CN113390370A - Object detection method and device, electronic equipment and storage medium - Google Patents
Object detection method and device, electronic equipment and storage medium Download PDFInfo
- Publication number
- CN113390370A CN113390370A CN202110534302.7A CN202110534302A CN113390370A CN 113390370 A CN113390370 A CN 113390370A CN 202110534302 A CN202110534302 A CN 202110534302A CN 113390370 A CN113390370 A CN 113390370A
- Authority
- CN
- China
- Prior art keywords
- data
- detection
- detected
- difference
- signal
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B15/00—Measuring arrangements characterised by the use of electromagnetic waves or particle radiation, e.g. by the use of microwaves, X-rays, gamma rays or electrons
- G01B15/04—Measuring arrangements characterised by the use of electromagnetic waves or particle radiation, e.g. by the use of microwaves, X-rays, gamma rays or electrons for measuring contours or curvatures
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B15/00—Measuring arrangements characterised by the use of electromagnetic waves or particle radiation, e.g. by the use of microwaves, X-rays, gamma rays or electrons
- G01B15/06—Measuring arrangements characterised by the use of electromagnetic waves or particle radiation, e.g. by the use of microwaves, X-rays, gamma rays or electrons for measuring the deformation in a solid
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/88—Radar or analogous systems specially adapted for specific applications
Abstract
The invention relates to an object detection method, an object detection device, an electronic device and a storage medium, wherein the object detection method comprises the following steps: acquiring a first detection signal output by a millimeter wave radar for scanning an object to be detected; calculating detection data corresponding to the object to be detected based on the first detection signal; calculating first difference data between the detection data and preset reference data, wherein the reference data is obtained by calculation based on a second detection signal output by the millimeter wave radar scanning reference object, and the shape of the reference object does not generate defects; and if the first difference data is larger than a preset first threshold value, determining that the shape of the object to be detected has a defect. According to the embodiment of the invention, the deformation quantity generated between the reference objects which are opposite to the object to be detected and have no defects in shape is obtained based on the detection data obtained by detecting the object to be detected and the reference data obtained by detecting the reference objects, and the defect generated in the shape of the object to be detected can be determined by comparing the deformation quantity with the preset first threshold value, so that the abrasion condition of the object to be detected is automatically detected, the detection result is more accurate and the efficiency is higher.
Description
Technical Field
The present application relates to the field of automation technologies, and in particular, to an object detection method and apparatus, an electronic device, and a storage medium.
Background
The machine fault detection means that after the lower computer is connected with the system, the system periodically sends a detection signal to the lower computer, and judges whether the system has a fault or not through a received response data frame; the fault type judgment means that after the system detects a fault, the type of the system fault is judged by analyzing the reason, the specific fault position and the fault reason of the system are diagnosed, and different measures are taken according to the fault reason to recover the system fault.
For equipment used for assembly line production in real life, the problems of machine element abrasion faults caused by equipment collision and long-term use of the machine generally occur in the production process, conventional fault diagnosis instruments are large and complex and need manual inspection, manual labor and time are consumed for inspecting each element through manual work, and the phenomenon that part of elements are missed is possibly caused due to fatigue of people or carelessness, so that the precision and accuracy are low, the efficiency is low, and the abrasion elements which are not found in time are installed on the machine, so that the production safety problem is caused. The light then the product is unqualified, returns the field and repaiies again, and then heavy has the part to drop, machine stagnation scheduling problem, and the personnel that influence work and still lead to using the machine are injured.
Disclosure of Invention
In order to solve the technical problems of low accuracy and low efficiency of manual inspection of machine element abrasion, the application provides an object detection method, an object detection device, an electronic device and a storage medium.
In a first aspect, the present application provides an object detection method, including:
acquiring a first detection signal output by a millimeter wave radar for scanning an object to be detected;
calculating detection data corresponding to the object to be detected based on the first detection signal;
calculating first difference data between the detection data and preset reference data, wherein the reference data are calculated based on a second detection signal output by the millimeter wave radar scanning reference object, and the shape of the reference object is not defective;
and if the first difference data is larger than a preset first threshold value, determining that the shape of the object to be detected has a defect.
Optionally, the calculating detection data corresponding to the object to be detected based on the first detection signal includes:
acquiring an electromagnetic wave signal transmitted to an object to be detected by the millimeter wave radar;
and calculating detection data corresponding to the object to be detected based on the electromagnetic wave signal and the first detection signal.
Optionally, the calculating detection data corresponding to the object to be detected based on the electromagnetic wave signal and the first detection signal includes:
the electromagnetic wave signal and the first detection signal are subjected to difference to obtain a difference frequency signal;
converting the difference frequency signal from a time domain to a frequency domain, and determining the phase of the difference frequency signal;
and determining the phase as the detection data corresponding to the object to be detected.
Optionally, the calculating detection data corresponding to the object to be detected based on the electromagnetic wave signal and the first detection signal includes:
the electromagnetic wave signal and the first detection signal are subjected to difference to obtain a difference frequency signal;
converting the difference frequency signal from a time domain to a frequency domain, and determining the frequency of the difference frequency signal;
and determining the frequency as the detection data corresponding to the object to be detected.
Optionally, calculating first difference data between the detection data and preset reference data includes:
subtracting the detection data from the reference data to obtain a difference value;
determining the difference as the first difference data.
Optionally, the method further comprises:
converting the first detection signal into first point cloud data;
acquiring second point cloud data converted from the second detection signal;
calculating second difference data between the first point cloud data and the second point cloud data;
and if the second difference data is larger than a preset second threshold, determining that the shape of the object to be detected is verified to generate a defect.
Optionally, calculating second difference data between the first point cloud data and the second point cloud data comprises:
extracting a first distance value and a first angle value between the millimeter wave radar and the object to be detected from the first point cloud data;
extracting a second distance value and a second angle value between the millimeter wave radar and the reference object from the second point cloud data;
constructing a first matrix based on the first distance values and first angle values, and constructing a second matrix based on the second distance values and second angle values;
and calculating the similarity between the first matrix and the second matrix, and determining the obtained similarity data as the second difference data.
In a second aspect, the present application provides an object detecting apparatus, comprising:
the acquisition module is used for acquiring a first detection signal output by a millimeter wave radar for scanning an object to be detected;
the first calculation module is used for calculating detection data corresponding to the object to be detected based on the first detection signal;
the second calculation module is used for calculating first difference data between the detection data and preset reference data, the reference data are obtained by calculation based on a second detection signal output by the millimeter wave radar scanning reference object, and no defect is generated in the shape of the reference object;
and the determining module is used for determining that the shape of the object to be detected has a defect if the first difference data is larger than a preset first threshold.
In a third aspect, the present application provides an electronic device, including a processor, a communication interface, a memory, and a communication bus, where the processor, the communication interface, and the memory complete mutual communication through the communication bus;
a memory for storing a computer program;
a processor configured to implement the object detection method according to any one of the first aspect when executing a program stored in a memory.
In a fourth aspect, the present application provides a computer-readable storage medium having stored thereon a program of an object detection method, which when executed by a processor, implements the steps of the object detection method of any one of the first aspects.
Compared with the prior art, the technical scheme provided by the embodiment of the application has the following advantages:
according to the embodiment of the invention, a first detection signal output by a millimeter wave radar for scanning an object to be detected is firstly obtained, then detection data corresponding to the object to be detected is calculated based on the first detection signal, then first difference data between the detection data and preset reference data is calculated, the reference data is calculated based on a second detection signal output by the millimeter wave radar for scanning the reference object, the shape of the reference object is not defective, and if the first difference data is larger than a preset first threshold value, the shape of the object to be detected can be determined to be defective.
According to the embodiment of the invention, the first difference data between the detection data obtained by detecting the object to be detected and the reference data obtained by detecting the reference object is calculated, namely the deformation quantity generated between the object to be detected and the reference object of which the shape does not generate defects is calculated, when the first difference data is larger than the preset first threshold value, the shape of the object to be detected can be determined to generate defects, the abrasion condition of the object can be automatically detected, the detection result is more accurate, and the efficiency is higher.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention.
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without inventive exercise.
Fig. 1 is a flowchart of an object detection method according to an embodiment of the present application;
FIG. 2 is a schematic diagram illustrating a normal component detection process according to an embodiment of the present disclosure;
FIG. 3 is a schematic diagram of a process for detecting a wear element according to an embodiment of the present disclosure;
FIG. 4 is a frequency domain plot of normal and wear elements after FFT, as provided by an embodiment of the present application;
fig. 5 is a structural diagram of an object detection apparatus according to an embodiment of the present application;
fig. 6 is a block diagram of an electronic device according to an embodiment of the present application.
Detailed Description
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.
In the related technology, for equipment used for flow line production in real life, the problems of equipment collision and machine element abrasion faults caused by long-term use of the machine usually occur in the production process, conventional fault diagnosis instruments are large and complex and need manual inspection, the inspection of each element is performed manually, manpower and time are consumed, and due to fatigue of people or carelessness, the phenomenon that part of elements are missed to be inspected possibly exists, so that the precision and accuracy are low, the efficiency is low, and the abrasion elements which are not found in time are installed on the machine, so that the production safety problem can be caused. The light then the product is unqualified, returns the field and repaiies again, and then heavy has the part to drop, machine stagnation scheduling problem, and the personnel that influence work and still lead to using the machine are injured. Therefore, the embodiment of the invention provides an object detection method, an object detection device, an electronic device and a storage medium, and the object detection method can be applied to the electronic device and the like.
As shown in fig. 1, the object detection method may include the steps of:
step S101, acquiring a first detection signal output by a millimeter wave radar for scanning an object to be detected;
in the embodiment of the invention, the object to be detected can refer to an element to be detected and the like, the millimeter wave radar can be arranged inside the electronic equipment or outside the electronic equipment, a CPU in the electronic equipment can be in communication connection with the millimeter wave radar, when whether the object to be detected is worn or not needs to be detected, the CPU can send a control instruction to the millimeter wave radar, the millimeter wave radar sends an electromagnetic wave signal to the object to be detected through an electromagnetic wave sending end according to the control instruction, the object to be detected reflects the electromagnetic wave signal to a plurality of directions, a part of the electromagnetic wave signal (such as millimeter wave) is reflected back to a receiving end antenna of the millimeter wave radar through the object to be detected and is received by the radar, the millimeter wave radar outputs a first detection signal, and further, the CPU of the electronic equipment can obtain the first detection signal.
In practical application, in order to ensure that a more accurate first detection signal can be received, the millimeter wave radar can be arranged on one surface of the object to be detected, no obstacle is blocked between the millimeter wave radar and the object to be detected, the distance between the millimeter wave radar and the object to be detected is located in the effective radiation range of the millimeter wave radar, and the millimeter wave radar is kept powered on and normal signal transmission and reception are kept.
In order to improve the accuracy of subsequent discrimination work, clutter filtering processing can be performed on a first detection signal received by the millimeter wave radar to obtain a filtered pure signal, so that clutter interference can be reduced.
Step S102, calculating detection data corresponding to the object to be detected based on the first detection signal;
due to the fact that the normal unworn object is used, because the electromagnetic wave signals transmitted by the millimeter wave radar are electromagnetic wave signals with preset waveforms, the first detection signals detected by the corresponding millimeter wave radar should also be regularly periodic, and as shown in fig. 2, when the object is abraded, the surface of the object is uneven, and the first detection signals reflected by the abraded part from the electromagnetic wave radar are abnormal. Therefore, it is necessary to calculate the change of the first detection signal with respect to the originally emitted electromagnetic wave signal, so in this step, the detection data corresponding to the object to be detected can be calculated based on the first detection signal.
Step S103, calculating first difference data between the detection data and preset reference data;
in the embodiment of the present invention, the reference data is calculated based on the second detection signal output by the millimeter wave radar scanning reference object, the shape of the reference object has no defect, and is used as a reference standard to measure the variation of the external form of the object to be detected, for example, the reference object may refer to an unworn element, in one embodiment of the present invention, the reference object may refer to an object to be detected that is not put into use, in another embodiment of the present invention, the reference object may also refer to an object in the same batch as the object to be detected, that is, the reference object and the external form of the object to be detected are completely the same;
in practical applications, the reference data of the reference object may be predetermined, specifically, the CPU may send a control instruction to the millimeter wave radar, as shown in fig. 3, the millimeter wave radar sends an electromagnetic wave signal to the reference object through the electromagnetic wave sending end according to the control instruction, the reference object reflects the electromagnetic wave signal in many directions, a part of the electromagnetic wave signal (for example, millimeter wave) is reflected back to the receiving end antenna of the millimeter wave radar through the reference object to be received by the radar, the millimeter wave radar outputs a second detection signal, and the reference data corresponding to the reference object is calculated based on the second detection signal.
In this step, the detection data and the reference data may be directly subtracted to obtain a difference value, and the difference value is determined as the first difference data.
And step S104, if the first difference data is larger than a preset first threshold value, determining that the shape of the object to be detected has a defect.
In this step, the first difference data may be compared with a preset first threshold, and if the first difference data is greater than the preset first threshold, it may be determined that the shape of the object to be detected has a defect, i.e., wear; if the first difference data is smaller than or equal to a preset first threshold, it can be determined that the shape of the object to be detected does not generate defects, namely is not worn.
According to the embodiment of the invention, a first detection signal output by a millimeter wave radar for scanning an object to be detected is firstly obtained, then detection data corresponding to the object to be detected is calculated based on the first detection signal, then first difference data between the detection data and preset reference data is calculated, the reference data is calculated based on a second detection signal output by the millimeter wave radar for scanning the reference object, the shape of the reference object is not defective, and if the first difference data is larger than a preset first threshold value, the shape of the object to be detected can be determined to be defective.
According to the embodiment of the invention, the first difference data between the detection data obtained by detecting the object to be detected and the reference data obtained by detecting the reference object is calculated, namely the deformation quantity generated between the object to be detected and the reference object of which the shape does not generate defects is calculated, when the first difference data is larger than the preset first threshold value, the shape of the object to be detected can be determined to generate defects, the abrasion condition of the object can be automatically detected, the detection result is more accurate, and the efficiency is higher.
In another embodiment of the present invention, the calculating the detection data corresponding to the object to be detected based on the first detection signal includes:
step 201, acquiring an electromagnetic wave signal emitted to an object to be detected by the millimeter wave radar;
step 202, calculating detection data corresponding to the object to be detected based on the electromagnetic wave signal and the first detection signal.
According to the embodiment of the invention, the detection data can be calculated based on the electromagnetic wave signal and the first detection signal, so that the variable quantity of the first detection signal relative to the electromagnetic wave signal can be conveniently known.
Electromagnetic wave signals are transmitted and return after encountering obstacles, and the receiving antenna receives the signals, so that a receiving time difference is generated due to a certain distance between the obstacles and the radar. As can be seen from fig. 2 and 3, the small circle is the radar and the large regular heptagon is the element with detection. The elements in fig. 2 are normal, the elements in fig. 3 are worn, so that the reflected echo received by the radar is prolonged, the time t is longer than the return wavelength of the normal elements, the received signal and the transmitted signal are the same, the difference is only the time difference, the time difference can be represented as a phase difference, and therefore whether the elements are worn or not can be judged through the phase difference. In still another embodiment of the present invention, the calculating detection data corresponding to the object to be detected based on the electromagnetic wave signal and the first detection signal includes:
step 301, subtracting the electromagnetic wave signal from the first detection signal to obtain a difference frequency signal;
by this step, the change of the first detection signal with respect to the electromagnetic wave signal can be calculated.
Step 302, converting the difference frequency signal from a time domain to a frequency domain, and determining the phase of the difference frequency signal;
in order to facilitate the analysis of the variation of the first detection signal relative to the electromagnetic wave signal in time and energy, in this step, the difference frequency signal may be converted into a frequency domain by a Fast Fourier Transform (FFT), and the analysis is performed in the frequency domain to obtain the phase of the difference frequency signal, which may be calculated by the following formula:
ΔΦ＝4πΔd/λ
where π is the circumference ratio, which is a determined value; Δ d is the size of the wear; λ is the wavelength of the millimeter wave, and is uniquely determined by the millimeter wave radar parameter, which is a unique fixed value when determining the transmission signal used by the millimeter wave radar. As can be seen from the formula, the phase is related to Δ d only, and the phase is positively related to Δ d.
Step 303, determining the phase as the detection data corresponding to the object to be detected.
The signals received by the millimeter waves and reflected by the detected element are subjected to FFT to obtain a frequency domain diagram, and the phase of the peak value in the frequency domain is the phase of the difference frequency signal. Suppose that the phase of the peak of the reference element in the frequency domain is Φ0Then the phase and phi of the normal element at the energy peak0The difference of (c) is small and the phase of the worn element at the energy peak is phi0The difference in phase difference is large, and thus whether the element is worn or not can be judged by comparing the two phases. According to the formula, assuming that the reference element Δ d is 0, the phase Φ0When Δ d is 0.5mm (mm) and the millimeter wave radar wavelength λ is 5mm (mm), the phase is Δ Φ is 0.4 pi. Accordingly, the preset first threshold may use a phase difference threshold in the embodiment of the present invention, and the phase difference threshold may be determined according to the element wear threshold. Assuming acceptable wear of the component up to d0Then, the phase difference threshold may be set to Δ Φ — 4 pi d0And/lambda. When the first difference data, i.e., the phase difference between the phase of the difference frequency signal of the object to be detected and the phase of the difference frequency signal of the reference object (which can be calculated in a similar manner to that in the present embodiment) is larger than this phase difference threshold value, it is determined that the part is worn.
The embodiment of the invention can automatically determine the phase of the difference frequency signal as the detection data, thereby being convenient for judging whether the object to be detected is worn or not based on the detection data in the follow-up process.
Electromagnetic wave signals are transmitted and return after encountering obstacles, and the receiving antenna receives the signals, so that a receiving time difference is generated due to a certain distance between the obstacles and the radar. As can be seen from fig. 2 and 3, the small circle is the radar and the large regular heptagon is the element with detection. The elements in fig. 2 are normal, the elements in fig. 3 are worn out by one, so that the reflected echo received by the radar is prolonged by a time t which is longer than the wavelength of the normal elements, and the received signal and the transmitted signal are identical, except for a time difference which can be expressed as a frequency difference on the other hand, so that whether the elements are worn out or not can be judged through the frequency difference. In still another embodiment of the present invention, the calculating detection data corresponding to the object to be detected based on the electromagnetic wave signal and the first detection signal includes:
step 401, subtracting the electromagnetic wave signal from the first detection signal to obtain a difference frequency signal;
by this step, the change of the first detection signal with respect to the electromagnetic wave signal can be calculated. Step 402, converting the difference frequency signal from a time domain to a frequency domain, and determining the frequency of the difference frequency signal;
in order to facilitate the analysis of the variation of the first detection signal with respect to the electromagnetic wave signal in time and energy, in this step, the difference frequency signal may be converted into a frequency domain by a Fast Fourier Transform (FFT), and the analysis may be performed in the frequency domain to obtain the frequency of the difference frequency signal.
The frequency can be calculated by the following formula:
Δf＝2μΔd/c
mu is the frequency modulation slope of the millimeter wave signal, which is uniquely determined by the millimeter wave radar parameter, and when the transmitting waveform used by the millimeter wave radar is determined, the parameter is a unique fixed value; Δ d is the size of the wear; c is the propagation velocity of light in the atmosphere, and is also a definite value. It can be seen from the formula that the frequency is only related to Δ d, and the frequency is positively related to Δ d.
Step 403, determining the frequency as the detection data corresponding to the object to be detected;
as shown in fig. 4, after the signals received by the millimeter waves and reflected by the detected element are subjected to FFT, a frequency domain diagram is obtained, and the frequency at which the peak value is located is the frequency of the difference frequency signal. The difference in frequency between the difference frequency signal obtained by the normal component and the difference frequency signal obtained by the reference component is small, while the difference in frequency between the difference frequency signal obtained by the worn component and the difference frequency signal obtained by the reference component is large. Whether the element is worn or not can be judged according to the frequency difference of the measured element and the reference element.
The frequency difference which can be detected by the millimeter wave radar is minimum
Where Fs is the sampling rate used by the system and N is the number of points for FFT of the difference signal. The formula combined with the frequency of the difference frequency signal can obtain that the minimum abrasion size which can be detected by using the frequency difference method is
Assuming that the chirp rate of the millimeter wave radar is 30M/μ s (unit of chirp rate, mega per microsecond), the sampling rate is 10M, the number of sampling points is 300, the number of FFT points used when FFT is performed is 512, and the light velocity c is an estimated value of 299792458M/s, the minimum size that can be detected is
And d is 0.0976 m, namely, the frequency difference method is selected for detection when the abrasion distance is greater than 9.76 cm, and the phase difference method is used for detection when the abrasion size is less than 9.76 cm. The minimum wear that can be detected by the frequency difference method is 9.76 cm. The frequency difference threshold is
Accordingly, in the embodiment of the present invention, a frequency difference threshold may be used to preset the first threshold, and when the frequency difference between the first difference data, that is, the frequency difference between the frequency of the difference frequency signal of the object to be detected and the frequency of the difference frequency signal of the reference object (which may be calculated in a similar manner as in the embodiment) is greater than the frequency difference threshold, it is determined that the part is worn.
The embodiment of the invention can automatically determine the frequency as the detection data, so that whether the object to be detected is worn or not can be judged conveniently based on the detection data.
Whether the element is worn or not can be detected by selecting a phase method or a frequency method, wherein the phase method is used for judging whether the element is worn or not when the element is worn less, and the frequency method is used for detecting when the element is worn more. Therefore, firstly, a frequency method is used for detection, and if the detected frequency difference is larger than a threshold value, the abrasion is judged; if the frequency difference is smaller than the threshold value, a phase method is used for accurate detection, if the phase difference is larger than the threshold value, abrasion is judged to exist, if the phase difference is smaller than the threshold value, abrasion does not exist, and the element is normal.
In yet another embodiment of the present invention, the method further comprises:
step 501, converting the first detection signal into first point cloud data;
because the signals reflected by the worn out components which do not reach the standard are different from the normal components, the first detection signals can be processed into first point cloud data through signal processing means such as distance FFT, speed FFT, channel accumulated amplitude energy matrix or Cfar and the like.
Step 502, obtaining second point cloud data converted from the second detection signal;
similarly, the second detection signal can be processed into second point cloud data by distance FFT, velocity FFT, channel accumulated amplitude energy matrix or Cfar and other signal processing means.
Step 503, calculating second difference data between the first point cloud data and the second point cloud data;
in this step, the difference between the first point cloud data and the second point cloud may be compared, resulting in second difference data.
Step 504, if the second difference data is larger than a preset second threshold, it is determined that the shape of the object to be detected is verified to generate a defect.
According to the embodiment of the invention, the first detection signal and the second detection signal are respectively converted into the first point cloud data and the second point cloud data, the difference between the first point cloud data and the second point cloud data is calculated, and then the difference is compared with the preset second threshold value, so that the judgment result about whether the object is worn or not in the embodiment is further verified, and the accuracy of part wear detection is improved.
In yet another embodiment of the present invention, calculating second difference data between the first point cloud data and the second point cloud data comprises:
step 601, extracting a first distance value and a first angle value between the millimeter wave radar and the object to be detected from the first point cloud data;
step 602, extracting a second distance value and a second angle value between the millimeter wave radar and the reference object from the second point cloud data;
step 603, constructing a first matrix based on the first distance value and the first angle value, and constructing a second matrix based on the second distance value and the second angle value;
step 604, calculating a similarity between the first matrix and the second matrix, and determining the obtained similarity data as the second difference data.
And obtaining distance and angle values after processing. The data returned by the normal element and the data generated by the wear element are respectively made into a matrix and marked, and the similarity of the new data is calculated through the matrix. Based on the similarity of the matrices, we find that the similarity of the wear element and the normal element is low, wherein the similarity formula of the matrix a and the matrix B is as follows:
where a denotes the normal element data matrix, B denotes the wear element data matrix, Tr denotes the trace (rank) of the matrix, a 'denotes the transposed matrix of a, B denotes the transposed matrix of B', and s denotes the number of dimensions of the matrix.
And carrying out similarity matching on the newly acquired data and normal equipment, judging the newly acquired data as a normal element if the newly acquired data is greater than a given threshold, and otherwise, judging the newly acquired data as a wear element.
According to the embodiment of the invention, the similarity between the matrixes can be automatically calculated, so that the second difference data between the first point cloud data and the second point cloud data, namely the difference between the first detection signal and the second detection signal, is obtained, and the result of the object abrasion judgment obtained by the embodiment can be further verified.
In still another embodiment of the present invention, as shown in fig. 5, there is also provided an object detecting apparatus including:
the acquisition module 11 is configured to acquire a first detection signal output by a millimeter wave radar for scanning an object to be detected;
a first calculating module 12, configured to calculate, based on the first detection signal, detection data corresponding to the object to be detected;
a second calculating module 13, configured to calculate first difference data between the detection data and preset reference data, where the reference data is calculated based on a second detection signal output by the millimeter wave radar scanning reference object, and a shape of the reference object is not defective;
the determining module 14 is configured to determine that the shape of the object to be detected has a defect if the first difference data is greater than a preset first threshold.
In another embodiment of the present invention, an electronic device is further provided, which includes a processor, a communication interface, a memory, and a communication bus, where the processor, the communication interface, and the memory complete communication with each other through the communication bus;
a memory for storing a computer program;
and the processor is used for realizing the object detection method in any one of the method embodiments when executing the program stored in the memory.
In the electronic device provided by the embodiment of the present invention, the processor implements, by executing the program stored in the memory, that a first detection signal output by the millimeter wave radar for scanning the object to be detected is first obtained, then the detection data corresponding to the object to be detected is calculated based on the first detection signal, and then first difference data between the detection data and preset reference data is calculated, where the reference data is calculated based on a second detection signal output by the millimeter wave radar for scanning the reference object, and the shape of the reference object is not defective, and if the first difference data is greater than a preset first threshold, it may be determined that the shape of the object to be detected is defective.
According to the embodiment of the invention, the first difference data between the detection data obtained by detecting the object to be detected and the reference data obtained by detecting the reference object is calculated, namely the deformation quantity generated between the object to be detected and the reference object of which the shape does not generate defects is calculated, when the first difference data is larger than the preset first threshold value, the shape of the object to be detected can be determined to generate defects, the abrasion condition of the object can be automatically detected, the detection result is more accurate, and the efficiency is higher.
The communication bus 1140 mentioned in the above electronic device may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The communication bus 1140 may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, only one thick line is shown in FIG. 6, but this is not intended to represent only one bus or type of bus.
The communication interface 1120 is used for communication between the electronic device and other devices.
The memory 1130 may include a Random Access Memory (RAM), and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory. Optionally, the memory may also be at least one memory device located remotely from the processor.
The processor 1110 may be a general-purpose processor, and includes a Central Processing Unit (CPU), a Network Processor (NP), and the like; the integrated circuit may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic device, or discrete hardware components.
In a further embodiment of the present invention, there is also provided a computer-readable storage medium having stored thereon a program of an object detection method, which when executed by a processor, implements the steps of the object detection method of any of the preceding method embodiments.
It is noted that, in this document, relational terms such as "first" and "second," and the like, may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The foregoing are merely exemplary embodiments of the present invention, which enable those skilled in the art to understand or practice the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended 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 (10)
1. An object detection method, comprising:
acquiring a first detection signal output by a millimeter wave radar for scanning an object to be detected;
calculating detection data corresponding to the object to be detected based on the first detection signal;
calculating first difference data between the detection data and preset reference data, wherein the reference data are calculated based on a second detection signal output by the millimeter wave radar scanning reference object, and the shape of the reference object is not defective;
and if the first difference data is larger than a preset first threshold value, determining that the shape of the object to be detected has a defect.
2. The object detection method according to claim 1, wherein the calculating detection data corresponding to the object to be detected based on the first detection signal includes:
acquiring an electromagnetic wave signal transmitted to an object to be detected by the millimeter wave radar;
and calculating detection data corresponding to the object to be detected based on the electromagnetic wave signal and the first detection signal.
3. The object detection method according to claim 2, wherein the calculating detection data corresponding to the object to be detected based on the electromagnetic wave signal and the first detection signal includes:
the electromagnetic wave signal and the first detection signal are subjected to difference to obtain a difference frequency signal;
converting the difference frequency signal from a time domain to a frequency domain, and determining the phase of the difference frequency signal;
and determining the phase as the detection data corresponding to the object to be detected.
4. The object detection method according to claim 2, wherein the calculating detection data corresponding to the object to be detected based on the electromagnetic wave signal and the first detection signal includes:
the electromagnetic wave signal and the first detection signal are subjected to difference to obtain a difference frequency signal;
converting the difference frequency signal from a time domain to a frequency domain, and determining the frequency of the difference frequency signal;
and determining the frequency as the detection data corresponding to the object to be detected.
5. The object detection method according to claim 1, wherein calculating first difference data between the detection data and preset reference data comprises:
subtracting the detection data from the reference data to obtain a difference value;
determining the difference as the first difference data.
6. The object detection method of claim 1, further comprising:
converting the first detection signal into first point cloud data;
acquiring second point cloud data converted from the second detection signal;
calculating second difference data between the first point cloud data and the second point cloud data;
and if the second difference data is larger than a preset second threshold, determining that the shape of the object to be detected is verified to generate a defect.
7. The object detection method of claim 6, wherein computing second difference data between the first point cloud data and the second point cloud data comprises:
extracting a first distance value and a first angle value between the millimeter wave radar and the object to be detected from the first point cloud data;
extracting a second distance value and a second angle value between the millimeter wave radar and the reference object from the second point cloud data;
constructing a first matrix based on the first distance values and first angle values, and constructing a second matrix based on the second distance values and second angle values;
and calculating the similarity between the first matrix and the second matrix, and determining the obtained similarity data as the second difference data.
8. An object detecting apparatus, characterized by comprising:
the acquisition module is used for acquiring a first detection signal output by a millimeter wave radar for scanning an object to be detected;
the first calculation module is used for calculating detection data corresponding to the object to be detected based on the first detection signal;
the second calculation module is used for calculating first difference data between the detection data and preset reference data, the reference data are obtained by calculation based on a second detection signal output by the millimeter wave radar scanning reference object, and no defect is generated in the shape of the reference object;
and the determining module is used for determining that the shape of the object to be detected has a defect if the first difference data is larger than a preset first threshold.
9. An electronic device is characterized by comprising a processor, a communication interface, a memory and a communication bus, wherein the processor and the communication interface are used for realizing mutual communication by the memory through the communication bus;
a memory for storing a computer program;
a processor for implementing the object detection method according to any one of claims 1 to 7 when executing a program stored in a memory.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium has stored thereon a program of an object detection method, which when executed by a processor implements the steps of the object detection method of any one of claims 1 to 7.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110534302.7A CN113390370B (en) | 2021-05-17 | 2021-05-17 | Object detection method and device, electronic equipment and storage medium |
| PCT/CN2022/071649 WO2022242204A1 (en) | 2021-05-17 | 2022-01-12 | Object detecting method and apparatus, electronic device, and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110534302.7A CN113390370B (en) | 2021-05-17 | 2021-05-17 | Object detection method and device, electronic equipment and storage medium |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113390370A true CN113390370A (en) | 2021-09-14 |
| CN113390370B CN113390370B (en) | 2023-01-13 |
Family
ID=77617080
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110534302.7A Active CN113390370B (en) | 2021-05-17 | 2021-05-17 | Object detection method and device, electronic equipment and storage medium |
Country Status (2)
| Country | Link |
|---|---|
| CN (1) | CN113390370B (en) |
| WO (1) | WO2022242204A1 (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2022242204A1 (en) * | 2021-05-17 | 2022-11-24 | 珠海格力电器股份有限公司 | Object detecting method and apparatus, electronic device, and storage medium |
Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP0121353A1 (en) * | 1983-03-07 | 1984-10-10 | New York Institute Of Technology | Projection moire topography |
| CN102012403A (en) * | 2010-11-01 | 2011-04-13 | 北京市市政工程研究院 | Judging method of incompactness defect in node of concrete structure by detection by ultrasonic method |
| CN103093196A (en) * | 2013-01-14 | 2013-05-08 | 大连理工大学 | Character interactive input and recognition method based on gestures |
| CN103257182A (en) * | 2013-06-07 | 2013-08-21 | 电子科技大学 | Pulse vortexing defect quantitative detection method and detection system |
| CN106570311A (en) * | 2016-10-12 | 2017-04-19 | 武汉数字工程研究所（中国船舶重工集团公司第七0九研究所） | Flight path continuity assessment method and system under complex conditions |
| CN107052086A (en) * | 2017-06-01 | 2017-08-18 | 扬州苏星机器人科技有限公司 | Stamping parts surface defect detection apparatus and detection method based on 3D vision |
| CN109614459A (en) * | 2019-03-06 | 2019-04-12 | 上海思岚科技有限公司 | Map structuring winding detection method and equipment applied to two-dimensional laser |
| CN109964096A (en) * | 2016-10-17 | 2019-07-02 | 因诺伊克斯压铸技术创新设备有限责任公司 | Terahertz measuring instrument |
| CN110044934A (en) * | 2019-04-01 | 2019-07-23 | 黑凤梨供应链管理（上海）有限公司 | A kind of surface fracture or the detection device and its detection method of surface state variation |
| CN111337924A (en) * | 2020-04-16 | 2020-06-26 | 湖南科技大学 | Crack identification and detection method for bridge health monitoring |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP5090315B2 (en) * | 2008-10-29 | 2012-12-05 | 株式会社日立製作所 | Ultrasonic flaw detection apparatus and ultrasonic flaw detection method |
| CN113390370B (en) * | 2021-05-17 | 2023-01-13 | 珠海格力电器股份有限公司 | Object detection method and device, electronic equipment and storage medium |
-
2021
- 2021-05-17 CN CN202110534302.7A patent/CN113390370B/en active Active
-
2022
- 2022-01-12 WO PCT/CN2022/071649 patent/WO2022242204A1/en unknown
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP0121353A1 (en) * | 1983-03-07 | 1984-10-10 | New York Institute Of Technology | Projection moire topography |
| CN102012403A (en) * | 2010-11-01 | 2011-04-13 | 北京市市政工程研究院 | Judging method of incompactness defect in node of concrete structure by detection by ultrasonic method |
| CN103093196A (en) * | 2013-01-14 | 2013-05-08 | 大连理工大学 | Character interactive input and recognition method based on gestures |
| CN103257182A (en) * | 2013-06-07 | 2013-08-21 | 电子科技大学 | Pulse vortexing defect quantitative detection method and detection system |
| CN106570311A (en) * | 2016-10-12 | 2017-04-19 | 武汉数字工程研究所（中国船舶重工集团公司第七0九研究所） | Flight path continuity assessment method and system under complex conditions |
| CN109964096A (en) * | 2016-10-17 | 2019-07-02 | 因诺伊克斯压铸技术创新设备有限责任公司 | Terahertz measuring instrument |
| CN107052086A (en) * | 2017-06-01 | 2017-08-18 | 扬州苏星机器人科技有限公司 | Stamping parts surface defect detection apparatus and detection method based on 3D vision |
| CN109614459A (en) * | 2019-03-06 | 2019-04-12 | 上海思岚科技有限公司 | Map structuring winding detection method and equipment applied to two-dimensional laser |
| CN110044934A (en) * | 2019-04-01 | 2019-07-23 | 黑凤梨供应链管理（上海）有限公司 | A kind of surface fracture or the detection device and its detection method of surface state variation |
| CN111337924A (en) * | 2020-04-16 | 2020-06-26 | 湖南科技大学 | Crack identification and detection method for bridge health monitoring |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2022242204A1 (en) * | 2021-05-17 | 2022-11-24 | 珠海格力电器股份有限公司 | Object detecting method and apparatus, electronic device, and storage medium |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113390370B (en) | 2023-01-13 |
| WO2022242204A1 (en) | 2022-11-24 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US9097805B2 (en) | Systems and methods for calibrating dual polarization radar systems | |
| AU2003250981B2 (en) | Method and device for determining an expectancy range for a level echo and a spurious echo | |
| US9261585B2 (en) | Radar apparatus using image change detector and method of operating the same | |
| Coppi et al. | A software tool for processing the displacement time series extracted from raw radar data | |
| CN110554049B (en) | Composite insulator defect detection device and method based on terahertz wave, and medium | |
| CN109254291B (en) | Doppler power spectrum data fusion method and device of cloud radar | |
| CN110443275B (en) | Method, apparatus and storage medium for removing noise | |
| CN113390370B (en) | Object detection method and device, electronic equipment and storage medium | |
| CN103852747B (en) | Increase the method for the acquisition probability of radar signal | |
| CN112213728A (en) | Ultrasonic distance measurement method and device, computer readable storage medium and robot | |
| CN117651882A (en) | Reflectivity correction method, reflectivity correction device, computer readable storage medium and terminal equipment | |
| CN113093168A (en) | Distance and speed measuring method and device, radar and readable storage medium | |
| KR101770742B1 (en) | Apparatus and method for detecting target with suppressing clutter false target | |
| CN111371436A (en) | Radar antenna scanning period measuring method, device, equipment and storage medium | |
| US20190154795A1 (en) | Testing system and method for testing the performance of a detector | |
| CN114859297A (en) | Bridge vibration target detection method and device | |
| CN111830479B (en) | Radar echo dual-component mixed amplitude distribution model parameter estimation method and device | |
| CN109239677A (en) | A kind of environment self-adaption CFAR detection thresholding determines method | |
| TWI474028B (en) | Frequency Leveling of Continuous Wave Radar and Its Measuring Method | |
| KR102192761B1 (en) | Method and apparatus for detecting target | |
| CN115047419A (en) | Constant false alarm rate detection method and device for millimeter wave radar | |
| CN111121678B (en) | Pipeline wall thickness detection method and device | |
| CN107783097B (en) | Target pairing and data processing platform | |
| CN107783083B (en) | Variable-period triangular wave and constant-frequency constant false alarm detection and data processing method | |
| CN107783085B (en) | Unit average selection threshold detection method applied to constant false alarm rate detection and data processing |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |