at least one piece of operating status data based on chronological order to obtain an operating status data sequence;
[0048] Segmenting the operating status data sequence according to a preset data segmentation strategy to obtain at least one operating status data subsequence, and selecting each operating status data in the at least one operating status data subsequence according to a preset data screening strategy to obtain abnormal operating status data corresponding to the at least one operating status data subsequence;
[0049] Determine whether each abnormal operation status data is greater than a first preset threshold;
[0050] If each abnormal operating status data is not greater than a first preset threshold, determining first abnormal operating status data and second abnormal operating status data from the each abnormal operating status data, defining an operating status data subsequence corresponding to the first abnormal operating status data as a first operating status data subsequence, and defining an operating status data subsequence corresponding to the second abnormal operating status data as a second operating status data subsequence;
[0051] Sliding a preset sliding window over the aligned first operating status data subsequence and the second operating status data subsequence, and determining whether the number of differences between the first operating status data and the second operating status data in the sliding window that exceeds a second preset threshold during each sliding operation is greater than a preset number threshold;
[0052] If the number is not greater than the preset threshold, the state of the numerically controlled cutting device within a preset time period is determined according to the first operating status data subsequence and the second operating status data subsequence.
[0053] The computer-readable storage medium may include a program storage area and a data storage area, wherein the program storage area may store an operating system and application programs required for at least one function; the data storage area may store data created based on the use of the condition monitoring system for CNC cutting equipment, etc. In addition, the computer-readable storage medium may include high-speed random access memory and may also include a memory, such as at least one disk storage device, flash memory device, or other non-volatile solid-state memory device. In some embodiments, the computer-readable storage medium may optionally include a memory remotely located relative to the processor, and these remote memories may be connected to the condition monitoring system for CNC cutting equipment via a network. Examples of the aforementioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.
[0054] Figure 3 Schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. Figure 3 As shown, the device includes: a processor 310 and a memory 320. The electronic device may also include: an input device 330 and an output device 340. The processor 310, the memory 320, the input device 330 and the output device 340 may be connected via a bus or other means. Figure 3 The example of the bus connection is taken as an example. The memory 320 is the computer-readable storage medium mentioned above. The processor 310 executes various functional applications and data processing of the server by running the non-volatile software programs, instructions and modules stored in the memory 320, that is, implements the above-mentioned method embodiment for the state monitoring method of CNC cutting equipment. The input device 330 can receive input digital or character information, and generate key signal input related to user settings and function control of the state monitoring system for CNC cutting equipment. The output device 340 may include a display device such as a display screen.
[0055] The electronic device can execute the method provided by the embodiment of the present invention, and has the functional modules and beneficial effects corresponding to the execution method. For technical details not fully described in this embodiment, please refer to the method provided by the embodiment of the present invention.
[0056] As an embodiment, the electronic device is applied to a condition monitoring system for CNC cutting equipment, and is used for a client, and includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to:
[0057] Acquire at least one piece of operating status data within a preset time period, and sort the at least one piece of operating status data based on chronological order to obtain an operating status data sequence;
[0058] Segmenting the operating status data sequence according to a preset data segmentation strategy to obtain at least one operating status data subsequence, and selecting each operating status data in the at least one operating status data subsequence according to a preset data screening strategy to obtain abnormal operating status data corresponding to the at least one operating status data subsequence;
[0059] Determine whether each abnormal operation status data is greater than a first preset threshold;
[0060] If each abnormal operating status data is not greater than a first preset threshold, determining first abnormal operating status data and second abnormal operating status data from the each abnormal operating status data, defining an operating status data subsequence corresponding to the first abnormal operating status data as a first operating status data subsequence, and defining an operating status data subsequence corresponding to the second abnormal operating status data as a second operating status data subsequence;
[0061] Sliding a preset sliding window over the aligned first operating status data subsequence and the second operating status data subsequence, and determining whether the number of differences between the first operating status data and the second operating status data in the sliding window that exceeds a second preset threshold during each sliding operation is greater than a preset number threshold;
[0062] If the number is not greater than the preset threshold, the state of the numerically controlled cutting device within a preset time period is determined according to the first operating status data subsequence and the second operating status data subsequence.
[0063] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus the necessary general hardware platform, or of course, by hardware. Based on this understanding, the essence of the above technical solution or the part that contributes to the existing technology can be embodied in the form of a software product. The computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods of each embodiment or certain parts of the embodiment.
[0064] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.
Claims
1. A method for monitoring the condition of a CNC cutting device, characterized in that: include: Acquire at least one piece of operating status data within a preset time period, and sort the at least one piece of operating status data based on chronological order to obtain an operating status data sequence; Segmenting the operating status data sequence according to a preset data segmentation strategy to obtain at least one operating status data subsequence, and selecting each operating status data in the at least one operating status data subsequence according to a preset data screening strategy to obtain abnormal operating status data corresponding to the at least one operating status data subsequence; Determine whether each abnormal operation status data is greater than a first preset threshold; If each abnormal operating status data is not greater than a first preset threshold, determining first abnormal operating status data and second abnormal operating status data from the each abnormal operating status data, defining an operating status data subsequence corresponding to the first abnormal operating status data as a first operating status data subsequence, and defining an operating status data subsequence corresponding to the second abnormal operating status data as a second operating status data subsequence; Sliding a preset sliding window over the aligned first operating status data subsequence and the second operating status data subsequence, and determining whether the number of differences between the first operating status data and the second operating status data in the sliding window that exceeds a second preset threshold during each sliding operation is greater than a preset number threshold; If the number is not greater than the preset threshold, the state of the numerically controlled cutting device within a preset time period is determined according to the first operating status data subsequence and the second operating status data subsequence.
2. A method for monitoring the state of a CNC cutting device according to claim 1, characterized in that: The step of dividing the running status data sequence according to a preset data division strategy to obtain at least one running status data subsequence comprises: The running status data sequence is divided based on a preset equal division to obtain at least one running status data subsequence.
3. A method for monitoring the state of a CNC cutting device according to claim 1, characterized in that: The selecting each operating status data in the at least one operating status data subsequence according to a preset data screening strategy to obtain abnormal operating status data corresponding to the at least one operating status data subsequence includes: The operating status data with the largest value is selected from each operating status data subsequence and defined as abnormal operating status data, that is, the abnormal operating status data corresponding to the at least one operating status data subsequence is obtained.
4. A method for monitoring the state of a CNC cutting device according to claim 1, characterized in that: After determining whether each abnormal operating state data is greater than a first preset threshold, the method further includes: If a certain abnormal operation status data is greater than a first preset threshold, it is directly determined that the state of the CNC cutting equipment within the preset time period is abnormal.
5. The method for monitoring the state of a CNC cutting device according to claim 1, wherein: Determining the first abnormal operation state data and the second abnormal operation state data from the respective abnormal operation state data includes: The difference between any two abnormal operating status data among the abnormal operating status data is calculated, and two abnormal operating status data corresponding to the maximum difference are selected and defined as the first abnormal operating status data and the second abnormal operating status data, respectively.
6. A method for monitoring the condition of a CNC cutting device according to claim 1, characterized in that: After determining whether the number of differences between the first operating status data and the second operating status data in the sliding window during each sliding operation is greater than a second preset threshold, the method further includes: If the number is greater than a preset threshold, it is directly determined that the state of the CNC cutting equipment is abnormal within a preset time period.
7. A method for monitoring the state of a CNC cutting device according to claim 1, characterized in that: Determining the state of the numerically controlled cutting device within a preset time period according to the first operating state data subsequence and the second operating state data subsequence includes: Obtaining a first difference value in the first operating status data subsequence and a second difference value in the second operating status data subsequence, and determining whether the first difference value and the second difference value are greater than a second preset threshold value; If both the first difference and the second difference are not greater than a second preset threshold, determining that the state of the CNC cutting device is normal within the preset time period; If the first difference or the second difference is greater than a second preset threshold, it is determined that the state of the numerical control cutting device within the preset time period is abnormal.
8. A condition monitoring system for CNC cutting equipment, characterized in that: include: an acquisition module configured to acquire at least one piece of operating status data within a preset time period, and sort the at least one piece of operating status data based on chronological order to obtain an operating status data sequence; a processing module configured to segment the operating status data sequence according to a preset data segmentation strategy to obtain at least one operating status data subsequence, and select each operating status data in the at least one operating status data subsequence according to a preset data screening strategy to obtain abnormal operating status data corresponding to the at least one operating status data subsequence; A first judgment module is configured to judge whether each abnormal operation status data is greater than a first preset threshold; a selection module configured to, if each abnormal operating status data is not greater than a first preset threshold, determine first abnormal operating status data and second abnormal operating status data from the each abnormal operating status data, define a subsequence of operating status data corresponding to the first abnormal operating status data as a first operating status data subsequence, and define a subsequence of operating status data corresponding to the second abnormal operating status data as a second operating status data subsequence; a second judgment module configured to slide on the aligned first operating status data subsequence and the second operating status data subsequence based on a preset sliding window, and determine whether the number of differences between the first operating status data and the second operating status data in the sliding window that exceeds a second preset threshold during each sliding is greater than a preset number threshold; The determination module is configured to determine the state of the CNC cutting device within a preset time period according to the first operating status data subsequence and the second operating status data subsequence if the number is not greater than a preset number threshold.
9. An electronic device, characterized in that: include: At least one processor, and a memory communicatively connected to the at least one processor, wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 7.
10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.