A high-efficiency chip package testing system and method

Abstract

The application relates to the technical field of electric fault detection and performance measurement, and discloses a high-efficiency chip packaging test system and method. Carrier differential filtering and impedance vector compensation operations are performed by a bump impedance unit to suppress test loop noise, peel off pin parasitic impedance interference, and obtain electrical calibration characteristics; potential difference sampling logic and standing wave ratio distortion decomposition means of a bump array unit are used to capture contact interface impedance deviation and represent crack electric signal characteristics; real-time current monitoring and displacement trajectory tracking technology of a load fault test unit are combined to execute electric variable threshold determination in association with physical degradation parameters, and packaging test evaluation results are output. The application realizes quantitative detection and dynamic electric performance evolution evaluation of internal electric contact defects of packaging, solves the limitation that hidden physical damage is difficult to represent in electric measurement, and significantly improves fault recognition resolution and determination efficiency of an electric detection system.

Description

Technical Field

[0001] This invention relates to the field of electrical fault detection and performance measurement technology, specifically to a high-efficiency chip packaging testing system and method. Background Technology

[0002] When characterizing the electrical performance of high-performance integrated circuits, the micro-array nodes formed by flip-chip packaging are the core path for electrical signal transmission, and the accurate measurement of their electrical connection quality is directly related to the accuracy of the test device's judgment of the device's function.

[0003] In existing technologies involving electrical variable measurements, traditional electrical test systems typically utilize general signal acquisition channels to feed commands to the chip under test (DUT). However, when performing precision electrical parameter probing on flip-chip packages, the inherent parasitic impedance in the measurement path often resonates electrically with the excitation carrier of the test device, causing distortion of the acquired voltage and current waveforms. This electrical interference caused by the measurement path makes it difficult for the probe device to extract the true interconnect impedance variables from high background noise, severely limiting the resolution of electrical test equipment in identifying microscopic electrical contact faults. Furthermore, existing electrical fault detection logics often focus on acquiring static voltage drops, lacking the ability to characterize the micro-ohmic contact resistance fluctuations generated by the DUT under dynamic current loads. This makes transient electrical defects such as microcracks easily misjudged as system thermal noise during the measurement phase.

[0004] The pain points of existing technologies are: on the one hand, electrical testing devices lack effective impedance decoupling logic, which cannot eliminate the masking effect of the probe path on the original electrical performance of the tested node in real time during the measurement process; on the other hand, there is a lack of an electrical testing architecture that can dynamically correlate electrical evolution characteristics with structural physical degradation, making it difficult for the testing system to accurately locate hidden electrical failure points and predict lifespan when performing high-throughput fault diagnosis.

[0005] In summary, for chips with high-density interconnect features, the question is how to construct an electrical testing device with impedance purification capabilities, enabling it to quantitatively detect and online determine minute contact electrical faults through specific electrical sampling sequences, thereby improving the fault capture efficiency during the electrical testing process.

[0006] Therefore, an efficient chip packaging and testing system and method are proposed. Summary of the Invention

[0007] The purpose of this invention is to provide a high-efficiency chip packaging testing system and method, which, through the substantial combination of impedance purification, bump array conduction mapping and load fault evolution evaluation, accurately detects and dynamically diagnoses and evaluates microscale contact electrical faults inside flip-chip packages.

[0008] To achieve the above objectives, the present invention provides the following technical solution: A high-efficiency chip packaging and testing system, comprising: The convex impedance unit acquires the original electrical signal data and performs reference signal denoising to generate the convex interconnect response flow; acquires the package electrical parameters, performs vector compensation operation on the convex interconnect response flow to generate the convex intrinsic impedance flow; constructs a path phase compensation model based on vector compensation and phase alignment logic, performs signal transmission delay synchronization on the convex intrinsic impedance flow, and generates flip-chip calibration characteristics. Bump array unit: Based on the potential difference acquisition logic, a contact electrical mapping model is constructed. Electrical parameter sampling operation is performed on the flip-chip calibration features to generate the bump array electrical conduction. The packaging stress offset parameters are obtained, and the carrier drift matrix is ​​compared on the bump array electrical conduction to generate bump defect feature elements. Based on the bump defect feature elements, the reflected wave standing wave ratio distortion decomposition is performed to generate crack electrical signal features. Load Fault Test Unit: By monitoring the current signal characteristics of the crack, the unit performs current shift trajectory tracking to generate a response trajectory set; it acquires physical degradation parameters, performs electrical performance deviation correlation calculation on the response trajectory set to generate evaluation parameter items; and it performs electrical variable threshold range limitation on the evaluation parameter items to generate the sealing test judgment result.

[0009] Preferably, the process of generating the convex interconnect response flow by the convex impedance unit includes: acquiring the original electrical signal data containing voltage amplitude and current phase, and the no-load reference signal generated by the test circuit; constructing a carrier differential filter model based on the carrier frequency range and characteristic impedance parameters; inputting the original electrical signal data and the no-load reference signal into the carrier differential filter model to perform phase synchronization alignment and differential mode component subtraction operations, canceling high-frequency resonant noise and extracting incoherent electrical performance fluctuation data to generate the convex interconnect response flow.

[0010] Preferably, the process of generating the convex intrinsic impedance current and flip-chip calibration features by the convex impedance unit includes: acquiring package electrical parameters containing parasitic inductance and interlayer capacitance data of package pins; mapping the package electrical parameters to parasitic impedance vectors using vector compensation logic; performing vector subtraction on the convex interconnect response current and parasitic impedance component vectors to generate the convex intrinsic impedance current; constructing a path phase compensation model based on vector compensation and phase alignment logic, inputting the convex intrinsic impedance current into the path phase compensation model to perform time-domain phase difference extraction to generate a time delay offset compensation amount; and performing signal transmission delay synchronization operation on the convex intrinsic impedance current using the time delay offset compensation amount to generate flip-chip calibration features.

[0011] Preferably, the process of generating convex array electrical conductivity by the convex array unit includes: constructing a contact electrical mapping model based on potential difference acquisition logic; inputting inverted calibration feature data into the contact electrical mapping model to perform node potential difference step sampling operation to generate array node potential set; acquiring preset detection current amplitude data; performing Ohm's law mapping transformation operation on the array node potential set using the preset detection current amplitude data to generate contact conduction quantization data; and performing conductivity feature vector encapsulation operation based on the contact conduction quantization data to generate convex array electrical conductivity.

[0012] Preferably, the process of generating bump defect feature elements and crack electrical signal features by the bump array unit includes: obtaining the encapsulation stress offset parameters; constructing a carrier drift matrix comparison model based on the thermal stress and piezoelectric effect of the bottom filler adhesive; inputting the bump array electrical conductivity data and the encapsulation stress offset parameters into the carrier drift matrix comparison model to perform an electrical fingerprint feature association matching operation, extracting the impedance deviation component that deviates from the standard conduction mode, and generating bump defect feature elements; constructing a standing wave ratio distortion decomposition model based on the pulse injection frequency and the transmission line impedance standard; inputting the bump defect feature elements into the standing wave ratio distortion decomposition model to perform a pulse reflection waveform sampling operation, separating the reflected wave voltage standing wave ratio distortion component, and generating crack electrical signal features.

[0013] Preferably, the process of generating a response trajectory set by the load fault test unit includes: acquiring the test current step load; capturing the node current distribution flow by performing current sampling monitoring on the convex array; constructing a convex contact impedance matrix based on the convex defect feature elements; and performing a current vector space coordinate comparison operation between the node current distribution flow and the convex contact impedance matrix based on the crack electrical signal characteristics to generate a response trajectory set.

[0014] Preferably, the process by which the load failure test unit generates evaluation parameters and sealing test results includes: acquiring physical degradation parameters containing the extension length of the convex crack and the deformation variables of the connection interface; performing an electrical parameter drift and structural physical damage degree mapping operation on the response trajectory set data and the physical degradation parameters to extract the electrical performance degradation fingerprint set and generate evaluation parameters; acquiring standard electrical variable fluctuation limit threshold data, performing a threshold boundary comparison operation on the evaluation parameters and the electrical variable fluctuation limit threshold, performing level matching based on the comparison operation, and generating sealing test results.

[0015] An efficient chip packaging testing method includes: The system acquires raw electrical signal data and performs reference signal denoising to generate a convex interconnect response flow. It also acquires package electrical parameters, performs vector compensation operations on the convex interconnect response flow, and generates convex intrinsic impedance flow. Based on vector compensation and phase alignment logic, it constructs a path phase compensation model, performs signal transmission delay synchronization on the convex intrinsic impedance flow, and generates flip-chip calibration characteristics. Based on the potential difference acquisition logic, a contact electrical mapping model is constructed. Electrical parameter sampling operation is performed on the flip-chip calibration feature to generate the convex array electrical conduction. The packaging stress offset parameter is obtained, and the carrier drift matrix is ​​compared on the convex array electrical conduction to generate convex defect feature elements. Based on the convex defect feature elements, the reflected wave standing wave ratio distortion decomposition is performed to generate crack electrical signal features. The current shift trajectory tracking operation is performed on the crack electrical signal characteristics by current monitoring to generate a response trajectory set; physical degradation parameters are obtained, and electrical performance deviation correlation calculation operation is performed on the response trajectory set to generate evaluation parameter items; electrical variable threshold range limitation operation is performed on the evaluation parameter items to generate the sealing test judgment result.

[0016] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. This invention utilizes a substantial combination design of carrier differential filtering, vector compensation operation, and phase time-domain alignment to construct an electrical calibration system with adaptive compensation capability within the convex impedance unit. This achieves physical separation of pin parasitic parameters from environmental resonant noise, establishing an initial electrical reference with phase consistency for subsequent electrical variable measurements.

[0017] 2. Through the coordinated processing of potential difference acquisition logic, carrier drift matrix comparison and standing wave ratio distortion decomposition in the convex array unit, the physical contact state of the hidden micro-convex array is converted into quantified electrical conduction characteristics and crack electrical signals, thereby realizing the electrical location locking of stress-induced defects and transforming the micro-deformation characteristics into quantifiable and extractable feature vectors in the electrical detection system.

[0018] 3. Based on the closed-loop evaluation logic of the load fault test unit for current displacement trajectory, electrical performance deviation correlation and evaluation parameter items, a coupled correlation model of structural degradation trajectory and electrical characteristic deviation under electrical load is established to complete the logical closed loop from transient electrical parameter sampling to dynamic reliability evolution judgment, so as to realize the quantitative identification and yield classification judgment results of the test system for complex electrical faults. Attached Figure Description

[0019] Figure 1 This is a schematic diagram of the structure of a high-efficiency chip packaging and testing system according to the present invention; Figure 2 This is a flowchart of a high-efficiency chip packaging and testing system according to the present invention; Figure 3 This is a flowchart of an efficient chip packaging and testing method according to the present invention. Detailed Implementation

[0020] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] Please see Figures 1 to 3 This invention provides a high-efficiency chip packaging and testing system and method, the technical solution of which is as follows:

[0022] Example 1 Reference Figure 1 , Figure 2 This embodiment provides a high-efficiency chip packaging and testing system, and its specific application process in the flip-chip packaging testing scenario of high-performance power electronic components. The specific steps are as follows: The convex impedance unit acquires the original electrical signal data and performs reference signal denoising to generate the convex interconnect response flow; acquires the package electrical parameters, performs vector compensation operation on the convex interconnect response flow to generate the convex intrinsic impedance flow; constructs a path phase compensation model based on vector compensation and phase alignment logic, performs signal transmission delay synchronization on the convex intrinsic impedance flow, and generates flip-chip calibration characteristics. Bump array unit: Based on the potential difference acquisition logic, a contact electrical mapping model is constructed. Electrical parameter sampling operation is performed on the flip-chip calibration features to generate the bump array electrical conduction. The packaging stress offset parameters are obtained, and the carrier drift matrix is ​​compared on the bump array electrical conduction to generate bump defect feature elements. Based on the bump defect feature elements, the reflected wave standing wave ratio distortion decomposition is performed to generate crack electrical signal features. Load Fault Test Unit: By monitoring the current signal characteristics of the crack, the unit performs current shift trajectory tracking to generate a response trajectory set; it acquires physical degradation parameters, performs electrical performance deviation correlation calculation on the response trajectory set to generate evaluation parameter items; and it performs electrical variable threshold range limitation on the evaluation parameter items to generate the sealing test judgment result.

[0023] Furthermore, the process of generating the convex interconnect response flow by the convex impedance unit includes: acquiring the original electrical signal data containing voltage amplitude and current phase, and the no-load reference signal generated by the test circuit; constructing a carrier differential filter model based on the carrier frequency range and characteristic impedance parameters; inputting the original electrical signal data and the no-load reference signal into the carrier differential filter model to perform phase synchronization alignment and differential mode component subtraction operations, canceling high-frequency resonant noise and extracting incoherent electrical performance fluctuation data to generate the convex interconnect response flow.

[0024] Specifically, the test circuit acquires raw electrical signal data containing voltage amplitude and current phase, as well as an unloaded reference signal generated by the test circuit. The raw electrical signal data consists of a millivolt-level transient voltage amplitude sequence and a milliradian-level current phase angle deviation captured by the flip-chip pin. The unloaded reference signal is the system background thermal noise and environmental electromagnetic induction waveform data recorded by the test circuit under open load conditions.

[0025] The process of constructing a carrier differential filtering model based on the carrier frequency range and characteristic impedance parameters includes: the carrier frequency range is set to 10MHz to 100MHz according to the operating frequency band of the test chip, which is used to define the frequency domain boundary of the effective detection signal; the characteristic impedance parameter is set to 50 ohms according to the physical structure of the test link, which is used to maintain the impedance matching state during signal transmission.

[0026] The carrier differential filtering model employs a two-port differential bridge circuit topology. Its core consists of a symmetrical dual-branch balanced input network and an arithmetic difference calculation unit with a high common-mode rejection ratio. Based on the 50-ohm characteristic impedance of the test link, a matching resistor is connected in parallel at the end of the symmetrical dual-branch balanced input network, with its resistance precisely set to 50 ohms. This configuration ensures impedance continuity, minimizing return loss in the 10MHz to 100MHz carrier frequency range, thereby suppressing reflection noise. The carrier differential filtering model integrates a bandpass filter operator, whose parameters are dynamically derived based on the carrier center frequency and bandwidth. Specifically: the filter order is set to third-order Butterworth type, utilizing its flat passband characteristics and a preset stopband descent slope to eliminate spurious interference outside the frequency domain boundaries; the cutoff frequency is set based on the carrier center frequency ±1 / 2 bandwidth; the quality factor Q is calculated by dividing the carrier center frequency by the bandwidth, and the resonant coefficients of the inductive and capacitive components in the circuit are configured based on the quality factor Q to finely adjust the filter's frequency selectivity. The arithmetic difference calculation unit executes a differential signal extraction algorithm to process the raw electrical signal received by the symmetrical dual-branch system. With no-load reference signal Vector cancellation is performed, and its difference operation logic follows the formula: ; in, This is the gain coefficient. is the gain coefficient, and is the time delay compensation amount extracted. The carrier differential filtering model receives the signal through the differential bridge circuit topology. First, it uses a bandpass filter operator to limit the signal bandwidth, and then uses an arithmetic difference calculation unit to extract the differential-mode component within the same frequency band and suppress common-mode interference. This process realizes real-time vector subtraction of the signal in the analog or digital domain, and finally generates a residual fluctuation component stripped of environmental background and system thermal noise at the output, providing pure raw data support for the subsequent accurate extraction of the convex point intrinsic impedance.

[0027] The phase synchronization alignment employs a discrete cross-correlation delay estimation algorithm from digital signal processing. This algorithm determines the time-domain deviation between the original electrical signal sequence and the idle reference signal sequence. It is achieved by performing a "sliding-product-summation" iterative calculation within a preset time window. Specifically, the idle reference signal sequence is gradually shifted along the time axis by k sampling periods; at each shift k, the original electrical signal sampling points within the overlapping area are multiplied point-to-point with the corresponding shifted reference signal sampling points; all product results under this shift are accumulated to generate the cross-correlation value corresponding to the current shift k. By traversing all possible shifts k, a correlation curve reflecting the signal similarity as a function of the shift is constructed. The shift corresponding to the global maximum point (i.e., the peak point) of this curve is the optimal time deviation required for the two signals to achieve waveform feature overlap. The system maps the shift to a time delay parameter on a physical time scale. The parameter is then output to the backend phase alignment module.

[0028] The differential-mode component subtraction operation uses vector component subtraction logic to perform algebraic subtraction of samples, using the original electrical signal as the minuend and the aligned no-load reference signal as the subtrahend, to cancel the high-frequency resonant noise of the common-mode distribution in the circuit. The extracted incoherent electrical performance fluctuation data is a residual electrical signal that reflects only the internal electrical characteristic offset of the flip-chip bump after removing environmental resonance interference. High-frequency synchronous sampling is performed on the residual electrical signal, and the signal is divided into several probe frames according to a preset time step. Subsequently, the time-domain residual voltage and current data of each probe frame are mapped to the complex frequency domain using Fast Fourier Transform or Hilbert Transform, and the impedance deviation value at each frequency node is calculated. Finally, the calculated impedance deviation value is aligned according to the spatial arrangement matrix of the flip-chip bump, encapsulated in an impedance offset vector matrix with timestamps, and synchronously associated with the transient power distribution sequence at each time point. The resulting structured digital stream is the bump interconnect response stream.

[0029] The convex interconnect response stream specifically includes an impedance offset vector matrix with timestamps and a transient power distribution sequence; wherein, the row dimension of the impedance offset vector matrix corresponds to the spatial coordinate index of the test contact, the column dimension corresponds to the characteristic frequency sampling point, and the matrix elements store complex impedance offset values; the transient power distribution sequence and the impedance offset vector matrix maintain a one-to-one correspondence on the time axis, and are used to record the energy fluctuation characteristics at the corresponding time.

[0030] This invention achieves physical separation of the original signal from the loop background noise through a carrier differential filtering model, and accurately eliminates environmental resonance interference by using cross-correlation phase alignment and vector component subtraction, ensuring that the bump interconnect response flow can truly reflect the micro impedance changes inside the package, thereby improving the signal-to-noise ratio and purity of the test signal from the data source.

[0031] Furthermore, the process of generating the convex intrinsic impedance current and flip-chip calibration features by the convex impedance unit includes: acquiring package electrical parameters containing parasitic inductance and interlayer capacitance data of package pins; mapping the package electrical parameters to parasitic impedance vectors using vector compensation logic; performing vector subtraction on the convex interconnect response current and parasitic impedance component vectors to generate the convex intrinsic impedance current; constructing a path phase compensation model based on vector compensation and phase alignment logic, inputting the convex intrinsic impedance current into the path phase compensation model to perform time-domain phase difference extraction to generate a time delay offset compensation amount; and using the time delay offset compensation amount to perform signal transmission delay synchronization operation on the convex intrinsic impedance current to generate flip-chip calibration features.

[0032] Specifically, package electrical parameters are obtained through preset package physical structure simulation data. These parameters include parasitic inductance of the package pins ranging from 0.1nH to 5.0nH and interlayer capacitance data ranging from 0.5pF to 10.0pF. The operating frequency determined by the carrier differential filtering model is obtained, and the inductive and capacitive reactance values ​​at each sampling point are calculated based on the parasitic inductance of the package pins and the interlayer capacitance. The calculation results are mapped to the complex frequency domain to generate complex impedance elements composed of imaginary reactance. According to the physical topology of the test link, the complex impedance elements are arranged according to the spatial position of the convex points to construct the parasitic impedance vector. The inductive reactance component is directly proportional to the test frequency, and the capacitive reactance component is inversely proportional to the test frequency. Vector subtraction uses the complex impedance value in the bump interconnect response flow as the minuend and the parasitic impedance vector as the subtrahend, performing point-to-point subtraction in the complex domain to remove the series parasitic reactance and parallel loss effects generated by external pins and substrate leads, generating the bump intrinsic impedance flow. The bump intrinsic impedance flow only characterizes the physical electrical properties of the microbump structure inside the flip chip.

[0033] The process of constructing a path phase compensation model based on vector compensation and phase alignment logic is as follows: The vector compensation logic mapping is performed as follows: The parasitic inductance value of the pin is multiplied by the carrier angular frequency to obtain the inductive reactance component characterizing the magnetic field energy storage effect; simultaneously, the reciprocal of the product of the carrier angular frequency and the interlayer capacitance value is taken to obtain the capacitive reactance component characterizing the electric field energy storage effect. The imaginary part of the parasitic impedance vector is determined by the vector difference between the inductive and capacitive reactance, reflecting the phase shift capability of the electrical signal; the real part is determined based on the resistivity and dielectric loss of the trace material, reflecting the amplitude attenuation characteristics of the electrical signal. The core of generating the carrier drift matrix lies in the piezoresistive effect tensor mapping. Its logical process is as follows: the normal stress and shear stress borne by the microbump in three axes are linearly combined and accumulated through the piezoresistive coefficient matrix of a specific semiconductor material, directly quantifying the change in lattice structure caused by mechanical stress as the relative rate of change of resistivity. Subsequently, this rate of change is multiplied by the initial geometric impedance of the bump to obtain the theoretical impedance offset induced only by stress. The matching process employs a multidimensional Euclidean distance algorithm. The specific operation is as follows: Multiple extracted electrical features (such as VSWR, distortion rate, and timestamp offset) are treated as coordinate points in a multi-dimensional space. The linear geometric distance between the measured coordinate point and the coordinate point of a preset standard failure model is calculated. When this distance is less than a preset range, the current signal feature is determined to match the corresponding failure mode, thereby identifying the specific type of physical defect. In the complex coordinate system, the measured total impedance vector containing parasitic interference is considered as the resultant vector, and the pre-calculated parasitic impedance vector is considered as the interference component. By performing subtraction operations on the real and imaginary parts of the complex vector respectively, the interference vector is geometrically removed from the total vector, and the difference vector is the eigenimpedance current of the bump that points only to the internal physical state of the chip.

[0034] Perform phase alignment logic calculation: Combined with the substrate dielectric constant (3.8 to 4.5), the propagation speed of the signal on the spatial vector path is calculated using phase alignment logic, and the sampled waveform of the convex intrinsic impedance current is cross-correlated with the system trigger reference pulse to determine the initial phase difference to be aligned.

[0035] The path phase compensation model first calculates the phase velocity of the signal in the transmission line. Specifically, it obtains a preset substrate dielectric constant (3.8 to 4.5), performs an arithmetic square root operation on it as the denominator, and performs a division operation using the speed of light in vacuum as the numerator to derive the actual propagation speed of the signal in the physical trace. Combined with the physical trace length from the probe to the chip contact, the theoretical transmission delay of the signal in the physical link is calculated.

[0036] Real-time phase characteristics and initial phase difference extraction: The system synchronously uses the Hilbert transform to perform analytic signal construction on the acquired original electrical signal. By performing an integral transform on the real-domain signal to generate an imaginary part signal orthogonal to it, a complex analytic envelope containing transient phase information is extracted. The argument of the transient complex vector is calculated using the complex analytic envelope to obtain the real-time phase distribution of the original signal in the time domain. This phase distribution is then subtracted from the phase of the unloaded reference signal to identify the initial phase difference between the two signals.

[0037] The path phase compensation model is constructed following vector superposition logic to integrate physical path deviation and system inherent error: by comparing the waveform sampling time of the intrinsic impedance current of the convex point with the system trigger reference pulse, and combining the aforementioned theoretical transmission delay, a delay offset compensation amount between 50ps and 200ps is generated, and multiplied by the test carrier frequency and converted by angle to transform it into a spatial phase angle characterizing the physical characteristics of the trace; the spatial phase angle and the time-domain phase angle converted from the initial phase difference are used as two independent phase vectors, and polar coordinate addition is performed in the complex plane to generate a comprehensive phase deviation.

[0038] Finally, the system utilizes the comprehensive phase deviation to perform a reverse phase rotation on the convex intrinsic impedance current, and combines this with digital interpolation translation logic to perform a reverse translation on the time axis equal to the time delay offset compensation amount, thereby eliminating phase deviation caused by inconsistent physical trace lengths. By translating the signal to the system's zero-time reference and mapping the signal strength to the standard range using a preset reference amplitude, spatial alignment is finally performed according to the chip's physical coordinates, generating a flip-chip calibration feature with high-fidelity position reference to eliminate spatiotemporal phase redundancy between different test channels.

[0039] This invention effectively eliminates the masking effect of encapsulation parasitic parameters on the weak electrical characteristics of bumps through vector subtraction, and solves the problem of signal phase misalignment under high-frequency testing by using time delay compensation based on the propagation characteristics of the medium. This ensures the physical specificity of the calibration features in the time and frequency domains, and provides a high signal-to-noise ratio electrical reference for subsequent sampling of electrical parameters for microcracks.

[0040] Furthermore, the process of generating convex array current conduction by the convex array unit includes: constructing a contact electrical mapping model based on potential difference acquisition logic; inputting inverted calibration feature data into the contact electrical mapping model to perform node potential difference step sampling operation to generate array node potential set; acquiring preset detection current amplitude data; performing Ohm's law mapping transformation operation on the array node potential set using the preset detection current amplitude data to generate contact conduction quantization data; and performing conductivity feature vector encapsulation operation based on the contact conduction quantization data to generate convex array current conduction.

[0041] Specifically, the potential difference acquisition logic is built based on the four-wire high-impedance differential sensing principle. While a constant current source injects current into the excitation path, a sensing loop independent of the excitation path monitors the potential across the target convex point. This logic utilizes a differential amplifier circuit to extract the transient difference between the probe and the reference ground, thereby eliminating parasitic voltage drops within the test cable and switch matrix.

[0042] The construction process of the contact electrical mapping model based on the potential difference acquisition logic is as follows: The contact electrical mapping model adopts a multi-dimensional correlation matrix mapping structure. The system obtains the physical distribution coordinate matrix (x, y) of the convex array and uses a row and column address decoding algorithm to assign the spatial vector to the corresponding electrical channel number. Using the aforementioned potential difference acquisition logic, an independent excitation and sensing address is configured for each channel, and the physical coordinates, channel number, and link gain calibration value are multi-dimensionally correlated to construct a mapping model that can realize the "coordinate to potential" conversion.

[0043] The process of inputting inverted calibration feature data into the contact electrical mapping model to perform node potential difference step sampling includes: During the step sampling operation, the system controls a gating switch composed of a low on-resistance solid-state analog multiplexer to sequentially connect channels according to an alternating reverse serpentine scanning logic. After the gating switch is turned on and a 50ns signal convergence stabilization period has elapsed, the system triggers sampling to obtain the net voltage drop value after excluding the system common-mode potential. Subsequently, the system associates the value with the physical coordinate index in real time and stores it in a high-speed cache. After the scan is completed, the system reorganizes the data in the form of a coordinate matrix to generate a structured data matrix (array node potential set) with physical space coordinates as row and column indices and net voltage drop as elements. The array node potential set is structurally represented as a structured data matrix with physical space coordinates as row and column indices and the net voltage drop value of the corresponding node as matrix elements.

[0044] The transient voltage drop values ​​corresponding to each data element are extracted from the array node potential set. The preset probe current amplitude data is the precise current value injected into the test circuit by the controlled constant current source of the system. The Ohm's law mapping transformation operation includes: multiplying the milliampere-level current amplitude data by 10. −3 Converted to amperes, the potential set of the array nodes is traversed synchronously, and the millivolt-level voltage drop value is multiplied by 10. −3 Converted to volts. Based on the conductance transformation logic of Ohm's law, the current value in amperes is used as the numerator, and the voltage drop in volts at the corresponding position in the array node potential set is used as the denominator, performing point-by-point division. During the calculation, if the voltage drop in the node potential set is detected to be lower than a preset noise threshold (determined as ultra-low resistance or short circuit), the conductance value corresponding to that physical coordinate is recorded as a preset saturation extreme value; thus, contact conduction quantization data in Siemens standard units, spatially corresponding one-to-one with the array node potential set, is derived.

[0045] The specific process of generating convex array conductivity current by performing conductivity feature vector encapsulation based on contact conduction quantization data includes: constructing a multi-dimensional feature vector for each physical convex point in the array. This vector uses the calculated contact conduction quantization data as the main feature dimension and associates the corresponding spatial topological coordinates (X, Y) using the contact electrical mapping model. Test metadata is dynamically attached to each feature vector. This metadata includes the real-time acquired test environment temperature (used to subsequently eliminate the temperature drift effect of impedance), the unique batch identifier of the chip under test, and a high-precision system timestamp. The feature vectors of each dimension are structurally merged according to the sampling order of node potential differences. Specifically, key-value pairs or structures are used to bind and encapsulate spatial information, electrical performance information, and environmental parameters. The encapsulated feature vector sequence is converted into a binary structured data stream with continuous logical addresses, and frame header check bits and data length identifiers are added. The resulting convex array conductivity current can completely and in real-time characterize the spatial distribution of microscopic conductivity and its dynamic evolution characteristics of the entire array of convex points in the current encapsulation batch.

[0046] This invention eliminates the ambiguity between the test channel and the physical location by constructing a high-precision contact electrical mapping model; it avoids transient interference during switch switching by using time-constrained step sampling. Combined with rigorous dimensional unification processing, it ensures that the conduction quantization data can accurately reflect the density of the convex physical connection, providing high spatial resolution original electrical evidence for subsequent identification of microcracks using the "carrier drift matrix".

[0047] Furthermore, the process of generating bump defect feature elements and crack electrical signal features by the bump array unit includes: acquiring the encapsulation stress offset parameters; constructing a carrier drift matrix comparison model based on the thermal stress and piezoelectric effect of the bottom filler adhesive; inputting the bump array electrical conductivity data and the encapsulation stress offset parameters into the carrier drift matrix comparison model to perform an electrical fingerprint feature association matching operation, extracting the impedance deviation component that deviates from the standard conduction mode, and generating bump defect feature elements; constructing a standing wave ratio distortion decomposition model based on the pulse injection frequency and the transmission line impedance standard; inputting the bump defect feature elements into the standing wave ratio distortion decomposition model to perform a pulse reflection waveform sampling operation, separating the reflected wave voltage standing wave ratio distortion component, and generating crack electrical signal features.

[0048] The specific process of constructing the carrier drift matrix comparison model includes: establishing the three-dimensional stress tensor distribution of the micro-bump contact interface using finite element analysis logic; introducing the piezoelectric resistance coefficient matrix of the corresponding semiconductor material to establish a linear coupling relationship between the three-dimensional stress tensor and the carrier migration rate; calculating the relative change component of the bump contact resistance based on the carrier migration rate, and combining it with the spatial coordinates of the bump array to generate a theoretical impedance offset matrix induced by stress, which serves as the judgment criterion for the carrier drift matrix comparison model.

[0049] The linear coupling relationship is realized through the piezoresistive effect tensor equation, specifically: the relative rate of change of resistivity is equal to the contracted product of the piezoresistive coefficient tensor and the stress tensor. In a three-dimensional spatial coordinate system, this equation linearly maps six independent stress components (including three normal stress components and three shear stress components) to anisotropic deviations of resistivity through their corresponding piezoresistive coefficients. Based on the relative rate of change of resistivity, the relative change components of the convex contact resistance are calculated. Combined with the spatial coordinates of the convex array, a theoretical impedance offset matrix induced by stress is generated, which serves as the criterion for judging the carrier drift matrix comparison model.

[0050] The system first retrieves the encapsulation stress offset parameter, which contains data on the dynamic change of the elastic modulus of the underfill adhesive due to thermal expansion coefficient mismatch under drastic temperature changes from 25°C to 150°C. Using pre-defined finite element analysis logic, the macroscopic residual thermal stress (0MPa to 120MPa) is decomposed and mapped to each micrometer-scale bump contact, calculating its three-dimensional stress tensor components along three spatial axes. After establishing the three-dimensional stress tensor, the model incorporates the piezoelectric resistivity matrix of a specific semiconductor material (such as silicon-based doping or a specific alloy). Utilizing the piezoelectric effect, the influence of mechanical stress on the semiconductor band structure is quantified as the carrier migration rate. Through this coupling relationship, the model can predict the fluctuation ratio of charge transport efficiency as carriers pass through the bump contact interface under specific thermal stress. Finally, the model converts the carrier migration rate into the corresponding resistivity offset value, obtaining the relative change component of the bump contact resistance. By combining the physical geometric dimensions (such as diameter and height) of each bump with its physical arrangement coordinates in the array, these discrete offset values ​​are reconstructed into a theoretical impedance offset matrix, i.e., a carrier drift matrix, that is perfectly aligned with the spatial dimension of the electrical conduction. This carrier drift matrix defines the normal electrical drift that should occur solely due to stress in the absence of any physical cracks, and serves as the criterion for comparing the carrier drift matrix with the model. This model transforms thermal stress parameters into a quantified impedance benchmark through the piezoelectric effect, accurately eliminating electrical noise caused by packaging stress, effectively identifying abnormal deviations caused by physical cracks, and significantly reducing the false defect reporting rate in packaging testing.

[0051] The process of performing electrical fingerprint feature association matching includes: the specific algorithm for electrical fingerprint feature association matching adopts multi-dimensional space Euclidean distance determination logic. The extracted crack electrical signal features are constructed as a test feature vector, and a standard defect fingerprint vector is called from a preset failure mode library; the Euclidean distance between the test feature vector and the standard defect fingerprint vector in the multi-dimensional electrical feature space is calculated, and the type and severity of the crack are determined by measuring whether this distance falls within a preset similarity threshold range.

[0052] First, the electrical conductivity of the convex array is obtained and converted into the corresponding measured impedance matrix using reciprocal operations. Simultaneously, the carrier drift matrix is ​​retrieved to compare with the theoretical impedance offset matrix generated by the model. This ensures that the two sets of data are perfectly aligned in spatial coordinates (physical location index) and frequency dimensions. Using the measured impedance matrix as input and the theoretical impedance offset matrix as reference, element-wise vector difference operations are performed to subtract the "normal" impedance drift caused by thermal stress from the bottom filler adhesive from the measured total impedance. In the difference results, random fluctuations caused by system quantization errors are filtered out using a preset dynamic threshold. The milliohm-level residual component deviating from the standard conduction mode is extracted; this component represents the impedance deviation component caused by poor physical contact or microcracks after excluding stress interference. The identified impedance deviation component is bound to the corresponding convex spatial coordinates, and a product scaling and deviation mapping are used, i.e.: ,in, As the defect credibility weight, For impedance deviation, The stress components at the nodes are combined with the current stress level at the nodes. Here is the stress influence function, which employs an exponential decay operator: ,in To calculate the "defect confidence weight" of this deviation component based on a preset sensitivity factor of the chip material's piezoelectric resistivity, the algorithm determines that the impedance deviation is still significant in a low-stress region, indicating a very high probability of a physical crack at that point, thus generating a high confidence weight close to 1.0. Conversely, if the impedance deviation is in a high-stress region and does not exceed the stress compensation range, a low confidence weight close to 0 is generated. Finally, the deviation amplitude, phase shift, and weight coefficients are aggregated and encapsulated to generate a convex defect feature element with physical location information.

[0053] The process of constructing the standing wave ratio distortion decomposition model includes: establishing the high-frequency pulse injection frequency range and the standard impedance of the system transmission line, and obtaining the flip-chip calibration characteristics as the reference reflection parameters; based on the geometric deformation characteristics of the internal crack of the micro-bump; calculating the deviation between the theoretical reflection coefficient and the standard impedance, establishing the mapping relationship between the standing wave ratio distortion components and the physical size of the crack, and generating the standing wave ratio distortion decomposition model.

[0054] First, the operating frequency band is set to 1GHz to 5GHz. Within this band, the wavelength can be shortened to the millimeter level, generating electromagnetic reflection from micrometer-sized protruding cracks. The system uses the inverted calibration feature as the initial reference frame, employing a 50-ohm standard transmission path (i.e., the reference reflection parameter) as the defect-free state, and records the reference standing wave ratio (theoretical value 1.0, actual system inherent echo value). The physical crack equivalent feature is treated as a sudden impedance network consisting of parallel capacitance and series resistance; the crack opening displacement corresponds to a change in capacitance, and the reduction in contact area corresponds to a change in resistance. Electromagnetic simulation logic is used to simulate the reflection coefficient generated when a high-frequency pulse passes through the equivalent network. Due to impedance mismatch caused by cracks, the signal will experience significant phase shift and amplitude attenuation. (The formula is used to...) , reflectance coefficient Converted to voltage standing wave ratio The VSWR distortion decomposition model is constructed by extracting characteristic parameters from the measured VSWR curve that deviate from the baseline value. Specifically, it identifies and extracts the distortion peak amplitude, envelope width data, and spatial location of phase abrupt change points from the measured VSWR curve. Subsequently, a multivariate mapping relationship is established between the distortion characteristic parameters and the crack depth and width components. The VSWR distortion decomposition model receives the measured reflected waveform as input and deconstructs it into quantifiable distortion components characterizing the nonlinear impedance of the crack through the correlation function. These distortion components correspond to the physical interface impedance fluctuations caused by microcracks and are used to analyze hidden fracture defects within the flip-chip package. This model utilizes the high sensitivity of high-frequency pulses to physical interface discontinuities to transform the weak impedance fluctuations caused by microcracks into quantifiable VSWR distortion components, achieving in-depth analysis of hidden fracture defects and significantly improving the accuracy of early failure prediction within the flip-chip package.

[0055] The specific process of pulse reflection waveform sampling operation is as follows: The pulse reflection waveform sampling operation executes time-domain reflection detection logic to identify impedance discontinuities inside the bulge. The specific process includes: injecting a high-frequency narrow pulse with a frequency range of 1GHz to 5GHz and a pulse width in the picosecond range into the channel under test according to the parameters determined by the VSWR distortion decomposition model, allowing it to propagate along the transmission line to the physical interface of the flip-chip bulge; simultaneously, using an ultra-high-speed sampling circuit, opening the sampling gate within a preset time window after triggering the reference pulse. Through time window alignment logic, the sampling point is positioned within the time period during which the pulse passes through the bulge and generates an echo. The sampling circuit acquires the transient amplitude and phase shift data of the reflected echo in real time, and extracts the reflected voltage signal reflecting the impedance mismatch intensity by calculating the waveform difference between the injected wave and the echo, generating a reflected voltage vector for VSWR calculation.

[0056] The process of separating the VSWR distortion component and generating crack electrical signal characteristics is as follows: The system substitutes the captured reflected voltage vector into the VSWR distortion decomposition model to calculate the measured VSWR. Through subtraction decomposition logic, the calibration feature (i.e., the system's inherent VSWR reference) is subtracted from the measured value, separating the reflected wave VSWR distortion component caused solely by the discontinuity (crack) within the convex point. Using the timestamp of the reflected wave peak and the medium propagation velocity, the precise location of the impedance abrupt change point on the physical link is calculated. The waveform distortion rate is extracted; a higher distortion rate indicates a larger crack opening displacement and a more pronounced nonlinear characteristic of the contact resistance. The waveform symmetry is analyzed; asymmetrical waveforms typically characterize the presence of an oxide layer or roughness on the crack surface, leading to nonlinear impedance, thus distinguishing it from simple contact defects. The resolved timestamp, distortion rate, waveform symmetry, and VSWR deviation are multidimensionally aggregated and encapsulated to generate crack electrical signal characteristics with physical diagnostic significance.

[0057] Furthermore, the process of generating the response trajectory set by the load fault test unit includes: acquiring the test current step load; capturing the node current distribution flow by performing current sampling monitoring on the convex array; constructing the convex contact impedance matrix based on the convex defect feature elements; and performing a current vector space coordinate comparison operation between the node current distribution flow and the convex contact impedance matrix based on the crack electrical signal characteristics to generate the response trajectory set.

[0058] The test current step load is a preset electrical stress excitation sequence. It is increased in 0.1A increments from 0.1A to 2.5A via a constant current source module, inducing current congestion at the internal defects of the bumps through gradually increasing charge flow density. Current sampling and monitoring are performed using a multi-channel current sensor array integrated into the test socket interface. Within each load step cycle, the sensor array synchronously captures the transient current values ​​of each physical contact and combines this with coordinate indexing to generate the node current distribution flow, which characterizes the macroscopic current carrying state of the array under different electrical stress levels.

[0059] The convex contact impedance matrix is ​​constructed based on the convex defect eigenvalues. Specifically, the impedance offset magnitude and phase information of each eigenvalue are extracted and injected as perturbation variables into the ideal circuit topology of the chip bottom contact. Through network node analysis, the discrete defect impedances are integrated into a physical parameter matrix characterizing the electrical damping distribution of the entire array, providing a physical background for the non-uniform resistivity distribution for current path derivation.

[0060] The system extracts the impedance offset magnitude (characterizing resistance increment) and phase information (characterizing inductive or capacitive reactance change) corresponding to each node from the convex defect feature elements generated earlier. Using a preset flip-chip calibration feature as a reference value, a scaling operation is performed on the impedance offset magnitude to obtain the impedance change rate, and a reference translation operation is performed on the phase information to extract the pure phase perturbation. These discrete milliohm-level deviations are transformed into impedance perturbation operators with complex properties. The ideal circuit topology of the bottom contacts of the flip chip is obtained, i.e., the standard impedance network in a defect-free state; the impedance perturbation operator is used as a perturbation variable and input into the corresponding circuit node or branch in the ideal circuit topology. Based on Kirchhoff's law, a set of circuit equations for the entire array is constructed. Through network node analysis, the potential distribution relationship between each interconnected node in the array is calculated after the perturbation variable is injected. This process considers the parasitic coupling between adjacent convex points and the residual impedance of the test link, associating discrete, local point defects into a continuous electrical system. The physical parameter matrix is ​​derived by solving the set of circuit equations. The specific process is as follows: Network node analysis is used to associate convex defects at discrete locations with the overall array topology, establishing underlying data reflecting the non-uniform resistivity distribution characteristics under complex stress conditions. The physical parameter matrix characterizes the overall electrical damping distribution of the array and serves as a physical reference for subsequently inferring current path redistribution behavior. The non-uniform resistivity background is used to quantitatively identify the charge flow shift induced by microcracks. This process, by associating local defects with the global topology through network node analysis, effectively reconstructs the non-uniform resistivity background under complex stress, providing an accurate physical reference for quantitatively identifying current redistribution caused by microcracks.

[0061] The current vector spatial coordinate comparison operation identifies charge flow anomalies caused by microcracks by spatially fitting the measured current flow direction with the theoretical path. Specific steps include: establishing a three-dimensional spatial coordinate system (x, y, z) with the chip center as the origin, based on the contact electrical mapping model; wherein, the plane parallel to the reference plane where the chip contacts are located is defined as the x-y plane, used to define the row and column physical distribution of the bump array in the horizontal dimension; the direction perpendicular to the x-y plane is defined as the z-axis, used to define the vertical transmission direction of the signal through the bumps. The abnormal deflection characteristics of the charge flow direction are extracted by calculating the deflection tensor of the measured current vector relative to the theoretical optimal path within the three-dimensional spatial coordinate system. Ohm's law mapping is performed on the current step load of the current using the bump contact impedance matrix to derive the theoretical vector direction of charge flow through each bump node under defect-free or known stress conditions. Based on the nonlinear inflection points locked by the crack electrical signal characteristics, nodes where impedance distortion occurs are sampled in a focused manner. The actual flow direction vector is extracted using the node current distribution flow captured by the sensor. Calculate the deflection tensor of the charge flow in space by subtracting the actual flow direction vector from the theoretical vector direction. Identify the flow component around the charge in the x-y plane caused by the charge avoiding the high-resistivity region of the crack. Identify the surge in vertical current density caused by the reduction in the effective current cross-sectional area due to the crack surface.

[0062] As the step current (from 0.1A to 2.5A) increases in a stepwise manner, the system records the current deflection tensor value under each load level in real time. The deflection tensor, transient current intensity, physical location number of the corresponding convex point, and timestamp of the current step are spatiotemporally aligned to construct a single-point evolution vector.

[0063] Initial stage: Record the initial load threshold at which the current vector begins to deviate from the theoretical path.

[0064] Evolutionary phase: Capturing the nonlinear growth process of vector offset caused by thermal expansion or electromigration of cracks due to Joule heating as current increases.

[0065] Failure threshold: The critical load value at which the current vector undergoes severe distortion or shows signs of an open circuit.

[0066] The evolution vectors of each stage are encapsulated into a structured dataset according to time series, ultimately generating the response trajectory set. This set digitally reproduces the physical evolution trajectory of the convex point from "existence of microcracks" to "electrically stressed degradation" and then to "failure".

[0067] This invention establishes a correlation model between step load and current spatial distribution, enabling quantitative tracking of changes in charge flow direction within flip-chip packages. It accurately captures the current path redistribution phenomenon caused by microcracks, providing spatiotemporally synchronized data for subsequent evaluation of the electrical degradation trajectory of interconnect structures.

[0068] Furthermore, the process by which the load failure test unit generates evaluation parameters and sealing test results includes: acquiring physical degradation parameters containing the convex crack extension length and the deformation variable of the connection interface; performing an electrical parameter drift and structural physical damage degree mapping operation on the response trajectory set data and the physical degradation parameters to extract the electrical performance degradation fingerprint set and generate evaluation parameters; acquiring standard electrical variable fluctuation limit threshold data; performing a threshold boundary comparison operation on the evaluation parameters and the electrical variable fluctuation limit threshold; performing level matching based on the comparison operation; and generating sealing test results.

[0069] Specifically, physical degradation parameters are reserved in the system as a system judgment benchmark, obtained through prior high-magnification microscopy or scanning acoustic microscopy. These parameters include the crack extension length of the convex point, ranging from 1 μm to 50 μm, and the interface deformation variable of 50 nm to 500 nm, characterizing material fatigue. The specific process of mapping electrical parameter drift to structural physical damage is as follows: based on a nonlinear geometric mapping model. Specifically, the current offset intensity recorded in the response trajectory set is used as input, and the geometric loss rate of the effective conductive cross-sectional area is calculated based on the crack extension length (1 μm-50 μm) and interface deformation variable (50 nm-500 nm) in the physical degradation parameters. Specifically, the nominal cross-sectional area of ​​the convex point is subtracted using the crack length to convert the degree of physical tearing into an electrical deviation coefficient characterizing the change in impedance ratio. Subsequently, this coefficient is used to perform feature deconstruction on the response trajectory set to extract a multidimensional electrical performance degradation fingerprint set composed of impedance change rate, peak VSWR drift, and current density distortion rate.

[0070] Multiple feature vector components are extracted from the electrical performance degradation fingerprint set, and sensitivity weights are assigned to each component. The impedance change rate is assigned the highest weight to prioritize reflecting mechanical damage to the interconnect structure. For example, the impedance change rate is assigned the highest weight, while the instantaneous fluctuation deviation is assigned a relatively lower weight, ensuring that the evaluation index prioritizes reflecting substantial mechanical damage to the interconnect structure. Using a multidimensional space vector magnitude calculation method, the aforementioned feature vector components are normalized using a mean-standard deviation approach. By obtaining the statistical benchmark of each feature component in a preset standard sample feature database, the standard deviation multiple of the measured feature value from the mean is calculated, thereby mapping features such as degradation rates, impedance drift, and distortion rates with different physical dimensions to a unified dimensionless numerical space, generating a comprehensive attenuation deviation value. This deviation value characterizes the total magnitude of the current chip's electrical performance deviating from the ideal, damage-free state. The comprehensive attenuation deviation value is input into a function such as the Sigmoid function or piecewise mapping logic, which compresses and maps the deviation value from the infinite domain to the standard interval [0,1], generating the evaluation parameter item. If the result approaches 1, it indicates minimal electrical attenuation and a high reliability of the interconnect structure; if the result approaches 0, it indicates that the electrical characteristics have significantly deviated from the baseline, and the structure faces an extremely high risk of failure. The generated index is dynamically compensated using packaging stress offset parameters to eliminate systematic offsets caused by environmental temperature or residual stress, ensuring that the evaluation parameters objectively represent only the reliability degradation caused by physical degradation.

[0071] Based on the industrial standard preset standard electrical variable fluctuation limit threshold data, the threshold data sets stringent indicators such as impedance change rate not exceeding 10%.

[0072] The threshold boundary comparison operation specifically involves mapping the real-time features in the evaluation parameters to a multidimensional hyperplane and calculating the Euclidean distance between them and the threshold boundary.

[0073] The ranking matching logic performs clustering based on the distance: Pass: Deviation distance is within the safe range, and reliability index > 0.9; Undetermined: The deviation is close to the threshold critical point, posing a risk of early crack evolution; Non-compliant: Deviation exceeds the threshold, and physical damage has led to electrical performance failure.

[0074] The final packaging and testing result is a structured instruction, which includes a yield level code, a failure probability value predicted based on the trajectory set (i.e., the expected percentage of remaining lifetime under the current stress), and test batch traceability information, and directly connects to the backend sorting machine to perform material sorting.

[0075] This invention establishes a mapping relationship between physical degradation parameters and electrical performance degradation fingerprints, thereby achieving quantitative electrical characterization of the internal physical damage state of flip-chip packages. By utilizing standard electrical variable thresholds to perform boundary comparison and yield determination, it improves the test system's ability to predict and classify hidden physical defects that evolve into electrical faults.

[0076] This invention constructs an electrical detection system for microscopic defects in flip-chip packages through the substantial combination of impedance purification, convex array conduction mapping, and load fault evolution evaluation. First, carrier differential filtering and vector phase compensation eliminate interference from pin parasitic parameters and environmental noise, ensuring the electrical purity and data specificity of the detection source. Second, by combining stress offset comparison and VSWR distortion decomposition techniques, precise capture and electrical performance characteristic mapping of microcracks within the concealed micro-convex array are achieved. Finally, through current displacement trajectory tracking under dynamic loads, a correlation model between the degree of physical damage and electrical characteristic deviations is established. This solution overcomes the limitations of traditional electrical testing methods in characterizing microscopic physical degradation processes, improving the identification resolution, lifetime prediction capability, and yield assessment of concealed faults in packaging and testing systems under complex load environments.

[0077] Example 2 This embodiment provides a specific application process of an efficient chip packaging testing method in the flip-chip packaging testing scenario of high-performance power electronic components. When performing electrical performance testing on flip chips with high-density microbump arrays, traditional testing methods struggle to directly obtain the true physical defects at the microbump interface due to the electrical shielding effect caused by parasitic parameters of the internal pins and thermal stress of the bottom filler. This method achieves dynamic detection of internal microcracks without damaging the packaging structure by executing a logical sequence of impedance purification, conduction quantization mapping, and load evolution evaluation.

[0078] In the initial stage of testing, raw electrical signal data is first acquired. A processing program consisting of carrier differential filtering logic is used to phase-align the captured raw electrical signal, containing millivolt-level voltage amplitude and milliradian-level current phase, with the unloaded reference signal generated by the test circuit. Subsequently, a reference signal subtraction denoising operation is performed. By canceling high-frequency environmental resonance noise, incoherent fluctuation components reflecting the electrical characteristic shift of the microbump interface are extracted, generating the bump interconnect response current. Based on this, preset package electrical parameters are retrieved, including pin parasitic inductance data ranging from 0.1nH to 5.0nH and interlayer capacitance data ranging from 0.5pF to 10.0pF. A vector subtraction operation is performed between the bump interconnect response current and the vectorized parasitic impedance vector to remove the electrical effects generated by the package substrate leads, generating the intrinsic bump impedance current that characterizes only the microbump structure inside the flip chip. Next, based on the preset physical length of the signal transmission path and the dielectric loss coefficient, a signal transmission delay synchronization operation is performed on the convex intrinsic impedance current. The phase deviation of the physical link is eliminated by time axis alignment, and finally a flip-chip calibration feature with high fidelity is generated.

[0079] After acquiring the flip-chip calibration features, the process proceeds to the convex array conduction mapping stage. A contact electrical mapping model is constructed based on the preset physical distribution coordinate matrix of the convex array and the topology parameters of the probe loop nodes. The flip-chip calibration feature data is input into the contact electrical mapping model, and a step sampling operation of the node potential difference is performed according to the preset physical coordinate sequence. The transient voltage drop of each micro-convex contact in the array is recorded, generating a structured array node potential set. Subsequently, the system's preset probe current amplitude data in the range of 10mA to 100mA is retrieved, and Ohm's law mapping transformation is performed on the voltage values ​​in the array node potential set using this current data. During the calculation, the consistency of the dimension conversion between milliampere-level current and millivolt-level voltage is strictly maintained, deriving contact conduction quantization data in Siemens units. By introducing a bias variable including the thermal stress parameters of the bottom filler adhesive and the piezoelectric effect coefficient, the contact conduction quantization data is compared with the carrier drift matrix to extract the impedance deviation component that deviates from the standard conduction mode, thereby generating convex defect feature elements. To further detect hidden cracks, time-domain reflection waveform analysis was performed based on high-frequency pulse injection frequencies from 1 GHz to 5 GHz. Voltage standing wave ratio distortion decomposition was performed on the feature elements of the convex defect to separate the waveform distortion components of the reflected wave and generate crack electrical signal features that include peak timestamps and distortion rate characteristics.

[0080] After static feature extraction, load failure evolution testing is performed. Dynamic current sampling and monitoring are conducted on the convex array by injecting test currents ranging from 0.1A to 2.5A in step loads, capturing the node current distribution under different load gradients. Using the convex defect feature elements generated in the previous steps, a contact impedance matrix reflecting the array's electrical properties is constructed. The real-time monitored node current distribution is compared with the contact impedance matrix using current vector space coordinates. By identifying the displacement tensor of the actual current vector relative to the theoretical path in the three-dimensional projection, the charge flow offset trajectory caused by physical crack obstruction is traced, generating a response trajectory set. Finally, physical degradation parameters containing convex crack extension length and interface deformation variables are obtained. Spatiotemporal coupling correlation operations are performed on the response trajectory set data and physical degradation parameters to extract an electrical performance degradation fingerprint set characterizing the failure trend, generating quantified evaluation parameters. Boundary comparison operations are performed between the evaluation parameters and standard-defined electrical variable fluctuation thresholds. Yield level matching is performed based on the offset distance of electrical features, ultimately generating a packaging and testing judgment result containing fault risk prediction and yield classification information.

[0081] The beneficial effects of this technical solution are as follows: By establishing a closed-loop evaluation system covering the entire process from physical impedance stripping to electrical conduction mapping and dynamic load evolution, in-depth electrical detection of hidden defects in flip-chip packages is achieved. Vector subtraction and phase alignment eliminate the masking effect of package parasitics; four-terminal sampling and VSWR analysis solve the problem of high-precision quantification of micro-bump contact resistance; and dynamic load monitoring enables real-time tracking of the physical damage evolution trajectory. This method significantly improves the accuracy of the packaging and testing system in identifying minute electrical faults under complex thermoelectric coupling environments, providing highly physically correlated quantitative data support for the reliability assessment of flip-chip packages.

[0082] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A high-efficiency chip packaging and testing system, characterized in that, include: Bump impedance unit: Acquires raw electrical signal data, performs reference signal denoising operation, and generates bump interconnect response flow; Obtain the package electrical parameters, perform vector compensation calculation on the bump interconnect response flow, and generate the bump intrinsic impedance flow; A path phase compensation model is constructed based on vector compensation and phase alignment logic. Signal transmission delay synchronization is performed on the convex point intrinsic impedance current to generate inverted calibration characteristics. Bump array unit: Based on the potential difference acquisition logic, a contact electrical mapping model is constructed. Electrical parameter sampling operation is performed on the flip-chip calibration features to generate the bump array electrical conduction. The packaging stress offset parameters are obtained, and the carrier drift matrix is ​​compared on the bump array electrical conduction to generate bump defect feature elements. Based on the feature elements of the convex defect, the reflected wave standing wave ratio distortion decomposition is performed to generate crack electrical signal features. Load Fault Test Unit: By monitoring the current signal characteristics of the crack, the unit performs current shift trajectory tracking to generate a response trajectory set; it acquires physical degradation parameters, performs electrical performance deviation correlation calculation on the response trajectory set to generate evaluation parameter items; and it performs electrical variable threshold range limitation on the evaluation parameter items to generate the sealing test judgment result.

2. The high-efficiency chip packaging and testing system according to claim 1, characterized in that, The process of generating the convex interconnect response flow by the convex impedance unit includes: acquiring the original electrical signal data containing voltage amplitude and current phase, as well as the no-load reference signal generated by the test circuit; constructing a carrier differential filter model based on the carrier frequency range and characteristic impedance parameters; inputting the original electrical signal data and the no-load reference signal into the carrier differential filter model to perform phase synchronization alignment and differential mode component subtraction operations, canceling high-frequency resonant noise and extracting incoherent electrical performance fluctuation data to generate the convex interconnect response flow.

3. The high-efficiency chip packaging and testing system according to claim 1, characterized in that, The process of generating the convex intrinsic impedance current and flip-chip calibration features by the convex impedance unit includes: acquiring package electrical parameters containing parasitic inductance and interlayer capacitance data of package pins; mapping the package electrical parameters to parasitic impedance vectors using vector compensation logic; performing vector subtraction on the convex interconnect response current and parasitic impedance component vectors to generate the convex intrinsic impedance current; constructing a path phase compensation model based on vector compensation and phase alignment logic, inputting the convex intrinsic impedance current into the path phase compensation model to perform time-domain phase difference extraction to generate a time delay offset compensation amount; and using the time delay offset compensation amount to perform signal transmission delay synchronization operation on the convex intrinsic impedance current to generate flip-chip calibration features.

4. The high-efficiency chip packaging and testing system according to claim 1, characterized in that, The process of generating convex array current conduction by the convex array unit includes: constructing a contact electrical mapping model based on potential difference acquisition logic; inputting inverted calibration feature data into the contact electrical mapping model to perform node potential difference step sampling operation to generate array node potential set; acquiring preset detection current amplitude data; performing Ohm's law mapping transformation operation on the array node potential set using the preset detection current amplitude data to generate contact conduction quantization data; and performing conductivity feature vector encapsulation operation based on the contact conduction quantization data to generate convex array current conduction.

5. The high-efficiency chip packaging and testing system according to claim 1, characterized in that, The process of generating bump defect feature elements and crack electrical signal features by the bump array unit includes: acquiring the encapsulation stress offset parameters; constructing a carrier drift matrix comparison model based on the thermal stress and piezoelectric effect of the bottom filler adhesive; inputting the bump array electrical conductivity data and the encapsulation stress offset parameters into the carrier drift matrix comparison model to perform an electrical fingerprint feature association matching operation, extracting the impedance deviation component that deviates from the standard conduction mode, and generating bump defect feature elements; constructing a standing wave ratio distortion decomposition model based on the pulse injection frequency and the transmission line impedance standard; inputting the bump defect feature elements into the standing wave ratio distortion decomposition model to perform a pulse reflection waveform sampling operation, separating the reflected wave voltage standing wave ratio distortion component, and generating crack electrical signal features.

6. The high-efficiency chip packaging and testing system according to claim 1, characterized in that, The process of generating a response trajectory set by the load fault test unit includes: acquiring the test current step load; capturing the node current distribution flow by performing current sampling monitoring on the convex array; constructing a convex contact impedance matrix based on the convex defect feature elements; and performing a current vector space coordinate comparison operation between the node current distribution flow and the convex contact impedance matrix based on the crack electrical signal characteristics to generate a response trajectory set.

7. The high-efficiency chip packaging and testing system according to claim 1, characterized in that, The process by which the load failure test unit generates evaluation parameters and packaging test results includes: acquiring physical degradation parameters containing the extension length of convex cracks and the deformation variables of the connection interface; performing an electrical parameter drift and structural physical damage degree mapping operation on the response trajectory set data and the physical degradation parameters to extract the electrical performance degradation fingerprint set and generate evaluation parameters; acquiring standard electrical variable fluctuation limit threshold data, performing threshold boundary comparison operation on the evaluation parameters and the electrical variable fluctuation limit threshold, performing level matching based on the comparison operation, and generating packaging test results.

8. A high-efficiency chip packaging testing method, characterized in that, include: Acquire the raw electrical signal data and perform reference signal denoising to generate a convex interconnect response stream; Obtain the package electrical parameters, perform vector compensation calculation on the bump interconnect response flow, and generate the bump intrinsic impedance flow; A path phase compensation model is constructed based on vector compensation and phase alignment logic. Signal transmission delay synchronization is performed on the convex point intrinsic impedance current to generate inverted calibration characteristics. Based on the potential difference acquisition logic, a contact electrical mapping model is constructed. Electrical parameter sampling operation is performed on the flip-chip calibration features to generate the convex array electrical conduction. The packaging stress offset parameters are obtained, and the carrier drift matrix is ​​compared on the convex array electrical conduction to generate convex defect feature elements. Based on the feature elements of the convex defect, the reflected wave standing wave ratio distortion decomposition is performed to generate crack electrical signal features. The current shift trajectory tracking operation is performed on the crack electrical signal characteristics by current monitoring to generate a response trajectory set; physical degradation parameters are obtained, and electrical performance deviation correlation calculation operation is performed on the response trajectory set to generate evaluation parameter items; electrical variable threshold range limitation operation is performed on the evaluation parameter items to generate the packaging and testing judgment result.

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