WO2020133954A1 - Procédé et dispositif d'analyse de performance numérique - Google Patents

Procédé et dispositif d'analyse de performance numérique Download PDF

Info

Publication number
WO2020133954A1
WO2020133954A1 PCT/CN2019/091610 CN2019091610W WO2020133954A1 WO 2020133954 A1 WO2020133954 A1 WO 2020133954A1 CN 2019091610 W CN2019091610 W CN 2019091610W WO 2020133954 A1 WO2020133954 A1 WO 2020133954A1
Authority
WO
WIPO (PCT)
Prior art keywords
metal
sampling data
product
group
detection rate
Prior art date
Application number
PCT/CN2019/091610
Other languages
English (en)
Chinese (zh)
Inventor
徐东
吴正
Original Assignee
帝沃检测技术(上海)有限公司
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by 帝沃检测技术(上海)有限公司 filed Critical 帝沃检测技术(上海)有限公司
Publication of WO2020133954A1 publication Critical patent/WO2020133954A1/fr

Links

Images

Classifications

    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N27/00Investigating or analysing materials by the use of electric, electrochemical, or magnetic means
    • G01N27/72Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating magnetic variables
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01VGEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V3/00Electric or magnetic prospecting or detecting; Measuring magnetic field characteristics of the earth, e.g. declination, deviation
    • G01V3/38Processing data, e.g. for analysis, for interpretation, for correction
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02PCLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/30Computing systems specially adapted for manufacturing

Definitions

  • the invention relates to the field of metal detectors, in particular to a digital performance analysis method and equipment.
  • the signal value of a normal product may jump within 100, when mixed with a certain size of metal foreign objects (such as 1.5mm), it will produce a larger signal that may be 300 or even 500.
  • the set threshold is 300, then any product whose signal value exceeds 300 is considered unqualified, that is, the metal detector determines that it has metal; at the same time, due to various reasons, even if the same foreign object passes repeatedly
  • the signal value generated each time is also different.
  • the current threshold setting is usually set according to the user's experience, but this threshold selected based on experience is different due to the uncertainty of the metal detector, the use environment and the feeling of each person.
  • the purpose of the present invention is to provide a digital performance analysis method and equipment, which selects a threshold based on reliable quantitative data, which not only meets the needs of low false detection rate but also realizes scientific monitoring of low missed detection rate.
  • a digital performance analysis method includes: acquiring a set of metal-free product sampling data and at least one set of metal-containing product sampling data; based on the metal-free product sampling data and the metal-containing product sampling data Distribution rule, calculate the product misdetection rate group corresponding to the metal-free product sampling data and the missing detection rate group corresponding to each group of metal-containing product sampling data; according to the product misdetection rate group, each group contains Metal product sampling data corresponding to the requirements of the missed detection rate group and false detection missed detection rate, select the corresponding value as the threshold.
  • appropriate thresholds are selected according to the requirements of false detection rate and missed detection rate, so that the selection of thresholds is supported by effective quantitative data ,
  • the selected threshold is more in line with the actual use requirements, reduce the false detection rate, missed detection rate, improve the monitoring efficiency of product quality and the quality of quality management work.
  • the product misdetection rate group corresponding to the metal-free product sampling data and each group of metal-containing product sampling are calculated
  • the missing detection rate group corresponding to each data includes: when the sampling data of the metal-free product and the sampling data of the metal-containing product conform to the normal distribution law, according to a preset normal formula, a preset limit parameter, the Sampling data of metal-free products and sampling data of each of the metal-containing products to calculate the product misdetection rate group corresponding to the metal-free product sampling data and the corresponding missing detection of each group of metal-containing product sampling data Rate group.
  • a preset normal formula may be used to calculate the missed detection rate group and the false detection rate group.
  • the preset limit parameter, the metal-free product sampling data and each of the metal-containing product sampling data the corresponding data of the metal-free product sampling data is calculated
  • the product false detection rate group and the corresponding missing detection rate group of each group of metal-containing product sampling data include: according to the metal-free product sampling data, calculate the corresponding product (signal) average and product standard deviation; For each group of metal-containing product sampling data, calculate the metal (signal) average and metal standard deviation corresponding to each group of metal-containing product sampling data; according to the product average, the product standard deviation, The preset limit parameter and the preset normal formula to calculate the product false detection rate group corresponding to the metal-free product sampling data; according to the preset limit parameter, the preset normal formula and each group of the The metal mean value and metal standard deviation corresponding to the metal-containing product sampling data are respectively calculated to obtain the missing detection rate group corresponding to each group of metal-containing product sampling data.
  • the preset limit parameters include: a minimum threshold, a maximum threshold, and a threshold interval value.
  • the setting of the maximum/small threshold can eliminate unnecessary data calculation and reduce the amount of calculation.
  • selecting the corresponding value as the threshold includes: according to each group containing Metal product sampling data corresponding to the missed detection rate group and the product misdetection rate group, draw a corresponding graph; according to the false detection missed detection rate requirements, select the corresponding value from the graph as a threshold.
  • the step S1 obtaining a set of metal-free product sampling data and at least one set of metal-containing product sampling data includes: when a certain time interval is reached, obtaining a set of metal-free product sampling data and at least one set of Metal product sampling data;
  • Step S2 calculates the product false detection rate corresponding to the metal-free product sampling data according to the distribution rule of the metal-free product sampling data and the metal-containing product sampling data
  • the missing detection rate group corresponding to the sampling data of each group and each group of metal-containing product sampling data includes: according to the distribution rule of the sampling data of the metal-free product and the sampling data of the metal-containing product obtained at a certain time interval, the calculated Describe the product false detection rate group corresponding to the metal-free product sampling data and the corresponding missing detection rate group for each group of metal-containing product sampling data.
  • the sampling data is periodically obtained, and the threshold value is periodically monitored, so that the threshold value of the metal detector meets actual production requirements.
  • the step S3 selects the corresponding value as the threshold according to the requirements of the product misdetection rate group, each group of metal-containing product sampling data corresponding to the missed detection rate group and the false detection missed detection rate, and further includes: The set threshold meets the requirements of the false detection and miss detection rate, this threshold is still used; when the set threshold does not meet the requirements of the false detection and miss detection rate, according to the product false detection rate group, each group contains metal The product sampling data corresponding to the requirements of the missed detection rate group and the false detection missed detection rate, re-select the corresponding value to update or prompt to update the threshold.
  • the present invention also provides a digital performance analysis device, including: an acquisition module for acquiring a set of metal-free product sampling data and at least one set of metal-containing product sampling data; a calculation module for calculating according to the metal-free product Product sampling data and the distribution law of the metal-containing product sampling data, the product misdetection rate group corresponding to the metal-free product sampling data and the corresponding missing detection rate of each group of metal-containing product sampling data are calculated Group; a selection module, used to select the corresponding value as the threshold according to the requirements of the product false detection rate group, the corresponding leakage detection rate group and the false detection leakage detection rate of each group of metal-containing product sampling data.
  • an appropriate threshold is selected according to the requirements of false detection and missed detection rate, so that the selection of the threshold is supported by effective quantitative data.
  • the threshold is more in line with the actual use requirements, reducing the false detection rate and missed detection rate, and improving the monitoring of product quality.
  • the calculation module is configured to calculate a product false detection rate group corresponding to the metal-free product sampling data according to the distribution rule of the metal-free product sampling data and the metal-containing product sampling data
  • the missing detection rate group corresponding to each group of metal-containing product sampling data includes: the calculation module, when the metal-free product sampling data and the metal-containing product sampling data conform to the normal distribution law, according to A preset normal formula, a preset limit parameter, the sampling data of the metal-free product and the sampling data of each metal-containing product, and the product misdetection rate group corresponding to the sampling data of the metal-free product is calculated Each group of metal-containing product sampling data corresponds to the corresponding missed detection rate group.
  • the calculation module calculates the metal-free product sampling data according to a preset normal formula, a preset limit parameter, the metal-free product sampling data and each metal-containing product sampling data
  • the corresponding product false detection rate group and the corresponding missing detection rate group for each group of metal-containing product sampling data include: the calculation module, calculating the corresponding product average and product standard based on the metal-free product sampling data Difference; and, according to each group of the metal-containing product sampling data, calculate the metal mean and metal standard deviation corresponding to each group of the metal-containing product sampling data; and, according to the product average, the product The standard deviation, the preset limit parameter and the preset normal formula to calculate the product false detection rate group corresponding to the metal-free product sampling data; and, according to the preset limit parameter and the preset normal formula
  • the metal mean value and metal standard deviation corresponding to the sampling data of each group of metal-containing products are respectively calculated, and the missed detection rate group corresponding to the sampling data of each group of metal-containing products is calculated respectively.
  • the selection module is configured to select the corresponding value as the threshold according to the requirements of the product false detection rate group, the corresponding missing detection rate group and the false detection leakage detection rate of each group of metal-containing product sampling data, including:
  • the drawing sub-module is used to draw the corresponding curve graph according to the corresponding missing detection rate group and the product false detection rate group of each group of metal-containing product sampling data; It is required to select the corresponding value from the graph as the threshold.
  • a camera module for real-time acquisition of the working state of the metal detector; the acquisition module is further used for identifying a set of metal-free product sampling data based on the real-time acquired working state of the metal detector and Sampling data for at least one set of metal-containing products.
  • the working state of the metal detector is obtained through the camera module to obtain the sampling data, the application range is wider, and the compatibility is higher.
  • the acquisition module is further configured to acquire a set of product sampling data containing no metal and at least one set of product sampling data containing metal when a certain time interval is reached.
  • the selection module is further configured to use the threshold when the set threshold meets the requirements of the false detection and miss detection rate; and, when the set threshold does not meet the requirements of the false detection and miss detection rate, Then, according to the requirements of the product misdetection rate group, each group of metal-containing product sampling data corresponding to the missed detection rate group and the false detection missed detection rate, the corresponding value is reselected to update or prompt to update the threshold.
  • the invention selects a suitable threshold value according to the requirements of the false detection rate and the missed detection rate according to the distribution rules of the metal-free product sampling data and the metal-containing product sampling data, so that the selection of the threshold is supported by effective quantitative data, and the selected threshold It is more in line with the actual use requirements, reduces the false detection rate, controls the missed detection rate, and improves product quality monitoring.
  • FIG. 3 is an interface display diagram of an embodiment of sampling data and preset limit parameters of the present invention.
  • 5 is a schematic diagram of an embodiment of the lowest limit value when selecting a threshold
  • FIG. 6 is a schematic diagram of the highest limit value when selecting the threshold value in FIG. 5;
  • FIG. 7 is a schematic structural diagram of an embodiment of a digital performance analysis device of the present invention.
  • FIG. 8 is a schematic structural diagram of another embodiment of the digital performance analysis device of the present invention.
  • FIG. 9 is a flowchart of another embodiment of the digital performance analysis method of the present invention.
  • the working principle of the metal detector is electromagnetic induction technology. There is a specially designed electromagnetic coil inside the metal detector. When the metal ball passes, it will cause changes in the electromagnetic field. The receiving circuit part detects this weak signal change, combined with a certain technology Means, through certain analysis and processing, the final determination of whether there is metal foreign matter in the product, and the threshold setting is the basis for the metal detector judgment.
  • the false detection rate refers to the rate at which normal products are judged to contain metals when the threshold is too low.
  • the missed detection rate is the rate at which products containing metals are judged to be normal products when the threshold is too high, thus failing to detect. Therefore, the reasonable setting of the threshold is very important.
  • the set threshold is getting lower and lower. This threshold has been approaching the normal signal value area of the product, such as 200, 190, 180, 130, 120, 100, 90, etc. Threshold After a gradual decrease, it will lead to an increase in false detections. Excessively high false detection rates will bring greater economic losses. The selection of thresholds based on experience alone cannot meet production needs and improve quality.
  • the digital performance analysis method is equivalent to an arithmetic program, which can be installed on the metal detector, or can be installed on another independent device to serve each metal detector.
  • FIG. 1 shows an embodiment of the present invention.
  • a digital performance analysis method includes:
  • S101 Obtain a set of sampling data of products containing no metal and at least one set of sampling data of products containing metal.
  • the sampling data of products without metal refers to the data obtained by the product itself passing through the metal detector.
  • sampling data refers to the data contained in the products containing related metal-over-metal detectors.
  • the implementation method is to put three different metals into the product to test the corresponding groups of metal-containing Product sampling data.
  • the number of sampled data in each group is set according to the actual accuracy, and can be any number.
  • metal balls for example: 1.5mm diameter iron beads, 2.0mm non-ferrous metal beads, 2.5mm stainless steel beads
  • the number of sampled data should be as much as possible, for example: set 200, 150, etc. in each group to improve Accuracy.
  • metal detectors due to the current technical reasons, the detection of metal detectors will be different due to the different shapes of metal foreign objects. For example: a wire with a diameter of 1mm and a length of 10mm may be detected at an angle , But it may not be detected after rotating a certain angle (for example: 90 degrees), so it is recommended to use the sphere as a standard.
  • the sampled data is obtained by the metal detector.
  • the program corresponding to the digital performance analysis method runs on the metal detector, it can be called directly; when this program is run on equipment other than the metal detector, it can be sent by the metal detector. It can also be identified by the camera module during the monitoring process of the metal detector.
  • the specific acquisition method of sampling data is not limited here.
  • S102 calculates the product misdetection rate group corresponding to the metal-free product sampling data and the missing detection corresponding to each group of metal-containing product sampling data according to the distribution rules of the metal-free product sampling data and the metal-containing product sampling data Rate group.
  • the product misdetection rate group is composed of the product misdetection rate corresponding to the sampling data of products containing no metal at different thresholds; a group of missed detection rate group refers to the corresponding missed detection of a group of metal-containing product sampling data at different thresholds Rate composition.
  • S103 selects the corresponding value as the threshold according to the product misdetection rate group, the corresponding misdetection rate group corresponding to each group of metal-containing product sampling data, and the actual misdetection miss detection rate requirements.
  • the false detection and missed detection rate requirements are determined according to the actual situation, for example: the false detection rate is required to be less than 0.1%, and the missed detection rate is also required to be less than 0.1%. Choose the value that satisfies less than 0.1% at the same time as the threshold.
  • S103 selects the corresponding value as the threshold according to the requirements of the product misdetection rate group, the corresponding misdetection rate group and the misdetection miss rate of each metal-containing product sampling data, including:
  • the calculated missed detection rate groups and product misdetection rate groups are drawn into corresponding graphs, so that users can intuitively understand the false detection rate and missed detection rate corresponding to each value, and understand the threshold value conveniently and quickly. Choose a reason.
  • the product false detection rate group is drawn to the left curve, and the three groups of metal-containing product sampling data corresponding to the missing detection rate group are drawn to the right three curves, when the false detection rate is required to be below 1 ⁇ It can be seen from Figures 5 and 6 that as long as the t value is set between 233 and 327, the product false detection rate of less than 1 ⁇ and the metal leakage detection rate can be ensured at the same time to ensure good production.
  • the threshold can be increased appropriately while ensuring the safe detection rate of the metal, as long as it does not exceed 327, that is, the adjustable range of the site is allowed to be 233-327, rather than relying on people The sense that the quantified numerical range improves quality control standards and quality.
  • an appropriate threshold is selected according to the requirements of the false detection rate and the missing detection rate, so that the selection of the threshold is supported by effective quantitative data.
  • the threshold value is more in line with the actual use requirements, reducing the false detection rate and missed detection rate, and improving the more accurate monitoring of product quality.
  • FIG. 2 shows another embodiment of the present invention.
  • a digital performance analysis method includes:
  • S201 acquires a set of sampling data of products containing no metal and at least one set of sampling data of products containing metal.
  • S202 calculates the product false detection rate group corresponding to the metal-free product sampling data and the missed detection corresponding to each group of metal-containing product sampling data according to the distribution rules of the metal-free product sampling data and the metal-containing product sampling data Rate groups include:
  • the preset normal formula and the preset limit parameters include: minimum threshold, maximum threshold and threshold interval value
  • metal-free product sampling data and each metal-containing product sampling data calculate the product misdetection rate group corresponding to the metal-free product sampling data and the corresponding missing detection rate group for each group of metal-containing product sampling data .
  • the preset limit parameter refers to the threshold range of the metal detector, and an appropriate minimum threshold, maximum threshold, and threshold interval value are set according to actual detection requirements.
  • the maximum threshold can be set to 1500, the minimum threshold is 5, and the threshold interval value is 1.
  • these data can be flexibly changed, for example: the maximum threshold is set to 1400, the minimum threshold is 10, the threshold interval value is 3 and so on. If the maximum threshold exceeds the value corresponding to the largest metal block, it is meaningless, and only unnecessary calculations are done. Therefore, the corresponding preset limit parameters can be set according to the actual metal detection requirements.
  • the normal distribution law has its corresponding statistical formula, which can be set as a preset normal formula for subsequent calculations.
  • S212 calculates according to a preset normal formula, a preset limit parameter (the preset limit parameter includes: a minimum threshold, a maximum threshold, and a threshold interval value), sampling data of metal-free products and sampling data of each metal-containing product
  • a preset limit parameter includes: a minimum threshold, a maximum threshold, and a threshold interval value
  • sampling data of metal-free products and sampling data of each metal-containing product include:
  • S2121 calculates the corresponding product average and product standard deviation based on the sampling data of products that do not contain metals
  • S2122 calculates the metal average and metal standard deviation corresponding to each group of metal sampling data according to the metal sampling data of each group.
  • the average value is the sum of the sampled data divided by the total number.
  • the standard deviation is calculated according to the following formula:
  • is the standard deviation
  • is the average value
  • ⁇ i is the ith data in a group of product sampling data
  • N is the total number of a group of product sampling data.
  • S2123 calculates the product false detection rate group corresponding to the metal-free product sampling data based on the product average, product standard deviation, preset limit parameters and preset normal formula;
  • S2124 calculates the leak detection rate group corresponding to each group of metal-containing product sampling data according to the preset limit parameters, the preset normal formula, and the respective metal average and metal standard deviation of each group of metal-containing product sampling data.
  • the preset normal formula is:
  • is the standard deviation
  • is the average value
  • x is the threshold
  • the threshold interval value is used for incremental calculation
  • F is the calculated probability.
  • Substituting different values of x into the above formula can calculate the sum of the probabilities less than or equal to the value of x. For products, values below x are normal, and values above x are false detections; for metals, values above x The value belongs to detection, and the value lower than x belongs to missing detection.
  • S203 selects the corresponding value as the threshold according to the product misdetection rate group, the corresponding misdetection rate group of each metal-containing product sampling data, and the actual misdetection leak detection rate requirements.
  • S203 selects the corresponding value as the threshold according to the product misdetection rate group, the corresponding misdetection rate group of each metal-containing product sampling data, and the false detection miss detection rate requirements, including:
  • S213 draws the corresponding curve chart according to the corresponding missing detection rate group and product false detection rate group of each group of metal-containing product sampling data; S223 selects the corresponding value from the curve chart as the threshold according to the requirements of the false detection leakage detection rate .
  • a digital performance analysis method includes:
  • S301 When a certain time interval is reached, acquire (preferably, the closest to the current time) a set of metal-free product sampling data and at least one set of metal-containing product sampling data.
  • S302 calculates the product false detection rate group corresponding to the metal-free product sampling data and each group of metal-containing product sampling data according to the distribution rules of the metal-free product sampling data and the metal-containing product sampling data obtained at a certain time interval The corresponding missed detection rate group.
  • S303 selects the corresponding value as the threshold according to the requirements of the product misdetection rate group, the corresponding misdetection rate group and the misdetection miss rate of each metal-containing product sampling data.
  • the threshold value selection in this embodiment may be periodically performed when actually used, and when a certain time interval is set sufficiently small, real-time monitoring may be achieved.
  • the metal detector selects a set of metal-free product sampling data and at least one set of metal-containing product sampling data based on the sampling data obtained in real time, and performs real-time/periodical calculations. Choose reasonable data as the threshold.
  • the metal detector When other equipment is used to monitor the threshold of the metal detector, it can monitor the metal detector in real time, obtain each sampling data in real time, select a set of product sampling data without metal and at least one set of product sampling data with metal for real-time /Periodic calculation, select reasonable data as threshold for metal detector.
  • a certain amount of data closest to the current time is taken for analysis, so that the calculation result is more in line with the current situation.
  • each group of metal-containing product sampling data corresponding to the missed detection rate group and the false detection missed detection rate selecting the corresponding value as the threshold includes:
  • the metal detector has been set with a threshold (may be a value set based on experience or a value selected based on the result calculated in real time), and put into actual product monitoring
  • a threshold may be a value set based on experience or a value selected based on the result calculated in real time
  • the currently set threshold may not meet the low miss detection rate of the metal and the low false detection rate of the product.
  • the product false detection rate group corresponding to the metal-free product sampling data is calculated and each group of metal-containing product sampling data corresponds to each The missed detection rate group includes:
  • the preset limit parameters the sampling data of metal-free products and the sampling data of each metal-containing product, The product misdetection rate group corresponding to the metal-free product sampling data and the missing detection rate group corresponding to each group of metal-containing product sampling data are calculated.
  • the preset limit parameters, the metal-free product sampling data and the metal-containing product sampling data, the product false detection rate group and each corresponding to the metal-free product sampling data are calculated
  • Groups of metal-containing product sampling data corresponding to the missing detection rate group include:
  • the preset limit parameters include: minimum threshold, maximum threshold and threshold interval value
  • the preset normal formula the product error corresponding to the sample data of metal-free products is calculated Inspection rate group
  • the leak detection rate group corresponding to the sample data of each group of metal-containing products is calculated.
  • the selection of the corresponding value as the threshold includes:
  • periodic/real-time monitoring is performed on the selection of the threshold to ensure that the threshold set by the metal detector can meet the actual production needs.
  • FIG. 7 shows an embodiment of a digital performance analysis device of the present invention, including:
  • the obtaining module 10 is used to obtain a set of sampling data of products containing no metal and at least one set of sampling data of products containing metal.
  • the sampling data of products without metal refers to the data obtained by the product itself passing through the metal detector.
  • sampling data refers to the data contained in the products containing related metal-over-metal detectors.
  • the implementation method is to put three different metals into the product to test the corresponding groups of metal-containing Product sampling data.
  • the number of sampled data in each group is set according to the actual accuracy, and can be any number. For example, as shown in Fig. 3, there are 4 sets of sampling data, one of which is the product sampling data of metal-free products, and the other three are the sampling data of metal-containing products. Each group has 100 data.
  • metal balls for example: 1.5mm diameter iron beads, 2.0mm non-ferrous metal beads, 2.5mm stainless steel beads.
  • metal detection ⁇ Obtained Due to the influence of various complex and inevitable objective factors, such as speed when passing, relative machine position, running track, conveyor belt, vibration, product temperature, ambient temperature, power supply voltage, atmospheric pressure, static electricity, complex electromagnetic in the workshop The environment and so on cause the signal of the metal ball to be almost the same every time it passes. Therefore, the number of sampled data should be as much as possible, for example: set 200, 150, etc. in each group to improve accuracy.
  • metal detectors due to the current technical reasons, the detection of metal detectors will be different due to the different shapes of metal foreign objects. For example: a wire with a diameter of 1mm and a length of 10mm may be detected at an angle , But it may not be detected after rotating a certain angle (for example: 90 degrees), so it is recommended to use the sphere as a standard.
  • Sampling data is obtained through metal detector monitoring.
  • the program corresponding to the digital performance analysis method runs on the metal detector, it can be directly called; when this program runs on equipment other than the metal detector, it can be sent by the metal detector It can also be identified by the camera module during the monitoring process of the metal detector.
  • the specific acquisition method of sampling data is not limited here.
  • the digital performance analysis device further includes: a camera module for real-time acquisition of the working state of the metal detector; the acquisition module 10 is further used for The working status of the metal detector acquired in real time identifies a set of product sampling data without metal and at least one set of product sampling data with metal.
  • the camera module is composed of several camera devices, and each camera device is used to monitor one or more metal detectors, and it photographs the working state of the metal detector (for example: test results when testing products and products containing metals)
  • Recognition and interpretation by the acquisition module 10 for example, the conversion of pictures to values according to the captured pictures, to obtain a set of product sampling data without metal and at least one set of product sampling data with metal.
  • the functions of the acquisition module 10, the calculation module 20, and the selection module 30 can be performed by one computer/server.
  • the camera device is connected to the computer/server (for example: each camera transmits the captured video signal to the computer/server via a network device through a high-speed data communication line.
  • the high-speed data communication line can be Ethernet, corporate LAN, or the Internet , Can also be various high-speed communication lines including USB) to ensure data transmission between the two.
  • the camera device can also work independently, and it automatically reminds when it finds that the false detection rate and the missing detection rate of the metal detector need to be adjusted.
  • the calculation module 20 is used to calculate the product misdetection rate group corresponding to the metal-free product sampling data and each group of metal-containing product sampling data according to the distribution rule of the metal-free product sampling data and the metal-containing product sampling data The corresponding missed detection rate group.
  • the selection module 30 is used to select the corresponding value as the threshold according to the requirements of the product false detection rate group, the corresponding missing detection rate group of each group of metal-containing product sampling data, and the actual false detection leakage detection rate.
  • the false detection and missed detection rate requirements are determined according to the actual situation, for example: the false detection rate is required to be less than 0.1%, and the missed detection rate is also required to be less than 0.1%. Choose the value that satisfies less than 0.1% at the same time as the threshold.
  • the selection module 30 is configured to select the corresponding value as the threshold according to the product false detection rate group, the corresponding missing detection rate group of each group of metal-containing product sampling data, and the actual false detection missing detection rate requirements:
  • the drawing sub-module 31 is used to draw a corresponding graph according to the corresponding missing detection rate group and product false detection rate group of each group of metal-containing product sampling data;
  • the selection sub-module 32 is used to select the corresponding value from the graph as the threshold according to the false detection and miss detection rate requirements.
  • the calculated missed detection rate groups and product misdetection rate groups are drawn into corresponding graphs, so that users can intuitively understand the false detection rate and missed detection rate corresponding to each value, and understand the threshold value conveniently and quickly. Choose a reason.
  • an appropriate threshold is selected according to the requirements of the false detection rate and the missing detection rate, so that the selection of the threshold is supported by effective quantitative data.
  • the threshold is more in line with the actual use requirements, reducing the false detection rate and the missed detection rate, and improving the monitoring of product quality.
  • FIG. 8 shows another embodiment of a digital performance analysis device, including:
  • the obtaining module 10 is configured to obtain a set of product sampling data without metal and at least one set of product sampling data with metal.
  • the digital performance analysis device further includes: a camera module 40 for acquiring the working state of the metal detector in real time; the acquisition module 10 It is further used to identify a set of metal-free product sampling data and at least one set of metal-containing product sampling data based on the working status of the metal detector acquired in real time.
  • the calculation module 20 is used to calculate the product misdetection rate group corresponding to the metal-free product sampling data and each group of metal-containing product sampling data according to the distribution rule of the metal-free product sampling data and the metal-containing product sampling data
  • the corresponding missed detection rate groups include:
  • the calculation module 20 when the sampling data of the product containing no metal and the sampling data of the product containing metal conform to the normal distribution law, according to the preset normal formula and the preset limit parameters (the preset limit parameters include: the minimum threshold, the maximum threshold and (Threshold interval value), metal-free product sampling data and each metal-containing product sampling data, the product misdetection rate group corresponding to the metal-free product sampling data and the corresponding leakage of each group of metal-containing product sampling data are calculated. Inspection rate group.
  • the preset limit parameter refers to the threshold range of the metal detector, and an appropriate minimum threshold, maximum threshold, and threshold interval value are set according to actual detection requirements.
  • the maximum threshold can be set to 1500, the minimum threshold is 5, and the threshold interval value is 1.
  • these data can be flexibly changed, for example: the maximum threshold is set to 1400, the minimum threshold is 10, the threshold interval value is 3 and so on.
  • the normal distribution law has its corresponding statistical formula, which can be set as a preset normal formula for subsequent calculations.
  • the calculation module 20 calculates the product false detection rate corresponding to the metal-free product sampling data according to the preset normal formula, the preset limit parameters, the metal-free product sampling data and the metal-containing product sampling data
  • the missing detection rate groups corresponding to the sampling data of each group and each group of metal-containing products include:
  • the calculation module 20 calculates the corresponding product average and product standard deviation based on the sampling data of the metal-free products; and, based on the sampling data of each group of metal-containing products, calculates the corresponding metal average of each group of metal-containing product sampling data Value and metal standard deviation; and, based on the product average, product standard deviation, preset limit parameters and preset normal formula, the product misdetection rate group corresponding to the product sampling data is calculated; and, according to the preset limit parameters, Suppose the normal formula and the metal mean value and metal standard deviation corresponding to the sampling data of each group of metal-containing products, respectively, and calculate the missing detection rate group corresponding to each group of metal-containing product sampling data.
  • the average value is the sum of the sampled data divided by the total number. For example: there are 150 data in a set of product sampling data, then add the 150 data and divide by 150 to get the average value of the product. Similarly, the average value of the metal corresponding to each group of metal sampling data.
  • the standard deviation is calculated according to the formula in the corresponding method embodiment described above. Please refer to the corresponding method embodiment, which will not be repeated here.
  • the preset normal formula please refer to the corresponding method embodiment. Substituting different values of x into the preset normal formula can calculate the sum of the probabilities less than or equal to the value of x. For products, below the value of x is normal, high The x value is a false detection; for metals, a value higher than x is detected, and a value lower than x is missed. For specific examples, please refer to the corresponding method embodiments, which will not be repeated here.
  • the selection module 30 is used to select the corresponding value as the threshold according to the product misdetection rate group, the corresponding misdetection rate group and the misdetection miss detection rate requirements of each group of metal-containing product sampling data.
  • the selection module 30 is configured to select the corresponding value as the threshold based on the product misdetection rate group, the corresponding misdetection rate group and the misdetection miss rate requirement of each metal-containing product sampling data, including:
  • the drawing sub-module 31 is used to draw a corresponding graph according to the corresponding missing detection rate group and product false detection rate group of each group of metal-containing product sampling data;
  • the selection sub-module 32 is used to select the corresponding value from the graph as the threshold according to the false detection and miss detection rate requirements.
  • the metal detector can be monitored by cameras and other devices to obtain sampling data, and the implementation methods are diversified to meet the application requirements of different occasions.
  • a digital performance analysis device includes:
  • the acquiring module 10 is configured to acquire (preferably, the closest to the current time) a set of metal-free product sampling data and at least one set of metal-containing product sampling data when a certain time interval is reached;
  • the calculation module 20 is used to calculate the product misdetection rate group corresponding to the metal-free product sampling data and each group of metal-containing product sampling data according to the distribution rule of the metal-free product sampling data and the metal-containing product sampling data The corresponding missing detection rate group;
  • the selection module 30 is used to select the corresponding value as the threshold according to the requirements of the product misdetection rate group, the corresponding misdetection rate group and the misdetection miss rate of each metal-containing product sampling data.
  • the threshold value selection in this embodiment may be periodically performed when actually used, and when a certain time interval is set sufficiently small, real-time monitoring may be achieved.
  • the metal detector selects a set of metal-free product sampling data and at least one set of metal-containing product sampling data based on the sampling data obtained in real time, and performs real-time/periodical calculations. Choose reasonable data as the threshold.
  • the metal detector When other equipment is used to monitor the threshold of the metal detector, it can monitor the metal detector in real time, obtain each sampling data in real time, select a set of product sampling data without metal and at least one set of product sampling data with metal for real-time /Periodic calculation, giving reasonable suggestions for metal detectors as thresholds.
  • a certain amount of data closest to the current time is taken for analysis, so that the calculation result is more in line with the current situation.
  • the selection module 30 is used to select the corresponding value as the threshold according to the requirements of the product false detection rate group, the corresponding leakage detection rate group and the false detection leakage detection rate of each group of metal-containing product sampling data, including:
  • the selection module 30 is used when the set threshold meets the requirements of false detection and miss detection rate, and the threshold is still used; and, when the set threshold does not meet the requirements of false detection and miss detection rate, according to the product misdetection rate group, Each group of metal-containing product sampling data corresponds to the requirements of the missed detection rate group and the false detection missed detection rate, and re-select the corresponding value to update or prompt to update the threshold.
  • the metal detector has been set with a threshold (may be a value set based on experience or a value selected based on the result calculated in real time), and put into actual product monitoring
  • a threshold may be a value set based on experience or a value selected based on the result calculated in real time
  • the currently set threshold may not meet the low miss detection rate of the metal and the low false detection rate of the product.
  • the calculation module 20 is configured to calculate the product false detection rate group corresponding to the metal-free product sampling data and the metal-containing product sampling data distribution product corresponding to the metal-free product sampling data and each group of metal-containing products
  • the corresponding missed detection rate groups of product sampling data include:
  • Calculation module 20 when the sampling data of metal-free products and the sampling data of metal-containing products conform to the normal distribution law, according to the preset normal formula, the preset limit parameters, the sampling data of metal-free products and the metal-containing product For product sampling data, calculate the product misdetection rate group corresponding to the metal-free product sampling data and the missing detection rate group corresponding to each group of metal-containing product sampling data.
  • the calculation module 20 calculates the product misdetection corresponding to the metal-free product sampling data according to the preset normal formula, the preset limit parameters, the metal-free product sampling data and the metal-containing product sampling data
  • the rate group and each group of metal-containing product sampling data corresponding to the missing detection rate group include:
  • the calculation module 20 calculates the corresponding product average and product standard deviation based on the sampling data of the metal-free products; and, based on the sampling data of each group of metal-containing products, calculates the corresponding metal average of each group of metal-containing product sampling data Value and metal standard deviation; and, based on the product average, product standard deviation, preset limit parameters (the preset limit parameters include: minimum threshold, maximum threshold, and threshold interval value) and the preset normal formula, the calculated metal-free).
  • the preset limit parameters include: minimum threshold, maximum threshold, and threshold interval value
  • the preset normal formula the calculated metal-free
  • the selection module 30 is configured to select the corresponding value as the threshold according to the requirements of the product misdetection rate group, the corresponding misdetection rate group and the misdetection miss rate of each metal-containing product sampling data, including:
  • the drawing sub-module 31 is used to draw a corresponding graph according to the corresponding missing detection rate group and product false detection rate group of each group of metal-containing product sampling data;
  • the selection sub-module 32 is used to select the corresponding value from the graph as the threshold according to the requirement of false detection and miss detection rate.
  • the digital performance analysis device when the digital performance analysis device is a non-metal detector device, the digital performance analysis device may further include: a camera module 40 for acquiring the working state of the metal detector in real time; The obtained working state of the metal detector identifies a set of sampling data of products without metal and at least one set of sampling data of products with metal.
  • periodic/real-time monitoring is performed on the selection of the threshold to ensure that the threshold set by the metal detector can meet the actual production needs.

Abstract

L'invention concerne un procédé et un dispositif d'analyse de performance numérique. Le procédé consiste à : acquérir un ensemble de données d'échantillon de produits ne contenant pas de métal et au moins un ensemble de données d'échantillon de produits contenant du métal ; conformément à la loi de distribution des données d'échantillon des produits ne contenant pas de métal et des données d'échantillon des produits contenant du métal, calculer un ensemble de taux de retombée de produits correspondant aux données d'échantillon des produits ne contenant pas de métal et un ensemble de taux d'omission correspondant à chaque ensemble de données d'échantillon des produits contenant du métal ; sélectionner une valeur correspondante en tant que seuil conformément à l'ensemble de taux de retombée de produits, l'ensemble de taux d'omission correspondant à chaque ensemble de données d'échantillon des produits contenant du métal et aux exigences du taux de retombée et du taux d'omission. Le procédé et le dispositif prennent en charge la sélection d'un seuil par des données quantifiées effectives, et un seuil sélectionné est plus en accord avec des exigences d'utilisation réelles, ce qui permet de réduire le taux de retombée, de garantir le taux d'omission et d'améliorer la surveillance de la qualité de produit.
PCT/CN2019/091610 2018-12-27 2019-06-17 Procédé et dispositif d'analyse de performance numérique WO2020133954A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN201811610109.1A CN109613108B (zh) 2018-12-27 2018-12-27 阈值选择方法及设备
CN201811610109.1 2018-12-27

Publications (1)

Publication Number Publication Date
WO2020133954A1 true WO2020133954A1 (fr) 2020-07-02

Family

ID=66012734

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2019/091610 WO2020133954A1 (fr) 2018-12-27 2019-06-17 Procédé et dispositif d'analyse de performance numérique

Country Status (2)

Country Link
CN (1) CN109613108B (fr)
WO (1) WO2020133954A1 (fr)

Families Citing this family (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109613108B (zh) * 2018-12-27 2022-09-20 帝沃检测技术(上海)有限公司 阈值选择方法及设备
CN110308491B (zh) * 2019-05-29 2021-11-05 浙江大华技术股份有限公司 物品探测方法、装置、存储介质及电子装置
CN112991294A (zh) * 2021-03-12 2021-06-18 梅特勒-托利多(常州)测量技术有限公司 异物检测方法、装置及计算机可读介质

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1488933A (zh) * 2002-08-22 2004-04-14 丰田自动车株式会社 良否判定装置、判定程序、方法以及多变量统计解析装置
CN101840003A (zh) * 2010-03-05 2010-09-22 清华大学 一种针对金属违禁品的绿色通道敞篷车雷达检测方法
CN103576206A (zh) * 2012-07-31 2014-02-12 上海太易检测技术有限公司 一种金属检测机
US20150234075A1 (en) * 2012-02-10 2015-08-20 Illinois Tool Works Inc. Metal detector
CN108885193A (zh) * 2016-03-25 2018-11-23 码科泰克株式会社 探伤装置以及利用探伤装置的缺陷检测方法
CN109613108A (zh) * 2018-12-27 2019-04-12 帝沃检测技术(上海)有限公司 阈值选择方法及设备

Family Cites Families (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP4444240B2 (ja) * 2006-06-15 2010-03-31 アンリツ産機システム株式会社 X線異物検出装置
CN104700345B (zh) * 2015-01-16 2017-10-17 天津科技大学 建立本福德定律阈值库提高半脆弱水印认证检测率的方法
CN107361763B (zh) * 2017-08-09 2020-10-09 广东虹勤通讯技术有限公司 一种心电图数据r波检测方法及装置
CN108364017B (zh) * 2018-01-24 2019-11-05 华讯方舟科技有限公司 一种图像质量分类方法、系统及终端设备
CN108918427B (zh) * 2018-06-06 2021-07-30 北京云端光科技术有限公司 物质检测的方法、装置、存储介质及电子设备

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1488933A (zh) * 2002-08-22 2004-04-14 丰田自动车株式会社 良否判定装置、判定程序、方法以及多变量统计解析装置
CN101840003A (zh) * 2010-03-05 2010-09-22 清华大学 一种针对金属违禁品的绿色通道敞篷车雷达检测方法
US20150234075A1 (en) * 2012-02-10 2015-08-20 Illinois Tool Works Inc. Metal detector
CN103576206A (zh) * 2012-07-31 2014-02-12 上海太易检测技术有限公司 一种金属检测机
CN108885193A (zh) * 2016-03-25 2018-11-23 码科泰克株式会社 探伤装置以及利用探伤装置的缺陷检测方法
CN109613108A (zh) * 2018-12-27 2019-04-12 帝沃检测技术(上海)有限公司 阈值选择方法及设备

Also Published As

Publication number Publication date
CN109613108B (zh) 2022-09-20
CN109613108A (zh) 2019-04-12

Similar Documents

Publication Publication Date Title
WO2020133954A1 (fr) Procédé et dispositif d'analyse de performance numérique
WO2020063819A1 (fr) Procédé d'analyse de données en temps réel pour réseau de tuyaux, et dispositif
Moschitta et al. Performance comparison of advanced techniques for voltage dip detection
CN108965055A (zh) 一种基于历史时间取点法的网络流量异常检测方法
CN106464988B (zh) 能量管理系统
CN101539533A (zh) 电池内部缺陷自动检测装置及方法
CN113344133A (zh) 一种时序行为异常波动检测方法及系统
CN106772656A (zh) 一种基于红外阵列传感器的室内人体检测方法
CN114511991A (zh) 矿井粉尘智能分析处理系统及方法
CN111157840A (zh) 故障波形相似度判断方法、控制设备及存储介质
CN111398339A (zh) 一种现场架空线路复合绝缘子发热缺陷分析判断方法及系统
CN113091832B (zh) 基于大数据可视化的变配电站智能监控方法及云监控平台
CN113934536A (zh) 面向边缘计算的数据采集方法
CN117573477A (zh) 异常数据监控方法、装置、设备、介质和程序产品
CN116937818A (zh) 对内部进行实时监控的高压直流配电柜监控系统
CN116317103A (zh) 一种配电网电压数据处理方法
TW201908995A (zh) 適應性機台稼動率分析系統及方法
CN116309344A (zh) 一种绝缘子异常检测方法、装置、设备和存储介质
JP2018107992A (ja) 電力使用量情報収集システム及び方法
CN106335977A (zh) 一种自来水加氯控制方法和系统
CN102034022A (zh) 一种基于倍频分析的信号处理方法及系统
CN115065704A (zh) 一种智慧工厂建设设备仪表智能监测分析预警系统
CN106600449B (zh) 一种自动的功率趋势识别方法
CN110907544B (zh) 一种变压器油中溶解气体含量异常阶跃数据识别方法
CN116449898B (zh) 一种开关柜温湿度远程控制系统

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 19905608

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 19905608

Country of ref document: EP

Kind code of ref document: A1

32PN Ep: public notification in the ep bulletin as address of the adressee cannot be established

Free format text: NOTING OF LOSS OF RIGHTS PURSUANT TO RULE 112(1) EPC (EPO FORM 1205A DATED 21/10/2021)

122 Ep: pct application non-entry in european phase

Ref document number: 19905608

Country of ref document: EP

Kind code of ref document: A1