CN115180364A - GMI magnetic sensor-based mining conveying belt foreign matter monitoring device and method - Google Patents
GMI magnetic sensor-based mining conveying belt foreign matter monitoring device and method Download PDFInfo
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- B65G43/00—Control devices, e.g. for safety, warning or fault-correcting
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Abstract
The invention discloses a GMI magnetic sensor-based mining conveying belt foreign matter monitoring device and method. The device comprises: the metal detection modules are arranged below an upper-layer transmission belt for transporting coal flows at equal intervals and are used for collecting magnetic field signals at different positions; the encoder is connected with the metal detection module and is used for controlling the metal detection module to acquire magnetic field signals at different positions within a set time interval; the intelligent analysis terminal detects and positions the foreign matters according to the magnetic field signals; the voice alarm is connected with the intelligent analysis terminal and used for alarming when the foreign body is detected. According to the invention, the metal foreign body detection module is arranged below the belt to detect the size and the change of the induction magnetic field in real time, when metal foreign bodies appear in coal flow transported by the belt, the magnetic field can generate abnormal waveform change, and the defect interference and the connection part interference of the conveyor belt are eliminated through the conversion and the change of an algorithm, so that the detection and the positioning of the metal foreign bodies are finally realized.
Description
Technical Field
The invention relates to the technical field of detection, in particular to a GMI magnetic sensor-based device and a GMI magnetic sensor-based method for monitoring foreign matters on a mining conveyor belt.
Background
At the in-process of transportation coal, ferromagnetic metal foreign matters such as stock, iron wire, I-steel on the conveyer belt can be transmitted through the conveyer belt along with the coal cinder, can cause the not rip of equidimension or fish tail to the conveyer belt very probably, can influence production when serious, cause great loss.
The existing related detection technical equipment mainly focuses on radio methods, electromagnetic methods, X-ray and video image AI detection methods. The methods have certain limitations on safety and accuracy due to low detection sensitivity, low detection speed, limited use scene, great influence of coal slime and water mist, damage to human bodies and the like.
Therefore, a highly reliable metal foreign matter monitoring device which is not influenced by water mist, coal slime and coal dust is urgently needed for the complex environment of the mine.
Disclosure of Invention
Based on the above, the invention aims to provide a device and a method for monitoring foreign matters on a mining conveyor belt based on a GMI magnetic sensor.
In order to achieve the purpose, the invention provides the following scheme:
a mining conveyer belt foreign matter monitoring devices based on GMI magnetic sensor includes:
the metal detection modules are distributed below an upper-layer transmission belt for transporting coal flows at equal intervals and used for collecting magnetic field signals at different positions;
the encoder is connected with the metal detection module and used for controlling the metal detection module to acquire magnetic field signals at different positions within a set time interval;
the intelligent analysis terminal is connected with the metal detection module through Ethernet and used for detecting and positioning the foreign matters according to the magnetic field signals;
and the voice alarm is connected with the intelligent analysis terminal and used for alarming when the foreign body is detected.
Optionally, the metal detection module is composed of a plurality of GMI magnetic sensor arrays.
Optionally, mining conveyer belt foreign matter monitoring devices still includes:
and the direct-current voltage-stabilizing power supply is respectively connected with the metal detection module, the intelligent analysis terminal and the voice alarm and is used for supplying power to the metal detection module, the intelligent analysis terminal and the voice alarm.
The invention also provides a GMI magnetic sensor-based method for monitoring foreign matters on the mining conveyor belt, which comprises the following steps:
collecting magnetic field signals at different positions through a plurality of metal detection modules; the metal detection modules are arranged below an upper-layer conveying belt for conveying coal flow at equal intervals; the metal detection module consists of a plurality of GMI magnetic sensor arrays;
for each metal detection module, calculating a maximum peak value and a first signal-to-noise ratio of the magnetic field signal;
judging whether a target signal exists or not based on the maximum peak value and the first signal-to-noise ratio; the target signal comprises a defect interference signal, a belt connection part interference signal and a foreign matter signal;
and when the judgment result shows that the target signal exists, excluding the defect interference signal and the belt connection part interference signal, and determining the existence and the position of the foreign matter.
Optionally, after acquiring magnetic field signals at different positions through a plurality of metal detection modules, the method further includes: and preprocessing the magnetic field signal.
Optionally, determining whether a target signal exists based on the maximum peak and the first signal-to-noise ratio includes:
comparing the maximum peak value to the peak threshold value;
comparing the first signal-to-noise ratio to a first signal-to-noise ratio threshold;
determining that a target signal is present when the maximum peak value is greater than the peak threshold value and the first signal-to-noise ratio is greater than the first signal-to-noise ratio threshold value.
Optionally, excluding the defect interference signal and the belt connection portion interference signal, and determining the existence and the position of the foreign object specifically includes:
counting the number of the peak values of the magnetic field signals which are larger than the peak value threshold value;
when the number is the same as the number of the GMI magnetic sensors or the difference value of the numbers is smaller than a number threshold value, determining the target signal as a belt connection part interference signal; otherwise, determining the target signal as a foreign matter signal or a defect interference signal;
when the fluctuation amplitude of the magnetic field signal is smaller than a fluctuation preset range, determining the target signal as a defect interference signal;
performing wavelet transformation on the magnetic field signal with the amplitude fluctuation amplitude larger than a preset range, and then calculating a second signal-to-noise ratio;
when the second signal-to-noise ratio is smaller than a second signal-to-noise ratio threshold value, determining that the target signal is a defect interference signal;
when the second signal-to-noise ratio is larger than or equal to the second signal-to-noise ratio threshold value, counting the number of points of head-to-tail jumping points of the magnetic field signal;
when the point number is smaller than the point number threshold value, determining the target signal as a defect interference signal, otherwise determining the target signal as a foreign matter signal;
and after the existence of the foreign matter is determined, determining the position of the foreign matter according to the positions of the head-tail jumping points of the magnetic field signals.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
according to the invention, the metal foreign body detection module is arranged below the belt to detect the size and the change of the induction magnetic field in real time, when metal foreign bodies appear in coal flow conveyed by the belt, the magnetic field generates abnormal waveform change, and the defect interference and the connection part interference of the conveying belt are eliminated through the conversion and the change of an algorithm, so that the detection and the positioning of the metal foreign bodies are finally realized. The invention is not influenced by water mist, coal slime and coal dust, once the metal foreign bodies move along with the conveying belt, the invention can accurately detect and timely warn to remind workers to remove potential safety hazards in time, thereby ensuring safe production and eliminating the potential safety hazards in early-stage prevention work.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without inventive exercise.
Fig. 1 is a deployment diagram of a mining conveyor belt foreign matter monitoring device based on a GMI magnetic sensor provided by the invention;
fig. 2 is a flow chart of a method for monitoring foreign matters on a mining conveyor belt based on a GMI magnetic sensor, provided by the invention;
FIG. 3 is a waveform diagram of a frame of magnetic field signals;
FIG. 4 is a waveform diagram of a magnetic field signal without a foreign object;
FIG. 5 is a waveform diagram of a magnetic field signal when a foreign object is present;
FIG. 6 is a graph of a substrate noise waveform;
FIG. 7 is a waveform diagram after the substrate noise differentiation;
FIG. 8 is a waveform diagram of a defect interference signal;
FIG. 9 is a waveform diagram after difference of defect interference signals;
FIG. 10 is a waveform diagram of a target signal;
FIG. 11 is a waveform diagram after differentiation of a target signal;
FIG. 12 is a general waveform diagram of a connection interference signal without a foreign object;
FIG. 13 is a partial enlarged waveform diagram of a connection interference signal when no foreign object is present;
FIG. 14 is a partial waveform diagram of a foreign object signal;
fig. 15 is a waveform diagram after wavelet transform of a foreign matter signal;
FIG. 16 is a partial waveform of a defect signal;
FIG. 17 is a waveform diagram after wavelet transform of a defect signal;
FIG. 18 is a waveform diagram of a trip point of a foreign object signal;
FIG. 19 is a diagram of a defect signal trip point waveform.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the 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 invention.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.
As shown in fig. 1, the invention provides a GMI magnetic sensor-based mining conveyor belt foreign matter monitoring device, which comprises: module, encoder, intelligent analysis terminal, audio alert are surveyed to a plurality of metals.
A plurality of metal detection modules are equidistantly arranged below an upper transmission belt for transporting coal flows and are used for acquiring magnetic field signals at different positions. In practical application, one detection module is composed of 4 GMI magnetic sensor arrays, and 3 magnetic foreign object detection modules are arranged at equal intervals, so that foreign objects on a 1.6-meter conveying belt can be monitored in a transportation state. The metal foreign body detection module based on the GMI magnetic sensor is installed below the upper-layer belt, and the distance between the detection surface and the belt is about 3 cm.
The encoder is connected with the metal detection module and used for controlling the metal detection module to acquire magnetic field signals at different positions within a set time interval. In practical application, a proper position is selected to be directly contacted with the bottom belt, the purpose is to synchronously move along with the conveying belt, and the function is equivalent to that the odometer accurately tells the position where the metal foreign matters stay after the machine is stopped.
The intelligent analysis terminal is connected with the metal detection module through the Ethernet and used for detecting and positioning the foreign matters according to the magnetic field signals.
And the voice alarm is connected with the intelligent analysis terminal and used for alarming when the foreign body is detected.
The apparatus provided by the invention further comprises: and the direct-current voltage-stabilizing power supply is respectively connected with the metal detection module, the intelligent analysis terminal and the voice alarm and is used for supplying power to the metal detection module, the intelligent analysis terminal and the voice alarm.
All modules in the GMI magnetic sensor-based mining conveyor belt foreign matter monitoring device are mining intrinsic safety type.
When the conveyer belt (i.e. the transmission belt) runs, the detection module reads magnetic field signals at certain intervals under the control of an encoder (synchronously moving with the transmission belt), then carries out analog-digital conversion on the magnetic field signals, uploads an intelligent analysis terminal through the Ethernet, wherein the intelligent analysis terminal is responsible for collecting, storing, preprocessing (including filtering, binaryzation, correlation, interpolation, framing and the like) of measurement data, analyzing and diagnosing metal foreign matters, finally controls a voice alarm, a de-ironing separator, a PLC (programmable logic controller) and start-stop equipment, and simultaneously sends related measurement data and analysis and diagnosis results to a computer and a server, thereby further completing the storage, summarization, statistics, storage and reporting of monitoring information, notifying a related management department in a short message form and providing access, control and query for remote users in a web mode.
Aiming at the device, the invention also provides a GMI magnetic sensor-based mining conveyor belt foreign matter monitoring method, as shown in FIG. 2, the method comprises the following steps:
step 1: collecting magnetic field signals at different positions through a plurality of metal detection modules; the metal detection modules are arranged below an upper-layer conveying belt for conveying coal flows at equal intervals; the metal detection module is composed of a plurality of GMI magnetic sensor arrays.
After the magnetic field signals at different positions are acquired by the plurality of metal detection modules, the magnetic field signals also need to be preprocessed, filtered, binarized, correlated, interpolated, framed and the like.
Step 2: for each of the metal detection modules, a maximum peak value and a first signal-to-noise ratio of the magnetic field signal are calculated.
And step 3: judging whether a target signal exists or not based on the maximum peak value and the first signal-to-noise ratio; the target signals include a defect interference signal, a belt connection portion interference signal, and a foreign matter signal. The method specifically comprises the following steps: comparing the maximum peak value to the peak threshold value; comparing the first signal-to-noise ratio to a first signal-to-noise ratio threshold; determining that a target signal is present when the maximum peak value is greater than the peak threshold value and the first signal-to-noise ratio is greater than the first signal-to-noise ratio threshold value.
And 4, step 4: and when the judgment result shows that the target signal exists, excluding the defect interference signal and the belt connection part interference signal, and determining the existence and the position of the foreign matter. The method specifically comprises the following steps: counting the number of the peak values of the magnetic field signals which are larger than the peak value threshold value; when the number is the same as that of the GMI magnetic sensors or the difference value of the numbers is smaller than a number threshold value, determining that the target signal is a belt connection part interference signal; otherwise, determining the target signal as a foreign matter signal or a defect interference signal; when the fluctuation amplitude of the magnetic field signal is smaller than a preset fluctuation range, determining that the target signal is a defect interference signal; performing wavelet transformation on the magnetic field signal with the amplitude fluctuation amplitude larger than the preset range and then calculating a second signal-to-noise ratio; when the second signal-to-noise ratio is smaller than a second signal-to-noise ratio threshold value, determining that the target signal is a defect interference signal; when the second signal-to-noise ratio is larger than or equal to the second signal-to-noise ratio threshold value, counting the number of points of head-tail jumping points of the magnetic field signal; when the point number is smaller than the point number threshold value, determining the target signal as a defect interference signal, otherwise determining the target signal as a foreign matter signal; and after the existence of the foreign matters is determined, determining the positions of the foreign matters according to the positions of the head-tail jumping points of the magnetic field signals.
The metal foreign matter detection device is arranged below the conveyor belt and is relatively close to the conveyor belt, so when the conveyor belt runs, other interferences, such as the self-defect interference and the connection part interference of the conveyor belt, can enter besides foreign matter signals. These interfering signals severely affect the detection of the target signal and must be filtered out.
The method is divided into two parts, wherein the first step is to perform rough measurement judgment and give two results, namely a non-target result and a target result. The judgment can be made by mistake, for example, the defect signal is regarded as a foreign matter signal, but the judgment cannot be missed. And secondly, performing accurate measurement and judgment, and further distinguishing target signals as foreign matter signals, defect interference signals or interference signals of a belt connecting part.
The specific embodiment is as follows:
1. rough judgment algorithm
The objective of the rough measurement algorithm is to judge whether a frame signal possibly has a target signal, and to introduce data possibly having the target signal into the precise judgment algorithm, so as to filter out a lot of invalid data.
(1) Data import
Magnetic field amplitude (amplitude unit is nano-nT) data of different positions collected by 1-M detection modules (generally 11 detection modules can cover a 1.6-meter wide belt) are selected, and each frame of data is analyzed. The detection distance of one frame of the detection module is 512mm, the waveform diagram of one frame is shown in fig. 3, the abscissa represents the number of points (positions), 512 points, and the distance is 512mm.
(2) Calculating maximum peak value and signal-to-noise ratio
1) And respectively calculating peak values of the single-frame data of the M paths, taking the maximum value, comparing the maximum value with a peak value threshold value, screening out data of which the peak value maximum value is greater than the peak value threshold value, considering that the frame data possibly has a target signal, and considering that the frame data has no target signal when the frame data is lower than the peak value threshold value.
2) The waveform of the target signal is generally steeper, so the signal-to-noise ratio is calculated after the difference is carried out on the original magnetic field signal. Carrying out differential calculation on one path of original magnetic field signals with the maximum single-frame peak value screened in the step 1), wherein the differential calculation formula is as follows:
a new set of single frame data is obtained.
The signal-to-noise ratio calculation formula is as follows:
where Ps and Pn represent the effective power of the signal and noise, respectively. And adopting the maximum value of the signals after the difference for Ps, adopting a base value far away from the maximum value for Pn, calculating the signal-to-noise ratio according to the formula, if the value is greater than a first signal-to-noise ratio threshold value, considering that the frame has the possibility of the existence of a target signal, and otherwise, considering that no target exists, and judging the next frame.
Fig. 4 is an original running chart of the conveyor belt without foreign matter, and it can be seen that some defect signals are also detected, and fig. 5 is a waveform chart with foreign matter, and the target amplitude is still relatively strong. Fig. 6 is a waveform of the substrate noise, and fig. 7 is a waveform diagram of the substrate noise after the substrate noise is differentiated, and it can be seen that the maximum value and the substrate ratio after the differentiation are relatively small, and no target signal can be considered. Fig. 8 is a diagram of a defective frame signal selected, and fig. 9 is a waveform diagram of a defective interference signal after differentiation, and it can be seen that the maximum value of the waveform after differentiation and the base ratio are very large, and the signal is identified as a suspected target signal. Fig. 10 is a waveform of one frame with a target signal, fig. 11 is a waveform diagram of the target signal after difference, and similarly, the maximum value of the waveform after difference and the base ratio are large, and the signal is also identified as a suspected target signal.
2. Precise judgment algorithm
After the rough judgment algorithm, the fine judgment algorithm further distinguishes foreign matter signals, defect interference signals and belt connection part interference signals.
(1) Connection interference discrimination and filtering
For link disturbances, the number of sensor peaks above a certain threshold can be counted because it causes a relatively consistent waveform for each sensor and also a high amplitude. After the screening of the rough judgment algorithm, the peak value and the peak value threshold value of the single-frame data of the M paths of sensors are compared, if the number is approximately equal to the total number of the sensors, the interference of the connecting part is considered, and the interference is eliminated. Fig. 12 to 13 show the overall waveform diagram and the partial enlarged view of the connection interference signal in the case of no foreign matter.
(2) Defect interference discrimination and filtering
Filtering the interference signals of the connecting part in the step (1), and then carrying out the steps (1) - (2) - (3) to distinguish:
(1) and judging and filtering small defect interference through amplitude judgment.
(2) And (3) large defect interference judgment: by observing the foreign matter interference waveform and the defect interference waveform, the defect signal frequency is relatively high, and the foreign matter signal frequency is low, and a continuous wavelet transform method is adopted.
The wavelet transform can transform a time signal into a time frequency domain, can better observe the local characteristics of the signal, and can simultaneously observe the time and frequency information of the signal. The wavelet transform formula is as follows:
the wavelet transform has two variables: a scale α (scale) and a translation τ (translation). The scale alpha controls the expansion of the wavelet function, and the translation amount tau controls the translation of the wavelet function. The scale corresponds to frequency (inverse ratio) and the amount of translation corresponds to time.
Selecting a proper fixed scale, utilizing continuous wavelet transformation, then calculating the signal-to-noise ratio SNR, and comparing the signal-to-noise ratio with a second signal-to-noise ratio threshold value, wherein the signal-to-noise ratio smaller than the second signal-to-noise ratio threshold value is defect interference.
Fig. 14 to 17 compare waveforms of the foreign matter signal and the interference signal after wavelet transform, and it can be seen from the graphs that the foreign matter signal is more prominent and enhanced after wavelet transform, and the defect signal is suppressed to some extent compared with the surrounding signal.
(3) The jump point judgment is used for further filtering the defect interference
And for defect interference with a larger signal-to-noise ratio, a jumping point judgment method is adopted for further judgment. Two frames of signals are continuously taken for a frame with larger signal-to-noise ratio, head-to-tail jumping point judgment is carried out on an original magnetic field signal, and a foreign matter signal is considered only if the number of points is larger than a point threshold value. Fig. 18 shows the transition points of the foreign matter signal, where the head and tail transition points are the 126 th point (3310) and the 428 th point (-3270), respectively, and fig. 19 shows the transition points of the defect signal, where the head and tail transition points are the 109 th point (-255) and the 365 th point (-3660), respectively. Through the comparison of the jumping point judgment, the duration of the foreign matter signal is dozens of points longer than that of the defect signal.
(3) Foreign object signal detection
After several rounds of judgment, the defect interference and the connection part interference can be effectively filtered, and finally, the foreign matter signal can be accurately detected.
The invention adopts passive measurement, does not apply any magnetic field, and truly reflects the metal foreign body induction magnetic field; it is not afraid that any non-magnetic conductive material is diffused in the space or attached to the equipment, and the cleaning is not needed. The metal detection module is designed according to the standard, adopts a modular structure, and can be randomly combined and spliced to adapt to belts with different widths. The invention is not affected by water mist and dust, is maintenance-free, and can carry out real-time online, nondestructive, passive, non-contact and non-radiation detection.
In the present specification, the embodiments are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other.
The principles and embodiments of the present invention have been described herein using specific examples, which are provided only to help understand the method and the core concept of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed. In view of the foregoing, the description is not to be taken in a limiting sense.
Claims (7)
1. The utility model provides a mining conveyer belt foreign matter monitoring devices based on GMI magnetic sensor which characterized in that includes:
the metal detection modules are distributed below an upper-layer transmission belt for transporting coal flows at equal intervals and used for collecting magnetic field signals at different positions;
the encoder is connected with the metal detection module and used for controlling the metal detection module to acquire magnetic field signals at different positions within a set time interval;
the intelligent analysis terminal is connected with the metal detection module through Ethernet and used for detecting and positioning the foreign matters according to the magnetic field signals;
and the voice alarm is connected with the intelligent analysis terminal and used for alarming when the foreign body is detected.
2. The GMI magnetic sensor-based mining conveyor belt foreign matter monitoring device according to claim 1, wherein the metal detection module is composed of a plurality of GMI magnetic sensor arrays.
3. The GMI magnetic sensor-based mining conveyor belt foreign matter monitoring device according to claim 1, further comprising:
and the direct-current voltage-stabilizing power supply is respectively connected with the metal detection module, the intelligent analysis terminal and the voice alarm and is used for supplying power to the metal detection module, the intelligent analysis terminal and the voice alarm.
4. A mining conveyer belt foreign matter monitoring method based on GMI magnetic sensors is characterized by comprising the following steps:
collecting magnetic field signals at different positions through a plurality of metal detection modules; the metal detection modules are arranged below an upper-layer conveying belt for conveying coal flows at equal intervals; the metal detection module consists of a plurality of GMI magnetic sensor arrays;
for each metal detection module, calculating a maximum peak value and a first signal-to-noise ratio of the magnetic field signal;
judging whether a target signal exists or not based on the maximum peak value and the first signal-to-noise ratio; the target signals comprise defect interference signals, belt connection part interference signals and foreign matter signals;
and when the judgment result shows that the target signal exists, excluding the defect interference signal and the belt connection part interference signal, and determining the existence and the position of the foreign matter.
5. The GMI magnetic sensor-based mining conveyor belt foreign matter monitoring method according to claim 4, wherein after the magnetic field signals at different positions are collected by the plurality of metal detection modules, the method further comprises the following steps: and preprocessing the magnetic field signal.
6. The GMI magnetic sensor-based mining conveyor belt foreign object monitoring method according to claim 4, wherein the judging whether a target signal exists or not based on the maximum peak value and the first signal-to-noise ratio specifically comprises:
comparing the maximum peak value to the peak threshold value;
comparing the first signal-to-noise ratio to a first signal-to-noise ratio threshold;
determining that a target signal is present when the maximum peak value is greater than the peak value threshold and the first signal-to-noise ratio is greater than the first signal-to-noise ratio threshold.
7. The GMI magnetic sensor-based mining conveyor belt foreign matter monitoring method according to claim 4, wherein the defect interference signal and the belt connection part interference signal are eliminated, and the existence and the position of foreign matter are determined, specifically comprising:
counting the number of the peak values of the magnetic field signals which are larger than the peak value threshold value;
when the number is the same as that of the GMI magnetic sensors or the difference value of the numbers is smaller than a number threshold value, determining that the target signal is a belt connection part interference signal; otherwise, determining the target signal as a foreign matter signal or a defect interference signal;
when the fluctuation amplitude of the magnetic field signal is smaller than a fluctuation preset range, determining the target signal as a defect interference signal;
performing wavelet transformation on the magnetic field signal with the amplitude fluctuation amplitude larger than the preset range and then calculating a second signal-to-noise ratio;
when the second signal-to-noise ratio is smaller than a second signal-to-noise ratio threshold value, determining that the target signal is a defect interference signal;
when the second signal-to-noise ratio is larger than or equal to the second signal-to-noise ratio threshold value, counting the number of points of head-to-tail jumping points of the magnetic field signal;
when the point number is smaller than the point number threshold value, determining the target signal as a defect interference signal, otherwise determining the target signal as a foreign matter signal;
and after the existence of the foreign matters is determined, determining the positions of the foreign matters according to the positions of the head-tail jumping points of the magnetic field signals.
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