A time series data curve rendering method, system, device and computer medium
By generating denoising thresholds and tension limit thresholds to control the control points of the Bézier curve, the overshoot problem of the Bézier curve is solved, ensuring the accuracy and stability of the performance curve of industrial equipment and supporting accurate analysis of equipment performance.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- FOUNDER SECURITIES CO LTD
- Filing Date
- 2026-05-21
- Publication Date
- 2026-07-03
AI Technical Summary
Existing technologies are prone to overshoot when generating Bézier curves, especially when performance data exhibits local extrema, leading to misjudgments of industrial equipment performance.
By acquiring the denoising threshold and tension limit threshold, and generating the longitudinal difference based on the lateral sampling interval of the target device performance curve, the longitudinal difference is detected and the longitudinal and lateral values of the control point are controlled to avoid overshoot and ensure that the curve presents a stable state near the data point.
It avoids spurious trends and overshoots on the performance curves of industrial equipment, ensuring that the curves accurately reflect equipment performance and supporting accurate performance analysis.
Smart Images
Figure CN122336099A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the fields of computer graphics and data visualization technology, and more specifically, to a method, system, device, and computer medium for rendering time-series data curves. Background Technology
[0002] Currently, in applications such as industrial equipment monitoring, medical electrocardiograms, and financial securities software, in order to improve the user's visual experience, taking industrial equipment as an example, discrete performance sampling points of industrial equipment, such as temperature per second, can be connected by Bezier curves to form a smooth trend graph.
[0003] In the process of generating Bézier curves, control points can be calculated using cubic Bézier interpolation or monotonic cubic spline interpolation. However, when performance data exhibits local extrema, such as peaks or troughs, these algorithms often produce overshoot, resulting in the rendered curve having a higher highest point than the actual value or a lower lowest point than the actual value, thus making it impossible to evaluate the performance of industrial equipment.
[0004] In conclusion, how to avoid misjudging the performance of industrial equipment is a problem that urgently needs to be solved by those skilled in the art. Summary of the Invention
[0005] The purpose of this application is to provide a time-series data curve rendering method, which can, to some extent, solve the technical problem of how to avoid misjudging the performance of industrial equipment. This application also provides a time-series data curve rendering system, an electronic device, and a computer-readable storage medium.
[0006] To achieve the above objectives, this application provides the following technical solution: Firstly, a method for rendering time-series data curves is provided, including: Acquire time-series performance data of industrial equipment; Based on the performance time series data, determine the current performance data point to be rendered and the first performance data point in the adjacent order; A denoising threshold is obtained, which is generated based on the lateral sampling interval of the target device performance curve; Detect whether the first longitudinal difference is less than the denoising threshold, wherein the first longitudinal difference includes the longitudinal difference between the current performance data point and the first performance data point; In response to the first longitudinal difference being less than the denoising threshold, the longitudinal value of the first control point is set to the longitudinal value of the current performance data point, and the first control point is located between the current performance data point and the first performance data point; Based on the current performance data point, the first control point, and the first performance data point, generate a curve segment on the performance curve of the target device.
[0007] Preferably, before detecting whether the first longitudinal difference is less than the denoising threshold, the method further includes: Detect whether the current performance data point is a local extremum; If the current performance data point is a local extremum, then the vertical value of the first control point is set to the vertical value of the current performance data point; If the current performance data point is not a local extremum, then the step of detecting whether the first longitudinal difference is less than the denoising threshold is performed.
[0008] Preferably, after setting the vertical value of the first control point to the vertical value of the current performance data point, the method further includes: Half of the horizontal sampling interval is used as the horizontal offset. The horizontal value of the current performance data point is offset by the horizontal offset amount and then used as the horizontal value of the first control point.
[0009] Preferably, obtaining the denoising threshold includes: Determine the lateral sampling interval of the target device's performance curve; The first proportional value of the horizontal sampling interval is set as the noise reduction threshold.
[0010] Preferably, after detecting whether the first longitudinal difference is less than the denoising threshold, the method further includes: In response to the first longitudinal difference being greater than or equal to the denoising threshold, a tension limit threshold is obtained, which is generated based on the lateral sampling interval; Detect whether the first vertical difference is greater than the first horizontal difference, wherein the first horizontal difference includes the horizontal difference between the current performance data point and the first performance data point; In response to the first longitudinal difference being greater than the first transverse difference, the longitudinal value of the first control point is generated by using the first longitudinal difference as a reference and the offset of the transverse value of the first control point is controlled within the tension limit threshold.
[0011] Preferably, obtaining the tension limit threshold includes: Determine the lateral sampling interval of the target device's performance curve; The second proportional value of the lateral sampling interval is set as the tension limit threshold.
[0012] Preferably, after detecting whether the first longitudinal difference is greater than the first transverse difference, the method further includes: In response to the first longitudinal difference being less than or equal to the first transverse difference, the transverse and longitudinal values of the first control point are generated using the geometric similar triangle scaling method.
[0013] Secondly, a time-series data curve rendering system is provided, including: The performance data acquisition module is used to acquire time-series performance data of industrial equipment; The data point determination module is used to determine the current performance data point to be rendered and the first adjacent performance data point based on the performance time series data. A noise reduction threshold acquisition module is used to acquire a noise reduction threshold, which is generated based on the horizontal sampling interval of the target device performance curve; The longitudinal value detection module is used to detect whether the first longitudinal difference is less than the denoising threshold, wherein the first longitudinal difference includes the longitudinal difference between the current performance data point and the first performance data point; The first generation module is configured to, in response to the first longitudinal difference being less than the denoising threshold, set the longitudinal value of the first control point to the longitudinal value of the current performance data point, wherein the first control point is located between the current performance data point and the first performance data point; The curve rendering module is used to generate curve segments on the performance curve of the target device based on the current performance data point, the first control point, and the first performance data point.
[0014] Thirdly, an electronic device is provided, comprising: Memory, used to store computer programs; A processor, configured to implement the steps of any of the above-described time-series data curve rendering methods when executing the computer program.
[0015] Fourthly, a computer-readable storage medium is provided, wherein a computer program is stored therein, and when executed by a processor, the computer program implements the steps of any of the above-described time-series data curve rendering methods.
[0016] This application provides a time-series data curve rendering method, which involves acquiring time-series performance data of industrial equipment; determining the current performance data point to be rendered and the adjacent first performance data point based on the performance time-series data; acquiring a denoising threshold, which is generated according to the horizontal sampling interval of the target equipment performance curve; detecting whether a first vertical difference is less than the denoising threshold, the first vertical difference including the vertical difference between the current performance data point and the first performance data point; responding to the first vertical difference being less than the denoising threshold, setting the vertical value of a first control point to the vertical value of the current performance data point, the first control point being located between the current performance data point and the first performance data point; and generating a curve segment on the performance curve of the target equipment based on the current performance data point, the first control point, and the first performance data point. In this application, considering that the change in industrial equipment performance per unit time is proportional to the time interval, a denoising threshold is generated based on the horizontal sampling interval of the target equipment performance curve. This denoising threshold is then bound to the sampling time scale, ensuring it adapts to the performance changes of the target equipment. Thus, when the first vertical difference is less than the denoising threshold, the vertical value of the first control point can be forcibly anchored to the current performance data point. This makes the noise segment of the performance curve near the current performance data point appear stable, with the curve curvature approaching 0, eliminating spurious trends and overshoot. Accurate performance analysis can then be performed based on the industrial equipment's performance curve. The time-series data curve rendering system, electronic device, and computer-readable storage medium provided in this application also solve the corresponding technical problems. Attached Figure Description
[0017] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of this application. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.
[0018] Figure 1 A flowchart illustrating a time-series data curve rendering method provided in this application embodiment; Figure 2 An interactive schematic diagram for rendering temperature curves of industrial equipment; Figure 3 This is a schematic diagram of the structure of a time-series data curve rendering system provided in an embodiment of this application; Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application; Figure 5 This is another structural schematic diagram of an electronic device provided in an embodiment of this application. Detailed Implementation
[0019] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.
[0020] Please see Figure 1 , Figure 1 A flowchart of a time-series data curve rendering method provided in an embodiment of this application.
[0021] This application provides a method for rendering time-series data curves, which may include the following steps: Step S101: Obtain the performance time-series data of the industrial equipment.
[0022] In practical applications, the performance time-series data of industrial equipment can be obtained first. The performance time-series data includes timestamps and performance values, which can be temperature values, humidity values, pressure values, vibration values, etc.
[0023] Step S102: Based on the performance time series data, determine the current performance data point to be rendered and the first performance data point in the adjacent order.
[0024] In practical applications, drawing the performance curve of a target device essentially involves plotting adjacent performance data points in the performance time series data onto a curve. Therefore, it is necessary to determine the current performance data point to be rendered and the first adjacent performance data point based on the performance time series data. The first performance data point can be the first data point after the current performance data point in the performance time series data, or it can be the first data point before the current performance data point. The choice can be made flexibly according to the requirements of drawing the performance curve.
[0025] Step S103: Obtain the denoising threshold, which is generated based on the horizontal sampling interval of the target device performance curve.
[0026] In practical applications, the horizontal axis value of the performance curve is determined based on the timestamp, and the vertical axis value is determined based on the performance value. Considering that the performance changes of industrial equipment are constrained by physical laws, that is, the timestamp and the performance value satisfy specific physical constraints, the performance curve can be drawn according to these physical constraints. Based on this, a denoising threshold can be generated according to the horizontal sampling interval of the target equipment performance curve, so that the control points of the performance curve can be constrained in the subsequent application of this denoising threshold.
[0027] Step S104: Detect whether the first longitudinal difference is less than the denoising threshold. The first longitudinal difference includes the longitudinal difference between the current performance data point and the first performance data point.
[0028] Step S105: In response to the first longitudinal difference being less than the denoising threshold, the longitudinal value of the first control point is set to the longitudinal value of the current performance data point, and the first control point is located between the current performance data point and the first performance data point.
[0029] In practical applications, after generating the denoising threshold, a first vertical difference between the current performance data point and the first performance data point can be generated. This difference can be of the absolute value type. Then, it is checked whether the first vertical difference is less than the denoising threshold. If it is, the vertical value of the first control point is set to the vertical value of the current performance data point. This way, when adjacent data points show small changes, the tangent slope calculation can be ignored, and the ordinate of the first control point can be directly forced to match the current performance data point. This automatically smooths out small fluctuations into straight lines, thus automatically straightening out minor oscillations in the curve and achieving visual denoising. The first control point is located between the current performance data point and the first performance data point, and is used to connect the two performance data points to form a curve segment of the performance curve.
[0030] It should be noted that when the first performance data point is the first data point after the current performance data point in the performance time series data, the first control point is also the control point between the current performance data point and the first data point thereafter, and the generated curve segment is the curve segment between the current control point and the first data point thereafter. When the first performance data point is the first data point before the current performance data point, the first control point is also the control point between the current performance data point and the first data point before it, and the generated curve segment is the curve segment between the current control point and the first data point before it. In either case, the curve segment between two adjacent data points can be generated according to the scheme of this application.
[0031] In an exemplary embodiment, when the current performance data point is a local extremum, the drawn performance curve is prone to deviation. To avoid this, before detecting whether the first vertical difference is less than the denoising threshold, it is also possible to detect whether the current performance data point is a local extremum. This local extremum can be a local maximum or a local minimum. When the performance value of the current performance data point is greater than the performance values of the two adjacent performance data points, the current performance data point is a local maximum; when the performance value of the current performance data point is less than the performance values of the two adjacent performance data points, the current performance data point is a local minimum. In response to the current performance data point being a local extremum, the vertical value of the first control point is set to the vertical value of the current performance data point. In response to the current performance data point not being a local extremum, the step of detecting whether the first vertical difference is less than the denoising threshold is performed. In this way, it can be ensured that the rendered curve strictly wraps within the data extremum range, avoiding the phenomenon of artificially inflated data points in the rendered curve.
[0032] In the exemplary embodiment, the lateral value of the first control point can be flexibly set as needed. For example, after setting the vertical value of the first control point to the vertical value of the current performance data point, half the value of the lateral sampling interval can be used as the lateral offset. The lateral value of the current performance data point is offset by the lateral offset and then used as the lateral value of the first control point. Specifically, when the first performance data point is the preceding data point of the current performance data point, the lateral value of the current performance data point is subtracted from the lateral offset to obtain the lateral value of the first control point. When the first performance data point is the following data point of the current performance data point, the lateral value of the current performance data point is added to the lateral offset to obtain the lateral value of the first control point.
[0033] In an exemplary embodiment, during the process of obtaining the denoising threshold, the horizontal sampling interval of the target device performance curve can be determined first; then, the first proportional value of the horizontal sampling interval can be set as the denoising threshold. This first proportional value can be determined based on the performance change rate coefficient of the industrial equipment, or it can be set based on empirical values, such as 1 / 8, 1 / 7, etc.
[0034] In specific application scenarios, a fixed first proportional value may lead to distorted rendering curves and misjudgments in operation and maintenance. To address this issue, a baseline value for the first proportional value can be determined during the process of establishing it. Then, a state factor, historical fluctuation factor, and environmental compensation factor for the industrial equipment are generated. The state factor decreases progressively according to the startup, stable operation, and standby phases of the industrial equipment. The historical fluctuation factor quantifies the deviation of the current noise level from the equipment's baseline noise level and can be determined using the 3σ principle for industrial equipment. The environmental compensation factor compensates for the impact of ambient temperature on the performance of the industrial equipment and increases with rising temperature. Finally, the baseline value, state factor, historical fluctuation factor, and environmental compensation factor are multiplied to obtain the first proportional value. This approach allows for the generation of the first proportional value based on the dynamic characteristics of the industrial equipment under different operating states, the time-varying characteristics of noise, and the impact of ambient temperature on the equipment's performance. This improves the rationality of the first proportional value and enables accurate rendering of performance curves for performance analysis of the industrial equipment.
[0035] In an exemplary embodiment, when performance data changes drastically in a short period of time, such as a precipitous drop, the change in performance value is much greater than the horizontal time interval. In this case, if the performance curve is drawn based on the tangent slope algorithm, it is easy to cause the curve control point to deviate from the reasonable area, resulting in visual distortion, knotting, or looping phenomena. To address this issue, this application, after detecting whether the first vertical difference is less than the denoising threshold, obtains a tension limit threshold in response to the first vertical difference being greater than or equal to the denoising threshold. The tension limit threshold is generated based on the horizontal sampling interval. It then detects whether the first vertical difference is greater than the first horizontal difference, which includes the horizontal difference between the current performance data point and the first performance data point. In response to the first vertical difference being greater than the first horizontal difference, it indicates that the performance curve trend is becoming steeper, and conventional horizontal interpolation may cause curve distortion. In this case, the first vertical difference is used as a benchmark to generate the vertical value of the first control point through a reverse projection algorithm, and the offset of the horizontal value of the first control point is controlled within the tension limit threshold. That is, the position of the first control point is inferred based on the vertical change rate, and the offset of the first control point is limited to the tension limit threshold range, which can avoid curve rendering collapse problems under extreme trends such as jumps and sudden drops. Conversely, in response to the first vertical difference being less than or equal to the first horizontal difference, it indicates that the performance curve trend is flat, and the horizontal and vertical values of the first control point can be generated using the geometric similar triangle scaling method.
[0036] In specific application scenarios, during the process of obtaining the tension limit threshold, the lateral sampling interval of the target equipment performance curve can be determined; the second proportional value of the lateral sampling interval is set as the tension limit threshold. The second proportional value can be determined based on the performance change rate coefficient of the industrial equipment, or it can be set based on empirical values. For example, the first proportional value can be 1 / 3, 1 / 4, etc.
[0037] Step S106: Generate a curve segment on the performance curve of the target device based on the current performance data point, the first control point, and the first performance data point.
[0038] In practical applications, after determining the information of the first control point, a curve segment can be generated on the performance curve of the target device based on the current performance data point, the first control point, and the first performance data point. The curve segment can be generated using methods such as cubic Bezier interpolation or monotonic cubic spline interpolation.
[0039] This application provides a time-series data curve rendering method, which involves acquiring time-series performance data of industrial equipment; determining the current performance data point to be rendered and the adjacent first performance data point based on the performance time-series data; acquiring a denoising threshold, which is generated according to the horizontal sampling interval of the target equipment performance curve; detecting whether a first vertical difference is less than the denoising threshold, the first vertical difference including the vertical difference between the current performance data point and the first performance data point; responding to the first vertical difference being less than the denoising threshold, setting the vertical value of a first control point to the vertical value of the current performance data point, the first control point being located between the current performance data point and the first performance data point; and generating a curve segment on the performance curve of the target equipment based on the current performance data point, the first control point, and the first performance data point. In this application, considering that the change in the performance of industrial equipment per unit time is proportional to the time interval, a denoising threshold is generated based on the horizontal sampling interval of the target equipment performance curve. This denoising threshold is then bound to the sampling time scale, making the denoising threshold compatible with the performance change of the target equipment. In this way, when the first vertical difference is less than the denoising threshold, the vertical value of the first control point can be forcibly anchored to the current performance data point, so that the noise segment of the performance curve near the current performance data point presents a stable state, and the curve curvature approaches 0. There are no spurious trends or overshoot phenomena, and performance analysis can be accurately performed based on the performance curve of the industrial equipment.
[0040] To facilitate understanding of this application's solution, the rendering of temperature profiles for industrial equipment will be used as an example for illustration. Figure 2 As shown, the following processes may be included: Assume the temperature curve rendering engine iterates through the temperature time series data of the industrial equipment to time points T1, T2, and T3, with corresponding temperature values of 10.00, 10.01, and 10.00, respectively; The geometry calculation module detects that the horizontal sampling pixel distance Delta X from T1 to T2 on the canvas is 10px, so the noise reduction threshold IgnoreY is calculated to be 10 / 8 = 1.25; then |P T2.y -P T1.y |The corresponding pixel difference is less than IgnoreY, so there is no need to calculate complex curvature. The Y coordinate of the control point Q1 to the left of point T2 is directly locked to 10.01. The rendering engine, based on Q1, can draw lines on the canvas that appear to be visually smooth straight lines, eliminating jagged edges. Assuming the rendering engine continues to iterate and obtains time points T5 and T6, the temperature instantly jumps from 10.00 to 20.00. The geometric calculation module calculates the horizontal sampling pixel distance Delta X=10px and the vertical height difference Delta Y=200px. It also detects that T6 is not an extreme point. Assuming that the temperature value will continue to rise, the subsequent process continues. The geometry calculation module determines that |Delta Y|>|Delta X|, indicating a vertically dominant mode. Therefore, it abandons the conventional method of calculating control points by dividing them into equal parts laterally, as this method would cause the control points to be too far apart on the X-axis, resulting in an S-shaped distortion. Instead, it adopts a long-side priority strategy, using the change in the Y-axis as a benchmark to limit the X-axis offset of the control points to no more than the tension limit threshold. Assuming the tension limit threshold is 10 / 3, the X-axis offset of the control points can be limited to no more than 3.3px. The rendering engine can draw a strong, straight, and uninterrupted upward curve on the canvas based on the control points.
[0041] It should be noted that this embodiment only uses the temperature performance curve of industrial equipment as an example to illustrate the solution. When rendering curves for electrocardiograms and stock K-line charts, the same principle can be applied, which will not be elaborated here.
[0042] Please see Figure 3 , Figure 3 This is a schematic diagram of the structure of a time-series data curve rendering system provided in an embodiment of this application.
[0043] This application provides a time-series data curve rendering system, which may include: Performance data acquisition module 101 is used to acquire time-series performance data of industrial equipment; The data point determination module 102 is used to determine the current performance data point to be rendered and the first adjacent performance data point based on performance time series data. The noise reduction threshold acquisition module 103 is used to acquire the noise reduction threshold, which is generated based on the horizontal sampling interval of the target device performance curve. The longitudinal value detection module 104 is used to detect whether the first longitudinal difference is less than the noise reduction threshold. The first longitudinal difference includes the longitudinal difference between the current performance data point and the first performance data point. The first generation module 105 is configured to, in response to the first longitudinal difference being less than the denoising threshold, set the longitudinal value of the first control point to the longitudinal value of the current performance data point, wherein the first control point is located between the current performance data point and the first performance data point; The curve rendering module 106 is used to generate curve segments on the performance curve of the target device based on the current performance data point, the first control point, and the first performance data point.
[0044] The time-series data curve rendering system provided in this application embodiment may further include: The extreme point detection module is used to detect whether the current performance data point is a local extreme point before the longitudinal value detection module detects whether the first longitudinal difference is less than the noise reduction threshold. The second generation module is used to set the vertical value of the first control point to the vertical value of the current performance data point if the current performance data point is a local extremum; and to perform the step of detecting whether the first vertical difference is less than the denoising threshold if the current performance data point is not a local extremum.
[0045] This application provides a time-series data curve rendering system. After the first generation module sets the vertical value of the first control point to the vertical value of the current performance data point, it can also use half the horizontal sampling interval as the horizontal offset; and after shifting the horizontal value of the current performance data point by the horizontal offset, it can use it as the horizontal value of the first control point.
[0046] This application provides a time-series data curve rendering system, wherein the noise reduction threshold acquisition module may include: The lateral sampling interval determination unit is used to determine the lateral sampling interval of the target device performance curve; The denoising threshold acquisition unit is used to set the first proportional value of the horizontal sampling interval as the denoising threshold.
[0047] The time-series data curve rendering system provided in this application embodiment may further include: The tension limit threshold acquisition module is used to acquire the tension limit threshold after the longitudinal value detection module detects whether the first longitudinal difference is less than the denoising threshold. If the first longitudinal difference is greater than or equal to the denoising threshold, the tension limit threshold is acquired. The tension limit threshold is generated based on the lateral sampling interval. The horizontal value detection module is used to detect whether the first vertical difference is greater than the first horizontal difference, the first horizontal difference including the horizontal difference between the current performance data point and the first performance data point; The third generation module is used to generate the longitudinal value of the first control point based on the first longitudinal difference and the first lateral difference, and to control the offset of the lateral value of the first control point within the tension limit threshold, in response to the first longitudinal difference being greater than the first lateral difference.
[0048] This application provides a time-series data curve rendering system, wherein the tension limit threshold acquisition module may include: The lateral sampling interval determination unit is used to determine the lateral sampling interval of the target device performance curve; The tension limit threshold acquisition unit is used to set the second proportional value of the lateral sampling interval as the tension limit threshold.
[0049] The time-series data curve rendering system provided in this application embodiment may further include: The fourth generation module is used to generate the horizontal and vertical values of the first control point by means of the method of proportional geometric similar triangles after the horizontal value detection module detects whether the first vertical difference is greater than the first horizontal difference.
[0050] This application also provides an electronic device and a computer-readable storage medium, both of which have the corresponding effects of the time-series data curve rendering method provided in the embodiments of this application. Please refer to... Figure 4 , Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.
[0051] An electronic device provided in this application includes a memory 201 and a processor 202. The memory 201 stores a computer program, and the processor 202 executes the computer program to implement the steps of the timing data curve rendering method described in any of the above embodiments.
[0052] Please see Figure 5 Another electronic device provided in this application embodiment may further include: an input port 203 connected to the processor 202 for transmitting commands input from the outside to the processor 202; a display unit 204 connected to the processor 202 for displaying the processing results of the processor 202 to the outside; and a communication module 205 connected to the processor 202 for enabling communication between the electronic device and the outside. The display unit 204 may be a display panel, a laser scanning display, etc.; the communication method adopted by the communication module 205 includes, but is not limited to, Mobile High-Definition Link (MHL), Universal Serial Bus (USB), High-Definition Multimedia Interface (HDMI), wireless connection: Wireless Fidelity (WiFi), Bluetooth communication technology, Bluetooth Low Energy communication technology, and communication technology based on IEEE 802.11s.
[0053] This application provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it implements the steps of the timing data curve rendering method described in any of the above embodiments.
[0054] The computer-readable storage media involved in this application include random access memory (RAM), memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disks, removable disks, CD-ROMs (compact disc read-only memory), or any other form of storage media known in the art.
[0055] This application provides a computer program product, including a computer program / instruction, which, when executed by a processor, implements the steps of the timing data curve rendering method described in any of the above embodiments.
[0056] For descriptions of relevant parts in the time-series data curve rendering system, electronic device, and computer-readable storage medium provided in the embodiments of this application, please refer to the detailed descriptions of the corresponding parts in the time-series data curve rendering method provided in the embodiments of this application, which will not be repeated here. Furthermore, parts of the technical solutions provided in the embodiments of this application that are consistent with the implementation principles of corresponding technical solutions in the prior art have not been described in detail to avoid excessive elaboration.
[0057] It should also be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.
[0058] The above description of the disclosed embodiments enables those skilled in the art to make or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims
1. A method for rendering time-series data curves, characterized in that, include: Acquire time-series performance data of industrial equipment; Based on the performance time series data, determine the current performance data point to be rendered and the first performance data point in the adjacent order; A denoising threshold is obtained, which is generated based on the lateral sampling interval of the target device performance curve; Detect whether the first longitudinal difference is less than the denoising threshold, wherein the first longitudinal difference includes the longitudinal difference between the current performance data point and the first performance data point; In response to the first longitudinal difference being less than the denoising threshold, the longitudinal value of the first control point is set to the longitudinal value of the current performance data point, and the first control point is located between the current performance data point and the first performance data point; Based on the current performance data point, the first control point, and the first performance data point, generate a curve segment on the performance curve of the target device.
2. The method according to claim 1, characterized in that, Before detecting whether the first longitudinal difference is less than the denoising threshold, the method further includes: Detect whether the current performance data point is a local extremum; If the current performance data point is a local extremum, then the vertical value of the first control point is set to the vertical value of the current performance data point; If the current performance data point is not a local extremum, then the step of detecting whether the first longitudinal difference is less than the denoising threshold is performed.
3. The method according to claim 1, characterized in that, After setting the vertical value of the first control point to the vertical value of the current performance data point, the following steps are also included: Half of the horizontal sampling interval is used as the horizontal offset. The horizontal value of the current performance data point is offset by the horizontal offset amount and then used as the horizontal value of the first control point.
4. The method according to any one of claims 1 to 3, characterized in that, To obtain the denoising threshold, the following steps are taken: Determine the lateral sampling interval of the target device's performance curve; The first proportional value of the horizontal sampling interval is set as the noise reduction threshold.
5. The method according to claim 1, characterized in that, After detecting whether the first longitudinal difference is less than the denoising threshold, the method further includes: In response to the first longitudinal difference being greater than or equal to the denoising threshold, a tension limit threshold is obtained, which is generated based on the lateral sampling interval; Detect whether the first vertical difference is greater than the first horizontal difference, wherein the first horizontal difference includes the horizontal difference between the current performance data point and the first performance data point; In response to the first longitudinal difference being greater than the first transverse difference, the longitudinal value of the first control point is generated by using the first longitudinal difference as a reference and the offset of the transverse value of the first control point is controlled within the tension limit threshold.
6. The method according to claim 5, characterized in that, To obtain the tension limit threshold, the following steps are taken: Determine the lateral sampling interval of the target device's performance curve; The second proportional value of the lateral sampling interval is set as the tension limit threshold.
7. The method according to claim 5, characterized in that, After detecting whether the first longitudinal difference is greater than the first transverse difference, the method further includes: In response to the first longitudinal difference being less than or equal to the first transverse difference, the transverse and longitudinal values of the first control point are generated using the geometric similar triangle scaling method.
8. A time-series data curve rendering system, characterized in that, include: The performance data acquisition module is used to acquire time-series performance data of industrial equipment; The data point determination module is used to determine the current performance data point to be rendered and the first adjacent performance data point based on the performance time series data. A noise reduction threshold acquisition module is used to acquire a noise reduction threshold, which is generated based on the horizontal sampling interval of the target device performance curve; The longitudinal value detection module is used to detect whether the first longitudinal difference is less than the denoising threshold, wherein the first longitudinal difference includes the longitudinal difference between the current performance data point and the first performance data point; The first generation module is configured to, in response to the first longitudinal difference being less than the denoising threshold, set the longitudinal value of the first control point to the longitudinal value of the current performance data point, wherein the first control point is located between the current performance data point and the first performance data point; The curve rendering module is used to generate curve segments on the performance curve of the target device based on the current performance data point, the first control point, and the first performance data point.
9. An electronic device, characterized in that, include: Memory, used to store computer programs; A processor, configured to implement the steps of the timing data curve rendering method as described in any one of claims 1 to 7 when executing the computer program.
10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the steps of the time-series data curve rendering method as described in any one of claims 1 to 7.