CN111719210B - Method and device for detecting abnormal spindle in spinning frame and readable storage medium - Google Patents
Method and device for detecting abnormal spindle in spinning frame and readable storage medium Download PDFInfo
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- CN111719210B CN111719210B CN202010532278.9A CN202010532278A CN111719210B CN 111719210 B CN111719210 B CN 111719210B CN 202010532278 A CN202010532278 A CN 202010532278A CN 111719210 B CN111719210 B CN 111719210B
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Abstract
The invention discloses a method and a device for detecting abnormal spindles in a spinning frame and a readable storage medium, wherein the method comprises the following steps: calculating the spindle speed mean value of each spindle in a spinning frame according to a plurality of spindle speeds of each spindle in a preset period; determining normal-speed spindles and abnormal-speed spindles in the spinning frame according to the spindle speed average values; determining an anomaly score for each spindle from the feature data set for each spindle; and determining a target abnormal spindle in the spinning frame according to each abnormal score, each normal speed spindle and each abnormal speed spindle. The invention prevents the yarn breakage by the target abnormal spindle, thereby reducing the occurrence of the yarn breakage condition and reducing the detection cost of the yarn breakage. And the abnormal spindle of the spinning frame is determined according to multiple dimensions such as the rotating speed of the spindle and the characteristic data of the spindle, so that the abnormal spindle is more accurately determined, and the yarn breakage prevention effect is favorably ensured.
Description
Technical Field
The invention relates to the technical field of cotton spinning, in particular to a method and equipment for detecting an abnormal spindle in a spinning frame and a readable storage medium.
Background
In the cotton spinning industry, yarn breakage detection is an important component of spun yarn production management. The detection modes are various, and include fixed-point detection and itinerant detection in terms of structure types; the detection principle can be divided into detection technologies such as steel wire ring movement photoelectric scanning, steel wire ring friction thermosensitive sensing, steel wire ring movement electromagnetic induction, and light path interruption of a yarn guide hook yarn strip.
However, the detection based on the structure type or the detection based on the detection principle is the detection after the completion of the spun yarn generation, and belongs to the post-detection, not the pre-detection to prevent the yarn breakage. Although yarn breakage can be detected by post-detection as opposed to pre-prevention, yarn breakage due to lack of pre-prevention increases and detection costs also increase. Therefore, how to reduce yarn breakage through prevention and reduce the yarn breakage detection cost is a technical problem to be solved at present.
Disclosure of Invention
The invention mainly aims to provide a method and equipment for detecting an abnormal spindle in a spinning frame and a readable storage medium, and aims to solve the technical problems of reducing yarn breakage and reducing the yarn breakage detection cost by preventing in the prior art.
In order to achieve the purpose, the invention provides a method for detecting abnormal spindles in a spinning frame, which comprises the following steps:
calculating the spindle speed mean value of each spindle in a spinning frame according to a plurality of spindle speeds of each spindle in a preset period;
determining normal-speed spindles and abnormal-speed spindles in the spinning frame according to the spindle speed average values;
determining an anomaly score for each spindle from the feature data set for each spindle;
and determining a target abnormal spindle in the spinning frame according to each abnormal score, each normal speed spindle and each abnormal speed spindle.
Optionally, the step of determining a target abnormal spindle in the spinning frame according to each abnormal score, each normal speed spindle and each abnormal speed spindle comprises:
determining a characteristic normal spindle and a characteristic abnormal spindle in the spinning frame according to each abnormal score;
determining normal spindles in the spinning machine according to the speed normal spindles and the characteristic normal spindles, and determining spindles to be determined in the spinning machine based on the normal spindles;
determining abnormal spindles and spindles to be determined in the spinning frame according to the abnormal speed spindles and the abnormal characteristic spindles;
and updating the abnormal spindles in the spinning frame according to the spindles to be determined to form target abnormal spindles in the spinning frame.
Optionally, the step of determining a characteristic normal spindle and a characteristic abnormal spindle in the spinning frame according to each abnormality score includes:
comparing each abnormal score with a preset score threshold value, and determining a first abnormal score which is greater than the preset score threshold value and a second abnormal score which is less than or equal to the preset score threshold value in each abnormal score;
determining spindles corresponding to each of the first anomaly scores as the characteristic anomalous spindles, and determining spindles corresponding to each of the second anomaly scores as the characteristic normal spindles.
Optionally, the step of determining a normal spindle in the spinning machine according to each of the normal speed spindles and each of the characteristic normal spindles, and determining a spindle to be determined in the spinning machine based on the normal spindle includes:
performing a first type intersection operation on each normal-speed spindle and each normal-characteristic spindle, determining the spindles falling into the first type intersection operation as normal spindles in the spinning frame, and determining other spindles except the normal spindles in the spinning frame as the spindles to be determined;
the step of determining the abnormal spindles and the spindles to be determined in the spinning frame according to each abnormal spindle with speed and each abnormal spindle with characteristics comprises the following steps:
and performing second type intersection operation on each speed abnormal spindle and each characteristic abnormal spindle, determining the spindles falling into the second type intersection operation as the abnormal spindles in the spinning frame, and determining the spindles falling out of the second type intersection operation as the spindles to be determined in the spinning frame.
Optionally, the step of updating the abnormal spindles in the spinning frame according to the spindles to be determined to form the target abnormal spindle in the spinning frame includes:
every interval preset detection period, obtaining a plurality of to-be-determined spindle speeds of each spindle to be determined in the preset detection period, and calculating the average value of the to-be-determined spindle speeds of each spindle to be determined;
dividing the spindles to be determined into spindles with normal speeds to be determined and spindles with abnormal speeds to be determined according to the mean values of the speeds to be determined of the spindles to be determined;
determining undetermined abnormal scores of the spindles to be determined according to the undetermined characteristic data set of the spindles to be determined;
and updating the abnormal spindles in the spinning frame according to the undetermined abnormal scores, the undetermined speed normal spindles and the undetermined speed abnormal spindles to form a target abnormal spindle in the spinning frame.
Optionally, the step of determining an anomaly score for each of the spindles from the feature data set for each of the spindles comprises:
acquiring the number of broken ends and the number of weak twists of each spindle in the preset period, and forming the average value of the spindle speed, the number of broken ends and the number of weak twists of each spindle into a characteristic data value of each spindle;
calculating the probability density of each spindle on each data in the characteristic data set, and determining the total probability density of each spindle according to each probability density of each spindle;
calculating an anomaly score for each of the spindles based on the total probability density for each of the spindles.
Optionally, the step of determining a normal-speed spindle and an abnormal-speed spindle in the spinning frame according to the spindle speed mean value includes:
calculating the integral mean value and standard deviation of each ingot speed mean value, and determining the ingot speed deviation between each ingot speed mean value and the integral mean value;
updating the standard deviation based on a preset multiple, and searching a first ingot speed deviation which is greater than the updated standard deviation and a second ingot speed deviation which is less than or equal to the updated standard deviation in the ingot speed deviations;
and determining spindles corresponding to each first spindle speed deviation as abnormal spindles, and determining spindles corresponding to each second spindle speed deviation as normal spindles.
Optionally, the step of calculating the mean spindle speed of each spindle in the spinning frame according to the plurality of spindle speeds of each spindle in a preset period comprises:
arranging a plurality of spindle speeds of each spindle in the spinning machine in a preset period according to a numerical sequence from large to small to form a numerical sequence of each spindle;
and transmitting the numerical values in the numerical value sequence of each spindle to a preset formula for calculation to generate the spindle speed average value of each spindle.
Further, in order to achieve the above object, the present invention further provides a detection apparatus for an abnormal spindle in a spinning frame, the detection apparatus for an abnormal spindle in a spinning frame comprising:
the calculation module is used for calculating the spindle speed mean value of each spindle in the spinning frame according to a plurality of spindle speeds of each spindle in a preset period;
the first determining module is used for determining the spindles with normal speed and the spindles with abnormal speed in the spinning frame according to the spindle speed average value;
a second determination module for determining an anomaly score for each of said spindles from a feature data set for each of said spindles;
and the third determining module is used for determining a target abnormal spindle in the spinning frame according to each abnormal score, each normal-speed spindle and each abnormal-speed spindle.
Further, in order to achieve the above object, the present invention further provides a detection apparatus for abnormal spindles in a spinning frame, the detection apparatus for abnormal spindles in a spinning frame includes a memory, a processor, and a detection program for abnormal spindles in a spinning frame stored on the memory and operable on the processor, and when the detection program for abnormal spindles in a spinning frame is executed by the processor, the steps of the detection method for abnormal spindles in a spinning frame are implemented.
Further, to achieve the above object, the present invention also provides a readable storage medium, on which a detection program of abnormal spindles in a spinning frame is stored, and the detection program of abnormal spindles in the spinning frame, when executed by a processor, implements the steps of the detection method of abnormal spindles in a spinning frame as described above.
The invention relates to a method and a device for detecting abnormal spindles in a spinning frame and a readable storage medium, which are characterized in that firstly, the spindle speed mean value of each spindle is calculated according to a plurality of spindle speeds of each spindle in the spinning frame in a preset period, and each spindle in the spinning frame is divided into a spindle with normal speed and a spindle with abnormal speed according to the spindle speed mean value; determining the abnormal score of each spindle according to the characteristic data value of each spindle; and further combining the abnormal score of each spindle, each normal-speed spindle and each abnormal-speed spindle to determine a target abnormal spindle in the spinning frame. The target abnormal spindle is used for preventing yarn breakage, so that the occurrence of yarn breakage is reduced, and the detection cost of yarn breakage is reduced. And the abnormal spindle of the spinning frame is determined according to multiple dimensions such as the rotating speed of the spindle and the characteristic data of the spindle, so that the abnormal spindle is more accurately determined, and the yarn breakage prevention effect is favorably ensured.
Drawings
FIG. 1 is a schematic structural diagram of a hardware operating environment of a device related to an embodiment of an abnormal spindle detection device in a spinning frame;
fig. 2 is a schematic flow chart of a method for detecting an abnormal spindle in a spinning frame according to a first embodiment of the invention.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The invention provides detection equipment for abnormal spindles in a spinning frame, and referring to fig. 1, fig. 1 is a structural schematic diagram of an equipment hardware operating environment related to the scheme of the detection equipment for abnormal spindles in the spinning frame.
As shown in fig. 1, the detection apparatus for an abnormal spindle in a spinning frame may include: a processor 1001, such as a CPU, a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. Wherein a communication bus 1002 is used to enable connective communication between these components. The user interface 1003 may include a Display screen (Display), an input unit such as a Keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface). The memory 1005 may be a high-speed RAM memory or a non-volatile memory (e.g., a magnetic disk memory). The memory 1005 may alternatively be a memory device separate from the processor 1001 described above.
Those skilled in the art will appreciate that the hardware structure of the detection device of the abnormal spindle in the spinning frame shown in fig. 1 does not constitute a limitation to the detection device of the abnormal spindle in the spinning frame, and may include more or less components than those shown in the drawings, or combine some components, or arrange different components.
As shown in fig. 1, the memory 1005, which is a readable storage medium, may include therein an operating system, a network communication module, a user interface module, and a detection program of an abnormal spindle in a spinning frame. The operating system is a program for managing and controlling detection equipment and software resources of abnormal spindles in the spinning frame, and supports the operation of a network communication module, a user interface module, the detection program of the abnormal spindles in the spinning frame and other programs or software; the network communication module is used to manage and control the network interface 1004; the user interface module is used to manage and control the user interface 1003.
In the hardware structure of the detection device for the abnormal spindle in the spinning frame shown in fig. 1, the network interface 1004 is mainly used for connecting a background server and performing data communication with the background server; the user interface 1003 is mainly used for connecting a client (user side) and performing data communication with the client; the processor 1001 may call the detection program of the abnormal spindle in the spinning frame stored in the memory 1005, and perform the following operations:
calculating the spindle speed mean value of each spindle in a spinning frame according to a plurality of spindle speeds of each spindle in a preset period;
determining normal-speed spindles and abnormal-speed spindles in the spinning frame according to the spindle speed average values;
determining an anomaly score for each spindle from the feature data set for each spindle;
and determining a target abnormal spindle in the spinning frame according to each abnormal score, each normal speed spindle and each abnormal speed spindle.
Further, the step of determining a target abnormal spindle in the spinning frame according to each abnormal score, each normal speed spindle and each abnormal speed spindle comprises:
determining a characteristic normal spindle and a characteristic abnormal spindle in the spinning frame according to each abnormal score;
determining normal spindles in the spinning machine according to the speed normal spindles and the characteristic normal spindles, and determining spindles to be determined in the spinning machine based on the normal spindles;
determining abnormal spindles and spindles to be determined in the spinning frame according to the abnormal speed spindles and the abnormal characteristic spindles;
and updating the abnormal spindles in the spinning frame according to the spindles to be determined to form target abnormal spindles in the spinning frame.
Further, the step of determining the characteristic normal spindle and the characteristic abnormal spindle in the spinning frame according to each abnormal score comprises the following steps:
comparing each abnormal score with a preset score threshold value, and determining a first abnormal score which is greater than the preset score threshold value and a second abnormal score which is less than or equal to the preset score threshold value in each abnormal score;
determining spindles corresponding to each of the first anomaly scores as the characteristic anomalous spindles, and determining spindles corresponding to each of the second anomaly scores as the characteristic normal spindles.
Further, the step of determining a normal spindle in the spinning machine according to each of the speed normal spindles and each of the characteristic normal spindles, and determining a spindle to be determined in the spinning machine based on the normal spindle includes:
performing a first type intersection operation on each normal-speed spindle and each normal-characteristic spindle, determining the spindles falling into the first type intersection operation as normal spindles in the spinning frame, and determining other spindles except the normal spindles in the spinning frame as the spindles to be determined;
the step of determining the abnormal spindles and the spindles to be determined in the spinning frame according to each abnormal spindle with speed and each abnormal spindle with characteristics comprises the following steps:
and performing second type intersection operation on each speed abnormal spindle and each characteristic abnormal spindle, determining the spindles falling into the second type intersection operation as the abnormal spindles in the spinning frame, and determining the spindles falling out of the second type intersection operation as the spindles to be determined in the spinning frame.
Further, the step of updating the abnormal spindles in the spinning frame according to the spindles to be determined to form the target abnormal spindle in the spinning frame includes:
every interval preset detection period, obtaining a plurality of to-be-determined spindle speeds of each spindle to be determined in the preset detection period, and calculating the average value of the to-be-determined spindle speeds of each spindle to be determined;
dividing the spindles to be determined into spindles with normal speeds to be determined and spindles with abnormal speeds to be determined according to the mean values of the speeds to be determined of the spindles to be determined;
determining undetermined abnormal scores of the spindles to be determined according to the undetermined characteristic data set of the spindles to be determined;
and updating the abnormal spindles in the spinning frame according to the undetermined abnormal scores, the undetermined speed normal spindles and the undetermined speed abnormal spindles to form a target abnormal spindle in the spinning frame.
Further, the step of determining an anomaly score for each of the spindles from the characteristic data set for each of the spindles comprises:
acquiring the number of broken ends and the number of weak twists of each spindle in the preset period, and forming the average value of the spindle speed, the number of broken ends and the number of weak twists of each spindle into a characteristic data value of each spindle;
calculating the probability density of each spindle on each data in the characteristic data set, and determining the total probability density of each spindle according to each probability density of each spindle;
calculating an anomaly score for each of the spindles based on the total probability density for each of the spindles.
Further, the step of determining normal-speed spindles and abnormal-speed spindles in the spinning frame according to the spindle speed average value comprises the following steps:
calculating the integral mean value and standard deviation of each ingot speed mean value, and determining the ingot speed deviation between each ingot speed mean value and the integral mean value;
updating the standard deviation based on a preset multiple, and searching a first ingot speed deviation which is greater than the updated standard deviation and a second ingot speed deviation which is less than or equal to the updated standard deviation in the ingot speed deviations;
and determining spindles corresponding to each first spindle speed deviation as abnormal spindles, and determining spindles corresponding to each second spindle speed deviation as normal spindles.
Further, the step of calculating the mean spindle speed value of each spindle in the spinning frame according to the spindle speeds of each spindle in a preset period comprises:
arranging a plurality of spindle speeds of each spindle in the spinning machine in a preset period according to a numerical sequence from large to small to form a numerical sequence of each spindle;
and transmitting the numerical values in the numerical value sequence of each spindle to a preset formula for calculation to generate the spindle speed average value of each spindle.
The specific implementation of the detection device for the abnormal spindle in the spinning frame is basically the same as that of each embodiment of the detection method for the abnormal spindle in the spinning frame, and the detailed description is omitted here.
The invention also provides a method for detecting the abnormal spindle in the spinning frame.
Referring to fig. 2, fig. 2 is a schematic flow chart of a first embodiment of a method for detecting an abnormal spindle in a spinning frame according to the present invention.
The embodiment of the invention provides an embodiment of a method for detecting abnormal spindles in a spinning frame, and it should be noted that although a logic sequence is shown in a flow chart, in some cases, the steps shown or described may be executed in a different sequence from the sequence shown here. Specifically, the method for detecting the abnormal spindle in the spinning frame in the embodiment includes:
step S10, calculating the spindle speed mean value of each spindle in the spinning frame according to the spindle speeds of each spindle in a preset period;
the method for detecting the abnormal spindle in the spinning frame is applied to an upper computer of a spinning frame system. All spinning frames configured by a spinning frame enterprise and an upper computer form a spinning frame system together. The spinning frame is a spinning machine which draws, twists and winds semi-finished roving or sliver into spun yarn bobbin yarn in the spinning process. The spinning machine system comprises a plurality of spinning machine enterprises, wherein components such as a controller, a control chip, a main control console and the like which are arranged in each spinning machine enterprise and used for controlling the spinning machine to operate form a lower computer of the spinning machine system, the upper computer is in communication connection with the plurality of lower computers through communication modes such as Modbus, TCP/IP and the like, and one lower computer corresponds to one spinning machine. The upper computer acquires the running data of each spinning frame from each lower computer through the computer, monitors the running of each spinning frame and realizes the detection of abnormal spindles in the spinning frames. The spindle is one of the main parts for twisting and winding on spinning machine and is an assembly with two-point supported slender revolving shaft as main body. The embodiment reflects whether the yarn produced by the spinning frame has broken yarn or not through the abnormality of the spindles.
Further, a preset period representing the detection interval time is preset according to the requirement, such as one week, half a month and the like. And when the detection reaches the preset period, the upper computer acquires a plurality of spindle speeds of each spindle in each spinning frame in the preset period through communication transmission with each lower computer. The spindle speed is the rotating speed of the spindles, and each lower computer reads the rotating speed of each spindle in the spinning machine according to a set reading period, such as 3 seconds, and stores the rotating speed in the storage unit corresponding to each lower computer at intervals of the reading period. The upper computer sends a communication request to each lower computer to request to acquire the rotating speed stored in the preset period of each lower computer, and the rotating speed is used as a plurality of spindle speeds of each spindle in each spinning frame in the preset period. Each spinning machine comprises a plurality of spindles, and the upper computer detects the spindles in each spinning machine in the same way.
Furthermore, after acquiring a plurality of spindle speeds of each spindle in the spinning frame in a preset period, the upper computer calculates the mean value of the spindle speed of each spindle in the preset period to characterize the rotation condition of each spindle in the spinning frame in the preset period. Specifically, the step of calculating the mean value of the spindle speed of each spindle in the spinning frame according to the spindle speeds of each spindle in a preset period comprises the following steps:
step S11, arranging a plurality of spindle speeds of each spindle in the spinning frame in a preset period according to the numerical value sequence from large to small to form a numerical value sequence of each spindle;
and step S12, transmitting the numerical values in the numerical value sequence of each spindle to a preset formula for calculation, and generating the spindle speed average value of each spindle.
Further, in order to facilitate calculation of the average value of the spindle speeds, the spindle speeds generated by each spindle in a preset period are arranged according to the sequence of the numerical values from large to small, and a numerical value sequence of each spindle is formed. Further, the numerical values may be arranged in order of arrival from the smallest to form a numerical sequence for each spindle. For example, if the spindle speeds of a certain spindle in the spinning frame in a preset period are 300, and the spindle speeds acquired according to the time sequence are respectively 200 rpm, 220 rpm, 195 rpm, and the like, the numerical sequence for the spindle is [220, 200, 195 ]. And further calculating the numerical value sequence of each spindle according to a preset first preset formula, and transmitting the numerical values in the numerical value sequence of each spindle to the first preset formula to obtain the spindle speed average value of each spindle. The first preset formula is shown as the following formula (1).
Where s is the mean ingot velocity, xi represents each value in the sequence of values, N represents the number of values in the sequence of values, i ═ 1, 2, 3 ·.
Step S20, determining a normal-speed spindle and an abnormal-speed spindle in the spinning frame according to the spindle speed average value;
further, after the mean value of the spindle speed of each spindle is calculated, the mean value of the spindle speeds is normally distributed. And (4) carrying out probability calculation on the spindle speed mean values in normal distribution, and determining the spindle corresponding to the spindle speed mean value with the probability value within a certain interval as the normal-speed spindle with normal rotation speed dimension in the spinning frame. And simultaneously, determining the spindle corresponding to the spindle speed mean value with the probability value outside the interval as the abnormal spindle with the abnormal speed dimension in the spinning frame. Therefore, all the spindles in the spinning frame are divided into normal-speed spindles and abnormal-speed spindles.
Step S30, determining the abnormal score of each spindle according to the characteristic data set of each spindle;
understandably, besides the rotating speed, the number of broken ends and the number of weak twists of the spinning frame in the running process also represent the running state of the spindle. The number of broken ends represents the number of times that the spun yarn on the yarn barrel is broken in a preset period in the process that the spindle drives the yarn barrel to rotate, and if the spun yarn on a certain spindle is broken 5 times in the preset period, the number of broken ends is 5. The weak twist times represent the times of rotation of the spindle at a rotating speed lower than a normal rotating speed in a preset period in the rotating process; if in the preset period, the number of times that the rotating speed of a certain spindle rotates at 75% -95% of the normal rotating speed is 10, and the number of times of weak twist of the spindle is 10; wherein, the spindle falls into the range of lower than the normal speed from the normal speed and rotates, and then recovers to the normal speed from the range of lower than the normal speed, and counts as a weak twist.
Further, the number of broken ends, the number of weak twists and the average value of the spindle speed representing the running state of the spindle in a preset period are used as the characteristic data of the spindle to form a characteristic data set of the spindle. And determining the abnormality score of each spindle according to the characteristic data set of each spindle. The more the possibility that the characteristic data collectively represent abnormal operation of the spindles is, the higher the abnormal score of the spindles is; otherwise the anomaly score is lower.
And step S40, determining a target abnormal spindle in the spinning frame according to each abnormal score, each normal speed spindle and each abnormal speed spindle.
Further, according to the abnormal score of each spindle and the divided normal-speed spindle and abnormal-speed spindle, the spindle which is possible to be abnormal in all the spindles of the spinning machine is predicted. If the abnormal score indicates that a certain spindle is an abnormal spindle and the spindle is an abnormal speed spindle, the spindle is indicated to be abnormal in multiple dimensions, and the spindle is predicted to be an abnormal spindle in the spinning machine. If the abnormal score indicates that a certain spindle is a normal spindle and the spindle is a normal-speed spindle, the spindle is normal in multiple dimensions and is predicted to be a normal spindle in a spinning machine. After all the spindles in the spinning frame are predicted, the spindles with the abnormal operation are predicted to form target abnormal spindles in the spinning frame, the spindles with the abnormal operation in the spinning frame are represented, and yarn breakage of spun yarns can be caused in the operation process. And then, outputting prompt information aiming at the determined target abnormal spindle to remind the target abnormal spindle to check in time, so that yarn breakage caused by abnormality is avoided, and the yarn breakage frequency is reduced. Meanwhile, the data such as the spindle speed average value, the speed normality, the speed abnormality, the characteristic data, the abnormality score and the like of each spindle can be generated into a spinning machine work shift report, a characteristic data report, a doffing report and the like, and the report is provided for spinning machine enterprises so as to monitor the production running condition of each spinning machine.
The method for detecting the abnormal spindles in the spinning frame comprises the steps of firstly calculating the spindle speed mean value of each spindle according to a plurality of spindle speeds of each spindle in the spinning frame in a preset period, and dividing each spindle in the spinning frame into a normal-speed spindle and an abnormal-speed spindle according to the spindle speed mean value; determining the abnormal score of each spindle according to the characteristic data value of each spindle; and further combining the abnormal score of each spindle, each normal-speed spindle and each abnormal-speed spindle to determine a target abnormal spindle in the spinning frame. The target abnormal spindle is used for preventing yarn breakage, so that the occurrence of yarn breakage is reduced, and the detection cost of yarn breakage is reduced. And the abnormal spindle of the spinning frame is determined according to multiple dimensions such as the rotating speed of the spindle and the characteristic data of the spindle, so that the abnormal spindle is more accurately determined, and the yarn breakage prevention effect is favorably ensured.
Further, based on the first embodiment of the method for detecting the abnormal spindle in the spinning frame, the second embodiment of the method for detecting the abnormal spindle in the spinning frame is provided.
The second embodiment of the method for detecting abnormal spindles in the spinning frame is different from the first embodiment of the method for detecting abnormal spindles in the spinning frame in that the step of determining the target abnormal spindle in the spinning frame according to each abnormal score, each normal speed spindle and each abnormal speed spindle comprises the following steps:
step S41, determining a characteristic normal spindle and a characteristic abnormal spindle in the spinning frame according to each abnormal score;
the anomaly score of the embodiment characterizes the anomaly of the spindles on each characteristic data, and the anomaly of the spindles characterized in the speed dimension is combined to determine the anomalous spindles in the spinning machine. Specifically, the abnormality of each spindle is reflected by the abnormality score of each spindle; the higher the anomaly score, the greater the likelihood of spindle abnormality, and vice versa. A preset scoring threshold value, such as 0.9, representing the abnormal scoring level is preset through multiple tests, and the characteristic normal spindles and the characteristic abnormal spindles in the spinning frame containing spindles are determined through the magnitude relation between the abnormal scoring of each spindle and the preset scoring threshold value. The spindles with normal characteristics are spindles with normal characteristic data, and the spindles with abnormal characteristics are spindles with abnormal characteristic data. Specifically, the step of determining the characteristic normal spindle and the characteristic abnormal spindle in the spinning frame according to the abnormal scores comprises the following steps:
step S411, comparing each abnormal score with a preset score threshold, and determining a first abnormal score which is greater than the preset score threshold and a second abnormal score which is less than or equal to the preset score threshold in each abnormal score;
step S412, spindles corresponding to each first abnormal score are determined as the characteristic abnormal spindles, and spindles corresponding to each second abnormal score are determined as the characteristic normal spindles.
Further, comparing each abnormal score with a preset score threshold respectively, searching abnormal scores which are larger than the preset score threshold in each abnormal score as first abnormal scores, and searching abnormal scores which are smaller than or equal to the preset score threshold in each abnormal score as second abnormal scores. The abnormality represented by the first abnormal score is relatively high, so that the spindle generating each first abnormal score is determined as a characteristic abnormal spindle. The abnormality represented by the second abnormality score is relatively low, so that the spindle that generated each second abnormality score is determined as the characteristic normal spindle.
Step S42, determining normal spindles in the spinning machine according to the speed normal spindles and the characteristic normal spindles, and determining spindles to be determined in the spinning machine based on the normal spindles;
step S43, according to each speed abnormal spindle and each characteristic abnormal spindle, determining an abnormal spindle and a spindle to be determined in the spinning frame;
further, after the characteristic normal spindles which are normal on the characteristic data in the spinning frame are determined, the normal spindles and the spindles to be determined in the spinning frame are determined in combination with the speed normal spindles which are normal on the speed dimension in the spinning frame. And performing intersection operation on the normal spindles with each speed and the normal spindles with each characteristic, and taking the intersection operation between the normal spindles with each speed and the normal spindles with each characteristic as the first type of intersection operation. The result obtained by the first type intersection operation is the spindle which is normal in speed dimension and characteristic data, the spindle is the spindle which falls into the first type intersection operation, and the spindle is determined as the normal spindle in the spinning frame. For spindles which are not in the intersection operation result, spindles which are only normal on the speed dimension or the characteristic data are used; the spindles are the spindles except the normal spindles in the spinning frame which fall into the intersection operation of the first kind, and the spindles are determined as the spindles to be determined in the spinning frame so as to further determine the abnormality.
Similarly, for the characteristic abnormal spindle abnormal in the spinning frame on the characteristic data, the abnormal spindle and the spindle to be determined in the spinning frame are determined by combining the speed abnormal spindle abnormal in the spinning frame on the speed dimension. And performing intersection operation on each speed abnormal spindle and each characteristic abnormal spindle, and taking the intersection operation between the two spindles as a second type of intersection operation. And the result obtained by the second type intersection operation is the spindle which is abnormal in speed dimension and characteristic data, the spindle is the spindle which falls into the second type intersection operation, and the spindle is determined as the abnormal spindle in the spinning frame. For spindles which are not in the intersection operation result, spindles which are abnormal only on the speed dimension or the characteristic data are used; the spindles falling outside the intersection operation of the second category are determined as spindles to be determined in the spinning frame, so as to further determine the abnormality.
And step S44, updating abnormal spindles in the spinning frame according to the spindles to be determined to form target abnormal spindles in the spinning frame.
Further, after the normal spindles, the abnormal spindles and the spindles to be determined in the spinning frame are determined, the abnormality of the spindles to be determined is continuously determined. And updating the initial abnormal spindle from the abnormal spindles determined again from the spindles to be determined to form the final target abnormal spindle in the spinning frame. Specifically, the method comprises the steps of updating abnormal spindles in a spinning machine according to spindles to be determined, and forming target abnormal spindles in the spinning machine, wherein the steps comprise:
step S441, every preset detection period, obtaining a plurality of to-be-determined spindle speeds of the to-be-determined spindles in the preset detection period, and calculating the average value of the to-be-determined spindle speeds of the to-be-determined spindles;
step S442, dividing the spindles to be determined into spindles with normal speeds to be determined and spindles with abnormal speeds to be determined according to the mean values of the speeds to be determined;
step S443, determining undetermined abnormal score of each spindle to be determined according to the undetermined characteristic data set of each spindle to be determined;
and step S444, updating the abnormal spindles in the spinning frame according to the undetermined abnormal scores, the undetermined speed normal spindles and the undetermined speed abnormal spindles to form target abnormal spindles in the spinning frame.
Further, a preset detection period for detecting the spindle to be determined again is preset. The cycle time of the preset detection period can be set to be shorter than the preset period so as to quickly determine the abnormality of the spindle to be determined. And every interval of the preset detection period, the upper computer acquires the to-be-determined spindle speed of the to-be-determined spindle generated in the preset detection period from the lower computer of each spinning frame, and further performs mean value calculation on the to-be-determined spindle speed of each to-be-determined spindle to obtain the mean value of the to-be-determined spindle speed of each to-be-determined spindle. And performing probability calculation on the speed average value of each spindle to be determined, and dividing the spindles to be determined into spindles with normal speeds to be determined and spindles with abnormal speeds to be determined according to the distribution interval of the probability values.
Further, an undetermined characteristic data set of each spindle to be determined in a preset detection period is formed, and an undetermined abnormity score of each spindle to be determined is generated according to the undetermined characteristic data set of each spindle to be determined. Determining the abnormal spindle with undetermined characteristics and the normal spindle with undetermined characteristics according to the size relation between each undetermined abnormal score and a preset score threshold; determining a new abnormal spindle and a new spindle to be determined in the spindles to be determined by intersection operation of the abnormal spindles with undetermined characteristics and the abnormal spindles with undetermined speed; and determining a new normal spindle and a new spindle to be determined in the spindles to be determined by the intersection operation of the normal spindles with undetermined characteristics and the normal spindles with undetermined speed. And marking the new abnormal spindle as the abnormal spindle of the spinning frame, determining the abnormal spindle in the spindles to be determined through each undetermined abnormal score, each undetermined speed normal spindle and each undetermined speed abnormal spindle, and updating the abnormal spindle in the spinning frame. And carrying out circular detection according to a preset detection period until the spindles to be determined are divided into normal spindles and abnormal spindles, finishing updating the abnormal spindles in the spinning frame, and determining the updated abnormal spindles as the target abnormal spindles in the spinning frame.
The abnormal spindles in the spinning frame and the spindles to be determined are determined by combining the spindles abnormal in the speed dimension and the spindles abnormal in the characteristic data, and a circulating detection mechanism is set for the spindles to be determined so as to further detect the abnormal spindles in the spindles to be determined, update the abnormal spindles in the spinning frame and form the final target abnormal spindles. The abnormal spindles are determined through multiple dimensions, and the spindles to be determined are detected in a circulating mode, so that the accuracy of the finally determined target abnormal spindles is improved.
Further, based on the first or second embodiment of the method for detecting abnormal spindles in the spinning frame of the present invention, a third embodiment of the method for detecting abnormal spindles in the spinning frame of the present invention is provided.
The third embodiment of the method for detecting abnormal spindles in the spinning frame differs from the first or second embodiment of the method for detecting abnormal spindles in the spinning frame in that the step of determining the abnormality score of each spindle according to the characteristic data set of each spindle comprises:
step S31, obtaining the broken end times and the weak twist times of each spindle in the preset period, and forming the average value of the spindle speed, the broken end times and the weak twist times of each spindle into the characteristic data value of each spindle;
step S32, calculating the probability density of each spindle on each data in the characteristic data set, and determining the total probability density of each spindle according to each probability density of each spindle;
step S33, calculating the abnormal score of each spindle according to the total probability density of each spindle.
In bookIn an embodiment, an anomaly score for characterizing spindle abnormality is generated by a feature data set for characterizing spindle operating state. Specifically, the lower computer detects broken ends and weak twists of all spindles in the spinning machine, and counts the broken ends and the weak twists in a preset period. The upper computer sends a communication request to the lower computer to obtain the weak twist times of each spindle after the number of broken ends in a preset period. And forming the spindle speed average value, the broken end times and the weak twist times of each spindle into a characteristic data set of each spindle. For example, the characteristic data set of the spindle Xi is Xi(s) for the spindle speed mean value s, the number of broken ends b and the number of weak twists wi,bi,wi) The characteristic data sets of the individual spindles can form a complete data set D, where D ═ X1,X2,X3,…,Xm}。
Further, an anomaly Score characterizing spindle anomalies is calculated based on the HOBS (Histogram-based Outlier Score) algorithm. The HOBS algorithm involves two parts, wherein the first part is used for calculating the probability density of each characteristic data set in the whole data set, namely the total probability density of each spindle on the characteristic data set; the second part calculates the anomaly score of each spindle from the calculated total probability density. In the process of calculating the total probability density, for each characteristic data set, calculating the probability density of the spindle with the characteristic data set on each data to reflect the possibility of any one of abnormal rotating speed, abnormal broken end and abnormal weak twist of the spindle; and further determining the total probability density of the spindles according to the probability density on each datum, and reflecting the overall possibility of the spindles comprehensively having abnormal rotating speed, abnormal broken ends and abnormal weak twist through each probability density. For the spindle speed mean value s, the number of broken ends b and the number of weak twists w, the probability density of a certain data in the characteristic data set is Ps(p)、Pb(P) and Pw(p); multiplying each probability density to obtain the total probability density P (P) of the spindle, namely P (P) ═ Ps(p)*Pb(p)*Pw(p)。
Furthermore, in the HBOS algorithm, a second preset formula for calculating the abnormal score is preset, and the calculated total probability density is transmitted to the second preset formula, so that the abnormal score of the spindle can be calculated. Wherein the second predetermined formula and its variants are:
where d represents the number of data in the feature data set, and HBOS (p) represents the anomaly score.
And carrying out logarithmic operation on the total probability density of each spindle through a second preset formula, and taking a negative value of a logarithmic operation result to obtain the abnormal score of each spindle.
It should be noted that the abnormal score calculated by each spindle through the second preset formula may be greater than the value 1 or smaller than the preset value 1, and in order to facilitate the uniform comparison with the preset score threshold, the embodiment is provided with a maximum ratio updating mechanism. Specifically, after the abnormal score of each spindle is obtained, the abnormal scores are compared among the abnormal scores, the maximum score value is determined, the ratio operation is carried out on the abnormal score of each spindle and the maximum score value, and the obtained ratio result is used as the updated abnormal score of each spindle.
In the embodiment, the total probability density of the spindle on the characteristic data set is calculated through the characteristic data value formed by the number of broken ends, the number of weak twists and the spindle speed average value, and then the abnormality score is determined according to the total probability density to represent the abnormality of the spindle. The abnormity of the spindles is reflected by a plurality of characteristic factors, so that the abnormal spindles can be determined more accurately.
Further, based on the first, second or third embodiment of the method for detecting abnormal spindles in the spinning frame of the present invention, a fourth embodiment of the method for detecting abnormal spindles in the spinning frame of the present invention is provided.
The fourth embodiment of the method for detecting abnormal spindles in the spinning frame is different from the first, second or third embodiments of the method for detecting abnormal spindles in the spinning frame in that the step of determining the normal-speed spindles and the abnormal-speed spindles in the spinning frame according to the average value of the spindle speeds comprises the following steps:
step S21, calculating the integral mean value and standard deviation of each ingot speed mean value, and determining the ingot speed deviation between each ingot speed mean value and the integral mean value;
step S22, updating the standard deviation based on a preset multiple, and searching a first ingot speed deviation which is greater than the updated standard deviation and a second ingot speed deviation which is less than or equal to the updated standard deviation in each ingot speed deviation;
step S23, determining the spindle corresponding to each first spindle speed deviation as the abnormal spindle speed, and determining the spindle corresponding to each second spindle speed deviation as the normal spindle speed.
In the embodiment, the spindle speed mean value of each spindle in normal distribution is processed through a 3 delta rule, and the spindle with normal speed and the spindle with abnormal speed in the spinning frame are determined. Specifically, the integral mean value and the standard deviation of each spindle speed mean value in normal distribution are calculated, namely the integral mean value and the standard deviation of the rotating speed of all spindles in the spinning frame in a preset period are calculated. And after the integral mean value is obtained, carrying out deviation calculation on each ingot speed mean value and the integral mean value respectively to obtain the ingot speed deviation between each ingot speed mean value and the integral mean value. And then, taking the preset 3 times as a preset multiple, and updating the standard deviation according to the preset multiple, namely multiplying the standard deviation by a preset multiple speed to obtain a new standard deviation. Comparing each ingot speed deviation with the updated standard deviation, and determining the ingot speed deviation larger than the updated standard deviation as a first ingot speed deviation; and determining as the second spindle speed deviation the spindle speed deviation of less than or equal to the updated standard deviation among the spindle speed deviations.
Further, the first ingot speed deviation represents that the average value of the ingot speed is within an abnormal probability interval of 3 delta rule, and the second ingot speed represents that the average value of the ingot speed is within a normal probability interval of 3 delta rule. And searching and generating the average value of the first spindle speeds, searching and generating the spindles of the average value of the spindle speeds, and determining the searched spindles as the spindles with abnormal speeds. Similarly, searching each spindle generating the spindle speed mean value by searching each spindle speed mean value generating each second spindle speed deviation, and determining each spindle obtained by searching as a speed abnormal spindle. In this way, the speed abnormal spindles which are characterized in the speed dimension are obtained, and the speed normal spindles which are characterized in the speed dimension are obtained.
In the embodiment, each spindle in the spinning frame is divided into a normal-speed spindle and an abnormal-speed spindle through an abnormal probability interval and a normal probability interval, and the abnormality of each spindle on the speed dimension is represented. The final target abnormal spindle in the spinning frame is determined from multiple dimensions by combining the abnormality of each spindle on the characteristic data, and the accuracy of the determined target abnormal spindle is improved.
The invention also provides a detection device for the abnormal spindle in the spinning frame. The detection device for the abnormal spindle in the spinning frame comprises:
the calculation module is used for calculating the spindle speed mean value of each spindle in the spinning frame according to a plurality of spindle speeds of each spindle in a preset period;
the first determining module is used for determining the spindles with normal speed and the spindles with abnormal speed in the spinning frame according to the spindle speed average value;
a second determination module for determining an anomaly score for each of said spindles from a feature data set for each of said spindles;
and the third determining module is used for determining a target abnormal spindle in the spinning frame according to each abnormal score, each normal-speed spindle and each abnormal-speed spindle.
Further, the third determining module comprises:
the first determining unit is used for determining a characteristic normal spindle and a characteristic abnormal spindle in the spinning frame according to each abnormal score;
a second determining unit, configured to determine a normal spindle in the spinning machine according to each of the normal speed spindles and each of the characteristic normal spindles, and determine a spindle to be determined in the spinning machine based on the normal spindle;
a third determining unit, configured to determine an abnormal spindle and a spindle to be determined in the spinning frame according to each speed abnormal spindle and each characteristic abnormal spindle;
and the updating unit is used for updating the abnormal spindle in the spinning frame according to each spindle to be determined to form a target abnormal spindle in the spinning frame.
Further, the first determining unit is further configured to:
comparing each abnormal score with a preset score threshold value, and determining a first abnormal score which is greater than the preset score threshold value and a second abnormal score which is less than or equal to the preset score threshold value in each abnormal score;
determining spindles corresponding to each of the first anomaly scores as the characteristic anomalous spindles, and determining spindles corresponding to each of the second anomaly scores as the characteristic normal spindles.
Further, the second determination unit is further configured to:
performing a first type intersection operation on each normal-speed spindle and each normal-characteristic spindle, determining the spindles falling into the first type intersection operation as normal spindles in the spinning frame, and determining other spindles except the normal spindles in the spinning frame as the spindles to be determined;
the third determination unit is further configured to:
and performing second type intersection operation on each speed abnormal spindle and each characteristic abnormal spindle, determining the spindles falling into the second type intersection operation as the abnormal spindles in the spinning frame, and determining the spindles falling out of the second type intersection operation as the spindles to be determined in the spinning frame.
Further, the update unit is further configured to:
every interval preset detection period, obtaining a plurality of to-be-determined spindle speeds of each spindle to be determined in the preset detection period, and calculating the average value of the to-be-determined spindle speeds of each spindle to be determined;
dividing the spindles to be determined into spindles with normal speeds to be determined and spindles with abnormal speeds to be determined according to the mean values of the speeds to be determined of the spindles to be determined;
determining undetermined abnormal scores of the spindles to be determined according to the undetermined characteristic data set of the spindles to be determined;
and updating the abnormal spindles in the spinning frame according to the undetermined abnormal scores, the undetermined speed normal spindles and the undetermined speed abnormal spindles to form a target abnormal spindle in the spinning frame.
Further, the second determining module further comprises:
the obtaining unit is used for obtaining the end breaking times and the weak twisting times of each spindle in the preset period, and forming the spindle speed average value, the end breaking times and the weak twisting times of each spindle into a characteristic data value of each spindle;
a first calculation unit for calculating the probability density of each spindle on the respective data in the characteristic data set and determining the total probability density of each spindle according to the respective probability density of each spindle;
a second calculating unit for calculating an anomaly score of each spindle according to the total probability density of each spindle.
Further, the first determining module further comprises:
the third calculating unit is used for calculating the integral mean value and the standard deviation of each ingot speed mean value and determining the ingot speed deviation between each ingot speed mean value and the integral mean value;
the searching unit is used for updating the standard deviation based on a preset multiple, and searching a first ingot speed deviation which is greater than the updated standard deviation and a second ingot speed deviation which is less than or equal to the updated standard deviation in the ingot speed deviations;
and the fourth determining unit is used for determining the spindle corresponding to each first spindle speed deviation as the abnormal spindle and determining the spindle corresponding to each second spindle speed deviation as the normal spindle.
Further, the calculation module further comprises:
the arrangement unit is used for arranging a plurality of spindle speeds of each spindle in a preset period in a numerical sequence from large to small in the spinning frame to form a numerical sequence of each spindle;
and the transmission unit is used for transmitting the numerical values in the numerical value sequence of each spindle to a preset formula for calculation to generate the spindle speed average value of each spindle.
The specific implementation of the detection device for the abnormal spindle in the spinning frame is basically the same as that of each embodiment of the detection method for the abnormal spindle in the spinning frame, and the detailed description is omitted here.
In addition, the embodiment of the invention also provides a readable storage medium.
The readable storage medium stores a detection program of abnormal spindles in the spinning frame, and the detection program of abnormal spindles in the spinning frame realizes the steps of the detection method of abnormal spindles in the spinning frame when being executed by the processor.
The readable storage medium of the present invention may be a computer readable storage medium, and the specific implementation manner of the readable storage medium of the present invention is substantially the same as that of each embodiment of the method for detecting an abnormal spindle in the spinning frame, and will not be described herein again.
The present invention is described in connection with the accompanying drawings, but the present invention is not limited to the above embodiments, which are only illustrative and not restrictive, and those skilled in the art can make various changes without departing from the spirit and scope of the invention as defined by the appended claims, and all changes that come within the meaning and range of equivalency of the specification and drawings that are obvious from the description and the attached claims are intended to be embraced therein.
Claims (9)
1. A method for detecting abnormal spindles in a spinning frame is characterized by comprising the following steps:
calculating the spindle speed mean value of each spindle in a spinning frame according to a plurality of spindle speeds of each spindle in a preset period;
determining normal-speed spindles and abnormal-speed spindles in the spinning frame according to the spindle speed average values;
acquiring the number of broken ends and the number of weak twists of each spindle in the preset period, and forming the mean value of the spindle speed, the number of broken ends and the number of weak twists of each spindle into a characteristic data set of each spindle;
determining a total probability density for each of said spindles from a characteristic data set for each of said spindles, determining an anomaly score for each of said spindles from said total probability density for each of said spindles;
determining a characteristic normal spindle and a characteristic abnormal spindle in the spinning frame according to each abnormal score;
determining normal spindles in the spinning machine according to the speed normal spindles and the characteristic normal spindles, and determining spindles to be determined in the spinning machine based on the normal spindles;
determining abnormal spindles and spindles to be determined in the spinning frame according to the abnormal speed spindles and the abnormal characteristic spindles;
and updating the abnormal spindles in the spinning frame according to the spindles to be determined to form target abnormal spindles in the spinning frame.
2. The method for detecting abnormal spindles in a spinning frame as claimed in claim 1, wherein the step of determining the characteristic normal spindles and the characteristic abnormal spindles in the spinning frame according to each of the abnormality scores comprises:
comparing each abnormal score with a preset score threshold value, and determining a first abnormal score which is greater than the preset score threshold value and a second abnormal score which is less than or equal to the preset score threshold value in each abnormal score;
determining spindles corresponding to each of the first anomaly scores as the characteristic anomalous spindles, and determining spindles corresponding to each of the second anomaly scores as the characteristic normal spindles.
3. The method of detecting abnormal spindles in a spinning frame as claimed in claim 1, wherein the step of determining the normal spindles in the spinning frame according to each of the speed normal spindles and each of the characteristic normal spindles, and determining the spindles to be determined in the spinning frame based on the normal spindles comprises:
performing a first type intersection operation on each normal-speed spindle and each normal-characteristic spindle, determining the spindles falling into the first type intersection operation as normal spindles in the spinning frame, and determining other spindles except the normal spindles in the spinning frame as the spindles to be determined;
the step of determining the abnormal spindles and the spindles to be determined in the spinning frame according to each abnormal spindle with speed and each abnormal spindle with characteristics comprises the following steps:
and performing second type intersection operation on each speed abnormal spindle and each characteristic abnormal spindle, determining the spindles falling into the second type intersection operation as the abnormal spindles in the spinning frame, and determining the spindles falling out of the second type intersection operation as the spindles to be determined in the spinning frame.
4. The method for detecting abnormal spindles in a spinning frame as claimed in claim 1, wherein the step of updating the abnormal spindles in the spinning frame according to the spindles to be determined to form the target abnormal spindle in the spinning frame comprises:
every interval preset detection period, obtaining a plurality of to-be-determined spindle speeds of each spindle to be determined in the preset detection period, and calculating the average value of the to-be-determined spindle speeds of each spindle to be determined;
dividing the spindles to be determined into spindles with normal speeds to be determined and spindles with abnormal speeds to be determined according to the mean values of the speeds to be determined of the spindles to be determined;
determining undetermined abnormal scores of the spindles to be determined according to the undetermined characteristic data set of the spindles to be determined;
and updating the abnormal spindles in the spinning frame according to the undetermined abnormal scores, the undetermined speed normal spindles and the undetermined speed abnormal spindles to form a target abnormal spindle in the spinning frame.
5. The method for detecting anomalous spindles in spinning frames according to any of claims 1 to 4, wherein said step of determining an anomaly score for each of said spindles on the basis of a characteristic data set for each of said spindles comprises:
acquiring the number of broken ends and the number of weak twists of each spindle in the preset period, and forming the average value of the spindle speed, the number of broken ends and the number of weak twists of each spindle into a characteristic data value of each spindle;
calculating the probability density of each spindle on each data in the characteristic data set, and determining the total probability density of each spindle according to each probability density of each spindle;
calculating an anomaly score for each of the spindles based on the total probability density for each of the spindles.
6. The method for detecting abnormal spindles in a spinning frame as claimed in any one of claims 1 to 4, wherein the step of determining the normal-speed spindles and the abnormal-speed spindles in the spinning frame according to the mean value of the spindle speeds comprises:
calculating the integral mean value and standard deviation of each ingot speed mean value, and determining the ingot speed deviation between each ingot speed mean value and the integral mean value;
updating the standard deviation based on a preset multiple, and searching a first ingot speed deviation which is greater than the updated standard deviation and a second ingot speed deviation which is less than or equal to the updated standard deviation in the ingot speed deviations;
and determining spindles corresponding to each first spindle speed deviation as abnormal spindles, and determining spindles corresponding to each second spindle speed deviation as normal spindles.
7. The method for detecting abnormal spindles in a spinning frame as claimed in any one of claims 1 to 4, wherein the step of calculating the mean value of the spindle speeds of each spindle in the spinning frame according to the plurality of spindle speeds of each spindle in a preset period comprises:
arranging a plurality of spindle speeds of each spindle in the spinning machine in a preset period according to a numerical sequence from large to small to form a numerical sequence of each spindle;
and transmitting the numerical values in the numerical value sequence of each spindle to a preset formula for calculation to generate the spindle speed average value of each spindle.
8. An abnormal spindle detection device in a spinning frame, characterized in that the abnormal spindle detection device in the spinning frame comprises a memory, a processor and a detection program of the abnormal spindle in the spinning frame stored on the memory and capable of running on the processor, wherein the detection program of the abnormal spindle in the spinning frame is executed by the processor to realize the steps of the detection method of the abnormal spindle in the spinning frame according to any one of claims 1 to 7.
9. A readable storage medium, characterized in that the readable storage medium stores thereon a detection program of abnormal spindles in a spinning frame, the detection program of abnormal spindles in a spinning frame implementing the steps of the detection method of abnormal spindles in a spinning frame according to any one of claims 1 to 7 when executed by a processor.
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| CN110485011A (en) * | 2019-09-30 | 2019-11-22 | 常州宏大智能装备产业发展研究院有限公司 | Ring spinning frame resultant yarn winding mechanism operating status on-line monitoring method |
| CN110952180A (en) * | 2019-12-23 | 2020-04-03 | 无锡物联网创新中心有限公司 | Spinning frame single spindle on-line measuring system |
| CN111122897A (en) * | 2019-12-23 | 2020-05-08 | 无锡物联网创新中心有限公司 | Spindle rotating speed capturing method in magnetoelectric single spindle detection system and related device |
| CN111074392A (en) * | 2019-12-31 | 2020-04-28 | 西门子工厂自动化工程有限公司 | Spinning frame spindle rotating speed control method and control system |
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