Acquired data preprocessing method of engineering machinery, engineering machinery and storage medium
By determining the target data frequency range in construction machinery and performing data filtering and resampling, the problem of low data quality of engineering machinery acquisition is solved, high-quality sampling data acquisition is achieved, and structural design is optimized.
Patent Information
- Application Number
- CN202411665038.0
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-20
- Publication Date
- 2025-02-25
AI Technical Summary
Under harsh working environments and complex working conditions, tower cranes and other construction machinery lead to low quality of sampled data collected, which in turn affects the accuracy of structural design.
By determining the target focus data frequency range of the target engineering machinery, data acquisition is performed based on the preset acquisition frequency range, frequency domain data is obtained, and filtered according to the frequency retention range, and filtered to obtain the filtered frequency domain data. Then the filtered data is fitted to obtain the signal function to be sampled, and the data is resampled to obtain high-quality target sampled data.
The filtering of the data collected by the engineering machinery and the resampling of free frequency is realized, and a large amount of non-focused data is collected is avoided, and high-quality sampled data is obtained, thereby optimizing and improving the structural design of the engineering machinery.
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Figure CN119513496A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the technical field of data acquisition, and in particular to a method for preprocessing acquired data of an engineering machinery, the engineering machinery and a storage medium. Background Art
[0002] With the rapid development of mechanical manufacturing technology, construction machinery such as tower cranes are widely used in a variety of engineering construction scenarios. Usually, during the operation of construction machinery, data is collected through sensors, and the structural design of the construction machinery is analyzed based on the collected sampling data. High-quality sampling data can be used to optimize and improve the structural design of construction machinery and improve the operating efficiency of construction machinery.
[0003] The quality of sampling data is affected by multiple factors such as timeliness, environment, working conditions and loads. However, construction machinery such as tower cranes are usually in harsh working environments and complex working conditions, resulting in low quality of collected sampling data. Low-quality sampling data can easily lead to errors in data analysis, which in turn leads to over-design or errors in the design direction of construction machinery. In addition, it is easy to collect a large amount of non-concern data and / or a large amount of data that needs attention is not collected during the data collection process. Missing data will also lead to low quality of sampling data, which will affect the structural design of construction machinery. Summary of the invention
[0004] The purpose of the embodiments of the present application is to provide a method for preprocessing collected data of an engineering machinery, an engineering machinery and a storage medium. The method for preprocessing collected data of an engineering machinery is used to solve the problem of low quality of sampled data collected in the prior art.
[0005] In order to achieve the above-mentioned purpose, the first aspect of the present application provides a method for preprocessing collected data of an engineering machinery, and the method for preprocessing collected data of an engineering machinery comprises:
[0006] Determine the target attention data frequency range corresponding to the target engineering machinery;
[0007] Collecting data of the target engineering machinery based on a preset acquisition frequency range to obtain frequency domain data of the target engineering machinery;
[0008] According to the target attention data and the target attention data frequency range, a frequency retention range is obtained;
[0009] Filtering the frequency domain data according to the frequency retention range to obtain filtered frequency domain data;
[0010] Fitting the filtered frequency domain data to obtain the signal function to be sampled;
[0011] Resample the signal function to be sampled to obtain target sampling data.
[0012] In the embodiment of the present application, the frequency reservation range is obtained according to the preset attention data and the target attention data frequency range, including:
[0013] Determining a preset coefficient based on the type of preset data of interest;
[0014] A frequency reservation range is obtained according to the target attention data frequency range, the preset coefficient and the preset percentage, wherein the preset percentage is the percentage of the preset attention data in the frequency reservation range.
[0015] In the embodiment of the present application, the preset coefficient is determined based on the type of preset attention data, including:
[0016] In a case where the type of the preset attention data is frequency data, determining the preset coefficient as the first coefficient;
[0017] In a case where the type of preset attention data is amplitude data, the preset coefficient is determined as the second coefficient.
[0018] In an embodiment of the present application, data collection is performed on a target engineering machinery based on a preset collection frequency range to obtain frequency domain data of the target engineering machinery, including:
[0019] Collect data of the target engineering machinery based on a preset acquisition frequency range to obtain discrete time domain data;
[0020] Perform fast Fourier transform on discrete time domain data to obtain frequency domain data;
[0021] Fit the filtered frequency domain data to obtain the signal function to be sampled, including:
[0022] Perform inverse Fourier transform on the filtered frequency domain data to obtain the signal function to be sampled.
[0023] In an embodiment of the present application, the frequency domain data includes an amplitude-frequency component sequence and a phase-frequency component sequence;
[0024] According to the frequency retention range, the frequency domain data is filtered to obtain filtered frequency domain data, including:
[0025] Convert the frequency retention range into a component sequence retention range;
[0026] The amplitude-frequency component sequence and the phase-frequency component sequence are filtered based on the component sequence retention range to obtain filtered frequency domain data.
[0027] In an embodiment of the present application, the amplitude-frequency component sequence and the phase-frequency component sequence are filtered based on the component sequence retention range to obtain filtered frequency domain data, including:
[0028] The components outside the reserved range of the amplitude-frequency component sequence and the phase-frequency component sequence are set to zero respectively to obtain the filtered frequency domain data.
[0029] In an embodiment of the present application, determining the target attention data frequency range corresponding to the target engineering machinery includes:
[0030] Performing modal analysis on the entire target engineering machinery and the components of the target engineering machinery respectively to obtain the natural frequency of the target engineering machinery;
[0031] Determining the excitation frequency of the target engineering machinery based on the load excitation of the target engineering machinery;
[0032] According to the natural frequency and excitation frequency, the target data frequency range corresponding to the target engineering machinery is determined.
[0033] In an embodiment of the present application, data resampling is performed on the sampled signal function to obtain target sampled data, including:
[0034] The data collection duration is discretized based on the target collection frequency to obtain multiple sampling points, wherein the target collection frequency is any frequency in a preset collection frequency range;
[0035] The signal function to be sampled is resampled according to multiple sampling points to obtain target sampling data.
[0036] A second aspect of the present application provides an engineering machine, comprising:
[0037] a memory configured to store instructions;
[0038] The processor is configured to call instructions from the memory and implement the above-mentioned method for preprocessing collected data of the engineering machinery when executing the instructions.
[0039] A third aspect of the present application provides a machine-readable storage medium having instructions stored thereon, the instructions being used to enable a machine to execute the above-mentioned method for preprocessing collected data of engineering machinery.
[0040] The present application provides a method for preprocessing collected data of engineering machinery, including: determining the target attention data frequency range corresponding to the target engineering machinery; collecting data on the target engineering machinery based on the preset collection frequency range to obtain the frequency domain data of the target engineering machinery; obtaining the frequency retention range according to the target attention data and the target attention data frequency range; filtering the frequency domain data according to the frequency retention range to obtain filtered frequency domain data; fitting the filtered frequency domain data to obtain a signal function to be sampled; resampling the signal function to be sampled to obtain target sampling data. The data of the engineering machinery is filtered and preprocessed by the frequency retention range to achieve filtering of the collected data of the engineering machinery and resampling of the free frequency. The target sampling data obtained by resampling are all attention data, which avoids the situation of collecting a large amount of non-attention data, and can obtain high-quality sampling data, thereby optimizing and improving the structural design of the engineering machinery.
[0041] Other features and advantages of the embodiments of the present application will be described in detail in the subsequent specific implementation section. BRIEF DESCRIPTION OF THE DRAWINGS
[0042] The accompanying drawings are used to provide a further understanding of the embodiments of the present application and constitute a part of the specification. Together with the following specific implementations, they are used to explain the embodiments of the present application, but do not constitute a limitation on the embodiments of the present application. In the accompanying drawings:
[0043] Figure 1 A schematic diagram of a flow chart of a method for preprocessing collected data of an engineering machinery according to an embodiment of the present application is schematically shown;
[0044] Figure 2 An example diagram of a modal analysis diagram according to an embodiment of the present application is schematically shown;
[0045] Figure 3 An example diagram of an amplitude-frequency component according to an embodiment of the present application is schematically shown;
[0046] Figure 4 An exemplary diagram of a phase-frequency component according to an embodiment of the present application is schematically shown;
[0047] Figure 5 An example diagram of target sampling data according to an embodiment of the present application is schematically shown. DETAILED DESCRIPTION
[0048] In order to make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the technical scheme 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. It should be understood that the specific implementation methods described herein are only used to illustrate and explain the embodiments of the present application, and are not used to limit the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.
[0049] It should be noted that if directional indication is involved in the embodiments of the present application, the directional indication is only used to explain the relative position relationship, movement status, etc. between the components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly.
[0050] In addition, if there are descriptions involving "first", "second", etc. in the embodiments of the present application, the descriptions of "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or suggesting their relative importance or implicitly indicating the number of technical features indicated. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In addition, the technical solutions between the various embodiments can be combined with each other, but they must be based on the ability of ordinary technicians in the field to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such combination of technical solutions does not exist and is not within the scope of protection required by this application.
[0051] Figure 1 The following is a schematic diagram showing a flow chart of a method for preprocessing collected data of an engineering machine according to an embodiment of the present application. Figure 1 As shown, the embodiment of the present application provides a method for preprocessing collected data of an engineering machinery, and the method for preprocessing collected data of an engineering machinery comprises the following steps:
[0052] S110, determining a target attention data frequency range corresponding to the target engineering machinery.
[0053] Perform modal analysis on the engineering machinery, and then determine the target data frequency range corresponding to the target engineering machinery based on the forced vibration response of the engineering machinery. It should be understood that the target engineering machinery is the engineering machinery that needs to be collected for data and then fatigue damage analysis. The model and configuration of the engineering machinery are set according to actual needs and are not limited here. For ease of understanding, the target engineering machinery in the embodiment of the present application is a tower crane equipment with model number W6017.
[0054] In an embodiment of the present application, determining the target attention data frequency range corresponding to the target engineering machinery includes:
[0055] Performing modal analysis on the entire target engineering machinery and the components of the target engineering machinery respectively to obtain the natural frequency of the target engineering machinery;
[0056] Determining the excitation frequency of the target engineering machinery based on the load excitation of the target engineering machinery;
[0057] According to the natural frequency and excitation frequency, the target data frequency range corresponding to the target engineering machinery is determined.
[0058] See also Figure 2 , Figure 2 An example diagram of a modal analysis diagram according to an embodiment of the present application is schematically shown.
[0059] Modal analysis is performed on the whole machine and the components of the target engineering machinery respectively to obtain modal analysis diagrams. It should be understood that modal analysis can be performed only on key components of the engineering machinery, wherein key components are components with relatively large load-bearing capacity and components with relatively weak fatigue life.
[0060] As shown in the figure, different colors in the modal analysis diagram represent different stress levels of the construction machinery. Through the modal analysis diagram, the natural frequency of the vibration response of the target construction machinery is obtained. Based on the load excitation of the target construction machinery, the excitation frequency of the target construction machinery is determined. According to the mechanical forced vibration response, which is composed of the excitation frequency and the natural frequency, the target data frequency range corresponding to the target construction machinery can be determined.
[0061] S120, collecting data on the target engineering machinery based on a preset collection frequency range to obtain frequency domain data of the target engineering machinery.
[0062] Data collection is performed on the target engineering machinery based on the preset collection frequency range. Specifically, any target frequency is taken from the preset collection frequency range, and data collection is performed on the target engineering machinery based on the target frequency to obtain discrete time domain data, and the time domain data is converted into frequency domain data of the target engineering machinery. It should be understood that the preset collection frequency range is determined based on the target data frequency range, and the preset collection frequency range can be any value more than twice the target data frequency range, which will not be elaborated here.
[0063] S130, obtaining a frequency reservation range according to the target attention data and the target attention data frequency range.
[0064] In actual data collection scenarios, the collected data includes multiple types of data of interest. The type of target data of interest is set according to actual needs, which can be frequency data or signal amplitude data, and is not limited here. Different types of target data of interest will result in different frequency retention ranges. The frequency retention range is obtained based on the target data of interest and the frequency range of the target data of interest.
[0065] In the embodiment of the present application, the frequency reservation range is obtained according to the target attention data and the target attention data frequency range, including:
[0066] Determine the preset coefficient based on the type of target focus data;
[0067] A frequency reservation range is obtained according to the frequency range of the target attention data, the preset coefficient and the preset percentage, wherein the preset percentage is the percentage of the target attention data in the frequency reservation range.
[0068] Different types of target attention data will result in different frequency retention ranges. Predetermine the coefficients corresponding to different types of relationship information, and determine the type of target attention data that needs to be paid attention to in the actual data collection scenario of engineering machinery. Determine the preset coefficient based on the type of target attention data. At the same time, in order to ensure that the attention data accounts for a preset percentage of the filtered frequency domain data. According to the frequency range of the target attention data, the preset coefficient and the preset percentage, the frequency retention range is obtained.
[0069] In the embodiment of the present application, the preset coefficient is determined based on the type of target attention data, including:
[0070] In a case where the type of the target attention data is frequency data, determining the preset coefficient as the first coefficient;
[0071] In a case where the type of the target attention data is amplitude data, a preset coefficient is determined as the second coefficient.
[0072] For ease of understanding, in the embodiment of the present application, the frequency range of the target attention data is [f1, f2], the first preset coefficient is at least greater than 2, and the second preset coefficient is at least greater than 10. Based on the type of the target attention data, the preset coefficient is determined. Specifically, when the type of the target attention data is frequency data, it is determined that the frequency data needs to be paid attention to, and the preset coefficient is determined as the first coefficient. In order to accurately restore the continuous time signal, the frequency retention range is at least twice the frequency range of the target attention data, that is, the frequency retention range can be [2f1, 2f2].
[0073] In the case where the type of the target data of interest is amplitude data, it is determined that the signal amplitude data is needed, and the preset coefficient is determined as the second coefficient. In order to ensure that the amplitude distortion is small, the frequency retention range is at least 10 times the frequency range of the target data of interest, that is, the frequency retention range can be [10f1, 10f2]. It should be understood that the lower limit value of the frequency range of the target data of interest is usually close to zero. In the case where the type of the target data of interest is frequency data, the frequency retention range can be [0, 2f2]. In the case where the type of the target data of interest is amplitude data, the frequency retention range can be [0, 10f2].
[0074] For ease of understanding, in the embodiment of the present application, when the frequency range of the target attention data is [0.013, 0.231], the preset percentage is 95%, and the type of the target attention data is amplitude data, according to the frequency range of the target attention data, the preset coefficient and the preset percentage, the frequency retention range is obtained as follows:
[0075]
[0076] Among them, f low is the lower limit of the frequency reservation range, f hight It is the upper limit value of the frequency retention range, that is, the frequency retention range is [0.075, 2.365].
[0077] S140, filtering the frequency domain data according to the frequency retention range to obtain filtered frequency domain data.
[0078] The frequency domain data is filtered according to the frequency retention range. Specifically, since the data of interest and the excitation signal of the tower crane are usually distributed in low frequencies, the data outside the frequency retention range in the frequency domain data is filtered out to obtain the filtered frequency domain data.
[0079] S150, fitting the filtered frequency domain data to obtain a signal function to be sampled.
[0080] The filtered frequency domain data is the pre-processed data corresponding to the engineering machinery. Since the pre-processed data needs to be re-sampled, the filtered frequency domain data needs to be fitted to obtain the signal function to be sampled.
[0081] S160, re-sampling the signal function to be sampled to obtain target sampling data.
[0082] By resampling the data of the signal function to be sampled, the preprocessed data can be resampled to obtain the target sampling data. According to the frequency range required by the engineering machinery, the frequency retention range is determined. The data of the engineering machinery is filtered and preprocessed through the frequency retention range to achieve the filtering of the engineering machinery collected data and the resampling of the free frequency. The target sampling data obtained by resampling are all the data of interest, avoiding the situation of collecting a large amount of non-interest data, and can obtain high-quality sampling data, thereby optimizing and improving the structural design of the engineering machinery.
[0083] In an embodiment of the present application, data collection is performed on a target engineering machinery based on a preset collection frequency range to obtain frequency domain data of the target engineering machinery, including:
[0084] Collect data of the target engineering machinery based on a preset acquisition frequency range to obtain discrete time domain data;
[0085] Perform fast Fourier transform on discrete time domain data to obtain frequency domain data;
[0086] Fit the filtered frequency domain data to obtain the signal function to be sampled, including:
[0087] Perform inverse Fourier transform on the filtered frequency domain data to obtain the signal function to be sampled.
[0088] Based on the preset acquisition frequency range, data of the target engineering machinery is collected to obtain discrete time domain data. Before filtering, the discrete time domain data needs to be converted into frequency domain data. It should be understood that the data conversion algorithm is set according to actual needs, and Laplace transform and Fourier transform can be used, which are not limited here.
[0089] For ease of understanding, fast Fourier transform is used in the embodiments of the present application. Specifically, the discrete Fourier transform (DFT) formula is as follows:
[0090]
[0091] Among them, the amplitude-frequency component of the discrete Fourier transform is N is the total number of discrete time domain data, k is the sampling point during data acquisition, n is the nth amplitude-frequency component, and j is the imaginary part.
[0092] In order to improve the solution efficiency, the symmetry of discrete Fourier transform is used to derive the formula of fast Fourier transform (FFT) as follows:
[0093]
[0094] in, N is the total number of discrete time domain data, k is the sampling point during data acquisition, n is the nth amplitude-frequency component, X is the sequence of discrete time domain data, and N is the total number of amplitude-frequency components.
[0095] After obtaining the filtered frequency domain data, perform inverse Fourier transform on the filtered frequency domain data to obtain the signal function to be sampled:
[0096]
[0097] Wherein, X is the sequence of discrete time domain data, N is the total number of discrete time domain data, k is the sampling point during data acquisition, n is the nth amplitude-frequency component, and j is the imaginary part.
[0098] In an embodiment of the present application, the frequency domain data includes an amplitude-frequency component sequence and a phase-frequency component sequence;
[0099] According to the frequency retention range, the frequency domain data is filtered to obtain filtered frequency domain data, including:
[0100] Convert the frequency retention range into a component sequence retention range;
[0101] The amplitude-frequency component sequence and the phase-frequency component sequence are filtered based on the component sequence retention range to obtain filtered frequency domain data.
[0102] Frequency domain data includes an amplitude-frequency component sequence and a phase-frequency component sequence. For ease of understanding, the amplitude-frequency component sequence in the embodiment of the present application is [A0, A1, A2, ... A n ], where A n is the nth amplitude-frequency component. The phase-frequency component sequence is [H0, H1, H2, …H n ], where H n is the nth phase frequency component.
[0103] The frequency retention range is converted into a component sequence retention range. Based on the component sequence retention range, the amplitude frequency component sequence and the phase frequency component sequence are filtered respectively to obtain filtered frequency domain data.
[0104] In an embodiment of the present application, the amplitude-frequency component sequence and the phase-frequency component sequence are filtered based on the component sequence retention range to obtain filtered frequency domain data, including:
[0105] The components outside the reserved range of the amplitude-frequency component sequence and the phase-frequency component sequence are set to zero respectively to obtain the filtered frequency domain data.
[0106] See also Figure 3 , Figure 3 An example diagram of an amplitude-frequency component according to an embodiment of the present application is schematically shown.
[0107] See also Figure 4 , Figure 4 An example diagram of a phase-frequency component according to an embodiment of the present application is schematically shown.
[0108] For ease of understanding, in the embodiment of the present application, the component sequence retention range is [1, 48]. The components outside the component sequence retention range in the amplitude-frequency component sequence and the phase-frequency component sequence are set to zero respectively to obtain filtered frequency domain data.
[0109] The data with subscripts outside [1, 48] in the amplitude-frequency component sequence and the phase-frequency component sequence are set to zero, and the amplitude-frequency component sequence after filtering is obtained as [A0, A1, A2…A 48 …0, 0, 0], and the phase-frequency component sequence after filtering is [H0, H1, H2…H 48…0, 0, 0]. As shown in the figure, the red point data is the data to be filtered for the amplitude-frequency component sequence, and the blue point data is the filtered amplitude-frequency component sequence. It should be understood that since the amplitude-frequency component has been obtained, the signal function to be sampled after the inverse Fourier transform can be:
[0110]
[0111] Among them, x(t) is the signal function to be sampled, t is the time series, A n is the nth amplitude-frequency component, N is the total number of discrete time domain data, k is the sampling point during data acquisition, n is the nth amplitude-frequency component, and j is the imaginary part.
[0112] At the same time, since the collected data of the engineering machinery does not contain an imaginary part, the signal function to be sampled obtained after the inverse Fourier transform in this embodiment is:
[0113]
[0114] Among them, x(t) is the signal function to be sampled, t is the time series, A n is the nth amplitude-frequency component, H n is the nth phase-frequency component, and N is the total number of discrete time domain data.
[0115] In an embodiment of the present application, data resampling is performed on the sampled signal function to obtain target sampled data, including:
[0116] The data collection duration is discretized based on the target collection frequency to obtain multiple sampling points, wherein the target collection frequency is any frequency in a preset collection frequency range;
[0117] The signal function to be sampled is resampled according to multiple sampling points to obtain target sampling data.
[0118] See also Figure 5 , Figure 5 An example diagram of target sampling data according to an embodiment of the present application is schematically shown.
[0119] After obtaining the signal function to be sampled, the data collection duration can be discretized based on the target collection frequency according to actual needs to obtain multiple sampling points, where the target collection frequency is any frequency in the preset collection frequency range. Substitute multiple sampling points into the signal function to be sampled, and the data can be resampled to obtain the target sampling data corresponding to the target collection frequency. As shown in the figure, the horizontal axis is time and the vertical axis is load. The blue data curve is the frequency domain data of the target engineering machinery obtained by collecting data on the target engineering machinery based on the preset collection frequency range. The red curve data is the target sampling data obtained by resampling the signal function to be sampled according to multiple sampling points.
[0120] The present application provides a method for preprocessing collected data of engineering machinery, including: determining the target attention data frequency range corresponding to the target engineering machinery; collecting data on the target engineering machinery based on the preset collection frequency range to obtain the frequency domain data of the target engineering machinery; obtaining the frequency retention range according to the target attention data and the target attention data frequency range; filtering the frequency domain data according to the frequency retention range to obtain filtered frequency domain data; fitting the filtered frequency domain data to obtain a signal function to be sampled; resampling the signal function to be sampled to obtain target sampling data. The data of the engineering machinery is filtered and preprocessed by the frequency retention range to achieve filtering of the collected data of the engineering machinery and resampling of the free frequency. The target sampling data obtained by resampling are all attention data, which avoids the situation of collecting a large amount of non-attention data, and can obtain high-quality sampling data, thereby optimizing and improving the structural design of the engineering machinery.
[0121] The present application also provides an engineering machine, including:
[0122] a memory configured to store instructions;
[0123] The processor is configured to call instructions from the memory and implement the above-mentioned method for preprocessing collected data of the engineering machinery when executing the instructions.
[0124] The processor includes a kernel, which retrieves the corresponding program unit from the memory. One or more kernels can be set, and the problem of low quality of sampled data collected in the prior art can be solved by adjusting kernel parameters.
[0125] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one memory chip.
[0126] An embodiment of the present application also provides a machine-readable storage medium, on which instructions are stored, and the instructions are used to enable a machine to execute the above-mentioned method for preprocessing collected data of engineering machinery.
[0127] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.
[0128] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.
[0129] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.
[0130] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.
[0131] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.
[0132] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.
[0133] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.
[0134] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.
[0135] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.
Claims
1. A method for preprocessing collected data of engineering machinery, characterized in that: The engineering machinery data collection preprocessing method comprises: Determine the target attention data frequency range corresponding to the target engineering machinery; Collecting data of the target engineering machinery based on a preset acquisition frequency range to obtain frequency domain data of the target engineering machinery; Obtaining a frequency reservation range according to the target attention data and the frequency range of the target attention data; Filtering the frequency domain data according to the frequency retention range to obtain filtered frequency domain data; Fitting the filtered frequency domain data to obtain a signal function to be sampled; The signal function to be sampled is resampled to obtain target sampling data.
2. The method for preprocessing collected data of engineering machinery according to claim 1, characterized in that: The step of obtaining a frequency reservation range according to the preset attention data and the target attention data frequency range includes: Determining a preset coefficient based on the type of the preset data of interest; A frequency reservation range is obtained according to the target attention data frequency range, the preset coefficient and the preset percentage, wherein the preset percentage is the percentage of the preset attention data in the frequency reservation range.
3. The method for preprocessing collected data of engineering machinery according to claim 2, characterized in that: The step of determining a preset coefficient based on the type of the preset data of interest includes: In a case where the type of the preset attention data is frequency data, determining the preset coefficient as a first coefficient; In a case where the type of the preset attention data is amplitude data, the preset coefficient is determined as the second coefficient.
4. The method for preprocessing collected data of engineering machinery according to claim 1, characterized in that: The step of collecting data on the target engineering machinery based on a preset collection frequency range to obtain frequency domain data of the target engineering machinery includes: Collecting data on the target engineering machinery based on the preset acquisition frequency range to obtain discrete time domain data; Performing a fast Fourier transform on the discrete time domain data to obtain frequency domain data; The step of fitting the filtered frequency domain data to obtain a signal function to be sampled includes: Perform inverse Fourier transform on the filtered frequency domain data to obtain the signal function to be sampled.
5. The method for preprocessing collected data of engineering machinery according to claim 1, characterized in that: The frequency domain data includes an amplitude-frequency component sequence and a phase-frequency component sequence; The filtering the frequency domain data according to the frequency reservation range to obtain filtered frequency domain data includes: Converting the frequency retention range into a component sequence retention range; The amplitude-frequency component sequence and the phase-frequency component sequence are filtered based on the component sequence retention range to obtain filtered frequency domain data.
6. The method for preprocessing collected data of engineering machinery according to claim 5, characterized in that: The filtering of the amplitude-frequency component sequence and the phase-frequency component sequence based on the component sequence retention range to obtain filtered frequency domain data comprises: The components of the amplitude-frequency component sequence and the phase-frequency component sequence that are outside the reserved range of the component sequence are set to zero respectively, so as to obtain filtered frequency domain data.
7. The method for preprocessing collected data of engineering machinery according to claim 1, characterized in that: The step of determining the target attention data frequency range corresponding to the target engineering machinery includes: Performing modal analysis on the entire target engineering machinery and the components of the target engineering machinery respectively to obtain the natural frequency of the target engineering machinery; Determining an excitation frequency of the target engineering machinery based on the load excitation of the target engineering machinery; A target attention data frequency range corresponding to the target engineering machinery is determined according to the natural frequency and the excitation frequency.
8. The method for preprocessing collected data of engineering machinery according to claim 1, characterized in that: The step of resampling the signal function to be sampled to obtain target sampling data includes: Discretizing the data collection duration based on the target collection frequency to obtain a plurality of sampling points, wherein the target collection frequency is any frequency in the preset collection frequency range; The signal function to be sampled is resampled according to the multiple sampling points to obtain target sampling data.
9. An engineering machine, characterized in that: include: a memory configured to store instructions; The processor is configured to call the instruction from the memory and implement the collected data preprocessing method of the engineering machinery according to any one of claims 1 to 8 when executing the instruction.
10. A machine-readable storage medium, characterized in that: The machine-readable storage medium stores instructions, which are used to enable the machine to execute the collected data preprocessing method for engineering machinery according to any one of claims 1 to 8.