CN113297943B - Equipment auxiliary control technology based on mixed reality - Google Patents
Equipment auxiliary control technology based on mixed reality Download PDFInfo
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- CN113297943B CN113297943B CN202110541479.XA CN202110541479A CN113297943B CN 113297943 B CN113297943 B CN 113297943B CN 202110541479 A CN202110541479 A CN 202110541479A CN 113297943 B CN113297943 B CN 113297943B
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2218/00—Aspects of pattern recognition specially adapted for signal processing
- G06F2218/08—Feature extraction
- G06F2218/10—Feature extraction by analysing the shape of a waveform, e.g. extracting parameters relating to peaks
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Abstract
The invention relates to an equipment auxiliary control technology based on mixed reality, which belongs to the field of equipment auxiliary control and comprises the steps of obtaining a preset waveform image and a real-time waveform image; judging whether a wave crest or a wave trough appears in the real-time waveform image at the current time point; if so, analyzing and calculating the wave crests and the wave troughs at the corresponding positions in the preset waveform image and the real-time waveform image to obtain a calculation result; the calculation result comprises a similarity value and a difference value to be measured between the two images; calculating a deviation value according to the similarity value; acquiring a preset fluctuation range value, judging whether the difference value to be detected at each position falls within the fluctuation range value or not and outputting a first judgment result; if the first judgment result is yes, judging whether the difference value to be detected is smaller than the deviation value, if so, indicating that the real-time waveform image at the current time is stable, and outputting the judgment result. The invention has the effect of improving the detection stability of the equipment.
Description
Technical Field
The application relates to the field of auxiliary control of equipment, in particular to an auxiliary control technology of equipment based on mixed reality.
Background
Mixed Reality (MR) is a further development of virtual reality technology, which builds an interactive feedback information loop among the real world, the virtual world and the user by presenting virtual scene information in a real scene to enhance the sense of reality experienced by the user; at present, the mixed reality technology is widely applied in various fields, wherein the mixed reality technology is also applied in the field of auxiliary control of equipment.
In the process of using some detection equipment, in order to avoid misoperation, a mixed reality technology can be used for operating on a pre-constructed virtual detection equipment model, and the real detection equipment is used for operating after the operation is skillful; during operation of the apparatus, the apparatus outputs a resultant waveform image which is a two-dimensional coordinate image having time as a horizontal axis and a correlation amount as a vertical axis, the waveform image representing a detection result of the detection apparatus.
With respect to the related art in the above, the inventors found that: when the equipment is used for operation, the waveform image output by the equipment represents a detection result, and sometimes, because the waveform image cannot be detected, when the waveform image has errors, the waveform image cannot be checked in time, so that the detection result may have errors, the detection of the equipment is inaccurate, and the detection stability is low.
Disclosure of Invention
The application provides an equipment auxiliary control technique based on mixed reality has the characteristics that the detection stability of equipment has been improved.
The application aims to provide an auxiliary control method of equipment based on mixed reality.
The above object of the present application is achieved by the following technical solutions:
a mixed reality-based equipment auxiliary control method comprises the following steps:
acquiring a preset waveform image and a real-time waveform image;
judging whether a wave crest or a wave trough appears in the real-time waveform image at the current time point;
when a peak or trough occurs:
obtaining a calculation result by analyzing and calculating the wave crest and the wave trough at the corresponding positions in the preset waveform image and the real-time waveform image;
the calculation result comprises a similarity value and a difference value to be measured between the real-time waveform image and a preset waveform image;
the difference value to be measured is the difference value between the time point of the real-time wave peak or the real-time wave trough in the real-time waveform image of the current time point and the time point of the preset wave peak or the preset wave trough at the corresponding position in the preset waveform image;
calculating a deviation value according to the similarity value;
acquiring a preset fluctuation range value, judging whether the difference value to be detected at each position falls within the fluctuation range value or not and outputting a first judgment result;
if the first judgment result is yes, judging whether the difference value to be detected is smaller than the deviation value, if so, indicating that the real-time waveform image at the current time is stable, and outputting the judgment result.
By adopting the technical scheme, firstly, starting from the detection of a real-time waveform image, when a peak or a trough appears in the real-time waveform image at the current time point, the real-time waveform image is compared with a preset waveform image, the time point calculation is carried out on the peak and the trough at the corresponding positions in the two images, the similarity of the two images and the difference value to be detected at each position are obtained, at the moment, whether the difference value to be detected falls within a fluctuation range value needs to be judged, because when the waveform image is output, some fluctuation may be generated in the real-time waveform image due to some conditions, and the generated fluctuation is stated to be normal fluctuation as long as the fluctuation falls within the range value; calculating a deviation value according to the similarity, comparing the difference value to be measured with the deviation value, if the difference value to be measured is smaller than the deviation value, the real-time waveform image is stable at the moment, because the deviation value explains the deviation generated by the image at each time point, if the difference value to be measured is smaller than the deviation value, the real-time waveform image is wholly delayed or advanced, but the stability of the image is not influenced; by the detection mode, the real-time waveform image shows the detection result of the equipment, and the stability of the image shows the stability of the equipment, so that the detection stability of the equipment is improved.
The application may be further configured in a preferred example to: and when the difference value to be measured is larger than the deviation value, the real-time waveform image representing the current time is unstable, and a prompt signal is output at the moment.
By adopting the technical scheme, when the difference value to be measured is greater than the deviation value, the local delay or advance of the real-time waveform image at the moment is shown, the image at the moment is proved to be unstable, and a worker needs to be prompted to check the equipment.
The present application may be further configured in a preferred example to:
the method for acquiring the similarity value between the real-time waveform image and the preset waveform image comprises the following steps: acquiring a preset time value of each preset peak and each preset valley in a preset waveform image according to the preset waveform image;
acquiring real-time values of each real-time peak and real-time trough at positions corresponding to preset peaks and preset troughs in the preset waveform image in the real-time waveform image according to the real-time waveform image;
obtaining a difference value to be measured at each position after subtracting the preset time value and the real-time value at each position and taking an absolute value of the subtraction result;
and calculating the difference value to be measured to obtain a similarity value.
The present application may be further configured in a preferred example to:
the method for obtaining the similarity value after calculating the difference value to be measured comprises the following steps:
calculating an average difference value according to the difference value to be measured at each position;
calculating to obtain a mean square difference value according to the mean difference value and the difference value to be measured at each position;
the mean square difference value is the similarity value.
The present application may be further configured in a preferred example, that the method of calculating the deviation value according to the similarity value includes: and obtaining a deviation value by subtracting the mean square difference value and the mean difference value and taking an absolute value of a difference result.
The application may be further configured in a preferred example to: the fluctuation range value refers to the fluctuation which is generated under the normal condition of the waveform image and does not influence the detection result.
The application may be further configured in a preferred example to: and smoothing the real-time waveform image after the real-time waveform image is obtained.
By adopting the technical scheme, when a real-time waveform image appears, noise may appear in the image due to some reasons, and at this time, the image needs to be smoothed, so that the influence of noise is reduced.
The second purpose of the application is to provide an equipment auxiliary control system based on mixed reality.
The second application object of the present application is achieved by the following technical scheme:
a mixed reality-based device assist control system, comprising:
the first acquisition module is used for acquiring a preset waveform image and a real-time waveform image;
the initial judgment module is used for judging whether a real-time wave crest or a real-time wave trough appears in the real-time waveform graph at the current time point;
the first calculation module is used for analyzing and calculating the wave crests and the wave troughs at the corresponding positions in the preset waveform image and the real-time waveform image to obtain a calculation result;
the second calculation module is used for calculating a deviation value according to the similarity value;
the second acquisition module is used for acquiring a preset fluctuation range value, judging whether the difference value to be detected at each position falls within the fluctuation range value or not and outputting a first judgment result;
and the judging module is used for judging whether the difference value to be detected is smaller than the deviation value, if so, the real-time waveform image at the current time is stable, and a judging result is output.
The third purpose of the application is to provide an intelligent terminal.
The third application purpose of the present application is achieved through the following technical scheme:
an intelligent terminal comprises a memory and a processor, wherein the memory stores computer program instructions of the mixed reality-based device auxiliary control method, and the computer program instructions can be loaded and executed by the processor.
The fourth purpose of the present application is to provide a computer medium capable of storing a corresponding program.
The fourth application purpose of the present application is achieved by the following technical scheme:
a computer readable storage medium storing a computer program that can be loaded by a processor and executed to perform any of the above-described mixed reality based device aiding control methods.
In summary, the present application includes at least one of the following beneficial technical effects:
by comparing the preset waveform image with the real-time waveform image, the similarity between the two images can be obtained through analysis and calculation, the wave crest and the wave trough at the corresponding position between the two images are compared from the output of the real-time waveform image, then whether the difference value to be measured at the corresponding position falls within the fluctuation range value is judged, if yes, whether the difference value to be measured is smaller than the deviation value is judged, and if the difference value to be measured is also smaller than the deviation value, the real-time waveform image at the moment is stable; by adopting the mode, the stability of the real-time waveform image can be accurately detected, and the detection stability of the equipment is further improved.
Drawings
Fig. 1 is a schematic flow chart of a method according to an embodiment of the present application.
Fig. 2 is a diagram illustrating a comparison example between the real-time waveform image S1 and the preset waveform image S0 in the embodiment of the present application.
Fig. 3 is a schematic system structure diagram according to an embodiment of the present application.
Description of reference numerals: 1. a first acquisition module; 2. an initial judgment module; 3. a first calculation module; 4. a second calculation module; 5. a second acquisition module; 6. and a judging module.
Detailed Description
The present application is described in further detail below with reference to the attached drawings.
The present embodiment is only for explaining the present application and is not limited to the present application, and those skilled in the art can make modifications without inventive contribution to the present embodiment as needed after reading the present specification, but all of them are protected by patent law within the scope of the claims of the present application.
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The embodiments of the present application will be described in further detail with reference to the drawings attached to the specification.
The application provides an auxiliary control method for equipment based on mixed reality, and the main flow of the method is described as follows.
As shown in fig. 1:
step S101: and acquiring a preset waveform image and a real-time waveform image.
It should be noted that, in this embodiment of the application, the device may be a detection device, a handheld device, or a wearable device, and only needs to satisfy that the device output image reflects a detection result, where the device output image may be one of the functions of the above devices, and a specific type of the device is not limited herein.
The preset waveform image is pre-stored in a database in the equipment, and when the image needs to be processed, the preset waveform image is called; the real-time waveform image is a waveform image obtained by real-time detection of the equipment.
Step S102: and judging whether a peak or a trough appears in the real-time waveform image at the current time point.
The method comprises the steps that a preset waveform image is stored in the equipment in advance, and the real-time waveform image is detection output by the equipment in real time; presetting a waveform image as a complete waveform image, wherein the image comprises wave crests and wave troughs, and similarly, the real-time waveform image is also a waveform image and also comprises the wave crests and the wave troughs; in the process of comparing the real-time waveform image with the preset waveform image, first, from the time of outputting the real-time waveform image, since an image pattern just started to be output by the real-time waveform image may not be a peak or a trough but a gentle curve, the real-time waveform image needs to be preprocessed.
The real-time waveform image may contain a plurality of noise points, and the elimination of noise components in the image is called image smoothing; it is common that the energy of the image is mostly concentrated in the bottom and middle frequency bands of the amplitude spectrum, and in the higher frequency bands, some information of the image is often buried by noise, so that the image needs to be smoothed to reduce noise points on the image.
After the real-time waveform image is subjected to smoothing processing, whether a peak or a trough appears in the real-time waveform image at the current time point needs to be judged; because the horizontal axis of the waveform image is time, namely, the waveform can be changed continuously along with the time, the waveform may have a rising trend or a falling trend; if the waveform is in a rising trend, the appearance of a wave peak is indicated, and if the waveform at the current time point is in a falling trend, the appearance of the wave peak of the real-time waveform image at the current time point is proved; if the waveform has a descending trend, the valley is about to appear, and if the waveform at the current time point has an ascending trend, the valley is proved to appear in the real-time waveform image at the current time point; similarly, in addition to the judgment of the waveform trend, the judgment may be performed by using a correlation value corresponding to each time point, for example, when the correlation value is 1s, 2,3s, and 5,6s, the correlation value is 1.5, and it can be judged by using the correlation value that the real-time waveform image has a peak at the time point of 3 s.
Step S103: when the wave crest or the wave trough appears, the wave crest and the wave trough at the corresponding positions in the preset waveform image and the real-time waveform image are analyzed and calculated to obtain a calculation result.
Step S104: and calculating deviation values according to the similarity values.
The calculation result comprises a similarity value between the real-time waveform image and the preset waveform image and a difference value to be detected, wherein the difference value to be detected is the difference value between the time point of the real-time wave peak or the real-time wave trough in the real-time waveform image at the current time point and the time point of the preset wave peak or the preset wave trough at the corresponding position in the preset waveform image.
Firstly, acquiring a preset time value of each preset peak and each preset valley in a preset waveform image according to the preset waveform image; then acquiring real-time values of each real-time peak and each real-time trough at positions corresponding to the preset peaks and the preset troughs in the preset waveform image in the real-time waveform image according to the real-time waveform image; obtaining a difference value to be measured at each position after subtracting the preset time value and the real-time value at each position and taking an absolute value of the subtraction result; calculating the difference value to be measured at each position to obtain an average difference value, and calculating according to the average difference value and the difference value to be measured at each position through a formula to obtain a mean square difference value, wherein the mean square difference value is a similarity value; and after the similarity value is obtained through calculation, the mean square difference value and the mean difference value are subtracted, and an absolute value of a difference result is removed to obtain a deviation value.
To explain the above process in detail, the following calculation is performed by specific examples and formulas; as shown in fig. 2, S0 is a preset waveform image, S1 is a real-time waveform image, and both waveform images are located in a coordinate system with a horizontal axis t and a vertical axis x; taking S0 as a reference, each preset peak and each preset valley in the preset waveform image S0 correspond to a time point, and certainly, in this example, a first position point of the preset waveform image S0 is a preset peak, and the preset peak is marked as P1; the next position point is a preset wave trough, and the preset wave trough is marked as P2; by analogy, corresponding marks are made for each position point and time point in the preset waveform image S0.
When the real-time waveform image S1 is output, the first real-time peak in the detected real-time waveform image S1 is marked as N1, the real-time peak N1 at this time is the first position point in the real-time waveform image S1, the preset peaks P1, N1 and P1 are in one-to-one correspondence in the preset waveform image S0 and the real-time peaks N2 and the preset valleys P2 at the next position point, and so on, the preset peaks and the real-time peaks or the preset valleys and the real-time valleys at the position points where the real-time waveform image S1 and the preset waveform image S0 are in one-to-one correspondence can be analyzed.
Then, the time points corresponding to P1 and N1 are subtracted, and an absolute value is obtained from the difference result to obtain a difference value T1 to be measured at the position, where in this example, the time point corresponding to P1 is P1, the time point corresponding to N1 is N1, then,
T1=|p1-n1|；
then the difference value T2 to T8 to be measured at each position is calculated in turn, and the difference value is calculated according to a formula,
A=（T1+T2+...+T8）/8；
calculating to obtain an average difference value A;
then according to the formula,
and calculating to obtain a mean square deviation value S, wherein the mean square deviation value S is a similarity value between the real-time waveform image S1 and the preset waveform image S0.
It can be understood that the mean square deviation value generally represents the discrete probability of the waveform image, and after the similarity value between the real-time waveform image S1 and the preset waveform image S0 is obtained, the deviation degree of the real-time waveform image S1 needs to be analyzed; the similarity value represents the discrete probability of the real-time waveform image S1, at which time according to the formula,
Q=|S-A|；
and obtaining a deviation value Q after calculation, wherein the mean square error is the average of the distances of the data from the true value, and the deviation value Q obtained by subtracting the mean square error from the average is the deviation degree of the real-time waveform image S1 compared with the preset waveform image S0.
Step S105: and acquiring a preset fluctuation range value, judging whether the difference value to be detected at each position falls within the fluctuation range value or not and outputting a first judgment result.
A fluctuation range value is preset in the equipment, and the fluctuation range value refers to the fluctuation of the waveform image under the normal condition without influencing the detection result; in the embodiment of the present application, the fluctuation range value can be understood as an offset that can be generated by a real-time peak or a real-time trough at each position; after a preset fluctuation range value is obtained, analyzing the difference value to be detected at each position, and judging whether the difference value to be detected at each position falls within the fluctuation range value or not; for example, in the above example, the difference value T1 to be measured at the position obtained by calculating the time points corresponding to P1 and N1 is compared with a preset fluctuation range value, whether the difference value T1 to be measured falls within the fluctuation range value is determined, and a first determination result is output; if the first judgment result is yes, the real-time waveform image at the current time is indicated to be a stable waveform, if the first judgment result is no, the real-time waveform image at the current time is indicated to be an unstable waveform, at the moment, a warning signal is output, the warning signal is used for prompting a worker that the detection result of the current equipment is an error result, and the equipment needs to be checked and maintained so as to ensure that the equipment can be stably detected, so that the detection stability of the equipment is improved.
In the embodiment of the present application, since the preset waveform image is used as a reference, when comparing the real-time waveform image with the preset waveform image, it should be ensured that the fluctuation of the real-time waveform image at each position does not exceed the preset fluctuation range value.
For example, the time points corresponding to each position in the preset waveform image are respectively I1 and I2.. I10, the time points corresponding to each position in the real-time waveform image are respectively J1 and J2.. J10, and then the to-be-measured difference | I1-J1|, | I2-J2|,. | I10-J10| at the corresponding position in the two images is obtained through calculation; when the fluctuation range value is set to 5-10, the difference values to be measured at the corresponding positions in the two images need to be satisfied to fall within the fluctuation range value of 5-10, that is, the condition is satisfied:
5<|I1-J1|<10、5<|I2-J2|<10、...、5<|I10-J10|<10；
the above conditions are parallel conditions, and only when all the above conditions are satisfied, it is indicated that the real-time waveform image at the current time is a stable waveform.
Step S106: if the first judgment result is yes, judging whether the difference value to be detected is smaller than the deviation value, if so, indicating that the real-time waveform image at the current time is stable, and outputting the judgment result.
When the first judgment result is yes, the difference value to be detected at each position is shown to be within a preset fluctuation range value, then the difference value to be detected and the deviation value are judged, whether the difference value to be detected is smaller than the deviation value or not is judged, if yes, the real-time waveform image at the current time is stable, and the judgment result is output; if not, the real-time waveform image at the current time is unstable, a prompt signal is output at the moment, and the prompt signal is also used for prompting a worker that the detection result of the current equipment is an error result, so that the equipment needs to be checked and maintained.
The present application further provides a device auxiliary control system based on mixed reality, as shown in fig. 3, the device auxiliary control system based on mixed reality includes:
the device comprises a first acquisition module 1, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring a preset waveform image and a real-time waveform image;
the initial judgment module 2 is used for judging whether a real-time wave crest or a real-time wave trough appears in the real-time waveform graph at the current time point;
the first calculating module 3 is used for analyzing and calculating the wave crests and the wave troughs at the corresponding positions in the preset waveform image and the real-time waveform image to obtain a calculating result;
the second calculating module 4 is used for calculating a deviation value according to the similarity value;
the second obtaining module 5 is configured to obtain a preset fluctuation range value, determine whether the difference value to be detected at each position falls within the fluctuation range value, and output a first determination result;
and the judging module 6 is used for judging whether the difference value to be detected is smaller than the deviation value, if so, the real-time waveform image at the current time is stable, and a judging result is output.
In order to better execute the program of the method, the application also provides an intelligent terminal which comprises a memory and a processor.
Wherein the memory is operable to store an instruction, a program, code, a set of codes, or a set of instructions. The memory may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function, instructions for implementing the mixed reality-based device auxiliary control method described above, and the like; the storage data area can store data and the like involved in the mixed reality-based device auxiliary control method.
A processor may include one or more processing cores. The processor executes or executes the instructions, programs, code sets, or instruction sets stored in the memory, calls data stored in the memory, performs various functions of the present application, and processes the data. The processor may be at least one of an application specific integrated circuit, a digital signal processor, a digital signal processing device, a programmable logic device, a field programmable gate array, a central processing unit, a controller, a microcontroller, and a microprocessor. It is understood that the electronic devices for implementing the above processor functions may be other devices, and the embodiments of the present application are not limited in particular.
The present application also provides a computer-readable storage medium, for example, comprising: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk. The computer readable storage medium stores a computer program that can be loaded by a processor and executes the mixed reality based device assist control method described above.
The foregoing description is only exemplary of the preferred embodiments of the application and is illustrative of the principles of the technology employed. It will be appreciated by those skilled in the art that the scope of the disclosure herein is not limited to the particular combination of features described above, but also encompasses other arrangements formed by any combination of the above features or their equivalents without departing from the spirit of the disclosure. For example, the above features may be replaced with (but not limited to) features having similar functions disclosed in the present application.
Claims (8)
1. A mixed reality-based equipment auxiliary control method is characterized by comprising the following steps:
acquiring a preset waveform image and a real-time waveform image;
judging whether a wave crest or a wave trough appears in the real-time waveform image at the current time point;
when a peak or trough occurs:
obtaining a calculation result by analyzing and calculating the wave crest and the wave trough at the corresponding positions in the preset waveform image and the real-time waveform image;
the calculation result comprises a similarity value and a to-be-detected difference value between the real-time waveform image and a preset waveform image;
the difference value to be measured is the difference value between the time point of the real-time wave peak or real-time wave trough in the real-time waveform image of the current time point and the time point of the preset wave peak or preset wave trough at the corresponding position in the preset waveform image;
calculating a deviation value according to the similarity value;
the method for obtaining the similarity value after calculating the difference value to be measured comprises the following steps:
calculating an average difference value according to the difference value to be measured at each position;
calculating to obtain a mean square difference value according to the mean difference value and the difference value to be measured at each position;
the mean square difference value is a similarity value;
the method for calculating the deviation value according to the similarity value comprises the following steps: the mean square difference value and the mean difference value are subjected to difference, and an absolute value of a difference result is obtained to obtain a deviation value;
acquiring a preset fluctuation range value, judging whether the difference value to be detected at each position falls within the fluctuation range value or not and outputting a first judgment result;
if the first judgment result is yes, judging whether the difference value to be detected is smaller than the deviation value, if so, indicating that the real-time waveform image at the current time is stable, and outputting the judgment result.
2. The mixed reality-based device auxiliary control method according to claim 1, wherein when the difference value to be measured is greater than a deviation value, the real-time waveform image representing the current time is unstable, and a prompt signal is output at this time.
3. The mixed reality-based device auxiliary control method according to claim 1, wherein the method of acquiring the similarity value between the real-time waveform image and the preset waveform image comprises:
acquiring a preset time value of each preset peak and each preset valley in a preset waveform image according to the preset waveform image;
acquiring real-time values of each real-time peak and each real-time trough at positions corresponding to preset peaks and preset troughs in the preset waveform image in the real-time waveform image according to the real-time waveform image;
obtaining a difference value to be measured at each position after subtracting the preset time value and the real-time value at each position and taking an absolute value of the subtraction result;
and calculating the difference value to be measured to obtain a similarity value.
4. The mixed reality-based device auxiliary control method according to claim 1, wherein the fluctuation range value refers to a fluctuation that does not affect the detection result and is generated under a normal condition of the waveform image.
5. The mixed reality-based device auxiliary control method according to claim 1, wherein the real-time waveform image is smoothed after the real-time waveform image is acquired.
6. A mixed reality-based auxiliary control system for equipment is characterized by comprising:
the device comprises a first acquisition module (1) for acquiring a preset waveform image and a real-time waveform image;
the initial judgment module (2) is used for judging whether a real-time wave crest or a real-time wave trough appears in the real-time waveform graph at the current time point;
the first calculation module (3) is used for analyzing and calculating the wave crests and the wave troughs at the corresponding positions in the preset waveform image and the real-time waveform image to obtain a calculation result; the calculation result comprises a similarity value and a to-be-detected difference value between the real-time waveform image and a preset waveform image; the difference value to be measured is the difference value between the time point of the real-time wave peak or the real-time wave trough in the real-time waveform image of the current time point and the time point of the preset wave peak or the preset wave trough at the corresponding position in the preset waveform image;
a second calculation module (4) for calculating a deviation value depending on the similarity value; the method for calculating the similarity value comprises the following steps:
calculating an average difference value according to the difference value to be measured at each position;
calculating to obtain a mean square difference value according to the mean difference value and the difference value to be measured at each position;
the mean square difference value is a similarity value;
the method for calculating the deviation value according to the similarity value comprises the following steps: the mean square difference value and the mean difference value are subjected to difference, and an absolute value of a difference result is obtained to obtain a deviation value;
the second acquisition module (5) is used for acquiring a preset fluctuation range value, judging whether the difference value to be detected at each position falls within the fluctuation range value or not and outputting a first judgment result;
and the judging module (6) is used for judging whether the difference value to be detected is smaller than the deviation value, if so, the real-time waveform image at the current time is stable, and a judging result is output.
7. An intelligent terminal, comprising a memory and a processor, the memory having stored thereon computer program instructions capable of being loaded by the processor and performing the method of any of claims 1-5.
8. A computer-readable storage medium, characterized in that a computer program is stored which can be loaded by a processor and which executes the method as claimed in any of the claims 1-5.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107395330A (en) * | 2017-08-28 | 2017-11-24 | 珠海市杰理科技股份有限公司 | The method, apparatus and computer equipment of Low Medium Frequency carrier wave detection |
| CN108108739A (en) * | 2017-12-18 | 2018-06-01 | 上海联影医疗科技有限公司 | Detection method, device, x-ray system and the storage medium of image target area |
| CN109864705A (en) * | 2019-01-07 | 2019-06-11 | 平安科技（深圳）有限公司 | The method, apparatus and computer equipment that pulse wave is filtered |
| CN110652318A (en) * | 2019-07-19 | 2020-01-07 | 飞依诺科技(苏州)有限公司 | Measurement method and system for obtaining arteriosclerosis index based on ultrasonic equipment |
| CN111191671A (en) * | 2019-11-18 | 2020-05-22 | 广东浩迪智云技术有限公司 | Electrical appliance waveform detection method and system, electronic equipment and storage medium |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2018135005A1 (en) * | 2017-01-23 | 2018-07-26 | オリンパス株式会社 | Signal processing device, photoacoustic wave imaging device, and signal processing method |
-
2021
- 2021-05-18 CN CN202110541479.XA patent/CN113297943B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107395330A (en) * | 2017-08-28 | 2017-11-24 | 珠海市杰理科技股份有限公司 | The method, apparatus and computer equipment of Low Medium Frequency carrier wave detection |
| CN108108739A (en) * | 2017-12-18 | 2018-06-01 | 上海联影医疗科技有限公司 | Detection method, device, x-ray system and the storage medium of image target area |
| CN109864705A (en) * | 2019-01-07 | 2019-06-11 | 平安科技（深圳）有限公司 | The method, apparatus and computer equipment that pulse wave is filtered |
| CN110652318A (en) * | 2019-07-19 | 2020-01-07 | 飞依诺科技(苏州)有限公司 | Measurement method and system for obtaining arteriosclerosis index based on ultrasonic equipment |
| CN111191671A (en) * | 2019-11-18 | 2020-05-22 | 广东浩迪智云技术有限公司 | Electrical appliance waveform detection method and system, electronic equipment and storage medium |
Non-Patent Citations (3)
| Title |
|---|
| Oscillography of Transient Processes at Physical Phase-to-ground Fault Modeling in Operational 6-35 kV Networks;A. I. Shirkovets等;《Proceedings of the 2011 3rd International Youth Conference on Energetics》;20111231;第1-6页 * |
| 基于波形相似度的容差模拟电路软故障诊断;钟建林等;《电工技术学报》;20120826(第08期);第222-229页 * |
| 心电监护仪屏幕波形提取算法研究;王秋思等;《软件导刊》;20200515(第05期);第94-97页 * |
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