CN115636103A - Working condition separation method, device, equipment and storage medium of PIU subsystem - Google Patents
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Abstract
The invention provides a working condition separation method, a working condition separation device, equipment and a storage medium of a PIU (particle image processing unit) subsystem, and solves the problem that the working condition separation method of the conventional PIU subsystem is low in efficiency. The method comprises the following steps: the method comprises the steps of obtaining bus data of a PIU subsystem, when the bus data are ordinary bus data, preprocessing the ordinary bus data according to a first preset method to obtain first ordinary bus data, and performing working condition separation processing on the first ordinary bus data according to a preset first clustering algorithm to obtain initial ordinary working condition data; when the bus data is the accelerometer bus data, performing working condition separation processing on the accelerometer bus data based on a preset second clustering algorithm to obtain initial acceleration working condition data; and according to a second preset method, carrying out data jitter removal processing on the initial common working condition data or the initial acceleration working condition data to obtain final common working condition data or final acceleration working condition data. The invention can improve the efficiency of the working condition separation of the PIU subsystem.
Description
Technical Field
The invention relates to the technical field of data mining, in particular to a working condition separation method, a working condition separation device, working condition separation equipment and a storage medium of a PIU (particle image processing unit) subsystem.
Background
An aircraft system is a large and complex aircraft system that travels off the ground, one of the most complex high-tech products manufactured by man. The PIU subsystem, namely a pilot operation interface unit system, is mainly used for realizing the transmission and display of pilot operation instructions and airplane information. In the actual flight process, due to changes of production conditions, environments, requirements and the like, the operation working conditions of all equipment of the airplane can be changed continuously, and along with the increasing complexity of the system structure and the flight environment of the airplane, the working condition changes become more complicated. Therefore, when the airplane is tested and diagnosed, the fault and abnormality detection under various working condition modes needs to be realized so as to improve the safety and reliability of the airplane, but the existing working condition separation method has the problem of low efficiency.
Disclosure of Invention
In view of this, embodiments of the present invention provide a method, an apparatus, a device, and a storage medium for separating operating conditions of a PIU subsystem, so as to solve the problem in the prior art that the operating condition separation method of the PIU subsystem has low efficiency.
In order to solve the technical problem, the application provides a working condition separation method of a PIU subsystem, which comprises the following steps:
acquiring bus data of a PIU subsystem, wherein the bus data comprises common bus data and accelerometer bus data, and the common bus data comprises a plurality of single frame data;
when the bus data is the common bus data, preprocessing the common bus data according to a first preset method to obtain first common bus data, wherein single-frame data of the first common bus data is discontinuously increased or continuously decreased;
according to a preset first clustering algorithm, performing working condition separation processing on the first common bus data to obtain initial common working condition data, wherein the initial common working condition data comprises highest-order data, lowest-order data and zero-order data;
when the bus data is the accelerometer bus data, based on a preset second clustering algorithm, performing working condition separation processing on the accelerometer bus data to obtain initial acceleration working condition data;
and according to a second preset method, carrying out data jitter removal processing on the initial common working condition data or the initial acceleration working condition data to obtain final common working condition data or final acceleration working condition data.
As some optional embodiments of the present application, the single frame data includes a removal tag, and when the bus data is the normal bus data, the step of preprocessing the normal bus data according to a first preset method to obtain first normal bus data includes:
traversing each single frame of data of the common bus data, and acquiring a difference value between each single frame of data and single frame data of a previous frame;
when the difference value is larger than a preset difference value or the difference value is smaller than the opposite number of the preset difference value, adding the increment pointers and setting the decrement pointers to be zero, wherein the initial values of the increment pointers and the decrement pointers are both 0;
when the difference value is smaller than a preset difference value or the difference value is larger than the opposite number of the preset difference value, setting the incremental pointer to be zero and adding one to the decremental pointer;
when the increasing pointer is more than or equal to 3 or the decreasing pointer is more than or equal to 3, setting the removal labels of the current single-frame data and the single-frame data of the previous 3 frames of the current single-frame data to be 1;
and removing all the single-frame data with the removal label of 1 to obtain first common bus data.
As some optional embodiments of the present application, the step of performing working condition separation processing on the first common bus data according to a preset first clustering algorithm to obtain initial common working condition data includes:
acquiring a first clustering reference distance according to a first preset distance division parameter and the range of the first common bus data;
creating a first working condition data set, wherein the first working condition data set comprises single-frame data of a first frame in the first common bus data;
sequentially acquiring the difference value between single frame data except for the first frame in the first common bus data and the average value of the created first working condition data set;
when the difference value is larger than the first clustering reference distance, newly creating a first working condition data set, and adding corresponding single-frame data into the newly created working condition data set;
when the difference value is smaller than or equal to the first clustering reference distance, adding the corresponding single-frame data into the corresponding first working condition data set;
and obtaining initial common working condition data according to all the first working condition data sets.
As some optional embodiments of the present application, the step of obtaining initial common operating condition data according to all the first operating condition data sets includes:
acquiring the average value and the absolute value average value of all the first working condition data sets;
taking the first working condition data set with the largest average value as the highest data;
taking the first working condition data set with the minimum average value as the lowest data;
and taking the first working condition data set with the minimum absolute value average value as zero position data.
As some optional embodiments of the present application, the single frame data includes a removal tag and an index tag, the index tag corresponds to a frame number of the single frame data in the accelerometer bus data, and when the bus data is the accelerometer bus data, based on a preset second clustering algorithm, the accelerometer bus data is subjected to condition separation processing to obtain initial acceleration condition data, including:
setting the removal tag of single-frame data with continuous three-frame increasing or continuous three-vibration decreasing in the accelerometer bus data as 1;
acquiring a second clustering reference distance according to a second preset distance dividing parameter and the frame number of the accelerometer bus data;
creating a second working condition data set, wherein the second working condition data set comprises initial data, and the initial data is single frame data with the minimum index tag in the single frame data with the removal tag of 1;
traversing the single-frame data which is not the initial data and has the removed tag of 1 in the accelerometer bus data according to the index tag, and acquiring the difference value of the index tag of the single-frame data and the single-frame data of the previous frame;
when the difference value is smaller than or equal to the second clustering reference distance, adding the corresponding single-frame data into a second working condition data set corresponding to the previous single-frame data;
when the difference value is larger than the second clustering reference distance, a second working condition data set is created again, and corresponding single-frame data are added into the created second working condition data set;
calculating the upper and lower bounds of the index labels of all the second working condition data sets;
setting the removal labels of the single-frame data between the upper boundary and the lower boundary to be 1;
and eliminating the data with the removed label being 1 to obtain initial acceleration working condition data.
As some optional embodiments of the present application, the performing data jitter removal processing on the common working condition data or the acceleration working condition data according to a second preset method to obtain final common working condition data or final acceleration working condition data includes:
sampling according to a preset sampling interval in the single-frame data of the initial common working condition data or the continuous preset number of the initial acceleration working condition data to obtain sampling data;
if the sampling data is increased or decreased, setting a removal label corresponding to the sampling data to be 1;
removing the data with the removed label of 1 to obtain intermediate common working condition data or intermediate acceleration working condition data;
acquiring an index hopping threshold, a hopping left pruning range and a hopping right pruning range;
acquiring single-frame data with index jump larger than the index jump threshold in the intermediate common working condition data or the intermediate acceleration working condition data according to the index tag, and recording the single-frame data as jump data;
setting removal tags of single frame data in the hopping left pruning range and the hopping right pruning range of the hopping data to be 1;
and eliminating the data with the removed label of 1 to obtain the final common working condition data or the final acceleration working condition data.
As some optional embodiments of the present application, the index jump threshold is 500 to 1000, and both the jump left pruning range and the jump right pruning range are 10 to 30.
In order to solve the technical problem, the present application further provides a working condition separating device of a PIU subsystem, which is characterized in that the device includes:
the system comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring bus data of a PIU subsystem, the bus data comprises common bus data and accelerometer bus data, and the common bus data comprises a plurality of single frame data;
the preprocessing module is used for preprocessing the common bus data according to a first preset method to obtain first common bus data when the bus data is the common bus data, wherein single-frame data of the first common bus data is discontinuously increased or continuously decreased;
the first working condition separation module is used for carrying out working condition separation processing on the first common bus data according to a preset first clustering algorithm to obtain initial common working condition data, wherein the initial common working condition data comprises highest data, lowest data and zero data;
the second working condition separation module is used for carrying out working condition separation processing on the accelerometer bus data based on a preset second clustering algorithm when the bus data are the accelerometer bus data to obtain initial acceleration working condition data;
and the data jitter removal module is used for performing data jitter removal processing on the initial common working condition data or the initial acceleration working condition data according to a second preset method to obtain final common working condition data or final acceleration working condition data.
In order to solve the above technical problem, the present application further provides an electronic device, including: at least one processor, at least one memory, and computer program instructions stored in the memory, which when executed by the processor, implement the method of the first aspect of the embodiments described above.
To solve the above technical problem, the present application also proposes a storage medium having stored thereon computer program instructions, which when executed by a processor implement the method of the first aspect in the above embodiments.
In summary, the invention has the following beneficial effects:
the application discloses a working condition separation method of a PIU subsystem, which comprises the steps of obtaining bus data of the PIU subsystem, wherein the bus data comprises common bus data and accelerometer bus data, and the common bus data comprises a plurality of single-frame data; when the bus data are the common bus data, preprocessing the common bus data according to a first preset method to obtain first common bus data, wherein single-frame data of the first common bus data are discontinuously increased or continuously decreased, due to preprocessing, the single-frame data of the obtained first common bus data are discontinuously increased or continuously decreased, data slope data are not suitable for any one of working condition data needing to be distinguished, and by removing a data slope, the speed of separating the working conditions can be increased, and the efficiency is improved; according to a preset first clustering algorithm, working condition separation processing is carried out on the first common bus data to obtain initial common working condition data, wherein the initial common working condition data comprise highest data, lowest data and zero data, the clustering algorithm is an unsupervised algorithm, and as a training set is not needed, the algorithm is simple and rapid, and the speed of working condition separation can be further improved; when the bus data are the accelerometer bus data, based on a preset second clustering algorithm, working condition separation processing is carried out on the accelerometer bus data to obtain initial acceleration working condition data, and it can be seen that the accelerometer bus data and the common bus data respectively pass through different clustering algorithms, so that the flexibility is high; and according to a second preset method, carrying out data shaking removal processing on the initial common working condition data or the initial acceleration working condition data to obtain final common working condition data or final acceleration working condition data.
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments of the present invention will be briefly described below, and for those skilled in the art, without any creative effort, other drawings can be obtained according to the drawings, and these drawings are all within the protection scope of the present invention.
FIG. 1 is a flow chart of a method for separating operating conditions of a PIU subsystem according to an embodiment of the present invention.
Fig. 2 is a schematic structural diagram of a condition separating device of the PIU subsystem according to an embodiment of the present invention.
Fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
Features of various aspects and exemplary embodiments of the present invention will be described in detail below, and in order to make objects, technical solutions and advantages of the present invention more apparent, the present invention will be further described in detail below with reference to the accompanying drawings and the embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not to be construed as limiting the invention. It will be apparent to one skilled in the art that the present invention may be practiced without some of these specific details. The following description of the embodiments is merely intended to provide a better understanding of the present invention by illustrating examples of the present invention.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrases "comprising 8230; \8230;" comprises 8230; "does not exclude the presence of additional like elements in a process, method, article, or apparatus that comprises the recited element.
The aircraft system is a complex engineering system and consists of a plurality of systems such as a navigation system, an electromechanical system, a flight management and flight control system, a power system, a communication system and the like. The subsystem of the Power Interface Unit (PIU) is a subsystem of a Pilot operation Interface Unit in the technical field of aviation, and can acquire electrical signals of each key component in an aircraft system through an Interface, convert the electrical signals into digital signals through a bus network of the electrical signals and transmit the digital signals to a computer to form test data.
However, based on a large amount of data obtained by an aircraft test, most of the existing aircraft fault detection is performed in a single-working-condition mode, most of complex working conditions are generally integrated into a global model, and only a group of normal data relationships and ranges are used as a basis for judging whether the system is abnormal or not. Actual tests show that normal test data obtained under different working conditions are different for the aircraft system with multiple working conditions. Therefore, it is not appropriate to use a single global model to detect the abnormality of the aircraft system, which may cause the parameter output deviation caused by the transformation between different working conditions to affect the judgment of the abnormality, and may also sacrifice the sensitivity of abnormality detection for considering more working conditions. Therefore, in order to solve the above problems, different working conditions need to be separated and then analyzed respectively.
At present, some researches adopt clustering or statistical analysis methods such as a k-means clustering algorithm, an SAGA algorithm, an FCM algorithm and the like to separate multiple working conditions in China. However, these methods are inefficient for large-scale data of aircraft systems and are not widely used, and further improvements are still needed.
In order to solve the technical problem, the application provides a working condition separation method of a PIU subsystem, and the method comprises the following steps:
s1, bus data of a PIU subsystem are obtained, wherein the bus data comprise common bus data and accelerometer bus data, and the common bus data comprise a plurality of single-frame data;
specifically, bus data of the PIU subsystem is obtained first, and the bus data can be divided into two types, namely common bus data and accelerometer bus data, according to the data working condition types included in the bus data, wherein the common bus data includes zero bit data, highest bit data and lowest bit data, in a specific embodiment, the common bus data includes first common bus data, second common bus data and third common bus data, the first common bus data includes lowest bit data and highest bit data, the second common bus data includes zero bit data, lowest bit data and highest bit data, and the initial threshold absolute values of the lowest bit data and the highest bit data are the same; the third common bus data comprises zero bit data, lowest bit data and highest bit data, wherein the initial threshold absolute values of the lowest bit data and the highest bit data are different; the accelerometer bus data are bus data generated in each accelerometer experiment and comprise normal overload measurement highest bit data and axial and lateral overload side zero bit data, wherein the normal overload measurement highest bit data and the axial and lateral overload side zero bit data can be divided into two working conditions, namely normal working conditions and jitter working conditions, and test data obtained under different working conditions are different.
S2, when the bus data are the common bus data, preprocessing the common bus data according to a first preset method to obtain first common bus data, wherein single-frame data of the first common bus data are discontinuously increased or continuously decreased;
specifically, bus data corresponding to each component in the PIU subsystem generally has a data slope, the data slope is a section of data with a continuous data increasing or decreasing trend, which is called a data slope (continuously increasing or decreasing or temporarily increasing or decreasing and then continuously increasing with a larger amplitude (trend increasing) or temporarily decreasing and then continuously decreasing with a larger amplitude (trend decreasing), the data slope is transition data of the data from a zero-position working condition to a highest (low) working condition or from the highest (low) working condition to the zero-position working condition, the data slope data does not belong to any of all working conditions needing to be distinguished, and is interference data which needs to be removed, so that the required zero-position working condition data, the highest-position working condition data and the lowest-position working condition data can be separated from the data of the removed data slope, therefore in this step, the common bus data is preprocessed according to a first preset method to obtain first common bus data, so that single-frame data of the first common bus data is discontinuously increased or continuously decreased to remove the data slope, and thus obtaining key position information such as jump efficiency by analyzing the less data and jump information, thereby improving analysis efficiency.
As some optional embodiments of the present application, the single frame data includes a removal tag, and when the bus data is the normal bus data, the step of preprocessing the normal bus data according to a first preset method to obtain first normal bus data includes:
s21, traversing each single frame of data of the common bus data, and acquiring a difference value between each single frame of data and the single frame of data of the previous frame;
specifically, in order to remove a data slope in common bus data, first, traversal needs to be performed on each single frame data in the common bus data to obtain a difference value between each single frame data and a single frame data of a previous frame, and an appearance position of the data slope can be determined according to the difference value, so that removal of the data slope is facilitated.
S22, when the difference value is larger than a preset difference value or the difference value is smaller than the opposite number of the preset difference value, adding the increment pointers and setting the decrement pointers to be zero, wherein the initial values of the increment pointers and the decrement pointers are both 0;
s23, when the difference value is smaller than a preset difference value or the difference value is larger than the inverse number of the preset difference value, setting the incremental pointer to be zero and adding one to the decremental pointer;
specifically, in order to realize identification of a data slope, an increment pointer and a decrement pointer are set, initial values of the increment pointer and the decrement pointer are both 0, when the difference is smaller than a preset difference or larger than the opposite number of the preset difference, the increment pointer is set to zero and the decrement pointer is incremented by one, when the difference is smaller than the preset difference or larger than the opposite number of the preset difference, the increment pointer is set to zero and the decrement pointer is incremented by one, the preset difference is a positive number, and the determination can be performed according to data characteristics of bus data, and no specific limitation is made herein; the data ramp can be quickly identified by setting the increment pointer and the decrement pointer, and when the value of the increment pointer or the decrement pointer exceeds a preset pointer value, the data ramp appears.
S24, when the increasing pointer is more than or equal to 3 or the decreasing pointer is more than or equal to 3, setting the removal labels of the current single-frame data and the single-frame data of the previous 3 frames of the current single-frame data to be 1;
specifically, in this embodiment, when the increment pointer or the decrement pointer is greater than or equal to 3, it indicates that three consecutive single-frame data are incremented or decremented, a data ramp occurs, three frames in the three consecutive single-frame data increments and decrements are the minimum frame number indicating that the data has an increment or decrement trend, the two consecutive frame incrementing and decrementing processes involve two frames of data and one increment or decrement, if the preset pointer value is adjusted to 2, the data on the non-data ramp is erroneously removed, and 3 frames can clearly indicate the increment and decrement trend of the data, and the non-data ramp data is not erroneously removed, and if the frame number is further increased, the missing detection and the missing removal of the data ramp are caused, so in this step, when the increment pointer is greater than or equal to 3 or the decrement pointer is greater than or equal to 3, the removal tags of the current single-frame data and the single-frame data of the previous 3 frames of the current single-frame data are both set to 1.
And S25, removing all the single-frame data with the removal labels of 1 to obtain first common bus data.
Specifically, in this step, all the single-frame data with the removal label of 1 are removed to obtain first general bus data, and the first general bus data does not have continuously increasing or continuously decreasing single-frame data, so that removal of a data slope is realized, and more key jump information such as data jump degree and data jump position can be obtained by analyzing less data information, thereby improving the efficiency of parameter correlation analysis.
S3, according to a preset first clustering algorithm, performing working condition separation processing on the first common bus data to obtain initial common working condition data, wherein the initial common working condition data comprises highest data, lowest data and zero data;
specifically, a first clustering algorithm is preset, and the first common sub-line data is subjected to working condition separation processing to obtain initial common working condition data, wherein the initial common working condition data comprises highest-bit data, lowest-bit data and zero-bit data, the preset first clustering algorithm can comprise a K-means clustering algorithm, a density-based clustering algorithm, a grid-based clustering method and the like, the clustering algorithms are all the prior art and are not described herein any more, the clustering algorithm is an unsupervised algorithm, and the algorithm is simple and quick and can further improve the speed of working condition separation because a training set is not needed.
As some optional embodiments of the present application, the step of performing working condition separation processing on the first common bus data according to a preset first clustering algorithm to obtain initial common working condition data includes:
s31, acquiring a first clustering reference distance according to a first preset distance division parameter and the range of the first common bus data;
specifically, first, a first clustering reference distance is obtained according to a first preset distance partition parameter and a range of the first common bus data, and the first clustering reference distance is calculated by the following formula
Dist＝range/range_div
In the formula, dist is the first clustering reference distance, range is the range of the first common bus data, range _ div is the first preset distance partition parameter, and the first preset distance partition parameter may be set according to actual conditions, in a specific embodiment, the value of the first preset distance partition parameter is 5.
S32, creating a first working condition data set, wherein the first working condition data set comprises single-frame data of a first frame in the first common bus data;
specifically, a first working condition data set is created firstly, and single-frame data of a first frame in the first common bus data is added into the first working condition data set to serve as initial data of the current first working condition data set, so that single-frame data except the single-frame data of the first frame can be obtained in subsequent algorithm steps and compared with an average value of the first working condition data set conveniently.
S33, sequentially obtaining the difference value of the single frame data except the first frame in the first common bus data and the average value of the created first working condition data set;
s34, when the difference value is larger than the first clustering reference distance, newly creating a first working condition data set, and adding corresponding single-frame data into the newly created working condition data set;
s35, when the difference value is smaller than or equal to the first clustering reference distance, adding corresponding single-frame data into a corresponding first working condition data set;
then, obtaining the difference value between the single frame data except the first frame in the first common bus data and the average value of the created first working condition data set in sequence, namely, comparing the single frame data of the second frame in the first common bus data with the average value of each created first working condition data set in sequence to obtain the difference value, when the difference value is greater than the first clustering reference distance, newly creating a first working condition data set, and adding the corresponding single frame data into the newly created first working condition data set; when the difference value is smaller than or equal to the first clustering reference distance, adding the corresponding single-frame data into the corresponding first working condition data set, and updating the average value of the corresponding first working condition data set; for example, first, a difference value between single frame data of a second frame and an average value of a first working condition data set 1 is obtained and recorded as a first difference value, where the first working condition data set 1 includes single frame data of a first frame, the first difference value is smaller than the first clustering reference distance, the single frame data of the second frame is added to the first working condition data set 1, and the average value of the first working condition data set 1 is updated, then, a second difference value between single frame data of a third frame in first common bus data and the updated average value is obtained, the second difference value is larger than the first clustering reference distance, a new first working condition data set 2 is created, the single frame data of the third frame is added to the first working condition data set 2, and so on until all the single frame data in the first common bus data are traversed;
and S36, obtaining initial common working condition data according to all the first working condition data sets.
Specifically, different working condition data in the first common bus data are separated through a clustering method, in the separation process, the first common bus data are subjected to frame-by-frame comparison and continuous updating of the average value of the working condition data, clustering is achieved, three data of a zero position state, a highest position state and a lowest position state are finally separated from the first common bus data, and a foundation is laid for subsequent multi-working condition fault diagnosis.
As some optional embodiments of the present application, the step of obtaining initial common operating condition data according to all the first operating condition data sets includes:
s361, obtaining the average value and the absolute value average value of all the first working condition data sets;
specifically, after each first working condition data set is obtained, an average value and an absolute value average value of each first working condition data set are obtained, and since single-frame data in each first working condition data set are different working condition data, it can be judged that each first working condition data set is highest data, lowest data or zero data through the average value and the absolute value average value of each first working condition data set;
s362, taking the first working condition data set with the largest average value as highest data;
s363, taking the first working condition data set with the minimum average value as the lowest data;
and S364, taking the first working condition data set with the minimum absolute value average value as zero position data.
Specifically, in each finally obtained first working condition data set, the first working condition data set with the minimum absolute value average value is data corresponding to a zero working condition and is recorded as zero data, the first working condition data set with the maximum average value is data corresponding to a highest working condition and is recorded as highest data, and the first working condition data set with the minimum average value is data corresponding to a lowest working condition and is recorded as lowest data.
S4, when the bus data are the accelerometer bus data, based on a preset second clustering algorithm, performing working condition separation processing on the accelerometer bus data to obtain initial acceleration working condition data;
specifically, when the bus data is the accelerometer bus data, based on a preset second clustering algorithm, performing working condition separation processing on the accelerometer bus data to obtain initial acceleration working condition data, in this embodiment, the accelerometer bus data includes normal overload measurement highest bit data and axial and lateral overload side zero position data, where the normal overload measurement highest bit data and the axial and lateral overload side zero position data can be divided into two working conditions, namely a normal working condition and a jitter working condition, test data obtained under different working conditions are different, and the initial acceleration working condition data obtained after the working condition separation processing only includes data of the normal working condition, so that the working condition separation of the accelerometer bus data is realized; in addition, because the data characteristics of the accelerometer bus data are different from those of the common bus data, the accelerometer bus data are subjected to working condition separation processing by different clustering methods, so that the flexibility of the algorithm is improved, and the efficiency of bus data working condition separation is improved.
As some optional embodiments of the present application, the single frame data includes a removal tag and an index tag, the index tag corresponds to a frame number of single frame data in the accelerometer bus data, and when the bus data is the accelerometer bus data, based on a preset second clustering algorithm, the accelerometer bus data is subjected to working condition separation processing to obtain initial acceleration working condition data, which includes:
s41, setting the removal tag of single-frame data with continuous three-frame increasing or continuous three-vibration decreasing in the accelerometer bus data as 1;
specifically, the data of the jitter working condition is formed by alternately forming a plurality of sections of increasing or decreasing data slopes, 3 frames in continuous 3-frame increasing and decreasing are the minimum frame number which shows that the data has an increasing or decreasing trend, the process of continuous two-frame increasing and decreasing relates to two frames of data and one-time increasing or decreasing, the increasing and decreasing once is defined as one-time oscillation, the one-time oscillation comprises one-time continuous increasing of two frames and one-time continuous decreasing of two frames, multiple continuous oscillations exist in the non-data slope of the data of the same working condition, if the data are adjusted to be 2 frames, the data of the normal working condition can be mistakenly removed, the 3-frame data can clearly show the increasing and decreasing trend of the data, the non-data slope data cannot be mistakenly removed, and if the frame number is further increased, the missing detection of the data slope in the jitter working condition data can be caused.
S42, acquiring a second clustering reference distance according to a second preset distance division parameter and the frame number of the accelerometer bus data;
specifically, a second clustering reference distance is obtained according to a second preset distance dividing parameter and the frame number of the accelerometer bus data, wherein the second clustering reference distance is calculated by the following formula:
Len_dist＝Len/Len_div
where Len _ dist is the second clustering reference distance, len _ div is the second preset distance partition parameter, and Len is the frame number of the accelerometer bus data, where the second preset distance partition parameter may be set according to an actual situation, and in a specific embodiment, the second preset distance partition parameter is 10.
S43, creating a second working condition data set, wherein the second working condition data set comprises initial data, and the initial data is single-frame data with the minimum index tag in the single-frame data with the removal tag of 1;
specifically, a second working condition data set is created firstly, and single-frame data with the smallest index tag in single-frame data with a tag of 1 removed in the accelerometer bus data is used as initial data of the second working condition data set;
s44, traversing the single-frame data which is not the initial data and has the removed tag of 1 in the accelerometer bus data according to the index tag, and acquiring the difference value of the index tag of the single-frame data and the previous single-frame data;
s45, when the difference value is smaller than or equal to the second clustering reference distance, adding the corresponding single-frame data into a second working condition data set corresponding to the previous single-frame data;
s46, when the difference value is larger than the second clustering reference distance, a second working condition data set is created again, and corresponding single-frame data is added into the created second working condition data set;
then, traversing the single-frame data, which is not the initial data and has the removed tag of 1, in the accelerometer bus data according to the index tag, acquiring a difference value between the single-frame data and the index tag of the previous single-frame data, newly creating a second working condition data set when the difference value is greater than the first clustering reference distance, and adding the corresponding single-frame data into the newly created second working condition data set; when the difference is smaller than or equal to the second clustering reference distance, adding the corresponding single-frame data into a second working condition data set corresponding to the previous single-frame data;
s47, calculating the upper bound and the lower bound of the index labels of all the second working condition data sets;
s48, setting the removal labels of the single-frame data between the upper bound and the lower bound to be 1;
and S49, eliminating the data with the removed label of 1 to obtain initial acceleration working condition data.
After all the second working condition data sets are obtained, calculating the upper bound and the lower bound of the index label of each second working condition data set, wherein the upper bound is the maximum value of the index label of the single-frame data in the second working condition data sets, the lower bound is the minimum value of the index label of the single-frame data in the second working condition data sets, setting the removal labels of the data between the upper bound and the lower bound to be 1, and eliminating the data with the removal labels of 1, so that the data of the jitter working conditions in the accelerometer bus data are removed, and the data of the normal working conditions are reserved and integrated and can be used for an algorithm.
And S5, according to a second preset method, carrying out data jitter removal processing on the initial common working condition data or the initial acceleration working condition data to obtain final common working condition data or final acceleration working condition data.
Specifically, after the common bus data and the accelerometer bus data are separated by the initial working condition, the obtained initial common working condition data or the initial acceleration working condition data have certain jitter at the position corresponding to the working condition conversion of the common bus data and the accelerometer bus data and need to be further removed, so the initial common working condition data or the initial acceleration working condition data are subjected to data jitter removal processing by a second preset method to obtain final common working condition data or final acceleration working condition data so as to remove the data jitter of the initial common working condition data or the initial acceleration working condition data,
as some optional embodiments of the present application, the performing data jitter removal processing on the common working condition data or the acceleration working condition data according to a second preset method to obtain final common working condition data or final acceleration working condition data includes:
s51, sampling is carried out on single-frame data of continuous preset number of the initial common working condition data or the initial acceleration working condition data according to preset sampling intervals to obtain sampling data;
specifically, in the first data slope removal, part of data slope data is not removed due to the fact that a small amount of continuous single-time incremental and single-time decremental alternate oscillation exists, the difference value of the data slope data and actual normal working condition data is smaller than 1/10 of the range difference of the whole data, and the incremental data trend still exists, and then sampling is carried out according to preset sampling intervals in the initial common working condition data or the continuous preset number of single-frame data of the initial acceleration working condition data to obtain sampling data;
s52, if the sampling data is increased or decreased, setting a removal label corresponding to the sampling data to be 1;
s53, eliminating the data with the removed label of 1 to obtain intermediate common working condition data or intermediate acceleration working condition data;
subsequently, if the sampled data is increasing or decreasing, setting a removal tag corresponding to the sampled data to 1, and removing the data with the removal tag of 1 to obtain intermediate common working condition data or intermediate acceleration working condition data in a specific embodiment, sampling is performed every 4 frames of data in single-frame data of 16 frames of which the initial common working condition data or the initial acceleration working condition data is continuous, and the 4 frames of data obtained by sampling are increasing or decreasing, then setting the removal tag of the 16 frames of data to 1, and removing the data with the removal tag of 1 to realize secondary removal of a data slope.
S54, acquiring an index jump threshold, a jump left pruning range and a jump right pruning range;
specifically, an index jump threshold, a jump left pruning range and a jump right pruning range are obtained, and the values of the index jump threshold, the jump left pruning range and the jump right pruning range can be set according to data characteristics;
in a specific embodiment, since the interval length between data of the same operating condition type is the length of other types of data at an interval between two pieces of data belonging to the same operating condition data type (and no operating condition data of the type is present between the two pieces of data) in the initial unprocessed data, when the interval length is greater than a certain degree, data oscillation in which single increment and single decrement alternate is generated at the start position and the end position of a data slope of data operating condition conversion is generated, the minimum value of the interval length for generating the oscillation is about 500-1000, and the minimum value can be referred to as an index jump threshold value; however, the length of the oscillation data is not large, and specifically, the oscillation data is located at about 10 to 30 frames of data where the index tag jump of the single frame data is greater than the index jump threshold, as some optional embodiments of the present application, the index jump threshold is 500 to 1000, the jump left pruning range and the jump right pruning range are both 10 to 30, and in a preferred embodiment, the index jump threshold is 500, and the jump left pruning range and the jump right pruning range are both 25.
S55, acquiring single-frame data with index jump larger than the index jump threshold in the intermediate common working condition data or the intermediate acceleration working condition data according to the index tag, and recording the single-frame data as jump data;
acquiring single-frame data with index jump larger than the index jump threshold value in the intermediate common working condition data or the intermediate acceleration working condition data according to the index tag, marking the single-frame data as jump data, wherein the index jump is the difference value of the index tags of the single-frame data of the previous frame and the single-frame data of the next frame, and when the difference value is larger than the index jump threshold value, marking the corresponding single-frame data as jump data and recording the position of the jump data;
s56, setting removal labels of single frame data in the hopping left pruning range and the hopping right pruning range of the hopping data to be 1;
and S57, eliminating the data with the removed label of 1 to obtain the final common working condition data or the final acceleration working condition data.
Specifically, after all the hopping data are acquired, the removal tags of the single-frame data in the hopping left pruning range and the hopping right pruning range of the hopping data are set to be 1, and the single-frame data with the removal tag of 1 is removed, so that the data shock is removed, the acquired final common working condition data or final acceleration working condition data are more accurate, and in the data processing process, the data processing is realized through the index tag and the removal tag, so that the initial attribute of the data is not lost, and the accuracy of working condition separation is further improved.
In summary, the working condition separation method of the PIU subsystem according to the present application obtains bus data of the PIU subsystem; when the bus data is the common bus data, preprocessing the common bus data according to a first preset method to obtain first common bus data, wherein single-frame data of the first common bus data is discontinuously increased or continuously decreased, so that the single-frame data of the obtained first common bus data is discontinuously increased or continuously decreased, data slope data is not suitable for any one of working condition data needing to be distinguished, and by removing a data slope, the speed of separating working conditions can be increased, and the efficiency is improved; according to a preset first clustering algorithm, working condition separation processing is carried out on the first common bus data to obtain initial common working condition data, wherein the initial common working condition data comprise highest-order data, lowest-order data and zero-order data, the clustering algorithm is an unsupervised algorithm, and the speed of working condition separation can be further increased because a training set is not needed, the algorithm is simple and quick; when the bus data are the accelerometer bus data, based on a preset second clustering algorithm, performing working condition separation processing on the accelerometer bus data to obtain initial acceleration working condition data, wherein the accelerometer bus data and the common bus data respectively pass through different clustering algorithms, so that the flexibility is high; and according to a second preset method, carrying out data jitter removal treatment on the initial common working condition data or the initial acceleration working condition data to obtain final common working condition data or final acceleration working condition data.
In order to solve the above technical problem, referring to fig. 2, the present application further provides a working condition separating device of a PIU subsystem, where the device includes:
the system comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring bus data of a PIU subsystem, the bus data comprises common bus data and accelerometer bus data, and the common bus data comprises a plurality of single frame data;
the preprocessing module is used for preprocessing the common bus data according to a first preset method to obtain first common bus data when the bus data are the common bus data, wherein single-frame data of the first common bus data are discontinuously increased or continuously decreased;
the first working condition separation module is used for carrying out working condition separation processing on the first common bus data according to a preset first clustering algorithm to obtain initial common working condition data, wherein the initial common working condition data comprises highest data, lowest data and zero data;
the second working condition separation module is used for carrying out working condition separation processing on the accelerometer bus data based on a preset second clustering algorithm when the bus data are the accelerometer bus data to obtain initial acceleration working condition data;
and the data jitter removal module is used for performing data jitter removal processing on the initial common working condition data or the initial acceleration working condition data according to a second preset method to obtain final common working condition data or final acceleration working condition data.
It should be noted that, each module in the operating condition separation apparatus of the PIU subsystem in this embodiment corresponds to each step in the operating condition separation method of the PIU subsystem in the foregoing embodiment one by one, and therefore, specific embodiments and achieved technical effects of this embodiment may refer to the implementation manner of the operating condition separation method of the PIU subsystem, which is not described herein again.
In addition, the operating condition separation method of the PIU subsystem according to the embodiment of the present invention described in conjunction with fig. 1 may be implemented by an electronic device. Fig. 3 shows a schematic diagram of a hardware structure of an electronic device according to an embodiment of the present invention.
The electronic device may comprise at least one processor 301, at least one memory 302 and computer program instructions stored in the memory 302 as shown, which when executed by the processor 301, implement the method of the above described embodiments.
In particular, the processor 301 may include a Central Processing Unit (CPU), or an Application Specific Integrated Circuit (ASIC), or may be configured to implement one or more Integrated circuits of the present invention.
The processor 301 may read and execute the computer program instructions stored in the memory 302 to implement the method for separating operating conditions of the PIU subsystem according to any of the embodiments described above.
In one example, the duty cycling apparatus of the PIU subsystem may further include a communication interface and a bus. As shown in fig. 3, the processor 301, the memory 302, and the communication interface 303 are connected via a bus 310 to complete communication therebetween. The communication interface is mainly used for realizing communication among modules, devices, units and/or equipment in the embodiment of the invention.
The bus includes hardware, software, or both that couple the components of the duty cycling apparatus of the PIU subsystem to each other. By way of example, and not limitation, a bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a Hyper Transport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an infiniband interconnect, a Low Pin Count (LPC) bus, a memory bus, a Micro Channel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a video electronics standards association local (VLB) bus, or other suitable bus, or a combination of two or more of these. A bus may include one or more buses, where appropriate. Although specific buses have been described and illustrated with respect to embodiments of the invention, any suitable buses or interconnects are contemplated by the invention.
In addition, in combination with the operating condition separation method of the PIU subsystem in the above embodiment, an embodiment of the present invention may provide a computer-readable storage medium to implement. The computer readable storage medium having stored thereon computer program instructions; the computer program instructions, when executed by a processor, implement the method for split behavior of a PIU subsystem of any of the above embodiments.
It is to be understood that the invention is not limited to the specific arrangements and instrumentality described above and shown in the drawings. A detailed description of known methods is omitted herein for the sake of brevity. In the above embodiments, several specific steps are described and shown as examples. However, the method processes of the present invention are not limited to the specific steps described and illustrated, and those skilled in the art can make various changes, modifications and additions, or change the order between the steps, after comprehending the spirit of the present invention.
The functional blocks shown in the above-described structural block diagrams may be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, it may be, for example, an electronic circuit, an Application Specific Integrated Circuit (ASIC), suitable firmware, plug-in, function card, or the like. When implemented in software, the elements of the invention are the programs or code segments used to perform the required tasks. The program or code segments can be stored in a machine-readable medium or transmitted by a data signal carried in a carrier wave over a transmission medium or a communication link. A "machine-readable medium" may include any medium that can store or transfer information. Examples of a machine-readable medium include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, radio Frequency (RF) links, and so forth. The code segments may be downloaded via computer networks such as the internet, intranet, etc.
It should also be noted that the exemplary embodiments noted in this patent describe some methods or systems based on a series of steps or devices. However, the present invention is not limited to the order of the above-described steps, that is, the steps may be performed in the order mentioned in the embodiments, may be performed in an order different from the order in the embodiments, or may be performed simultaneously.
As described above, only the specific embodiments of the present invention are provided, and it can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes of the system, the module and the unit described above may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again. It should be understood that the scope of the present invention is not limited thereto, and any equivalent modifications or substitutions can be easily made by those skilled in the art within the technical scope of the present invention.
Claims (10)
1. A working condition separation method of a PIU subsystem is characterized by comprising the following steps:
the method comprises the steps of obtaining bus data of a PIU subsystem, wherein the bus data comprises common bus data and accelerometer bus data, and the common bus data comprises a plurality of single-frame data;
when the bus data are the common bus data, preprocessing the common bus data according to a first preset method to obtain first common bus data, wherein single-frame data of the first common bus data are discontinuously increased or continuously decreased;
according to a preset first clustering algorithm, performing working condition separation processing on the first common bus data to obtain initial common working condition data, wherein the initial common working condition data comprises highest data, lowest data and zero data;
when the bus data is the accelerometer bus data, based on a preset second clustering algorithm, performing working condition separation processing on the accelerometer bus data to obtain initial acceleration working condition data;
and according to a second preset method, carrying out data jitter removal processing on the initial common working condition data or the initial acceleration working condition data to obtain final common working condition data or final acceleration working condition data.
2. The method for separating the operating conditions of the PIU subsystem according to claim 1, wherein the single frame of data includes a removal tag, and the step of preprocessing the normal bus data according to a first preset method to obtain first normal bus data when the bus data is the normal bus data includes:
traversing each single frame of data of the common bus data, and acquiring a difference value between each single frame of data and the single frame of data of the previous frame;
when the difference value is larger than a preset difference value or the difference value is smaller than the opposite number of the preset difference value, adding the increment pointers and setting the decrement pointers to be zero, wherein the initial values of the increment pointers and the decrement pointers are both 0;
when the difference value is smaller than a preset difference value or the difference value is larger than the opposite number of the preset difference value, setting the incremental pointer to be zero and adding one to the decremental pointer;
when the increasing pointer is more than or equal to 3 or the decreasing pointer is more than or equal to 3, setting the removal labels of the current single-frame data and the single-frame data of the previous 3 frames of the current single-frame data to be 1;
and removing all the single-frame data with the removal label of 1 to obtain first common bus data.
3. The working condition separation method of the PIU subsystem according to claim 1, wherein the step of performing working condition separation processing on the first common bus data according to a preset first clustering algorithm to obtain initial common working condition data comprises:
acquiring a first clustering reference distance according to a first preset distance division parameter and the range of the first common bus data;
creating a first working condition data set, wherein the first working condition data set comprises single frame data of a first frame in the first common bus data;
sequentially acquiring the difference value between single frame data except for the first frame in the first common bus data and the average value of the created first working condition data set;
when the difference value is larger than the first clustering reference distance, newly creating a first working condition data set, and adding corresponding single-frame data into the newly created working condition data set;
when the difference value is smaller than or equal to the first clustering reference distance, adding the corresponding single-frame data into the corresponding first working condition data set;
and obtaining initial common working condition data according to all the first working condition data sets.
4. The operating condition separation method of the PIU subsystem of claim 3, wherein the step of obtaining initial common operating condition data from all of the first operating condition data sets comprises:
acquiring the average value and the absolute value average value of all the first working condition data sets;
taking the first working condition data set with the maximum average value as the highest data;
taking the first working condition data set with the minimum average value as the lowest data;
and taking the first working condition data set with the minimum absolute value average value as zero data.
5. The method for separating the operating conditions of the PIU subsystem according to claim 1, wherein the single frame data includes a removal tag and an index tag, the index tag corresponds to a number of frames of single frame data in the accelerometer bus data, and when the bus data is the accelerometer bus data, the method for separating the operating conditions of the accelerometer bus data based on a preset second clustering algorithm to obtain initial acceleration operating condition data includes:
setting the removal tag of single-frame data with continuous three-frame increasing or continuous three-vibration decreasing in the accelerometer bus data to be 1;
acquiring a second clustering reference distance according to a second preset distance division parameter and the frame number of the accelerometer bus data;
creating a second working condition data set, wherein the second working condition data set comprises initial data, and the initial data is single frame data with the minimum index tag in the single frame data with the removal tag of 1;
traversing the single-frame data which is not the initial data and has the removal tag of 1 in the accelerometer bus data according to the index tag, and acquiring the difference value of the index tag of the single-frame data and the previous single-frame data;
when the difference value is smaller than or equal to the second clustering reference distance, adding the corresponding single-frame data into a second working condition data set corresponding to the previous single-frame data;
when the difference value is larger than the second clustering reference distance, a second working condition data set is created again, and corresponding single-frame data is added into the created second working condition data set;
calculating the upper and lower bounds of the index labels of all the second working condition data sets;
setting the removal labels of the single-frame data between the upper boundary and the lower boundary to be 1;
and eliminating the data with the removed label of 1 to obtain initial acceleration working condition data.
6. The working condition separation method of the PIU subsystem according to claim 5, wherein the obtaining of the final common working condition data or the final acceleration working condition data by performing data jitter removal on the common working condition data or the acceleration working condition data according to a second preset method comprises:
sampling according to a preset sampling interval in a continuous preset number of single-frame data of the initial common working condition data or the initial acceleration working condition data to obtain sampling data;
if the sampling data is increased or decreased, setting a removal label corresponding to the sampling data to be 1;
removing the data with the removed label of 1 to obtain intermediate common working condition data or intermediate acceleration working condition data;
acquiring an index hopping threshold, a hopping left pruning range and a hopping right pruning range;
acquiring single-frame data with index jump larger than the index jump threshold in the intermediate common working condition data or the intermediate acceleration working condition data according to the index tag, and recording the single-frame data as jump data;
setting removal tags of single frame data within the hopping left pruning range and the hopping right pruning range of the hopping data to 1;
and eliminating the data with the removed label of 1 to obtain the final common working condition data or the final acceleration working condition data.
7. The method for separating the working conditions of the PIU subsystem according to claim 6, wherein the index jump threshold is 500-100, and the jump left pruning range and the jump right pruning range are both 10-30.
8. An operating condition separating device of a PIU subsystem, which is characterized by comprising:
the system comprises a first acquisition module, a second acquisition module and a control module, wherein the first acquisition module is used for acquiring bus data of a PIU subsystem, the bus data comprises common bus data and accelerometer bus data, and the common bus data comprises a plurality of single frame data;
the preprocessing module is used for preprocessing the common bus data according to a first preset method to obtain first common bus data when the bus data are the common bus data, wherein single-frame data of the first common bus data are discontinuously increased or continuously decreased;
the first working condition separation module is used for carrying out working condition separation processing on the first common bus data according to a preset first clustering algorithm to obtain initial common working condition data, wherein the initial common working condition data comprises highest data, lowest data and zero data;
the second working condition separation module is used for carrying out working condition separation processing on the accelerometer bus data based on a preset second clustering algorithm to obtain initial acceleration working condition data when the bus data are the accelerometer bus data;
and the data jitter removal module is used for performing data jitter removal processing on the initial common working condition data or the initial acceleration working condition data according to a second preset method to obtain final common working condition data or final acceleration working condition data.
9. An electronic device, comprising: at least one processor, at least one memory, and computer program instructions stored in the memory, which when executed by the processor, implement the method of any one of claims 1-7.
10. A storage medium having computer program instructions stored thereon, which when executed by a processor implement the method of any one of claims 1-7.
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