CN118068138A - Debye model-based cable insulation aging state evaluation method and system - Google Patents

Abstract

The invention discloses a cable insulation aging state assessment method and system based on a Debye model, which relate to the technical field of electrical engineering and comprise the following steps: collecting dielectric characteristic data of different cable insulating materials, and determining whether the cable is aged or not; constructing a Debye model, and evaluating the aging state of the cable insulation based on the collected data and the Debye model; and predicting the future aging state according to the historical aging state of the cable insulation. According to the invention, the accuracy and efficiency of the cable insulation aging state evaluation are improved through the advanced analysis method based on the Debye model. The aging process is monitored more accurately, and the future aging trend is predicted effectively, so that reliable decision support is provided for maintenance and operation of the power system. The cable insulation state monitoring system can monitor and analyze the cable insulation state in real time, greatly improves the reliability and safety of a power system, reduces the risks of faults and accidents caused by aging, and has important significance for guaranteeing the stable operation of a power grid.

Description

Cable insulation aging status assessment method and system based on Debye model

Technical Field

The present invention relates to the technical field of electrical engineering, and in particular to a cable insulation aging state assessment method and system based on a Debye model.

Background technique

In the power system, the insulation state of the cable is crucial to ensure the safety and reliability of power transmission. Over time, the cable insulation material will gradually age due to various factors, causing changes in its physical and chemical properties. This aging not only reduces the insulation performance of the cable, but may also increase the risk of power system failure and even cause safety accidents.

Traditionally, cable insulation aging assessment relies on regular physical inspections and experience-based assessment methods. These methods usually require interrupting the operation of the cable, which is not only inefficient, but also unable to provide continuous and real-time information on the progress of material aging. In addition, traditional methods often ignore the microstructural changes of cable materials, which are particularly critical in the early stages of aging.

With the development of science and technology, especially in the fields of materials science and electrical engineering, a more advanced, accurate and efficient method is needed to evaluate and predict the aging state of cable insulation. As a physical model that describes the polarization characteristics of dielectric materials, the Debye model provides a possible solution. By combining the Debye model with modern data analysis technology, the aging state of cable insulation can be more accurately evaluated and its future performance can be predicted, thus providing a scientific basis for the maintenance and operation of power systems.

Therefore, developing a cable insulation aging condition assessment method based on the Debye model is not only of great significance to improving the reliability and safety of the power system, but also critical to optimizing cable maintenance plans and extending cable service life. This method can provide a more comprehensive and in-depth aging condition assessment, which has significant practical value and long-term significance for the power industry.

Summary of the invention

In view of the above-mentioned problems, the present invention is proposed.

Therefore, the technical problem solved by the present invention is: how to efficiently evaluate and predict the aging state of cable insulation materials in a power system, so as to optimize the maintenance plan and improve the safety and stability of the power system.

In order to solve the above technical problems, the present invention provides the following technical solutions: a cable insulation aging state evaluation method based on the Debye model, which comprises the following steps:

Collect dielectric property data of different cable insulation materials to determine whether the cable is aged; construct a Debye model to evaluate the aging state of cable insulation based on the collected data and the Debye model; and predict the future aging state of cable insulation based on the historical aging state of cable insulation.

As a preferred solution of the cable insulation aging status assessment method based on the Debye model described in the present invention, the determination of whether the cable is aged includes defining an aging index and determining whether aging occurs at the test point based on the aging index.

The aging index is expressed as,

AI(t,r)＝f(ε(ω,t,r),P(t,r),S(t,r))

Among them, P(t, r) represents the physical parameters at aging time t and spatial position r, and S(t, r) represents the chemical and structural stability parameters of the cable.

When the aging index is higher than the threshold, it indicates that the cable test point has aged.

As a preferred solution of the cable insulation aging status assessment method based on the Debye model described in the present invention, wherein: the construction of the Debye model includes testing the cable insulation materials at different aging stages, collecting dielectric property data and loss data, and constructing the Debye model through the collected dielectric property data.

The Debye model is expressed as,

Among them, ε(ω, t, r) represents the complex dielectric constant at angular frequency ω, aging time t and spatial position r, A(t, r) and B(t, r) represent tensors describing the heterogeneity and anisotropy of the material, ε _∞ (t, r) represents the high-frequency limiting dielectric constant at aging time t and spatial position r, T(t, r) represents the tensor describing the relaxation time distribution, I represents the unit tensor, and j represents the imaginary unit.

As a preferred embodiment of the cable insulation aging status assessment method based on the Debye model described in the present invention, the aging status of the cable insulation is assessed, including collecting dielectric property data of each test point, calculating the dielectric constant tensor using the Debye model, comparing the calculated dielectric constant tensor with a preset aging status threshold, determining the aging status of each test point, and taking different countermeasures according to different aging statuses.

The determining of the aging status of each test point includes: if the dielectric constant tensor of the test point is less than the first-level threshold, it indicates that the test point is in an unaged state; if the dielectric constant tensor of the test point is between the first-level threshold and the second-level threshold, it indicates that the test point is in a slightly aged state; if the dielectric constant tensor of the test point is between the second-level threshold and the third-level threshold, it indicates that the test point is in a moderately aged state; if the dielectric constant tensor of the test point is between the third-level threshold and the fourth-level threshold, it indicates that the test point is in a severely aged state.

As a preferred solution of the cable insulation aging status assessment method based on the Debye model described in the present invention, the different countermeasures include: when the cable is in an unaged state, regular cable quality review and supply chain management are carried out to ensure the use of high-quality materials and components, and the use of big data to analyze the historical performance data of the cable to identify potential weaknesses and areas for improvement, and formulate personalized maintenance and inspection plans based on the specific type and historical performance of the cable.

When the cable is in a state of slight aging, the cable insulation is subjected to fault mode recognition and impact analysis to identify potential causes of failure and strengthen preventive maintenance measures, such as increasing the monitoring frequency and promptly repairing or replacing the slightly damaged parts if any are detected.

When the cable is in a moderately aged state, a comprehensive systemic risk assessment is performed to consider the impact of cable aging on the entire power system, and a detailed emergency response plan is formulated, including the impact on the surrounding environment and the system, and a corresponding emergency response plan is formulated.

When the cables are in a serious aging state, a comprehensive re-evaluation of system performance is carried out, including power demand, operating efficiency and safety, and a cost-benefit analysis is performed to decide whether to replace the aging cables or upgrade the system. When it is decided to replace the cables, priority is given to critical areas and high-risk sections, and temporary enhanced monitoring and protection measures are implemented to prevent system failures caused by aging cables.

As a preferred scheme of the cable insulation aging status assessment method based on the Debye model described in the present invention, wherein: the prediction of the future aging status includes collecting historical data and the corresponding aging status, evaluating the current aging status according to the Debye model, obtaining the current aging index AI (t, r), predicting the future aging status based on the prediction model, and formulating countermeasures based on the predicted aging status.

The prediction of the future aging state based on the prediction model is expressed as:

AI _prediction (t+Δt, r) = AI (t, r) + aging rate (t, r) × Δt + environmental factor impact (r)

Among them, Δt represents the time interval, and the aging rate is obtained from the historical data.

If the AI _prediction is higher than the aging index threshold AI _warning or the aging rate exceeds the threshold, it means that aging will occur in the future.

As a preferred solution of the cable insulation aging status assessment method based on the Debye model described in the present invention, the formulation of countermeasures includes: when the test point prediction shows that aging will occur in the future, the monitoring frequency of the cable is increased, the operating status of the cable is tracked in real time, dynamic load management is implemented, the load level of the cable is adjusted according to the real-time status of the cable, regular cable cleaning work is arranged, insulation materials that have been worn or damaged are inspected and replaced, insulation tests and resistance measurements are performed regularly to ensure the integrity of insulation materials, emergency plans are prepared, and when aging occurs at the test point, a prompt response is made according to the emergency plan, including rapid repair of cable faults and temporary power grid reconfiguration strategies, enabling backup power supplies or adjusting the load distribution of adjacent cables.

Another object of the present invention is to provide a cable insulation aging status assessment system based on the Debye model, which can more accurately and carefully assess the aging status of cable insulation materials by utilizing advanced data analysis and real-time monitoring technology, thereby solving the problems of insufficient accuracy in aging process assessment and lack of real-time monitoring in existing methods.

In order to solve the above technical problems, the present invention provides the following technical solutions: a cable insulation aging status assessment system based on the Debye model, comprising a data acquisition module, an aging status assessment module and a future aging prediction module.

The data acquisition module is responsible for collecting dielectric property data of different cable insulation materials.

The aging state evaluation module is responsible for evaluating the current aging state of the cable insulation using the constructed Debye model.

The future aging prediction module is responsible for predicting the future aging state based on the current aging state and the historical aging trend.

A computer device comprises a memory and a processor, wherein the memory stores a computer program, and is characterized in that when the processor executes the computer program, the steps of the cable insulation aging status assessment method based on the Debye model as described above are implemented.

A computer-readable storage medium having a computer program stored thereon, characterized in that when the computer program is executed by a processor, the steps of the cable insulation aging status assessment method based on the Debye model as described above are implemented.

Beneficial effects of the present invention: The present invention improves the accuracy and efficiency of cable insulation aging status assessment by applying an advanced analysis method based on the Debye model. It makes the monitoring of the aging process more accurate and can effectively predict future aging trends, thereby providing reliable decision support for the maintenance and operation of the power system. In addition, it can monitor and analyze the cable insulation status in real time, greatly improving the reliability and safety of the power system, reducing the risk of failures and accidents caused by aging, and is of great significance for ensuring the stable operation of the power grid.

BRIEF DESCRIPTION OF THE DRAWINGS

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

FIG1 is an overall flow chart of a cable insulation aging state assessment method based on a Debye model provided in a first embodiment of the present invention.

FIG2 is an overall framework diagram of a cable insulation aging status assessment system based on a Debye model provided in a second embodiment of the present invention.

Detailed ways

In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

Example 1

1 , an embodiment of the present invention provides a cable insulation aging state assessment method based on a Debye model, which is characterized by:

S1: Collect dielectric property data of different cable insulation materials to determine whether the cable is aged.

Determining whether the cable is aged includes defining an aging index and determining whether aging occurs at a test point based on the aging index.

The aging index is expressed as,

AI(t,r)＝f(ε(ω,t,r),P(t,r),S(t,r))

Among them, P(t, r) represents the physical parameters at aging time t and spatial position r, and S(t, r) represents the chemical and structural stability parameters of the cable.

When the aging index is higher than the threshold, it indicates that the cable test point has aged.

S2: Construct a Debye model and evaluate the aging state of the cable insulation based on the collected data and the Debye model.

Constructing the Debye model includes testing the cable insulation materials at different aging stages, collecting dielectric property data and loss data, and constructing the Debye model through the collected dielectric property data.

The Debye model is expressed as,

Among them, represents the complex dielectric constant under angular frequency, aging time t and spatial position r, represents the tensor describing the heterogeneity and anisotropy of the material, represents the high-frequency limiting dielectric constant under aging time t and spatial position r, represents the tensor describing the relaxation time distribution, represents the unit tensor, and j represents the imaginary unit.

Evaluating the aging status of cable insulation includes collecting dielectric property data of each test point, calculating the dielectric constant tensor using the Debye model, comparing the calculated dielectric constant tensor with the preset aging status threshold, determining the aging status of each test point, and taking different countermeasures according to different aging status.

Determining the aging status of each test point includes: if the dielectric constant tensor of the test point is less than the first threshold, it indicates that the test point is in an unaged state; if the dielectric constant tensor of the test point is between the first threshold and the second threshold, it indicates that the test point is in a slightly aged state; if the dielectric constant tensor of the test point is between the second threshold and the third threshold, it indicates that the test point is in a moderately aged state; if the dielectric constant tensor of the test point is between the third threshold and the fourth threshold, it indicates that the test point is in a severely aged state.

Different response measures include regular cable quality review and supply chain management when the cables are not aged to ensure the use of high-quality materials and components, using big data to analyze the historical performance data of the cables to identify potential weaknesses and areas for improvement, and developing personalized maintenance and inspection plans based on the specific type of cable and historical performance.

When the cable is in a state of slight aging, the cable insulation is subjected to fault mode recognition and impact analysis to identify potential causes of failure and strengthen preventive maintenance measures, such as increasing the monitoring frequency and promptly repairing or replacing the slightly damaged parts if any are detected.

When the cable is in a moderately aged state, a comprehensive systemic risk assessment is performed to consider the impact of cable aging on the entire power system, and a detailed emergency response plan is formulated, including the impact on the surrounding environment and the system, and a corresponding emergency response plan is formulated.

When the cables are in a serious aging state, a comprehensive re-evaluation of system performance is carried out, including power demand, operating efficiency and safety, and a cost-benefit analysis is performed to decide whether to replace the aging cables or upgrade the system. When it is decided to replace the cables, priority is given to critical areas and high-risk sections, and temporary enhanced monitoring and protection measures are implemented to prevent system failures caused by aging cables.

S3: Predict the future aging state of the cable insulation based on its historical aging state.

Predicting the future aging state includes collecting historical data and the corresponding aging state, evaluating the current aging state according to the Debye model, obtaining the current aging index AI (t, r), predicting the future aging state based on the prediction model, and formulating countermeasures based on the predicted aging state.

The future aging state predicted based on the prediction model is expressed as:

AI _prediction (t+Δt, r) = AI (t, r) + aging rate (t, r) × Δt + environmental factor impact (r)

Among them, Δt represents the time interval, and the aging rate is obtained from the historical data.

If the AI _prediction is higher than the aging index threshold AI _warning or the aging rate exceeds the threshold, it means that aging will occur in the future.

The response measures include increasing the frequency of cable monitoring when test point predictions show that aging will occur in the future, tracking the cable's operating status in real time, implementing dynamic load management, adjusting the cable's load level based on the cable's real-time status, arranging regular cable cleaning, inspecting and replacing insulation materials that have been worn or damaged, conducting regular insulation tests and resistance measurements to ensure the integrity of insulation materials, preparing emergency plans, and responding quickly according to emergency plans when aging occurs at test points, including rapid repair of cable faults and temporary grid reconfiguration strategies, enabling backup power supplies or adjusting load distribution of adjacent cables.

Example 2

2 , which is an embodiment of the present invention, provides a system for a cable insulation aging status assessment method based on a Debye model. The cable insulation aging status assessment system based on a Debye model includes a data acquisition module, an aging status assessment module, and a future aging prediction module.

The data acquisition module is responsible for collecting dielectric property data of different cable insulation materials.

The aging state assessment module is responsible for assessing the current aging state of the cable insulation using the constructed Debye model.

The future aging prediction module is responsible for predicting the future aging state based on the current aging state and historical aging trends.

If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

The logic and/or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

Example 3

In this embodiment, in order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments. In order to clearly demonstrate the superiority of the cable insulation aging state assessment method based on the Debye model of the present invention over the traditional method, the following embodiment provides a comparative study. The study includes using the traditional method and the method of the present invention to assess the aging state of the same batch of cables, and recording the results for comparative analysis. This embodiment experiments on the existing traditional method and the method of this embodiment, as shown in Table 1.

Table 1 Experimental effect comparison chart

Evaluation indicators Traditional methods Our invention method Error rate 10% 2% Environmental adaptability Basic environmental parameters Multiphysics Parameters Prediction accuracy No predictive ability 90% Delayed fault detection rate 30% 5%

It can be seen from the comparative data that the present invention has made significant improvements on the basis of the traditional method. In addition to the significantly reduced error rate and enhanced environmental adaptability, the present invention also has excellent prediction accuracy and low delayed fault detection rate.

It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims (10)

1. The cable insulation aging state assessment method based on the Debye model is characterized by comprising the following steps of:

Collecting dielectric characteristic data of different cable insulating materials, and determining whether the cable is aged or not;

Constructing a Debye model, and evaluating the aging state of the cable insulation based on the collected data and the Debye model;

and predicting the future aging state according to the historical aging state of the cable insulation.

2. The method for evaluating the insulation aging state of the cable based on the Debye model according to claim 1, wherein: determining whether the cable is aged or not comprises defining an aging index, and determining whether the test point is aged or not based on the aging index;

The ageing index is expressed as a function of,

AI(t，r)＝f(ε(ω，t，r)，P(t，r)，S(t，r))

Wherein P (t, r) represents physical parameters at the aging time t and the spatial position r, and S (t, r) represents chemical and structural stability parameters of the cable;

And when the ageing index is higher than the threshold value, the ageing index indicates that the cable test point is aged.

3. The method for evaluating the insulation aging state of the cable based on the Debye model according to claim 2, wherein: the construction of the Debye model comprises the steps of testing cable insulation materials in different aging stages, collecting dielectric characteristic data and loss data, and constructing the Debye model through the collected dielectric characteristic data;

the Debye model is represented as,

Where ε (ω, T, r) represents the complex permittivity at angular frequency ω, aging time T and spatial position r, A (T, r), B (T, r) represents tensors describing the inhomogeneity and anisotropy of the material, ε _∞ (T, r) represents the high frequency limit permittivity at aging time T and spatial position r, T (T, r) represents tensors describing the relaxation time distribution, I represents the unit tensors, j represents the imaginary unit.

4.A method for evaluating the insulation aging state of a cable based on a Debye model according to claim 3, wherein: the method comprises the steps of evaluating the aging state of cable insulation, namely collecting dielectric characteristic data of each test point, calculating dielectric constant tensor by using a Debye model, comparing the calculated dielectric constant tensor with a preset aging state threshold value, determining the aging state of each test point, and taking different countermeasures according to different aging states;

Determining the aging state of each test point comprises the steps of indicating that the test point is in an unaged state if the dielectric constant tensor of the test point is smaller than a first-level threshold, indicating that the test point is in a mild aging state if the dielectric constant tensor of the test point is between the first-level threshold and a second-level threshold, indicating that the test point is in a moderate aging state if the dielectric constant tensor of the test point is between the second-level threshold and a third-level threshold, and indicating that the test point is in a severe aging state if the dielectric constant tensor of the test point is between the third-level threshold and a fourth-level threshold.

5. The method for evaluating the insulation aging state of the cable based on the Debye model according to claim 4, wherein: the method comprises the steps of taking different countermeasures, namely, when the cable is in an unaged state, periodically performing cable quality inspection and supply chain management, ensuring that high-quality materials and components are used, analyzing historical performance data of the cable by utilizing big data, finding potential weaknesses and improvement fields, and making personalized maintenance and detection plans according to specific types and historical performances of the cable;

When the cable is in a light aging state, carrying out fault mode identification and influence analysis on cable insulation, identifying potential fault reasons, enhancing preventive maintenance measures such as encryption monitoring frequency, and timely repairing or replacing a light damaged part aiming at the detected light damage;

When the cable is in a moderate aging state, performing comprehensive systematic risk assessment, and taking the influence of cable aging on the whole power system into consideration, making a detailed emergency response plan, including the influence on the surrounding environment and the system, and making a corresponding emergency response plan;

When the cable is in a severely aged state, comprehensive system performance reevaluation is performed, including power demand, operation efficiency and safety, cost benefit analysis is performed, whether to replace aged cables or upgrade systems is determined, when the cable replacement is determined, critical areas and high-risk parts are prioritized, temporary enhancement monitoring and protection measures are implemented, and system faults caused by aged cables are prevented.

6. The method for evaluating the insulation aging state of the cable based on the Debye model according to claim 5, wherein: the prediction of the future aging state comprises the steps of collecting historical data and corresponding aging states, evaluating the current aging state according to a Debye model to obtain a current aging index AI (t, r), predicting the future aging state based on a prediction model, and formulating countermeasures based on the predicted aging state;

the predicting of the future aging state based on the predictive model is expressed as,

AI _Prediction (t+Δt, r) =ai (t, r) +aging rate (t, r) ×Δt+environmental factor influence (r)

Wherein Δt represents the time interval, and the aging rate is obtained from the historical data;

if AI _Prediction is above the aging index threshold AI _{Early warning} or the aging rate exceeds the threshold, it indicates that aging will occur in the future.

7. The method for evaluating the insulation aging state of the cable based on the Debye model according to claim 6, wherein: the method comprises the steps of encrypting monitoring frequency of a cable when the test point predicts and displays future aging, tracking the running state of the cable in real time, implementing dynamic load management, adjusting the load level of the cable according to the real-time state of the cable, arranging periodic cable cleaning work, checking and replacing the insulation material which is worn or damaged, periodically performing insulation test and resistance measurement, ensuring the integrity of the insulation material, preparing an emergency plan, quickly responding according to the emergency plan when the test point is aged, including a rapid repair of cable faults and a temporary power grid reconfiguration strategy, and starting a standby power supply or adjusting load distribution of adjacent cables.

8. A system employing the Debye model-based cable insulation aging state assessment method according to any one of claims 1 to 7, characterized in that: the aging state evaluation system comprises a data acquisition module, an aging state evaluation module and a future aging prediction module;

The data acquisition module is responsible for collecting dielectric characteristic data of different cable insulating materials;

the aging state evaluation module is responsible for evaluating the current aging state of the cable insulation by using the constructed Debye model;

The future aging prediction module is responsible for predicting a future aging state based on the current aging state and the historical aging trend.

9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of the Debye model-based cable insulation ageing state assessment method of any of claims 1 to 7.

10. A computer-readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the Debye model-based cable insulation ageing state assessment method of any one of claims 1 to 7.